Memory systems of the brain

Abstract

Humans have long been fascinated by how memories are formed, how they can be damaged or lost, or still seem vibrant after many years. Thus the search for the locus and organization of memory has had a long history, in which the notion that is is composed of distinct systems developed during the second half of the 20th century.A fundamental dichotomy between conscious and unconscious memory processes was first drawn based on evidences from the study of amnesiac subjects and the systematic experimental work with animals. The use of behavioral and neural measures together with imaging techniques have progressively led researchers to agree in the existence of a variety of neural architectures that support multiple memory systems.This article presents a historical lens with which to contextualize these idea on memory systems, and provides a current account for the multiple memory systems model.

Full text

Memory systems of the brain
Alvaro Pastor
Universitat Oberta de Catalunya, Computer Science, Multimedia and
Telecommunications Department, Barcelona, Spain
alvaropastor@uoc.edu
January 1, 2020
Abstract
Humans have long been fascinated by how memories are formed, how they can be
damaged or lost, or still seem vibrant after many years. Thus the search for the locus
and organization of memory has had a long history, in which the notion that is is
composed of distinct systems developed during the second half of the 20th century. A
fundamental dichotomy between conscious and unconscious memory processes was first
drawn based on evidences from the study of amnesiac subjects and the systematic
experimental work with animals. The use of behavioral and neural measures together
with imaging techniques have progressively led researchers to agree in the existence of a
variety of neural architectures that support multiple memory systems. This article
presents a historical lens with which to contextualize these idea on memory systems,
and provides a current account for the multiple memory systems model.
Introduction
Memory is a quintessential human ability by means of which the nervous system can
encode, store, and retrieve a variety of information [1, 2]. It affords the foundation for
the adaptive nature of the organism, allowing to use previous experience and make
predictions in order to solve the multitude of environmental situations produced by
daily interaction. Not only memory allows to recognize familiarity and return to places,
but also richly imagine potential future circumstances and assess the consequences of
behavior. Therefore, present experience is inexorably interwoven with memories, and
the meaning of people, things, and events in the present depends largely on previous
experience.
Questions concerning the nature and organization of memory systems are
fundamental to our understanding of the processes underlying learning and memory in
humans and other animals. Due to its importance and complexity, the subject of
memory is connected with some of the most profound questions of philosophy and
biology, and as such, has been approached from different perspectives and
methodologies. Along the way, idealists and materialists, empiricists and nativists,
behaviorists and cognitivists, have confronted ideas about memory. First from
philosophy through introspection and intuition, complemented later with anatomical
and physiological observations. Then neuropsychology, through observation of patients
with various defects in memory which developed the notion of a dichotomous
organization of memory. More recently, relevant contributions from neurobiology and
cognitive neuroscience, using various behavioral and neural measures together with
1/36
arXiv:2009.01083v1 [q-bio.NC] 1 Sep 2020

imaging techniques, have progressively led researchers to postulate distinctions among
various memory systems supported by different neural architectures, for example, by the
hippocampus and related structures, the amygdala, the striatum, and the cerebellum.
The tradition of memory research considered in this article is that of experimental
psychology and cognitive neuroscience amassed over the past decades. While a major
part of early research assumed a unitary view on memory, some authors assumed
dichotomous classifications based generally on the distinction of conscious and
unconscious memory processes. Accordingly, relevant distinctions between memory
systems have been proposed including but not limited to: episodic and semantic
memory [3, 4], taxon and locale memory [5], habit memory and cognitive memory [6, 7],
working memory and long term memory [8–10], implicit and explicit memory [11,12],
declarative and non declarative memory [13], declarative and procedural memory [14],
fast and slow memory systems [15,16].
In the last years, there is growing consensus about the nature and organization of
memory. Supported on cognitive and neurobiological and neuropsychological evidence,
memory is conceived as a set of separate, highly specialized, neural mechanisms that
interact to reach a common goal. However, the complete extent of their features and
interactions is yet to be fully understood.
The first part of this article presents a brief historical review with which to
reevaluate and contextualize the current theories and frameworks on human memory
systems. The second part presents an account for the components of the multiple
memory systems model, with some clues regarding the functional basis of memory
processes. The memory systems comprised in this article are part of the most accepted
and disseminated at present time. Debate about which of the different taxonomies of
memory most appropriately organizes all available experimental data is beyond the
scope of the present study.
1 Historical background
The nature of human memory and its organization have been object of study,
speculation and debate for several centuries, in a variety of areas including philosophical
inquiry, cognitive psychology, biology and neuroscience. In looking at the history of the
localisation and organization of memory it is necessary to turn to ancient theories
regarding the nature of soul and its relation to the body [17].
In early allusions to memory, ancient Egyptians considered it was solely supported by
the heart, as the centralized seat of cognitive processes [18]. Contrary to other organs,
the hearts of Egyptian mummies were kept carefully intact to ensure eternal life. Brains,
on the other hand, were ideally removed via transnasal excerebration, a technique
devised for this purpose by Egyptian embalmers [19]. In classical greek philosophy,
memory was considered as part of the eternal and immaterial nature of the soul. In
Theatetus, a major work written circa 369 BCE which explores the nature of knowledge,
Plato introduces the problem of remembering in the analogy of the wax into which our
perceptions and thoughts stamp images of themselves. An early distinction was made
between the passive retention of perceptions and active memory. Plato described active
memory in its episodic features, as ”the power which the soul has of recovering, when by
itself, some feeling which she experienced when in company with the body” [20]. Later in
the fourth century BCE, Aristotle returned to the notion that the soul is not a separate
substance from the body, as Plato had taught, but inherently bound into it, affording
its form. Aristotle came from a medical family and his biological bent is shown in its
influence on most of his philosophy. Informed by his biological researches, in
Metaphysica, Aristotle presented a thoroughly materialistic theory, in which the soul or
souls were distributed throughout the entire living body [21]. Also in de Anima, the
2/36

soul was conceptualized as distributed in the body. While, according to Plato, memory
is one of the higher faculties and partakes of the eternal nature of the soul, for Aristotle
memory is dependent upon a physical process, and perishes with the body. In spite of
this, Aristotle acknowledged the existence of a center on which sensory input converged
and from which behavior was initiated. This, for Aristotle, is the location of common
sense or sensus communis, where besides the external senses such as sight and smell
were processed, internal senses such as memory and imagination were sustained.
Aristotle established that the cognitive center was located at the heart, and that the
vegetative soul was fluid and distributed everywhere in the body [22, 23]. The operation
of memory as then conceived, may be inferred from the kinds of memory that the
classical philosophers observed. Aristotle worked on a tract devoted to the subject of
memory called De memoria et reminiscentia. Its second chapter was devoted mainly to
the recollection and association of ideas. In dichotomous fashion, Aristotle distinguishes
the mere persistence and direct reproduction of a presentation, from voluntary
recollection, which is possible only by the association of ideas, by similarity, contrast,
and contiguity. In the Aristotelian view, persistence memory is an attribute of animals
and humans, while the voluntary recollection is unique to humans [22,24,25].
Increasingly, philosophical inquiry on memory was influenced by anatomical and
physiological studies. In the first century BCE the Byzantine surgeon Poseidonius
produced the first written assignments of mental functions to specific cerebral regions.
Based from observations of head injuries, Poseidonius argued that lesions at the front of
the brain interfere with apprehension of all types of sensation, whereas trauma of the
posterior part results in memory deficit, and damage to the middle ventricle produces a
disturbance of reason [26]. At the end of the fourth century CE, Nemesius of Emesa
carried forward the ideas of ventricular function and proposed a schema which remained
fairly standard for several centuries. In De Natura Hominis, claimed that the anterior
ventricles accounted for the mixing of sensations and for imagination, the middle
ventricle for cogitation and reason, and the posterior ventricle for memory [27, 28].
Augustine of Hippo, Roman theologian and philosopher at the end of fourth century
CE, presented an account of human memory orchestrated by the brain and divided in
different and complementary instances: sensible memory, intellectual memory, memory
of memories, memory of feelings and passion, and memory of forgetting [29]. Sense
memory, for example, preserved and reproduced idealized images of visible objects,
sounds, odors and other items available to the senses. Intellectual memory on the other
hand, contained our knowledge of the sciences, of literature and dialectic, and of the
questions relating to these subjects. This memory, unlike the memory of sense,
contained not the images of things, but the things themselves [30]. The philosopher’s
contribution foresees in striking detail some of the most relevant theories of modern
psychology and neuroscience about memory, including the differences between sense
memory and intellectual memory, similar to current episodic and semantic memory
definitions.
During the following decades, philosophical conceptions and directions in memory
research in the Western tradition remained divided between either the views of Aristotle
or those of Plato and Augustine of Hippo.
An important milestone is found in the mid 16th century. The work of Andreas
Vesalius in De humani corporis fabrica libri septum, helped developed an opposition to
the medieval theory that the soul resides in the ventricles, believing these to be mere
channels for the passage of the fluid anima and explicitly identified the brain as the
main organ of intelligence, movement, and sensation [31]. Likewise, English physician
Thomas Willis helped establish as well that activities are not carried out in the
ventricles but in the brain substance itself. Also, Willis proposed a direct correlation
between complexity of gyri convolutions and availability of cognitive abilities including
3/36

memory. [32].
Willis’ ideas were contemporary to those of the French mathematician and
philosopher Descartes, and the notion of the correlation between physical and psychic
processes was clearly understood by the dualists of the seventeenth century. In De
homine Descartes elaborated the mechanistic concept of human sensation and motion,
and retained the ancient idea of the soul residing in the pineal gland, according to him
located in the ventricles. When the mind wills to recall anything, Descartes wrote, this
volition causes the pineal gland to incline itself successively this way and that, and impel
the animal spirits to various parts of the brain until they come to that part in which are
traces left by the object we would remember. Descartes explained the physical processes
involved in memory in accordance with his crude physiology, following the belief that
the soul resides in the ventricles and that the fluid in them can be animated. This ideas
prevailed into the end of the 18th century [33].
The doctrine of the Cartesians, that memory was conditioned by traces left in the
brain, was developed by the physiologists of the 18th century into a materialistic and
mechanical view of memory. In an extreme example, the physiologist Albrecht von
Haller interested in the time occupied in psychic processes, estimated that a third of a
second was sufficient time for the production of one idea. Von Haller and others then
calculated that in a hundred years a human must collect during her wake period a total
of 1 577 880 000 traces. By assuming the weight of the brain elements that were then
conceived with the power for preserving impressions, then obtained 205 542 traces must
be found in one gram of brain substance [23].
Early in 19th century, Franz Joseph Gall aimed again at settling the conceptual
dispute, and contributed to establish that memory was located solely in the brain and
was not located in the heart nor the ventricles as it was previously posited. Based on an
anatomical and physiological data, Gall also acknowledged that the brain contains
independent but interacting regions, and later interpreted that differences in behavior
are due to differential development of these brain regions [34]. To support his argument,
Gall drew on observations of within and between individual differences in memory for
particular kinds of information. Noting that some individuals have excellent memory for
places but not music whereas others exhibit the opposite pattern, Gall contended such
differences could not exist if memory constituted a unitary faculty [35,36]. A few years
later, physician Marie-Jean-Pierre Flourens investigated Gall’s controversial views on
cerebral localization by removing anatomically defined areas of the brain of an animal
and watching its behaviour. The results did not favour the idea of cerebral localization
and led him to conclude that the brain functioned as a whole and thus arose the concept
of cerebral equipotentiality [37, 38]. Much debate ensued, due to the fact that his
experiments were mainly on birds, and the techniques used were considered imperfect.
In contrast, French philosopher Maine de Biran published in 1804 a remarkable
attempt to organize human memory within a taxonomic construct, distinguishing
separate memory systems instead of a single unity: representative memory, that is the
conscious recall of facts and events, mechanical memory, responsible for learning of
habits and skills, and sensitive memory, regarding emotional information [39,40].
Psychologist and philosopher William James followed along these lines with his
Principles of Psychology in 1890. Despite no experimental evidences presented, a
number of very important observations were made. The distinction between memory
and habit, which led him to write separate chapters on both. Besides the distinction of
habit, James also postulated two other different kinds of memory, establishing the
difference between primary and secondary memory, which could be interpreted as an
anticipation of the modern distinctions of short term memory (STM) and long term
memory (LTM) [41, 42].
Bergson’s reflections on memory in Matter and Memory from 1896 also contributed
4/36

to the modern non unitary view of memory. The French philosopher proposed
distinctions between habit memory and episodic memories. For Bergson habit involved
repetition, is effortless and, once formed, non-representational. Despite being non
representational its effect percolates into the present and in part defines behavior. In
contrast, what he understood as episodic memories were representational, involved a
unique non-repeatable event, and its recollection, requires an act of will which involves
an active letting go of the attachment to the present [43,44]. In his 1949 work The
Concept of Mind the English philosopher Gilbert Ryle also distinguished between two
types of memory: knowing-that, a type of memory that does not directly inform action
but is expressed through regulative propositions; and knowing-how, a type of executive
memory that cannot be built up from pieces of knowing-that and is actualized through
enactment [45]. These suggestive approaches to the nature and organization of memory
and the subjective experience of recollection may be considered as the most influential
in Western philosophy of the twentieth century.
While these are seen as the earliest attempts in the study of memory, what was
demanded in order to fully understand its nature and organization was not only
philosophical discourse or psychological intuition, but experimental inquiry.
In a major contribution in the study of memory, the psychologist Hermann
Ebbinghaus published in 1885 [46] a pioneering experimental and quantitative treatment
of memory, displaying new ideas and methods for rigorous and systematic controlled
experiments on memory, that have had an enduring influence throughout the twentieth
century of memory research. A revolutionary concept in ¨
Uber das Ged¨achtnis was the
idea that memory research was not deemed to be the investigation of pre existing
memories but that memory contents to be tested needed to be created and modified in
the laboratory as an integral part of the experimental procedure [46, 47]. Ebbinghaus
invented the paradigm of the nonsense syllable as learning materials of homogenous
difficulty beyond the familiarity of words and prose. This notion defined a task in which
a multitude of variables can be defined and their influences on remembering behaviors
observed. He used strict controls on the timing and number of study trials, allowed time
for recall, and retention interval, and measured the difficulty of learning a list by the
number of study trials required to attain one correct recall. Moreover, Ebbinghaus
introduced the idea of measurable degrees of learning by noting the savings in relearning
a list he had learned earlier. Using this measure Ebbinghaus was able to devise his
famous forgetting curve relating percent savings to retention interval. [48, 49].
Even in Ebbinghaus’ earliest experiments it was clear that learning depended greatly
on the nature of the content, whether numbers, nonsense syllables, words, meaningful
sentences or poetry, as these vary greatly in their familiarity and meaningfulness to
subjects. By studying isolated variables, Ebbinghaus was able to observe the influence
of the different types of learnt contents on memory performance, as well as the mode of
their presentation, and the strategies subjects used in learning them. The memories
established can then be tested by direct measurement of recall, recognition and
reconstruction, or by a variety of indirect measures. Ebbinghaus’ experimental
framework set the foundations for the modern era of memory studies, and remains the
prototype for its research almost 150 years after.
At the dawn of the twentieth century, two relevant contributions to the
understanding of memory were presented in relation to the study of reflexes. The
Russian neurologist and anatomist Vladimir Mikhailovich Bekhterev presented
Pathways of brain and bone marrow in 1900, exposing an association of memory with
the hippocampus based on the study of amnesia in patients with hippocampal
degeneration. In addition to his later Foundations for Brain Functions Theory
Bekhterev presented his views on the functions of the parts of the brain and the nervous
system and developed a theory of conditioned reflexes which describe automatic
5/36

responses to the environment called association reflex [50, 51].
Similarly, the scientific mainstream of behaviorism, with its main exponents
Thorndike, Pavlov, Watson and Skinner, held that all learning is the attachment of
responses to stimuli [52]. Therefore they studied the characteristics and components of
a particular type of learning: that which is derived from repeated association between a
stimulus and a response,named classical conditioning, and that which is derived from
association between a stimulus and a behavior, called operative conditioning [50,53].
Pavlov’s studies are related to a type of memory that later would be called associative
memory, while Fitts and Posner’s studies [54] are considered the first aiming to explain
procedural memory. It may be argued that the knowledge on memory produced by
these experimental works of behaviorism was among the most important in the early
days of twentieth century.
Guided by the then prevalent and straightforward view that stimulus-response
learning is supported by connections between sensory areas in the posterior cortical
areas and motor areas in the frontal cortex, Karl Lashley’s conducted pioneering efforts
in the search for engrams [55]. Engrams were viewed as fundamental to the
understanding of memory, as the physical structures in which memory traces were
stored. Using maze learning in rats he aimed to map the cortical areas and pathways
that support memory formation. As the search proved unsuccessful, Lashley subscribed
Flourens’ view on the indivisible brain, meaning that there were no localizations of
memory in different parts of the brain [56]. He concluded that the memory trace was
widely distributed both within cortical areas and throughout the cortex and that any of
the neurons within cortical areas could support the engram, naming this principle
equipotentiality. Also contributed the notion that involved brain areas acted together to
support the engram, naming this principle mass action [57].
Later in 1934 Donald Hebb, student of Lashley, followed the interest in how the
brain gets organized to generate abilities such as memory. His 1949 work The
Organization of Behavior presented cell assemblies and the connection between cells
that fire together, advancing studies of memory consolidation [58,59]. The dual-trace
hypothesis of memory subsequently proposed by Hebb in 1949 offered a specific
physiological theory of memory consolidation. According to Hebb’s hypothesis, neural
activity initiated by an experience persists in the form of reverberating activity in
neural circuits of STM, and that the formation of LTM means the stabilization of these
circuits leading to permanent synaptic change [60].
During the following decades, as psychology struggled to assert itself as a scientific
discipline, a large wealth of knowledge about memory was supported on an increasing
number of experimental studies. The work of Edward Tolman distinguishes from many
of his behaviorist contemporaries on its focus on memory and behavior. Though Tolman
was greatly influenced by Watson’s behaviorism, Tolman’s cognitive, anti-reductionist
emphasis on purpose and macroscopic or molar behavior stood in stark contrast to many
of the learning theories of his contemporaries [61, 62]. The battle was sustained between
these two schools of thought, stimulus-response learning versus cognitive learning,
specially at the level of animal behavior. Tolman proposed that there is more than one
kind of learning in animals and humans. Unlike motor patterns, well understood by
behaviorists, other types of learning were postulated outside the stimuli-response logic.
Importantly, a distinction between memory systems is rooted in this debate between
place-learning, a position advocated by Tolman [63], and response-learning, a position
advocated by Hull who asserted that learning was a general process [64].
Such behavioral findings suggested the potential co-existence of at least two distinct
learning systems. However they did not have the effect of shifting the debate concerning
how many memory systems there were. Other authors argued that these two kinds of
learning existed, but that they did not represent fundamentally different things, instead
6/36

they are accountable by the use of different cues [65].
A very important contribution of Tolman to the study of memory as set of dedicated
systems was the Cognitive Map theory, which provided deep insights into how animals
represent information about the world and how these representations inform behavior.
Tolman developed this idea of a cognitive map as an alternative to the then-common
metaphor of a central switchboard for learning and memory, typical of
stimulus-response formulations. According to this view, animals maintained a set of
complex, integrated expectancies or hypotheses of their world [66]. Tolman would later
call these complex integrated expectancies cognitive maps [63]. For Tolman, learning is
acquiring expectancies, that is probability characteristics of the environment. The
organism thus typically learns a cognitive map not a mere movement pattern. His later
writings emphasized the use of multiple expectancies to inform behavioral performance,
particularly when an animal is faced with a choice [67,68].
Consistent with the emerging understanding that processing and memory storage
could not easily be separated from one another neurobiologically, the theory of the
cognitive map was embodied within a multiple memory systems perspective.
Importantly, it claimed that the brain memory systems differed based on the nature of
the contents of the memories they processed, and not only based the length of time that
memory storage was supported. As such, this view critically differed from the more
traditional perspectives of cognitive psychology and cognitive neuropsychology prevalent
a the time which saw systems as differing primarily in terms of how long information
remained within them, not in terms of the type of information involved.
It is relevant for the study of memory systems that two kind of differences that
render memory systems distinct were settled. First, the distinct memory systems might
be computationally different at their circuitry level in order to be efficient, a notion
later developed by Sherry and Shacter’s theory of functional incompatibility [16]. Fodor
also addresses the notion of modularity [69], understood as separate domain specific
modules that handle certain sort of contents. The functionalities of these modules are
hardwired and not acquired through learning processes. Second, systems might differ in
terms of the length of time during which information is to be stored within them, which
can require different underlying mechanisms. Beyond the study of animals, these two
non mutually exclusive approaches to memory systems were further expanded to
humans in the study of focal cerebral damage.
Since the 1950’s Scoville, Penfield, Hebb and Milner, documented the effects of
surgical lesions of temporal lobe on human declarative memory, finding severe
anterograde amnesia and retrograde amnesia with temporal gradient [70–75]. A well
known case of study was that of the severe epileptic patient Henri Molaison (H.M.) who
in 1953 underwent surgical removal of brain structures in the MTL (MTL) including the
hippocampus to cure him of his epileptic seizures. As a result of this surgery, H.M. was
profoundly impaired in the acquisition of certain forms of information. He became
unable to consciously recollect new events in his life or new facts about the world.
However, H.M. retained the ability to remember other types of information. While
other cognitive functions remained intact, H.M.’s experience was greatly influenced by a
permanent present tense. If rehearsed and attention was held, a patient such as H.M.
could keep a short list of numbers in mind for several minutes. But would prove unable
if distracted or when the amount of material to be remembered exceeded what can be
held in immediate memory.
Early evidence from H.M’s case supported the mainstream view that memory is
composed of systems which differed in terms of how long can they keep the memory for.
By having removed large portions of hippocampus H.M. had only distorted the
consolidation of the LTM system [76].
Subsequently, Milner reported that H.M. could learn and perform new sensorimotor
7/36

tasks. Although H.M.’s memory impairment disabled learning for all forms of materials,
including scenes, words or faces, he proved capable of learning a complex hand – eye
coordination skill, namely mirror drawing, over a period of 3 days even without
awareness of having been previously trained or tested [77]. This selectivity of H.M.’s
amnesia related to the type of learned activity or content, suggested the existence of
two distinct forms of memory corresponding to each type of material: declarative
memory and procedural memory. It was presumed that these systems were dependant
on separate neural systems, and that by lesion or degenerative processes, amnesiac
patients were only disabled in their declarative memory functions [78–80].
These findings contrasted with prevailing views at the time by linking a memory
disturbance to damage to a specific part of the brain. However these theories were
attempted in animal models, namely monkeys and rats, leading to no amnesia, thus
discussions and uncertainties about a content based organization of memory systems
ensued for several years [81–84].
In the following sections an account is provided regarding these two kinds of
taxonomies and a brief review of the relations and differences between memory systems.
2 Persistence-based taxonomy
The 60’s saw a growing interest in developing mathematical models of learning and
memory. Despite that the mainstream view accepted only one global memory system
responsible for handling many kinds of information, this assumption did allow an
implicit division of memory in memory systems which differed in terms of their capacity
to store contents within them.
In the previous section, a review on the historical evolution showed that allusions to
memory taxonomies based on time persistence had been present for several centuries,
despite the apparent triviality of its insight on how memory is organized. One possible
catalyst for the emergent importance of this perspective during the early 60’s, was the
influence of the computer revolution which may have served as inspiration for thinking
about memory from an information processing approach.
In its most influential consolidation, Atkinson and Shiffrin [85] settled in 1968 a
model of human memory divided into three classes, ultra short-term memory, STM, and
LTM, which became known as the multi store or modal model of memory. In addition
to identifying the three different memory types, Atkinson and Shiffrin also suggested
that they stand in a rather fixed relationship to one another. They proposed that stored
information is processed sequentially entering the brain through the sensory system into
ultra-short-term, passes through STM and ends up in LTM. This processing chain can
terminate when information is forgotten from one of the memory stores.
Figure 1.
In the 1950’s and early 60’s the conception of memory was largely inspired
by an information processing approach, in which systems differed in terms of duration,
processing and storing information for varying periods of time.
8/36

2.1 Ultra short term memory
According to this model, Ultra short term memory, or sensory memory, makes
instantaneous sensory information available for processing for less than 120
milliseconds [86]. This kind of memory is specific to a particular sensory system and
does not appear to be shared across sensory systems. In the visual system, ultra short
term memory is the reason, why, for example, apparent continuous motion is perceived
when watching a movie instead of 24 individual frames per second.
Authors have suggested that ultra short term memory is limited to only a few
hundred milliseconds in duration because the memory traces decay naturally [85]. Due
to this timescale this form of memory would operate outside of awareness, and since it is
entirely driven by external stimuli, it lies outside conscious control. For these reasons,
some researchers suggest that ultra short term memory may be a component of the
sensory system rather than a memory system.
2.2 Short term and Working memory
In the late 50’s the consolidation of the notion of a STM system began with the
empirical support which observed that, provided the prevention of active rehearsal, even
small amounts of information showed rapid forgetting [87, 88]. The pattern of memory
decay appeared to differ from that observed in standard LTM experiments, which led to
the view that performance depended on a separate short term store. It was then
thought that STM operated as a crucial antechamber of LTM storage.
During the 60s, methods were developed for studying visual perception and motor
responses with single-cell recordings from awake, behaving monkeys performing a classic
delayed response task, which requires holding information in memory for a brief period.
This work identified cells in prefrontal cortex that were maximally active during the
delay portion of the task of 15 to 60 seconds [85, 89–91].
However, various problems stemmed from the view of STM held by this model.
First, it was challenged the notion that the probability of an item being stored in LTM
as a function of its maintenance on short term system. A number of studies
demonstrated that active verbal rehearsal was not linked to durable LTM [92]. This
argument gave way to the theory called levels of memory [93]. This theory proposed
that an item in order to be remembered, for instance a word on a page, could be
processed at a series of encoding levels which started with the visual appearance of the
item, its sound when pronounced, and later its meaning and relationships with other
related memory experiences. A second challenge was provided by the neuropsychological
evidence of patients with an STM deficit while preserving LTM intact. The then
prevalent STM model failed to provide explanation for this phenomena, as it argued
that poor performance of STM should have also led to impaired LTM capacity. These
challenges led researchers to reformulate the STM hypothesis and postulate a
multicomponent system which was termed working memory.
Working memory refers to the capacity to maintain temporarily a limited amount of
information in mind, which can then be used to support various abilities, including
learning, reasoning, and preparation for action [8]. It is generally acknowledged that
working memory can store information for up to 20 seconds, and according to some
experimental studies its maximum capacity is four chunks of information [94]. Despite
its acquisition being without a conscious effort, working or short-term memory can be
controlled consciously and is less dependent on sensory inputs than ultra-short-term
memory. Most importantly, through rehearsal, the spontaneous decay of working
memory may be prevented.
According to Baddeley and his tripartite model [9, 95] working memory is comprised
by the phonological loop, which support retrieval temporary storage and rehearse of
9/36

phonological material, the visuospatial sketchpad to perform maintenance of visual
representation of stimuli and their position in space [8,9], and a central executive sub
system which is a limited capacity supervisory attentional system [96] that orchestrates
and mediates the manipulation of contents from visuospatial and phonological sub
systems. However, there is evidence indicating that spatial and object working memory
may be separable [95]. Single cell recording studies in nonhuman primates have revealed
different activations in ventral and dorsal prefontal cortex during object working
memory performance for the first and spatial working memory performance for the
latter.
In 2000 Baddeley included in this model the episodic buffer involved in linking
information across domains to form integrated units of visual, spatial, and verbal
information with episodic chronological ordering. This episodic buffer is also assumed to
have links to LTM and semantic meaning. The working memory model currently
consists of four elements that process information: the central executive for attention
control; the visuospatial sketchpad, which creates and maintains a visuospatial
representation; the phonological buffer, which stores and consolidates new words; and
the episodic buffer which stores and integrates information from different sources [10].
Figure 2.
The year 2000 version of the multi-component working memory model according
to Baddeley which includes the episodic buffer. The episodic buffer is interpreted to be
controlled by the central executive, and it is capable of multi-dimensional information
storage, providing a temporary interface between the phonological loop, the visuospatial
sketchpad and long term memory (LTM). The buffer serves as a modelling space that is
separate from LTM, but which forms an important stage in long- term episodic learning.
In this schematic view, faded areas represent systems capable of accumulating long-term
knowledge, and unshaded areas represent fluid capacities such as attention and temporary
storage.
Working memory is therefore central to the ability to select and implement
goal-directed behavior, to exercise what are termed executive functions. Indeed, recent
discussions emphasize a broad role of prefrontal cortex in cognitive control, an idea that
implies top-down influences from prefrontal cortex that direct attention and organize
action [97, 98]. The prefrontal cortex allows memory to be accessed strategically, and it
orchestrates the use of learned rules so that knowledge relevant to current goals can be
brought to mind and put to flexible use.
2.3 Long term memory
Assumed as a group of systems responsible for the capacity to store information over
long periods of time [99]. LTM differs from STM in that the memory contents would no
longer be vulnerable to spontaneous decay, nonetheless, some memories may be
forgotten due to interference from memories that are stored later. Another key
difference to short-term memory is that subjects recall these items not in isolation, but
including the relationships between them, and the spatiotemporal context in which they
10/36

are embedded. This makes LTM singular due to its larger capacity for the storage of
arbitrary combinations of different kinds of information [100].
Analysis indicates that the hippocampus and associated structures of the MTL serve
to generate LTM traces. Clinical evidence indicates that damage to the hippocampus
produces anterograde amnesia. At the cellular-molecular level, the intricacies of
synaptic plasticity, a candidate model for memory storage, are being studied in great
detail [101], however, the link between single neuron computation and computation at
the network level is poorly understood. It remains unclear how neuronal cooperativity
in intact networks relates to memories or how network activity in the behaving animal
brings about synaptic modification [102].
In recent years, psychologists have gathered numerous pieces of evidence for the view
that our memories are in fact constructions of what happened in the past. Memories are
stored in the brain in a distributed pattern in the outer layer of the cortex, related to
the area of the brain that initially processed them [99]. In this view, a visual aspect of
an experience is normally stored in the visual cortex, an auditory aspect of an
experience is stored in the auditory cortex, and a motion element of an experience is
stored in the sensory motor cortex. When a memory is retrieved, all its fragments are
put back together rarely identical to the initial experience [103].
In past decades, little thought was given to the possibility that there might be some
constraint on the kind of information these memory systems could handle or the rules by
which they operate. Over the years, several aspects of Atkinson and Shiffrin’s taxonomy
have been questioned. The main criticisms can be divided into two classes. First, their
taxonomy artificially splits memories of the same kind into different taxa. Several
authors have proposed that STM and LTM are instances of the same unitary memory
that happen to have different properties. Second, Atkinson and Shiffrin associate
together disparate kinds of memories into a single system. Furthermore, The dominant
view of a single memory system prevented the selective nature of amnesia from being
systematically explored for several decades. For the most part neuropsychologists
working with human subjects accepted the single system premise and the view that
damage to the brain to varying degrees accounted for the global amnesia observed in
subjects with various etiologies [104, 105]. Despite these controversies, Atkinson and
Shiffrin’s taxonomy has been one of the most influential taxonomies of memory.
Advances in neurobiology and behavioral neuroscience contributed to modify this
approach. During the 70s a genuine change occurred in the way memory is thought of,
and various new phenomena began to be addressed as memory related, using different
tasks to measure different specialized functionalities. Perceptual memory or
representation systems are an example of this broadening [106]. Phenomena like object
priming or fragment completion, added to the view that processing and memory storage
occur in the same circuits has emerged from the neurobiological literature. [107–109].
Importantly, the discovery of the declarative memory systems with the view that the
hippocampus has a selective role in learning, began in the late 60s and took more than
20 years to unfold.
3 The discovery of declarative memory systems
The first observations of H.M., and the results of formal testing, were reported in 1957
by Scoville and Milner [73] in a seminal paper that shed light on three fundamental
principles: a) memory is a distinct brain function, separable from general cognitive and
language functions; b) the MTL is not necessary for immediate memory since this was
largely normal in H.M; and c) MTL structures are not the final storage location for
memories, since although the removal of these structures showed severe amnesia in
H.M., the patient still retained large portions of memories of his childhood [110]. This
11/36

publication became one of the most cited papers in neuroscience and is still frequently
cited.
Importantly, subsequent findings from H.M. established that memory was not a
monolithic system that handles all types of information, but a highly interconnected set
of systems. Due to the the fact that H.M. and other amnesic patients demonstrated
intact learning and retention of certain motor, perceptual and cognitive skills, memory
was thought to be comprised of at least two separate systems and that only one kind of
memory, declarative memory, is impaired in amnesia [77,79,111,112].
Nevertheless, patients with hippocampal damage typically have a normal vocabulary,
and their general knowledge of facts remains intact. Interestingly, the opposite pattern
of memory loss is associated with a specific form of neurodegenerative disease known as
semantic dementia in which recent events are retrieved accurately while the meaning of
words and knowledge about world facts is greatly impaired [113].
3.1 Declarative memory
Declarative memory provides a fast and flexible way to represent the external world,
and the ability to make inferences from and generalizations across facts derived from
multiple processing sources. It supports the encoding of memories in terms of
relationships among multiple items and events. Declarative memory allows remembered
material to be compared and contrasted. The stored representations are flexible and can
guide performance under a wide range of test conditions [114]. A key characteristic is
that declarative memory is explicit and accessible to conscious awareness. That is, it
may be brought to mind verbally as a proposition, or non verbally as an
image [13, 99, 115, 116].
It is widely accepted that declarative memory has two major components: semantic
memory, responsible for processing facts about the world; and episodic memory, the
ability to re-experience a time and place specific event in its original context [4,40].
Declarative memory depends on the integrity of neural systems damaged in amnesia,
namely the hippocampus and MTL associated structures. Amnesic patients’ defects in
memory extend to both verbal and nonverbal material, and involve information
acquired through all sensory modalities. Other etiologies of amnesia have also
contributed useful data to support theories on declarative memory, including
encephalitis, anoxia and ischemia, Korsakoff’s syndrome, and psychiatric patients whose
memories were impaired as a result of electroconvulsive therapy [117, 118].
Several theories regarding the role of the hippocampus in memory have been
proposed over the years. All regard the hippocampus as being critical for episodic
memory, but there are key differences in whether they view the hippocampus as having
a time limited role in episodic memory and in whether they deem it to be necessary for
the acquisition of non-contextual information. The pattern of spared and impaired
cognitive processes in patients with hippocampal damage, combined with results from
animal models of amnesia, has lead to the Declarative Theory of hippocampal
function [119]. Some researchers have focused on building a neural level understanding
of hippocampal function in a specific cognitive domain such as the theory of the
Cognitive Map [5]. While others have sought more specific characterizations of
hippocampal function, drawing on experimental data from animals and humans with
the Multiple Trace Theory [120], the Dual Process Theory [121], and the Relational
Theory [122].
In addition to MTL structures the acquisition of episodic memory requires the
involvement of other brain systems, especially the frontal lobes [123–127].
A number of considerations suggest that the capacity for declarative knowledge is
phylogenetically recent, reaching its greatest development in mammals with the full
elaboration of medial temporal structures, especially the hippocampal formation and
12/36

associated cortical areas. This capacity allows an animal to record and access the
particular encounters that led to behavioral change. The stored memory is flexible and
accessible to all modalities [128].
The declarative memory system has a distinct developmental evolution through
individual’s lifetime. In most species hippocampus is not fully developed at birth and
processess of neurogenesis are constant throughout life in some cases [129]. In humans
the hippocampus and related structures incur in a dramatic size change in the first two
years of life, enabling the memory function after 18 to 24 months, and only reaching full
adult function after reaching 10 to 12 years of age. As such, phenomena such as
infantile amnesia defined as the inability to form episodic memory early in life is
starting to be understood [130–132]. Similarly, in spatial navigation tasks, children
younger than two years old fail at distal cue use in navigation, as it requires a fully
functioning hippocampus [128, 133, 134].
3.2 Declarative systems
Tulving proposed the distinction between Episodic and semantic memory as two types
of declarative memory subsystems. Both types of memory are declarative due to the
fact that retrieval of episodic and semantic information may be carried out explicitly
and subjects are aware that stored information is being accessed [3, 4, 135]. This
distinction devised by Tulving has in many ways fulfilled its purpose of understanding,
and accounting for, the broader range of memory phenomena and experimental findings,
and has formed the foundation for decades of theoretical and experimental work in the
cognitive neuroscience of memory.
Of particular interest has been the extent to which semantic and episodic memory
have a shared dependence on the hippocampus. In contrast to the definitive evidence
for the link between hippocampus and episodic memory, the role of the hippocampus in
semantic memory has been a topic of considerable debate. Amnesic patients do have
great difficulty acquiring semantic knowledge, but they can typically succeed to some
extent after much repetition [136, 137]. In Tulving’s work on the severely amnesic
patient K.C., he reports how eventually the patient learned to complete arbitrary
three-word sentences during a large number of training trials distributed over many
months despite the absence of any memory at all for training episodes [138]. Episodic
memory can be virtually absent in some severely amnesic patients who can still
accomplish some semantic learning.
The key structures that support declarative memory are the hippocampus and the
MTL adjacent structures, such as entorhinal, perirhinal, and parahippocampal cortices,
which make up much of the parahippocampal gyrus [115]. These structures are
organized hierarchically, and their anatomy suggests how the structures might
contribute differently to the formation of declarative memory, for example, in the
encoding of objects in perirhinal cortex, or scenes in parahippocampal cortex, and in
the forming of associations between them in the hippocampus [139–141].
One interpretation is that both episodic and semantic memory depend on the brain
system damaged in amnesia, the hippocampus and MTL related structures, and that
episodic memory additionally depends on the integrity of the frontal lobes. Patients
with frontal lobe damage, who are not amnesic, exhibit a phenomenon termed source
amnesia which refers to loss of information about when and where a remembered item
was acquired [142,143]. In this sense, source amnesia appears to reflect a loss of episodic
memory related to frontal lobe dysfunction, which in turn reflects a disconnection
between facts and their contexts. The greater contribution that frontal lobe function
makes to episodic memory, compared to semantic memory, would give a 1biological
support to the distinction between episodic memory and semantic memory [114].
13/36

In their infuential book The Hippocampus as a Cognitive Map, O’Keefe and Nadel
suggested that the then recently discovered place cells found within the hippocampus
provided the neurobiological substrate of the Cognitive Map [5]. Subsequent
investigations of hippocampal place cell activity further developed the notion of the
hippocampus mediating place information and the functions of such data coordination
beyond spatial domains [144].
3.2.1 Episodic memory
Episodic memory was conceived by Tulving [3], at a time when information processing
models dominated. Episodic memory refers to autobiographical memory for events in its
when, what and how components, linked together in a coherent spatial and temporal
context. This includes the spatiotemporal relations between events. A key feature of
episodic memory is its unique role to allow the individual to mentally travel back into
her personal past [145, 146].
The precise details that characterize episodic memory have been, and continue to be,
debated, but time, space and sense of self are widely accepted as key elements [147
–
151].
Episodic memory is affected by aging processes [152], and there have been findings of
sex differences in its performance [153, 154], but results are still inconclusive [155].
It has been suggested that episodic memory in the hippocampus is formed by
combining spatial information from the medial entorhinal cortex [156,157] with non
spatial information from the lateral entorhinal cortex [158,159]. A number of imaging
studies have revealed evidence linking MTL activation with episodic encoding. MTL
activation has been observed under conditions in which exposure to novel stimulus
materials is compared with exposure to familiar materials. Imaging studies have also
illuminated the contributions of distinct prefrontal regions to encoding and
retrieval [160–162].
Recent studies have helped to establish that these neural systems also support the
capacity to imagine and to simulate episodes expected to occurr in the
future [4, 145, 163, 164]. The ability to pre experience future events has been referred by
some authors as prospection [165] and by others as episodic future thinking [166–168].
Some early observations along these lines were reported related to the patient K.C.,
who was investigated extensively over 20 years since a head injury left him with large
bilateral hippocampal lesions which caused a remarkable case of memory
impairment [109,138,169]. K. C. was unable to provide a description of his personal
future for any time period, immediate or distant, describing his mental state as blank.
Interestingly he used exactly the same definition of mental state when asked to think
about the past [109, 170]. A later investigation in another patient, D. B., who became
amnesic as a result of cardiac arrest and consequent anoxia revealed that he, like K. C.,
exhibited deficits in both retrieving past events and imagining future events [171].
A study led by Hassabis examined the ability of five patients with documented
bilateral hippocampal amnesia to imagine new experiences, such as being at a desired
location in an ideal situation [151]. Based on the content, spatial coherence and
subjective qualities of the participants’ imagined scenarios, the ability to imagine of the
subjects with hippocampal lesions was greatly reduced in richness and content.
Due to the fact that hippocampal amnesics have difficulty imagining new
experiences, Hassabis concluded that the hippocampus plays a key role in recombining
details of previous experiences into a coherent new imagined construction.
This interpretation that hippocampus mediates both future episode thinking and
imagination, assumes that the episodic memory is constructive rather than a
reproductive system. Since the future is not an exact repetition of the past, it requires a
system that can draw on the past to flexibly extract and recombine elements of previous
experiences. In this view, fundamental features of a memory are distributed widely
14/36

across different parts of the brain [139]. Therefore, retrieval of a past experience
involves a process of pattern completion, in which the process of recall pieces together
some subset of distributed features that comprise a particular past experience [172, 173].
Consistent with this approach, neuroimaging studies focused on the brain activity
during the construction of past and future events, have revealed regions exhibiting
common activity, which included the left portion of the hippocampus and the right
occipital gyrus, especially during the elaboration phase, when participants are focused
on generating details about the remembered or imagined event [174,175].
3.2.2 Semantic memory
Tulving postulated that semantic memory consists of a mental thesaurus encompassing
a wide range of organized information including facts, concepts and vocabulary
necessary for language [4, 135]. Semantic memory can be distinguished from episodic
memory by virtue of its lack of association with spatiotemporal contexts [1], and does
not require subjective reexperiencing of the episode in which the knowledge was
acquired. These systems differed as well in terms of the conditions and consequences of
retrieval. Unlike episodic memory, retrieval from semantic memory was thought to leave
its contents unaltered and to provide new input into episodic memory. Retrieval from
episodic memory, in contrast, was thought to modify the contents of the system. Also,
episodic and semantic memory were thought to differ in their dependence on each other:
whereas semantic memory was thought to be independent from episodic memory in
terms of recording and maintaining information, episodic memory could be strongly
influenced by, and depend on, information in semantic memory at encoding [176].
Originally, Tulving viewed episodic and semantic memory as two functionally
separate systems, but he also emphasized the features shared between them and their
close interaction. For example, retention of information in both systems was thought to
be automatic, because it did not require ongoing effort; for both systems, retrieval of
information could be prompted by highly relevant cues or questions, even if the retrieval
process itself is outside of awareness. Personal semantic memory, that is semantic
knowledge that relates to the self, represents another common area of semantic and
episodic memory, increasingly supported by neuropsychological evidence [177, 178]
Semantic memory has been associated with an overlapping network of neural regions,
with recent research invested in elucidating the roles of anterior and lateral temporal
neocortex and ventrolateral pre frontal cortex [179
–
181]. Imaging studies have suggested
that the semantic attributes of a stimulus are stored near the cortical regions that
underlie perception of those attributes, while have also highlighted that retrieval from
semantic memory and encoding into episodic memory share underlying component
processes [182].
Figure 3.
A taxonomy that includes declarative and non declarative memory systems,
including the different kinds of awareness of the subject. Although non declarative mem-
ory was not yet fully understood, compelling evidence pointed at distinct specialized
components of memory outside of the episodic and semantic domains.
15/36

3.3 Non declarative memory
There were early suggestions in the animal literature that more than just motor skills
were intact after lesions of hippocampus or related structures [5, 183, 184]. However,
these proposals greatly differed from each other, and they came at a time when the
findings in experimental animals was not in agreement with findings from human
amnesia and memory [78, 112].
Evidences of the extent of non declarative systems in humans came from the task of
reading mirror-reversed words [111], a perceptual skill which amnesic patients acquired
at a normal rate despite poor memory for the words that they read. Thus, perceptual
skills, not just motor skills, were intact. Later, amnesiac patients with the ability to
resolve stereoscopic images [185], learning of an artificial grammar [186], and learning of
new categories of items [187]. The accumulating data led to further arguments about the
extent and nature of what is not included in the notion of declarative memory [105,112].
The notion of procedural memory was originally devised to contrast with declarative
memory [111, 188]. Whereas this notion appropriately describes a wide variety of
skill-based kinds of learning, certain memory phenomena were clearly not declarative,
but also not well accommodated by the notion of procedural memory. Subsequently, the
concept of non declarative memory emerged as an umbrella which would cover human
memory capacities that support skill and habit learning, perceptual priming, and other
forms of behavior, which are expressed through performance rather than
recollection [189]. For example procedural skills, such as knowing how to ride a bicycle,
are expressed through performance in riding a bicycle; priming memory, which
underpins our ability to recognize words and other perceptual skills, is accessed
implicitly as it is performed. Non declarative memory is neither true nor false, does not
require conscious reflection on the past, or event knowledge that memories are being
formed by past events. Non declarative memory is shaped by experience, but unlike
declarative memory which is flexible and can guide behavior in multiple contexts, the
acquired knowledge in non declarative memory is thought to be rigidly organized [99].
Authors have suggested that non declarative memory is phylogenetically old. and
that it may have developed as a set of special purpose learning abilities. Memory
formation is then thought as the result of cumulative changes stored within the
particular neural systems engaged during learning [114]. Most non declarative memory
functions are present at the onset of human life, few age-related improvements have
been found from 3 months on, and evidences have highlighted that these systems remain
stable since the 9th month of life [190–192]. The idea that non declarative memory
remains stable as age progresses has come to be widely accepted. For instance, several
studies of priming in normal aging have not reported significant decline, while
cross-sectional studies employing a range of different tasks have reported
non-significantly different priming between groups of young and older adults [193,194].
Yet not all authors agree on the idea of preserved non declarative functions in older
individuals, and some have argued that these inconclusive results need to be further
substantiated [195].
3.4 Non declarative systems
Neuroimaging studies have led researchers to attempt establishing the main neural
structures identified in relation to current non declarative systems. For example, the
striatum has been linked to memory of skills and habits, and active sections of the
neocortex have been related to priming. Classical conditioning of skeletal musculature
has an essential dependence on the cerebellum, while emotional conditioning has been
correlated to activation of the amygdala [2, 114].
It is debated to this day the role of the hippocampus and related structures in non
16/36

declarative learning. One proposal is that, whereas conscious recollection depends on
the hippocampus, it is also important for unconscious memory under some
circumstances [196, 197]. Other work, based on functional magnetic resonance imaging
(fMRI), has implicated MTL structures in the unaware learning of sequences and other
tasks with complex contingencies [198,199]. Considering that fMRI data cannot
establish a necessary role for a particular structure, this remains a debated topic.
The role of non declarative memory system in supporting syntactic processing is also
still unclear. In studies with patients with Korsakoff’s syndrome who display deficits in
all subdomains of declarative memory, yet their non declarative memory remains intact,
patients showed robust syntactic priming effects, the phenomenon in which participants
adopt the linguistic behaviour of their partner [200].
3.4.1 Conditioning: Skeletal responses
Study of nondeclarative memory began with motor skills and perceptual skills. The best
understood example of nondeclarative memory in vertebrates is classical conditioning of
the eyeblink response, specifically delay eyeblink conditioning. In delay conditioning, a
neutral conditioned stimulus (CS), such as a tone, is presented just before an
unconditioned stimulus (US), such as an airpuff to the eye. The essential memory trace
for the conditioned eyeblink response and other discrete conditioned motor responses
was discovered is formed and stored in the cerebellar interpositus nucleus [201].
Critically, delay eyeblink conditioning is intact in amnesia and is acquired independently
of awareness [202,203]. Largely on the basis of work with rabbits, delay eyeblink
conditioning proved to depend on the cerebellum and associated brain stem circuitry.
Forebrain structures are not necessary for acquisition or retention of classically
conditioned eyeblink responses. These discoveries are on of the most successful
examples of localizing a memory trace within the vertebrate brain [204].
3.4.2 Priming and perceptual learning
The next of these to come under study was the phenomenon of priming. Priming was
defined as the improvement in the ability to to detect or classify a stimulus as the result
of a recent encounter with the same or a related stimulus [205, 206].
Evidence for the distinct priming phenomenon came from both normal subjects and
amnesic patients that perform normally when tests are structured using non memory
kind of instructions [108, 205, 206]. For example, amnesic patients often performed well
when they were given three-letter word stems as cues for previously presented words,
event without recognizing the stimuli as having been presented before. With
conventional memory instructions (use each cue to help in remembering a recently
presented word), healthy subjects outperformed the patients [207]. Thus, it became
evident that priming is an unconscious memory phenomenon and is entirely
independent of the MTL.
Priming effects are distinct from declarative memory in two other important aspects.
The information acquired by priming is fully accessible only through the same sensory
modality in which material was presented initially. And priming effects are short lived,
since in both normal control and amnesic patients it declined after 2 hours [206].
Priming is presumably adaptive because animals evolved in a world where stimuli
that are encountered once are likely to be encountered again. Perceptual priming would
result advantageous as improves the speed and fluency by which organisms interact with
familiar stimuli. For example, in the case of visual priming, the posterior visual cortex
becomes more efficient at processing precisely those stimuli that have been processed
recently. This plasticity occurs well before information reaches the limbic structures
important for declarative memory [163].
17/36

Evidence of independence of the phenomena of priming and the type of memory
impaired in amnesia was reproduced by the studies of perceptual priming [208, 209], and
conceptual priming [210]. These works showed that severely amnesic patients can
exhibit fully intact priming while performing at chance on conventional recognition
memory tests for the same test items.
3.4.3 Conditining: Emotional responses
Emotional conditioning is understood as system of non declarative memory that is
responsible for the assessment whether an encountered stimulus has positive or negative
value. In humans, associative fear learning proceeded normally after hippocampal
lesions, even though the CS – US pairings could not be reported [211]. It has been
shown that the amygdala has a critical role in fear learning, and its function and
connectivity appears to be conserved widely across species. In human neuroimaging
studies, the amygdala was activated not only by fear but by strongly positive emotions
as well [212].
The biological study of fear learning and its reversal, for instance fear extinction has
considerable relevance for clinical disorders such as phobias, post-traumatic stress
disorder, and other anxiety disorders [213].
In addition to its importance for emotional learning, the amygdala also exerts an
important modulatory influence on both declarative and non declarative
memory [214, 215]. Thus, activity in the amygdala, and the effect of this activity on
other structures, is responsible for the fact that emotionally arousing events are typically
remembered better than emotionally neutral events. The importance of the amygdala
for modulating memory has also been demonstrated with neuroimaging. Volunteers
rated the arousing effects of either neutral scenes or emotionally distressing scenes and
then took a memory test for the scenes two weeks later [216]. Increased activity in the
amygdala at the time of learning was associated with higher arousal ratings for the
scenes and improved accuracy on the later memory test. Interestingly, this effect
occurred in the left amygdala for women and in the right amygdala for men [217].
3.4.4 Procedural: Skills and habits
One important discovery in the 1980s was that the gradual trial-and-error learning that
leads to the formation of habits was supported by the striatum [6,218,219]. Habit
memory is characterized by automatized, repetitive behavior and, unlike declarative
memory, is insensitive to changes in reward value [220]. Tasks that assess habit learning
are often structured so that explicit memorization is not useful, and individuals must
depend more on intuition. In this learning, what is presumably acquired is a set of
dispositions to perform a task in a particular way, and not factual knowledge about the
world. Unlike declarative memory, which is flexible and can guide behavior in different
contexts, the acquired knowledge in this case is rigidly organized. Habit memory
subsequently became an important focus of study [221].
The difference between declarative memory and habit memory was shown for
memory-impaired patients with hippocampal lesions and patients with Parkinson’s
disease [219]. Amnesic patients can acquire a variety of skills at an entirely normal rate.
These include motor skills [222], perceptual and motor skills [111, 223], and cognitive
skills [224].
Currently is known, striatal neuronal plasticity enables basal ganglia circuits to
interact with other structures and thereby contribute to the processing of procedural
memory [225]. The cerebellum is involved in the execution of movements and the
perfection of motor agility needed procedural skills. Damage to this area can impede
one from relearning motor skills and recent studies have linked it to the process of
18/36

automating unconscious skills during the learning phase [226]. The limbic system shares
anatomical structures with a component of the striatum, which assumes primary
responsibility for the control of procedural memory. Reward-based learning of this kind
depends on dopamine neurons in the midbrain, which project to the striatum and signal
the information value of the reward. The dorsolateral striatum is crucial for the
development of habits in coordination with other brain regions while together with the
infralimbic cortex appear to work together to support a fully formed habit [227].
3.4.5 Non associative memory
Non associative memory is understood as a robust form of behavioral memory, based on
newly learned behavior through repeated exposure to an isolated stimulus. This form of
memory is developed even in invertebrate animals who do not have a capacity for
declarative memory. It differs from associative learning in that it does not require the
temporal pairing between two different sensory stimuli or between a sensory stimulus
and corresponding response feedback [228, 229]. There are two well known types of
non-associative learning: habituation and sensitization. Habituation is a decrease in
response to a benign stimulus when the stimulus is presented repeatedly, while
sensitization describes an augmentation of the response. Habituation is thought to be
related to a decrease in the efficiency of synaptic transmission, which may be caused by
a conductivity change in the membrane of the stimulated neuron. In turn, the process
of sensitization may be due to a provision in transmission, whether it may be
presynaptic or postsynaptic [230].
A well understood and simple form of non associative memory is olfactory
habituation, in which responsiveness to stable but behaviorally non significant stimuli is
decreased in relation to exposition [231, 232].
4 Multiple memory systems
In biology, a system is defined in terms of both structure and function. In its
application to the domain of memory, multiple memory systems is understood as the set
of different neurocognitive structures whose physiological workings produced the
introspectively apprehensible and objectively identifiable consequences of learning and
memory. The various memory systems can be distinguished in terms of its brain
mechanisms, the different kinds of information they process and the principles by which
they operate [233].
As it has been noted, early interpretations of memory assumed a unitary model that
could be used in many different ways [234, 235]. However, in most of the history of the
study of memory, dichotomous classifications of memory had been put to use, such as
procedural versus declarative [236], semantic and episodic [3,4], habit and
memory [6, 7, 184], dispositional and representational [237], taxon versus locale [5].
Although a minority, distinctions among three and even more memory systems have
also been put forward [170].
One of the earliest references to memory systems appeared in a 1972 paper by
Tulving [3]. There were other less known efforts in favor of memory systems such as the
1979 article by Warrington in which she discussed neuropsychological evidence
supporting a distinction between STM and LTM systems, and between two kinds of
LTM systems, namely event memory and semantic memory [238–240].
In the early 1980s, the cerebellum was discovered to be essential for delay eyeblink
conditioning [241] a form of learning preserved both in animals with hippocampal
lesions [242] and in severely amnesic patients [202]. Then, the striatum was identified as
important for the sort of gradual, feedback-guided learning that results in habit
19/36

memory [6, 218]. A similar contrast between declarative memory and habit memory was
later demonstrated for amnesic patients and patients with Parkinson’s disease [219].
Finally, it was shown that still other types of learning, which involve the attachment of
positive or negative valence to a stimulus, as in fear conditioning or conditioned place
preference, have an essential dependence on the amygdala [243–245].
Based on evidence from human studies, these and other models attempted to
embrace the large amount that has been learned about neuroanatomy, the molecular
and cellular biology of synaptic change, and the organization of brain systems. Work
with experimental animals, namely rats and monkeys without which a systematic study
of memory would have proved impossible, also supported the notion of multiple memory
systems.
Given this wide variety of evidence related to memory phenomena and its supporting
neural sustrates, in the mid 1980s the perspective abandoned an account of human
memory based on a two-part dichotomy and shifted to a more complex taxonomy [239].
Critically, the notion of non declarative memory was introduced and conceptualized as
an umbrella term referring to several memory systems supporting the wide panorama of
memory related phenomena found in human and animal research [189,233].
Figure 4.
Taxonomy of mammalian long term memory systems according to Squire [114].
The taxonomy lists the brain structures thought to be especially important for each form
of declarative and non declarative memory.
Sherry and Schacter approached the concept of memory systems from an
evolutionary perspective, proposing that different systems evolve as special adaptations
of information storage and retrieval for specific and functionally incompatible
purposes [16]. In their evolutionary view, Sherry and Shacter elaborate the idea of
functional incompatibility, examining components of this evolution such as natural
selection, heritable variation in memory, memory and reproductive success, and
adaptive specialization [246]. The notion assumes that in order to solve different
environmental problems, the animal must make feasible different requirements of the
information processing strategies, and that these different requirements can call for
distinct neural circuitries [148, 247].
The memory systems of the mammalian brain operate independently and in parallel
to support different behaviors. In some circumstances, memory systems are described as
working cooperatively to optimize behavior and in other circumstances are described as
working competitively. How they compete or substitute one for the other is a topic of
current interest [248
–
250]. Packard demonstrated the parallel works of multiple memory
systems in rats [251].
When the stratial caudate nucleus was inactive, the parallel memory system
supported by the hippocampus was unmasked. A similar stance has been described in
20/36

humans performing a virtual navigation task that could be solved by either a spatial or
nonspatial strategy [252]. As training progressed participants tended to shift to a
nonspatial strategy, then showing increased activity in the stratial caudate nucleus,
which emerged as training progressed. Although many tasks can be acquired by more
than one memory system, other tasks strongly favor one system over another.
Prefrontal cortex may be important in determining which memory system gains control
over behavior [253]. Several other factors increase the tendency to adopt one memory
system over another, in this case, a striatal strategy. In this sense, relevant evidence has
been obtained from studies of stress [254], and aging [255]. Although many tasks can be
acquired by more than one memory system, other tasks strongly favor one system over
another.
Similarly, a common feature of skill learning in humans is that trying to memorize,
and use declarative memory, can disrupt performance, as revealed by fMRI activity in
the MTL early during learning [256]. When learning progressed, activity decreased in
the MTL, and activity increased in the striatum. Moreover, when the task was modified
so as to encourage the use of declarative memory, less activity was observed in the
striatum and more activity was observed in the MTL.
Using these notions of multiple memory systems, researchers were increasingly more
able to place theoretical speculation within a neurobiological framework, thus reaching a
more accurate understanding and classification of memory.
Conclusion
The nature of memory and its organization has been central to discussion on memory
for several centuries. The evolution of the idea that there are multiple forms of memory,
each supported by a distinct brain system, began in the mid 20th century and is now
widely accepted and fundamental to the contemporary study of learning and
memory [1, 103, 139].
The multiple memory systems framework is supported by an enormous amount of
data learned in the past decades about neuroanatomy and cognitive neuroscience, and it
has been able to accommodate a large variety of empirical observations of memory
performance. It seems justifiable to conceptualize that the various memory components
of memory have distinct neural architectures and operational principles, and serve
different domain-specific purposes. Despite these memory systems operate
independently and in parallel to support different behaviors, in some circumstances,
memory systems may work cooperatively to optimize behavior and in other
circumstances work competitively. It is still debated, however, how to best characterize
their mutual relations and interactions. It remains beyond the scope of this article to
evaluate the strengths and weaknesses of all proposed distinctions between memory
systems.
A relevant implication of the multiple memory systems framework is that the
therapeutic targets for various kinds of memory disorders would demand different
interventions based on the known supporting neural architectures. Future investigation
that combine cognitive, neuropsychological and neuroimaging approaches will further
our understanding of the relations among the systems that together constitute the
foundation of memory. Therefore, it is foreseeable that the notion of multiple memory
systems remains dynamic, and that new specifications of memory systems emerge in the
future grounded on empirical evidence.
21/36

References
1. D. Schacter, A. Wagner, and R. Buckner. Memory systems of 1999. In
E. Tulving and F. I. M. Craik, editors, The Oxford handbook of memory, 2000.
2.
L. Squire. Memory and brain systems: 1969-2009. The Journal of Neuroscience,
29:12711 – 12716, 2009.
3. E. Tulving. Episodic and semantic memory. In E. Tulving and W. Donaldson,
editors, Organization of memory. Academic Press, 1972.
4. E. Tulving. Elements of episodic memory. Oxford University Press, 1983.
5. J. O’keefe and L. Nadel. The Hippocampus as a Cognitive Map. Oxford
University Press, 1978.
6.
M. Mishkin, B. Malamut, and J. Bachevalier. Memories and habits: Two neural
systems. In & N. M. Weinberger G. Lynch, J. L. McGaugh, editor, Neurobiology
of learning and memory. Guilford Press, New York, New York, USA, 1984.
7. M. Mishkin and H. L. Petri. Memories and habits: Some implications for the
analysis of learning and retention. In L. R. Squire and N. Butters, editors,
Neuropsychology of memory. Guilford Press, New York, New York, USA, 1984.
8. A. Baddeley and G. Hitch. Working memory. In Psychology of Learning and
Motivation, 1974.
9. A. Baddeley. Working Memory. Oxford University Press, 1986.
10. A. Baddeley. The episodic buffer: a new component of working memory?
Trends in Cognitive Sciences, 4:417–423, 2000.
11. P. Graf and D. Schacter. Implicit and explicit memory for new associations in
normal and amnesic subjects. Journal of experimental psychology. Learning,
memory, and cognition, 11 3:501–18, 1985.
12. D. Schacter. Implicit memory: History and current status. Journal of
Experimental Psychology: Learning, Memory, and Cognition, 13 3:501–518, 1987.
13.
L. Squire and S. Zola. Structure and function of declarative and nondeclarative
memory systems. Proceedings of the National Academy of Sciences of the United
States of America, 93 24:13515–22, 1996.
14. N. Cohen and H. Eichenbaum. Memory, amnesia, and the hippocampal system.
The MIT Press, 1993.
15. J. L. McClelland, B. McNaughton, and R. O’Reilly. Why there are
complementary learning systems in the hippocampus and neocortex: insights
from the successes and failures of connectionist models of learning and memory.
Psychological review, 102 3:419–457, 1995.
16. D. Sherry and D. Schacter. The evolution of multiple memory systems.
Psychological review, 94(4):439–454, 1987.
17. E. Engelhardt. Cerebral localization of higher functions: Memory-related
anatomic structures. Dementia & Neuropsychologia, 14:75 – 79, 2020.
18. B. Ziskind and B. Halioua. [concepts of the heart in ancient egypt]. Medecine
sciences : M/S, 20 3:367–73, 2004.
22/36

19.
A. A. Fanous and W. T. Couldwell. Transnasal excerebration surgery in ancient
egypt. Journal of Neurosurgery JNS, 116(4):743 – 748, 2012.
20. W. H. Burnham. Memory, historically and experimentally considered. The
American Journal of Psychology, 2(1):39–90, 1888.
21.
Aristotle and J. Sachs. Aristotle’s Metaphysics : a new translation. Green Lion
Press, 1999.
22. D. Bloch. Aristotle on Memory and Recollection. Brill, 2007.
23. D. Draaisma. Metaphors of memory. Cambridge University Press, 2000.
24.
R. Lo Presti. Localizing memory and recollection: The sixteenth-century italian
commentaries on aristotle’s de memoria et reminiscentia and the question
concerning the degrees of (dis)embodiment of the “psychic” processes. In The
Parva naturalia in Greek, Arabic and Latin Aristotelianism. Springer, 2018.
25. R. Sorabji. Aristotle On Memory. University of Chicago Press, 2006.
26. L.H. Marshall and H.W. Magoun. The ventricles and their functions. In
Discoveries in the Human Brain, Totowa, NJ, 1998. Humana Press.
27. K. W. Parry. Locating memory and imagination: From nemesius of emesa to
john of damascus. In Dreams, Memory and Imagination in Byzantium. Brill,
2018.
28. G. Panteleakos, E. Poulakou-Rebelakou, and M. Koutsilieris. Anatomy and
physiology in the work of nemesius of emesa ”on the nature of man”. Acta
medico-historica adriatica : AMHA, 11 2:319–28, 2013.
29. A. of Hippo. The Confessions of Saint Augustine. Modern Library, New York,
1999.
30. J. Cassel, D. Cassel, and L. Manning. From augustine of hippo´s memory
systems to our modern taxonomy in cognitive psychology and neuroscience of
memory: A 16-century nap of intuition before light of evidence. Behavioral
Sciences, 3:21 – 41, 2013.
31. A. Vesalius. The Fabric of the Human Body. An Annotated Translation of the
1543 and 1555 Editions of ”De Humani Corporis Fabrica Libri Septem”, by D.H.
Garrison and M.H. Hast. Karger International, 2014.
32. A. Wragge-Morley. Imagining the soul: Thomas willis (1621-1675) on the
anatomy of the brain and nerves. Progress in brain research, 243:55–73, 2018.
33. E. A. Urban. On matters of mind and body: regarding descartes. The Journal
of analytical psychology, 63 2:228–240, 2018.
34. A.H. Buck. The Dawn of Modern Medicine. Forgotten Books, 2009.
35.
S. Finger and P. Eling. Franz Joseph Gall: Naturalist of the Mind, Visionary of
the Brain. Oxford University Press, 2019.
36.
P. Eling and S. Finger. Franz joseph gall on the cerebellum as the organ for the
reproductive drive. Frontiers in Neuroanatomy, 13, 2019.
37. J. M. Pearce. Marie-jean-pierre flourens (1794-1867) and cortical localization.
European Neurology, 61:311 – 314, 2009.
23/36

38. P. Flourens. Examen de la phr´enologie. Paulin, Paris, 1842.
39. F. P. G. Maine de Biran. The influence of habit on the faculty of thinking.
Williams and Wilkins (first published in 1804), Baltimore, 1929.
40. D. Schacter and E. Tulving. What are the memory systems of 1994. In D. L.
Schacter & E. Tulving, editor, Memory systems 1994. The MIT Press, 1994.
41. R. Thompson. The neurobiology of learning and memory: William james in
retrospect. Psychological Science, 1:172 – 173, 1990.
42. S. L. Hawkins. William james, gustav fechner, and early psychophysics.
Frontiers in Physiology, 2, 2011.
43. H. L. Bergson. Matter and Memory (authorized translation by Nancy M. Paul
and W. Scott Palmer). Allen, London, 1910.
44.
T. Perri. Bergson’s philosophy of memory. Philosophy Compass, 9:837–847, 2014.
45. G. Ryle. The concept of mind. Hutchinson, San Francisco, 1949.
46. Hermann Ebbinghaus. Memory: a contribution to experimental psychology.
Annals of neurosciences, 20 4:155–6, 2013.
47. H. Ebbinghaus. ¨
Uber das Ged¨achtnis. WBG - Wissenschaftliche
Buchgesellschaft, Darmstadt, 2014.
48. H. Ebbinghaus, F. Klix, and H. Hagendorf. Human memory and cognitive
capabilities : mechanisms and performances. Humboldt University, Berlin, 1986.
49.
E. J. Newman and E. F. Loftus. Updating ebbinghaus on the science of memory.
Europe’s Journal of Psychology, 8:209–216, 2012.
50. M. Mishkin. Behaviorism, cognitivism and the neuropsychology of memory.
American Scientist, 82 1:30–37, 2016.
51. P. A. Ertmer and T. J. Newby. Behaviorism, cognitivism, constructivism:
Comparing critical features from an instructional design perspective.
Performance Improvement Quarterly, 26(2):43–71, 2013.
52. K. R. Clark. Learning theories: Behaviorism. Radiologic technology, 90
2:172–175, 2018.
53. J. B. Watson. Psychology as the behaviorist views it. Psychological Review, 20
2:158–177, 1913.
54.
P. M. Fitts. The information capacity of the human motor system in controlling
the amplitude of movement. Journal of experimental psychology, 47 6:381–91,
1954.
55. K. S. Lashley. In search of engram. In Society for Experimental Biology,
Physiological mechanisms in animal behavior. (Society’s Symposium IV.), page
454–482. Academic Press, 1988.
56.
K. Lashley. Brain Mechanisms and Intelligence. A quantitative study of injuries
to the brain. University of Chicago Press, 1929.
57. Jack Orbach and F. A. Beach. Neuropsychology after Lashley: fifty years since
the publication of Brain mechanisms and intelligence. Lawrence Erlbaum
Associates, 1982.
24/36

58.
G. L. Shaw. Donald hebb: The organization of behavior. In Aertsen A. Palm G.,
editor, Brain Theory, Berlin, 1986. Springer.
59.
G. M. Shepherd. Learning and memory: Donald hebb, brenda milner, and h. m.
In Creating Modern Neuroscience: The Revolutionary 1950s. Oxford University
Press, 2009.
60.
J. D. McGaugh. Memory–a century of consolidation. Science, 287 5451:248–51,
2000.
61. E. C. Tolman and I. Krechevsky. Means-end-readiness and hypothesis–a
contribution to comparative psychology. Psychological Review, 40(1):60–70,
1933.
62. E. C. Tolman and E. Brunswik. The organism and the causal texture of the
environment. Psychological Review, 42:43–77, 1935.
63. E. C. Tolman. Cognitive maps in rats and men. Psychological review, 55
4:189–208, 1948.
64. C. L. Hull. Principles of behavior : an introduction to behavior theory.
Appleton-Century, 1943.
65.
F. Restle. Discrimination of cues in mazes: a resolution of the place-vs.-response
question. Psychological review, 64 4:217–28, 1957.
66.
E. C. Tolman. Purposive behavior in animals and men. Century/Random House
UK, London, 1932.
67. E.C. Tolman. Behavior and psychological man. University of California Press,
1966.
68. D. Carroll. Purposive Behaviorism, page 99–124. Cambridge University Press,
2017.
69. J. Fodor. Modularity of mind. The MIT Press, 1983.
70. W. Scoville. The limbic lobe in man. Journal of neurosurgery, 11 1:64–6, 1954.
71.
B. Milner and W. Penfield. The effect of hippocampal lesions on recent memory.
Transactions of the American Neurological Association, 80th Meeting:42–8, 1955.
72.
W. Penfield and B. Milner. Memory deficit produced by bilateral lesions in the
hippocampal zone. A.M.A. archives of neurology and psychiatry, 79 5:475–97,
1958.
73. W. Scoville and B. Milner. Loss of recent memory after bilateral hippocampal
lesions. Journal of Neurology, Neurosurgery & Psychiatry, 20:11 – 21, 1957.
74.
H. Friedman and N. Allen. Chronic effects of complete limbic lobe destruction in
man. Neurology, 19:679 – 679, 1969.
75. D. Hebb and W. Penfield. Human behavior after extensive bilateral removal
from the frontal lobes. Arch NeurPsych, 44(2):421–438, 1940.
76. B. Milner. Psychological defects produced by temporal lobe excision. Research
publications - Association for Research in Nervous and Mental Disease,
36:244–57, 1958.
25/36

77.
B. Milner. Les troubles de la memoire accompagnant des lesions hippocampiques
bilaterales. In Physiologie de l’Hippocampe, Paris, 1962. C.N.R.S.
78. B. Milner. Effects of different brain lesions on card sorting: The role of the
frontal lobes. Arch Neurol., 9(1):90–100, 1963.
79. L. Squire. The legacy of patient h.m. for neuroscience. Neuron, 61:6–9, 2009.
80. S. Baxendale. Amnesia in temporal lobectomy patients: Historical perspective
and review. Seizure, 7:15–24, 1998.
81.
W. Freeman and J. W. Watts. An interpretation of the functions of the frontal
lobe. The Yale Journal of Biology and Medicine, 11:527 – 539, 1939.
82. J. L. Finan. Effects of frontal lobe lesions on temporally organized behavior in
monkeys. Journal of Neurophysiology, 2(3):208–226, 1939.
83. J. Orbach, B. Milner, and T. Rasmussen. Learning and retention in monkeys
after amygdala-hippocampus resection. Archives of neurology, 3:230–51, 1960.
84. G. Kimble. Psychology as a science. The Scientific Monthly, 77(3):156–160,
1953.
85. R. Atkinson and R. Shiffrin. Human memory: A proposed system and its
control processes. In Psychology of Learning and Motivation, 1968.
86. M. Coltheart. Iconic memory and visible persistence. Perception &
Psychophysics, 27:183–228, 1980.
87. J. Brown. Some tests of the decay theory of immediate memory. Quarterly
Journal of Experimental Psychology, 10:12 – 21, 1958.
88. T.J. Ricker, E. Vergauwe, and N. Cowan. Decay theory of immediate memory:
From brown (1958) to today (2014). Quarterly Journal of Experimental
Psychology, 69:1969 – 1995, 2016.
89. J. Fuster and G. E. Alexander. Neuron activity related to short-term memory.
Science, 173:652 – 654, 1971.
90. J. Fuster. Anatomy of the prefrontal cortex. In The Prefrontal Cortex.
Academic Press, 2008.
91.
G. Williams and P. Goldman-Rakic. Modulation of memory fields by dopamine
dl receptors in prefrontal cortex. Nature, 376:572–575, 1995.
92. F. I. Craik and M. J. Watkins. The role of rehearsal in short-term memory.
Journal of Verbal Learning & Verbal Behavior, 12(6):599–607, 1973.
93. F. Craik and R. Lockhart. Levels of processing: A framework for memory
research. Journal of Verbal Learning & Verbal Behavior, 11(6):671–684, 1972.
94. N. Cowan. The magical number 4 in short-term memory: a reconsideration of
mental storage capacity. The Behavioral and brain sciences, 24 1:87–114;
discussion 114–85, 2001.
95. A. Baddeley and G. Hitch. Developments in the concept of working memory.
Neuropsychology, 8(4):485–493, 1994.
96. T. Shallice. Specific impairments of planning. Philosophical transactions of the
Royal Society of London. Series B, Biological sciences, 298 1089:199–209, 1982.
26/36

97. J. M. Fuster. The prefrontal cortex—an update time is of the essence. Neuron,
30:319–333, 2001.
98. E. Rich and M. Shapiro. Rat prefrontal cortical neurons selectively code
strategy switches. The Journal of Neuroscience, 29:7208 – 7219, 2009.
99. L. Squire. Declarative and nondeclarative memory: Multiple brain systems
supporting learning and memory. Journal of Cognitive Neuroscience, 4:232–243,
1992.
100.
A. Baddeley. Essentials of Human Memory (Classic Edition). Psychology Press,
London, 2013.
101. L. Squire and E. Kandel. Memory: From Mind to Molecules. Scientific
American Library, 1999.
102. G. Buzs´aki. Theta oscillations in the hippocampus. Neuron, 33:325–340, 2002.
103. H. Eichenbaum and N. Cohen. From conditioning to conscious recollection:
Memory systems of the brain. In Oxford psychology series; no. 35. Oxford
University Press, 2001.
104.
E. Warrington and L. Weiskrantz. A study of learning and retention in amnesic
patients. Neuropsychologia, 6(3):283–291, 1968.
105. E. K. Warrington and L. Weiskrantz. New method of testing long-term
retention with special reference to amnesic patients. Nature, 217:972–974, 1968.
106. L. M. Raskin. Long-term perceptual memory in children with learning
disabilities. Journal of Learning Disabilities, 4:182 – 185, 1971.
107. D. Schacter and H. F. Crovitz. Memory function after closed head injury: A
review of the quantitative research. Cortex, 13:150–176, 1977.
108. E. Tulving, D. Schacter, and H. A. Stark. Priming effects in word-fragment
completion are independent of recognition memory. Journal of Experimental
Psychology: Learning, Memory, and Cognition, 8(4):336–342, 1982.
109. E. Tulving, D. Schacter, D. McLachlan, and M. Moscovitch. Priming of
semantic autobiographical knowledge: A case study of retrograde amnesia.
Brain and Cognition, 8:3–20, 1988.
110. L. Squire and J. Wixted. The cognitive neuroscience of human memory since
h.m. Annual review of neuroscience, 34:259–88, 2011.
111. N. Cohen and L. Squire. Preserved learning and retention of pattern-analyzing
skill in amnesia: dissociation of knowing how and knowing that. Science, 210
4466:207–10, 1980.
112. B. Milner, S. Corkin, and H.L. Teuber. Further analysis of the hippocampal
amnesic syndrome: 14-year follow-up study of h.m. Neuropsychologia,
6(3):215–234, 1968.
113. K. Patterson, P. Nestor, and T. Rogers. Where do you know what you know?
the representation of semantic knowledge in the human brain. Nature Reviews
Neuroscience, 8:976–987, 2007.
114.
L. Squire. Memory systems of the brain: A brief history and current perspective.
Neurobiology of Learning and Memory, 82:171–177, 2004.
27/36

115. L. Squire and S. Zola-Morgan. The medial temporal lobe memory system.
Science, 253:1380 – 1386, 1991.
116.
A. Baddeley, O. Bueno, L. Cahill, J. Fuster, I. Izquierdo, J. D. McGaugh, R. G.
Morris, L. Nadel, A. Routtenberg, G. Xavier, and C. da Cunha. The brain
decade in debate: I. neurobiology of learning and memory. Brazilian journal of
medical and biological research, 33 9:993–1002, 2000.
117. J. Gabrieli, J. Brewer, and R. Poldrack. Images of medial temporal lobe
functions in human learning and memory. Neurobiology of Learning and
Memory, 70:275–283, 1998.
118. A. R. Preston, D. Shohamy, C. Tamminga, and A. Wagner. Hippocampal
function, declarative memory, and schizophrenia: Anatomic and functional
neuroimaging considerations. Current Neurology and Neuroscience Reports,
5:249–256, 2005.
119. L. Squire. Mechanisms of memory. Lancet, 1 7586:140–2, 1969.
120.
L. Nadel and M. Moscovitch. Memory consolidation, retrograde amnesia and the
hippocampal complex. Current Opinion in Neurobiology, 7:217–227, 1997.
121. J. Aggleton and M. Brown. Episodic memory, amnesia, and the
hippocampal-anterior thalamic axis. The Behavioral and brain sciences, 22
3:425–44; discussion 444–89, 1999.
122.
N. Cohen, R. Poldrack, and H. Eichenbaum. Memory for items and memory for
relations in the procedural/declarative memory framework. Memory, 5
1-2:131–78, 1997.
123. E. Tulving. Memory: Performance, knowledge, and experience. European
Journal of Cognitive Psychology, 1(1):3–26, 1989.
124. A. Shimamura, J. S. Janowsky, and L. Squire. What is the role of frontal lobe
damage in memory disorders. In & A. L. Benton H. S. Levin, H. M. Eisenberg,
editor, Frontal lobe function and dysfunction. Oxford University Press, 1991.
125. P. Hal´asz. The relationship of medial temporal lobe epilepsy with the
declarative memory system. Journal of Epileptology, 24:157–165, 2016.
126. G. Stebbins, M. Carrillo, J. Dorfman, Courtney L Dirksen, J. Desmond,
D. Turner, D. Bennett, R. Wilson, G. Glover, and J. Gabrieli. Aging effects on
memory encoding in the frontal lobes. Psychology and aging, 17 1:44–55, 2002.
127. M. Moscovitch, R. Westmacott, A. Gilboa, D. Addis, R. Rosenbaum,
I. Viskontas, S. Priselac, E. Svoboda, M. Ziegler, S. Black, F. Gao, C. Grady,
M. Freedman, S. K¨ohler, L. Leach, B. Levine, M. McAndrews, L. Nadel,
G. Proulx, B. Richards, L. Ryan, K. A. Stokes, and G. Winocur. Hippocampal
complex contribution to retention and retrieval of recent and remote episodic
and semantic memories: Evidence from behavioral and neuroimaging studies of
healthy and brain-damaged people. In Dynamic Cognitive Processes. Springer,
2005.
128. L. Tommasi, M. Peterson, and L. Nadel. Cognitive Biology: Evolutionary and
Developmental Perspectives on Mind, Brain, and Behavior. The MIT Press,
2009.
28/36

129. H. Praag, A. F. Schinder, B. Christie, N. Toni, T. Palmer, and F. Gage.
Functional neurogenesis in the adult hippocampus. Nature, 415:1030–1034, 2002.
130. L. Nadel and S. Zola-Morgan. Infantile amnesia: A neurobiological perspective.
In M. Moscovitch, editor, Infant Memory, pages 145–172. Plenum Press, 1984.
131. A. Travaglia, R. Bisaz, E. S. Sweet, R. Blitzer, and C. Alberini. Infantile
amnesia reflects a developmental critical period for hippocampal learning.
Nature neuroscience, 19:1225 – 1233, 2016.
132. H. B. Madsen and J. H. Kim. Ontogeny of memory: An update on 40 years of
work on infantile amnesia. Behavioural Brain Research, 298:4–14, 2016.
133. J. Edgin, G. Span`o, K. Kawa, and L. Nadel. Remembering things without
context: development matters. Child development, 85 4:1491–502, 2014.
134. J. O Edgin, Y. Liu, K. L. Hughes, G. Span`o, and C. A. C. Clark. The ”eyes
have it,” but when in development?: The importance of a developmental
perspective in our understanding of behavioral memory formation and the
hippocampus. Hippocampus, 2019.
135. E. Tulving. Concepts of human memory. In L. R. Squire, N. M. Weinberger,
G. Lynch, and J. L. McGaugh, editors, Memory: Organization and locus of
change. Oxford University Press, 1991.
136.
E. Glisky, D. Schacter, and E. Tulving. Computer learning by memory-impaired
patients: Acquisition and retention of complex knowledge. Neuropsychologia,
24:313–328, 1986.
137. P. Bayley, R. O’Reilly, T. Curran, and L. Squire. New semantic learning in
patients with large medial temporal lobe lesions. Hippocampus, 18 6:575–83,
2008.
138. E. Tulving, C. Hayman, and C. Macdonald. Long-lasting perceptual priming
and semantic learning in amnesia: a case experiment. Journal of experimental
psychology. Learning, memory, and cognition, 17 4:595–617, 1991.
139.
L. Squire, C. Stark, and R. E. Clark. The medial temporal lobe. Annual review
of neuroscience, 27:279–306, 2004.
140. B. Staresina, K. Duncan, and L. Davachi. Perirhinal and parahippocampal
cortices differentially contribute to later recollection of object- and scene-related
event details. The Journal of Neuroscience, 31:8739 – 8747, 2011.
141. L. Davachi. Item, context and relational episodic encoding in humans. Current
Opinion in Neurobiology, 16:693–700, 2006.
142. J. Janowsky, A. Shimamura, and L. Squire. Source memory impairment in
patients with frontal lobe lesions. Neuropsychologia, 27:1043–1056, 1989.
143. A. Shimamura and L. Squire. A neuropsychological study of fact memory and
source amnesia. Journal of experimental psychology. Learning, memory, and
cognition, 13 3:464–73, 1987.
144. A. D. Redish. Beyond the cognitive map: From place cells to episodic memory.
The MIT Press, 1999.
29/36

145. T. Suddendorf and M. Corballis. Mental time travel and the evolution of the
human mind. Genetic, social, and general psychology monographs, 123 2:133–67,
1997.
146. H. Eichenbaum, T. Otto, and N. Cohen. Two functional components of the
hippocampal memory system. Behavioral and Brain Sciences, 17:449–472, 1994.
147.
E. Tulving. Episodic memory: from mind to brain. Annual review of psychology,
53:1–25, 2002.
148. D. Schacter, D. Addis, D. Hassabis, V. C. Mart´ın, R. N. Spreng, and
K. Szpunar. The future of memory: Remembering, imagining, and the brain.
Neuron, 76:677–694, 2012.
149. M. Howard and H. Eichenbaum. Time and space in the hippocampus. Brain
Research, 1621:345–354, 2015.
150. D. Schiller, H. Eichenbaum, E. Buffalo, L. Davachi, D. Foster, S. Leutgeb, and
C. Ranganath. Memory and space: Towards an understanding of the cognitive
map. The Journal of Neuroscience, 35:13904 – 13911, 2015.
151.
D. Hassabis, D. Kumaran, S. Vann, and E. Maguire. Patients with hippocampal
amnesia cannot imagine new experiences. Proceedings of the National Academy
of Sciences, 104:1726 – 1731, 2007.
152.
A. Lundervold, D. Wollschl¨ager, and E. Wehling. Age and sex related changes in
episodic memory function in middle aged and older adults. Scandinavian
Journal of Psychology, 55:225 – 232, 2014.
153. F. Pauls, F. Petermann, and A. C. Lepach. Gender differences in episodic
memory and visual working memory including the effects of age. Memory,
21:857 – 874, 2013.
154.
A. Herlitz, E. Airaksinen, and E. Nordstr¨om. Sex differences in episodic memory:
the impact of verbal and visuospatial ability. Neuropsychology, 13 4:590–7, 1999.
155. N. Persson, J. Wu, Q. Zhang, T. Liu, Jing Shen, Ruyi Bao, M. Ni, Yi Wang,
and P. Spincemaille. Age and sex related differences in subcortical brain iron
concentrations among healthy adults. NeuroImage, 122:385–398, 2015.
156. T. Hafting, M. Fyhn, S. Molden, M. Moser, and E. Moser. Microstructure of a
spatial map in the entorhinal cortex. Nature, 436:801–806, 2005.
157.
F. Savelli, D. Yoganarasimha, and J. Knierim. Influence of boundary removal on
the spatial representations of the medial entorhinal cortex. Hippocampus, 18
12:1270–82, 2008.
158. M. Hasselmo. A model of episodic memory: Mental time travel along encoded
trajectories using grid cells. Neurobiology of Learning and Memory, 92:559–573,
2009.
159.
R. Hayman and K. Jeffery. How heterogeneous place cell responding arises from
homogeneous grids–a contextual gating hypothesis. Hippocampus, 18 12:1301–13,
2008.
160. T. Shallice, P. Fletcher, C. Frith, P. Grasby, R. Frackowiak, and R. Dolan.
Brain regions associated with acquisition and retrieval of verbal episodic
memory. Nature, 368:633–635, 1994.
30/36

161.
C. Frith and R. Dolan. Brain mechanisms associated with top-down processes in
perception. Philosophical transactions of the Royal Society of London. Series B,
Biological sciences, 352 1358:1221–30, 1997.
162. C. Kirwan, J. Wixted, and L. Squire. Activity in the medial temporal lobe
predicts memory strength, whereas activity in the prefrontal cortex predicts
recollection. The Journal of Neuroscience, 28:10541 – 10548, 2008.
163. D. Schacter, D. Addis, and R. Buckner. Remembering the past to imagine the
future: the prospective brain. Nature Reviews Neuroscience, 8:657–661, 2007.
164.
E. Maguire and D. Hassabis. Role of the hippocampus in imagination and future
thinking. Proceedings of the National Academy of Sciences, 108:E39 – E39, 2011.
165. R. Buckner. Prospection and the brain. Behavioral and Brain Sciences,
30:318–319, 2007.
166. C. Atance and D. K. O’Neill. Episodic future thinking. Trends in Cognitive
Sciences, 5:533–539, 2001.
167. C. Atance. Future thinking in young children. Current Directions in
Psychological Science, 17:295 – 298, 2008.
168. C. Atance, S. Nur Celebi, S. Mitchinson, and C. E. V. Mahy. Thinking about
the future: Comparing children’s forced-choice versus ”generative” responses in
the ”spoon test”. Journal of experimental child psychology, 181:1–16, 2019.
169. R. Rosenbaum, S. K¨ohler, D. Schacter, M. Moscovitch, and E. Tulving. The
case of k.c.: contributions of a memory-impaired person to memory theory.
Neuropsychologia, 43:989–1021, 2005.
170. E. Tulving. How many memory systems are there. American Psychologist,
40:385–398, 1985.
171. S. Klein, J. Loftus, and J. Kihlstrom. Memory and temporal experience: The
effects of episodic memory loss on an amnesic patient’s ability to remember the
past and imagine the future. Social Cognition, 20:353–379, 2002.
172.
D. Marr. Simple memory: a theory for archicortex. Philosophical transactions of
the Royal Society of London. Series B, Biological sciences, 262 841:23–81, 1971.
173. K. Norman and R. O’Reilly. Modeling hippocampal and neocortical
contributions to recognition memory: a complementary-learning-systems
approach. Psychological review, 110 4:611–46, 2003.
174. T. Tsukiura, T. Fujii, T. Takahashi, R. Xiao, M. Sugiura, J. Okuda, T. Iijima,
and A. Yamadori. Medial temporal lobe activation during context-dependent
relational processes in episodic retrieval: An fmri study. Human Brain Mapping,
17:203–213, 2002.
175.
K. Szpunar, J. Watson, and K. McDermott. Neural substrates of envisioning the
future. Proceedings of the National Academy of Sciences, 104:642 – 647, 2007.
176. D. L. Greenberg and M. Verfaellie. Interdependence of episodic and semantic
memory: evidence from neuropsychology. Journal of the International
Neuropsychological Society : JINS, 16 5:748–53, 2010.
31/36

177. L. Renoult, P. S. Davidson, D. Palombo, M. Moscovitch, and B. Levine.
Personal semantics: at the crossroads of semantic and episodic memory. Trends
in Cognitive Sciences, 16:550–558, 2012.
178. M. Grilli and M. Verfaellie. Personal semantic memory: Insights from
neuropsychological research on amnesia. Neuropsychologia, 61:56–64, 2014.
179.
S. L. Thompson-Schill, M. D’Esposito, G. K. Aguirre, and M. Farah. Role of left
inferior prefrontal cortex in retrieval of semantic knowledge: a reevaluation.
Proceedings of the National Academy of Sciences of the United States of
America, 94 26:14792–7, 1997.
180.
T. Atir-Sharon, A. Gilboa, H. Hazan, E. Koilis, and L. Manevitz. Decoding the
formation of new semantics: Mvpa investigation of rapid neocortical plasticity
during associative encoding through fast mapping. Neural Plasticity, 2015, 2015.
181.
M. N. Coutanche and S. L. Thompson-Schill. Creating concepts from converging
features in human cortex. Cerebral cortex, 25 9:2584–93, 2015.
182. S. Cappa. Imaging studies of semantic memory. Current Opinion in Neurology,
21:669–675, 2008.
183. D. Gaffan. Recognition impaired and association intact in the memory of
monkeys after transection of the fornix. Journal of comparative and physiological
psychology, 86 6:1100–9, 1974.
184. R. Hirsh. The hippocampus and contextual retrieval of information from
memory: a theory. Behavioral biology, 12 4:421–44, 1974.
185. W. C. Benzing and L. Squire. Preserved learning and memory in amnesia:
intact adaptation-level effects and learning of stereoscopic depth. Behavioral
neuroscience, 103-3:538–47, 1989.
186. B. Knowlton, S. J. Ramus, and L. Squire. Intact artificial grammar learning in
amnesia: Dissociation of classification learning and explicit memory for specific
instances. Psychological Science, 3:172 – 179, 1992.
187. B. Knowlton and L. Squire. The learning of categories: parallel brain systems
for item memory and category knowledge. Science, 262 5140:1747–9, 1993.
188.
T. Winograd. Frame representations and the declarative/procedural controversy.
In D.G. Bobrow and A. Collins, editors, Representation and Understanding,
pages 185 – 210. Morgan Kaufmann, San Diego, 1975.
189.
L. Squire and S. Zola-Morgan. Memory: brain systems and behavior. Trends in
Neurosciences, 11:170–175, 1988.
190. M. W. Alibali and K. R. Koedinger. The developmental progression from
implicit to explicit knowledge: A computational approach. Behavioral and Brain
Sciences, 22(5):755–756, 1999.
191. T. Kolling, F. Graf, and M. Knopf. Cross cultural perspectives on declarative
and nondeclarative memory from infancy to early childhood. Child Development
Perspectives, 10:28–32, 2016.
32/36

192. I. A. V¨ohringer, T. Kolling, F. Graf, S. Poloczek, I. Fassbender, C. Freitag,
B. Lamm, J. Suhrke, J. Teiser, M. Teubert, H. Keller, A. Lohaus, G. Schwarzer,
and M. Knopf. The development of implicit memory from infancy to childhood:
On average performance levels and interindividual differences. Child
development, 89 2:370–382, 2018.
193. D. Fleischman. Repetition priming in aging and alzheimer’s disease: An
integrative review and future directions. Cortex, 43:889–897, 2007.
194. P. E. J. Spaan and J. G. W. Raaijmakers. Priming effects from young-old to
very old age on a word-stem completion task: Minimizing explicit contamination.
Aging, Neuropsychology, and Cognition, 18:107 – 86, 2011.
195.
E. V. Ward, C. J. Berry, and D. R. Shanks. Age effects on explicit and implicit
memory. Frontiers in Psychology, 4, 2013.
196.
D. E. Hannula and A. J. Greene. The hippocampus reevaluated in unconscious
learning and memory: at a tipping point? Frontiers in Human Neuroscience, 6,
2012.
197. D. Shohamy and N. Turk-Browne. Mechanisms for widespread hippocampal
involvement in cognition. Journal of experimental psychology. General, 142
4:1159–70, 2013.
198.
M. Chun and E. Phelps. Memory deficits for implicit contextual information in
amnesic subjects with hippocampal damage. Nature Neuroscience, 2:844–847,
1999.
199.
H. E. Schendan, M. Searl, R. Melrose, and C. Stern. An fmri study of the role of
the medial temporal lobe in implicit and explicit sequence learning. Neuron,
37:1013–1025, 2003.
200. E. Heyselaar, K. Segaert, S. J. W. Walvoort, R. P. C. Kessels, and P. Hagoort.
The role of nondeclarative memory in the skill for language: Evidence from
syntactic priming in patients with amnesia. Neuropsychologia, 101:97–105, 2017.
201. D. McCormick, D. Lavond, G. Clark, R. Kettner, Christina E. Rising, and
R. Thompson. The engram found? role of the cerebellum in classical
conditioning of nictitating membrane and eyelid responses. Bulletin of the
Psychonomic Society, 18(3):103–105, 1981.
202.
R. E. Clark and L. Squire. Classical conditioning and brain systems: the role of
awareness. Science, 280 5360:77–81, 1998.
203. D. Schacter. Memory and awareness. Science, 280:59 – 60, 1998.
204. R. Thompson and J. Steinmetz. The role of the cerebellum in classical
conditioning of discrete behavioral responses. Neuroscience, 162:732–755, 2009.
205.
E. Tulving and D. Schacter. Priming and human memory systems. Science, 247
4940:301–6, 1990.
206.
D. Schacter and R. Buckner. Priming and the brain. Neuron, 20:185–195, 1998.
207. P. Graf and G. Mandler. Activation makes words more accessible, but not
necessarily more retrievable. Journal of Verbal Learning & Verbal Behavior,
23(5):553–568, 1984.
33/36

208.
S. Hamann and L. Squire. Intact perceptual memory in the absence of conscious
memory. Behavioral neuroscience, 111 4:850–4, 1997.
209.
C. Stark and L. Squire. Recognition memory and familiarity judgments in severe
amnesia: no evidence for a contribution of repetition priming. Behavioral
neuroscience, 114 3:459–67, 2000.
210. D. Levy, C. Stark, and L. Squire. Intact conceptual priming in the absence of
declarative memory. Psychological Science, 15:680 – 686, 2004.
211.
A. Bechara, D. Tranel, H. Damasio, R. Adolphs, C. Rockland, and A. Damasio.
Double dissociation of conditioning and declarative knowledge relative to the
amygdala and hippocampus in humans. Science, 269:1115 – 1118, 1995.
212. S. Hamann and H. Mao. Positive and negative emotional verbal stimuli elicit
activity in the left amygdala. Neuroreport, 13:15–19, 2002.
213. G. Quirk and D. Mueller. Neural mechanisms of extinction learning and
retrieval. Neuropsychopharmacology, 33:56–72, 2008.
214. J. Mcgaugh and B. Roozendaal. Emotional hormones and memory modulation.
In Larry Squire, editor, Encyclopedia of Neuroscience. Springer, 2009.
215.
L. Cahill, B. Roozendaal, and J. L. McGaugh. The neurobiology of memory for
aversive emotional events. In M. E. Bouton & M. S. Fanselow, editor, Learning,
motivation, and cognition: The functional behaviorism of Robert C. Bol les.
American Psychological Association, 1997.
216.
L. Cahill, M. Uncapher, L. A. Kilpatrick, M. Alkire, and J. Turner. Sex-related
hemispheric lateralization of amygdala function in emotionally influenced
memory: an fmri investigation. Learning & memory, 11 3:261–6, 2004.
217. B. Roozendaal and J. L. McGaugh. Memory modulation. Behavioral
Neuroscience, 125(6):797–824, 2011.
218. M. G. Packard, R. Hirsh, and N. White. Differential effects of fornix and
caudate nucleus lesions on two radial maze tasks: evidence for multiple memory
systems. In The Journal of neuroscience : the official journal of the Society for
Neuroscience, 1989.
219.
B. Knowlton, J. Mangels, and L. Squire. A neostriatal habit learning system in
humans. Science, 273:1399 – 1402, 1996.
220. A. Dickinson. Actions and habits: the development of behavioural autonomy.
Philosophical Transactions, 308 1135:67–68, 1985.
221. M. Liljeholm and J. O’Doherty. Contributions of the striatum to learning,
motivation, and performance: an associative account. Trends in Cognitive
Sciences, 16:467–475, 2012.
222. D. N. Brooks and A. Baddeley. What can amnesic patients learn?
Neuropsychologia, 14:111–122, 1976.
223. M. J. Nissen and P. Bullemer. Attentional requirements of learning: Evidence
from performance measures. Cognitive Psychology, 19:1–32, 1987.
224.
L. Squire and M. Frambach. Cognitive skill learning in amnesia. Psychobiology,
18(1):109–117, 1990.
34/36

225. S. Haber, J. Fudge, and N. McFarland. Striatonigrostriatal pathways in
primates form an ascending spiral from the shell to the dorsolateral striatum.
The Journal of Neuroscience, 20:2369 – 2382, 2000.
226.
A. Kreitzer. Physiology and pharmacology of striatal neurons. Annual review of
neuroscience, 32:127–47, 2009.
227. W. Schultz. Updating dopamine reward signals. Current Opinion in
Neurobiology, 23:229 – 238, 2013.
228.
P. Groves and R. Thompson. Habituation: a dual-process theory. Psychological
review, 77 5:419–50, 1970.
229. S. Prescott. Interactions between depression and facilitation within neural
networks: updating the dual-process theory of plasticity. Learning & memory, 5
6:446–66, 1998.
230. D. Glanzman. Common mechanisms of synaptic plasticity in vertebrates and
invertebrates. Current Biology, 20:R31–R36, 2010.
231. R. Pellegrino, K. Usik, J. Warr, T. Hummel, and A. Sorokowska.
Electrophysiological investigation of associative and non associative memory
odours. Flavour and Fragrance Journal, 34:211–216, 2019.
232. D. Wilson, S. Watanabe, H. Milner, and J. A. Ainge. Lateral entorhinal cortex
is necessary for associative but not nonassociative recognition memory.
Hippocampus, 23:1280 – 1290, 2013.
233. D.L. Schacter and E. Tulving. Memory systems 1994. The MIT Press, Boston
MA, 1994.
234. M. Humphreys, J. D. Bain, and R. Pike. Different ways to cue a coherent
memory system: A theory for episodic, semantic, and procedural tasks.
Psychological Review, 96(2):208–233, 1989.
235. H. Roediger, M. S. Weldon, and B. Challis. Explaining dissociations between
implicit and explicit measures of retention: A processing account. In H. L.
Roediger III & F. I. M. Craik, editor, Varieties of memory and consciousness:
Essays in honour of Endel Tulving. Lawrence Erlbaum Associates, 1989.
236. N. Cohen. Preserved learning capacity in amnesia: Evidence for multiple
memory systems. Behavioral Neuroscience, 103 3:538–547, 1984.
237.
G. Thomas and P. S. Spafford. Deficits for representational memory induced by
septal and cortical lesions (singly and combined) in rats. Behavioral
neuroscience, 98 3:394–404, 1984.
238.
E. Warrington. Neuropsychological evidence for multiple memory systems. Ciba
Foundation symposium, 69:153–66, 1979.
239. E. Tulving. Memory and consciousness. Canadian Psychology/Psychologie
canadienne, 26(1):1–12, 1985.
240. M. R. Polster, L. Nadel, and D. Schacter. Cognitive neuroscience analyses of
memory: A historical perspective. Journal of Cognitive Neuroscience, 3:95–116,
1991.
35/36

241. D. McCormick, G. Clark, D. Lavond, and R. Thompson. Initial localization of
the memory trace for a basic form of learning. Proceedings of the National
Academy of Sciences of the United States of America, 79 8:2731–5, 1982.
242. L. W. Schmaltz and J. Theios. Acquisition and extinction of a classically
conditioned response in hippocampectomized rabbits (oryctolagus cuniculus).
Journal of comparative and physiological psychology, 79 2:328–33, 1972.
243. M. Davis. The role of the amygdala in fear and anxiety. Annual review of
neuroscience, 15:353–75, 1992.
244. R. G. Phillips and J. LeDoux. Differential contribution of amygdala and
hippocampus to cued and contextual fear conditioning. Behavioral neuroscience,
106 2:274–85, 1992.
245.
E. Phelps and J. LeDoux. Contributions of the amygdala to emotion processing:
From animal models to human behavior. Neuron, 48:175–187, 2005.
246. D. Sherry, L. F. Jacobs, and S. Gaulin. Spatial memory and adaptive
specialization of the hippocampus. Trends in Neurosciences, 15:298–303, 1992.
247. D. Schacter. Searching for memory : the brain, the mind, and the past. Basic
Books, 1996.
248. M. G. Packard and J. Goodman. Factors that influence the relative use of
multiple memory systems. Hippocampus, 23 11:1044–52, 2013.
249. O. Lungu, O. Monchi, G. Albouy, T. Jubault, E. Ballarin, Y. Burnod, and
J. Doyon. Striatal and hippocampal involvement in motor sequence chunking
depends on the learning strategy. PLoS ONE, 9, 2014.
250. S. Goodroe, J. Starnes, and T. I. Brown. The complex nature of
hippocampal-striatal interactions in spatial navigation. Frontiers in Human
Neuroscience, 12, 2018.
251. M. G. Packard and J. D. McGaugh. Inactivation of hippocampus or caudate
nucleus with lidocaine differentially affects expression of place and response
learning. Neurobiology of Learning and Memory, 65:65–72, 1996.
252. G. Iaria, M. Petrides, A. Dagher, B. Pike, and V. Bohbot. Cognitive strategies
dependent on the hippocampus and caudate nucleus in human navigation:
Variability and change with practice. The Journal of Neuroscience, 23:5945 –
5952, 2003.
253. R.J. McDonald and N.S. Hong. How does a specific learning and memory
system in the mammalian brain gain control of behavior? Hippocampus,
23(11):1084–1102, 2013.
254.
L. Schwabe and O. Wolf. Stress and multiple memory systems: from thinking to
doing. Trends in Cognitive Sciences, 17:60–68, 2013.
255. K. Konishi and V. Bohbot. Spatial navigational strategies correlate with gray
matter in the hippocampus of healthy older adults tested in a virtual maze.
Frontiers in Aging Neuroscience, 5, 2013.
256. R. Poldrack and J. Gabrieli. Characterizing the neural mechanisms of skill
learning and repetition priming: evidence from mirror reading. Brain : a
journal of neurology, 124 Pt 1:67–82, 2001.
36/36