Alessandro Treves

Scuola Internazionale Superiore di Studi Avanzati di Trieste | SISSA · Area of Neuroscience

Under what conditions can prefrontal cortex direct the composition of brain states, to generate coherent streams of thoughts? Using a simplified Potts model of cortical dynamics, crudely differentiated into two halves, we show that once activity levels are regulated, so as to disambiguate a single temporal sequence, whether the contents of the sequ...

Rather than a natural product, a computational analysis leads us to characterize déjà vu as a failure of memory retrieval, linked to the activation in neocortex of familiar items from a compositional memory in the absence of hippocampal input, and to a misappropriation by the self of what is of others.

Hippocampal place cells in bats flying in a 200m tunnel have been shown to be active at multiple locations, with considerable variability in place field size and peak rate. We ask whether such disorderly representation of one's own position in a large environment could be stored in memory through Hebbian plasticity, and be later retrieved from a pa...

Under what conditions can prefrontal cortex direct the composition of brain states, to generate coherent streams of thoughts? Using a simplified Potts model of cortical dynamics, crudely differentiated into two halves, we show that once activity levels are regulated, so as to disambiguate a single temporal sequence, whether the contents of the sequ...

We introduce, in a previously studied Potts model of long-range cortical interactions, a differentiation between a frontal and a posterior subnetwork. ``Frontal'' units, representing patches of anterior cortex, are endowed with a higher number $S$ of attractor states, in keeping with the larger number of local synaptic contacts of neurons there, th...

To fully embrace situations of radical uncertainty, we argue that the theory should abandon the requirements that narratives, in general, must lead to affective evaluation, and that they have to explain (and potentially simulate) all or even the bulk of the current decisional context. Evidence from studies of incidental learning show that narrative...

We introduce, in a previously studied Potts model of long-range cortical interactions, a differentiation between a frontal and a posterior subnetwork. "Frontal'' units, representing patches of anterior cortex, are endowed with a higher number $S$ of attractor states, in keeping with the larger number of local synaptic contacts of neurons there, tha...

To test the idea that poetic meter emerged as a cognitive schema to aid verbal memory, we focused on classical Italian poetry and on three components of meter: rhyme, accent, and verse length. Meaningless poems were generated by introducing prosody-invariant non-words into passages from Dante’s Divina Commedia and Ariosto’s Orlando Furioso. We then...

We consider a model of associative storage and retrieval of compositional memories in an extended cortical network. Our model network is comprised of Potts units, which represent patches of cortex, interacting through long-range connections. The critical assumption is that a memory, for example of a spatial view, is composed of a limited number of...

We consider a model of associative storage and retrieval of compositional memories in an extended cortical network. Our model network is comprised of Potts units, which represent patches of cortex, interacting through long-range connections. The critical assumption is that a memory is composed of a limited number of items, each of which has a pre-e...

Incidental memory can be challenged by increasing either the retention delay or the memory load. The dorsal hippocampus (dHP) appears to help with both consolidation from short-term (STM) to long-term memory (LTM), and higher memory loads, but the mechanism is not fully understood. Here we find that female mice, despite having the same STM capacity...

An essential role of the hippocampal region is to integrate information to compute and update representations. How this transpires is highly debated. Many theories hinge on the integration of self-motion signals and the existence of continuous attractor networks (CAN). CAN models hypothesise that neurons coding for navigational correlates – such as...

This chapter gives a short overview of computational models dealing with two fundamental building blocks in spatial cognition: grid and place cells, and of the open issues such models may help address.

Several lines of evidence, including the discovery of place cells, have contributed to the notion that the hippocampus serves primarily to navigate the environment, as a repository of spatial memories, like a drawer full of charts; and that in some species it has exapted on this original one an episodic memory function. We argue that recent evidenc...

Can the neural activity expressing the same mental processes in two different individuals be somehow aligned? Recent evidence suggests that in some cases it can, in mice, at least when they think about space, but possibly even when conjuring up something more abstract.

Spatial cognition in naturalistic environments, for freely moving animals, may pose quite different constraints from that studied in artificial laboratory settings. Hippocampal place cells indeed look quite different, but almost nothing is known about entorhinal cortex grid cells, in the wild. Simulating our self-organizing adaptation model of grid...

Is progress in understanding the neural basis for spatial navigation relevant to the human language faculty? Not so much at the shortest scale, where movement is continuous, a recent study in the space of vowels suggests. At a much larger scale, however, that of the verbalization of run-away thoughts, a rich phenomenology appears to involve critica...

We discuss simple models for the transient storage in short-term memory of cortical patterns of activity, all based on the notion that their recall exploits the natural tendency of the cortex to hop from state to state—latching dynamics. We show that in one such model, and in simple spatial memory tasks we have given to human subjects, short-term m...

Episodic memory has a dynamic nature: when we recall past episodes, we retrieve not only their content, but also their temporal structure. The phenomenon of replay, in the hippocampus of mammals, offers a remarkable example of this temporal dynamics. However, most quantitative models of memory treat memories as static configurations, neglecting the...

Memory can be challenged by increasing both its required duration and the amount of information to be encoded, namely the memory load . The dorsal hippocampus (dHP) has been involved in memory consolidation, which is the stabilization of a trace from short-term (STM) to long-term memory (LTM), as well as in the ability to process high information l...

To test the idea that poetic meter emerged as a cognitive schema to aid verbal memory, we focused on classical Italian poetry and on three components of meter: rhyme, accent, and verse length. Meaningless poems were generated by introducing prosody-invariant non-words into passages from Dante’s Divina Commedia and Ariosto’s Orlando Furioso. We then...

To test the idea that poetic meter emerged as a cognitive schema to aid verbal memory, we have focused on classical Italian poetry and on its three basic components of meter: rhyme, accent and verse length. Meaningless poems were generated by introducing prosody-invariant non-words into passages from Dante's Divina Commedia and Ariosto's Orlando Fu...

We discuss simple models for the transient storage in short-term memory of cortical patterns of activity, all based on the notion that their recall exploits the natural tendency of the cortex to hop from state to state -- latching dynamics. We show that in one such model, and in simple spatial memory tasks we have given to human subjects, short-ter...

An essential role of the hippocampal region is to integrate information to compute and update representations. How this takes place is highly debated. Many theories hinge on the integration of self-motion signals and the existence of continuous attractor networks (CAN). CAN models hypothesise that neurons coding for navigational correlates − such a...

An essential role of the hippocampal region is to integrate information to compute and update representations. How this transpires is highly debated. Many theories hinge on the integration of self-motion signals and the existence of continuous attractor networks (CAN). CAN models hypothesise that neurons coding for navigational correlates – such as...

We derive the Gardner storage capacity for associative networks of threshold linear units, and show that with Hebbian learning they can operate closer to such Gardner bound than binary networks, and even surpass it. This is largely achieved through a sparsification of the retrieved patterns, which we analyze for theoretical and empirical distributi...

Episodic memory has a dynamic nature: when we recall past episodes, we retrieve not only their content, but also their temporal structure. The phenomenon of replay, in the hippocampus of mammals, offers a remarkable example of this temporal dynamics. However, most quantitative models of memory treat memories as static configurations, neglecting the...

Are the grid cells discovered in rodents relevant to human cognition? Following up on two seminal studies by others, we aimed to check whether an approximate 6-fold, grid-like symmetry shows up in the cortical activity of humans who "navigate" between vowels, given that vowel space can be approximated with a continuous trapezoidal 2D manifold, span...

We show that associative networks of threshold linear units endowed with Hebbian learning can operate closer to the Gardner optimal storage capacity than their binary counterparts and even surpass this bound. This is largely achieved through a sparsification of the retrieved patterns, which we analyze for theoretical and empirical distributions of...

The Phonological Output Buffer (POB) is thought to be the stage in language production where phonemes are held in working memory and assembled into words. The neural implementation of the POB remains unclear despite a wealth of phenomenological data. Individuals with POB impairment make phonological errors when they produce words and non-words, inc...

Cover legend: The cover image is based on the Research Article Partial coherence and frustration in self‐organizing spherical grids by Federico Stella et al, https://doi.org/10.1002/hipo.23144.

The way grid cells represent space in the rodent brain has been a striking discovery, with theoretical implications still unclear. Unlike hippocampal place cells, which are known to encode multiple, environment-dependent spatial maps, grid cells have been widely believed to encode space through a single low-dimensional manifold, in which coactivity...

The discovery of Grid Cells has suggested that the rodent brain employs a universal metric to navigate at least flat environments, based on the hexagonal representation of 2D spaces expressed by these cells (Moser et al., 2008). Finding similar cells in other species, e.g. in bats (Yartsev et al., 2011), has raised the question of whether similar m...

The Potts associative memory can be regarded as a model of extended cortical networks characterized, near a critical line, by spontaneous latching dynamics, i.e. the unguided hopping from one attractor to the next. Can Potts dynamics also be guided, and follow specific instructed transitions between attractors? In this paper, we study to what exten...

Nearby grid cells have been observed to express a remarkable degree of long‐range order, which is often idealized as extending potentially to infinity. Yet their strict periodic firing and ensemble coherence are theoretically possible only in flat environments, much unlike the burrows which rodents usually live in. Are the symmetrical, coherent gri...

Nearby grid cells have been observed to express a remarkable degree of long-range order, which is often idealized as extending potentially to infinity. Yet their strict periodic firing and ensemble coherence are theoretically possible only in flat environments, much unlike the burrows which rodents usually live in. Are the symmetrical, coherent gri...

A statistical analysis of semantic memory should reflect the complex, multifactorial structure of the relations among its items. Still, a dominant paradigm in the study of semantic memory has been the idea that the mental representation of concepts is structured along a simple branching tree spanned by superordinate and subordinate categories. We p...

Metric functions for phoneme perception capture the similarity structure among phonemes in a given language and therefore play a central role in phonology and psycho-linguistics. Various phenomena depend on phoneme similarity, such as spoken word recognition or serial recall from verbal working memory. This study presents a new framework for learni...

A statistical analysis of semantic memory should reflect the complex, multifactorial structure of the relations among its items. Still, a dominant paradigm in the study of semantic memory has been the idea that the mental representation of concepts is structured along a simple branching tree spanned by superordinate and subordinate categories. We p...

We analyze an autoassociative network of Potts units, coupled via tensor connections, as an effective model of extended cortical networks with distinct short and long-range synaptic connections. To study semantic memory, organized in terms of the relations between the attributes of real-world knowledge, we formulate a generative model of item repre...

An autoassociative network of Potts units, coupled via tensor connections, has been proposed and analysed as an effective model of an extensive cortical network with distinct short-and long-range synaptic connections, but it has not been clarified in what sense it can be regarded as an effective model. We draw here the correspondence between the tw...

We study latching dynamics in the adaptive Potts model network, through numerical simulations with randomly and also weakly correlated patterns, and we focus on comparing its slowly and fast adapting regimes. A measure, Q, is used to quantify the quality of latching in the phase space spanned by the number of Potts states S, the number of connectio...

We study latching dynamics in the adaptive Potts model network, through numerical simulations with randomly and also weakly correlated patterns, and we focus on comparing its slowly and fast adapting regimes. A measure, Q, is used to quantify the quality of latching in the phase space spanned by the number of Potts states S, the number of connectio...

A unique topographical representation of space is found in the concerted activity of grid cells in the rodent medial entorhinal cortex. Many among the principal cells in this region exhibit a hexagonal firing pattern, in which each cell expresses its own set of place fields (spatial phases) at the vertices of a triangular grid, the spacing and orie...

Analysing aspects of how our brain processes language may provide, even before the language faculty is really understood, useful insights into higher order cognitive functions. We take a small exploratory step in this direction with an attempt to test the ability of a standard, biologically plausible self-organising neural network to learn the asso...

The grid cells discovered in the rodent medial entorhinal cortex have been proposed to provide a metric for Euclidean space, possibly even hardwired in the embryo. Yet one class of models describing the formation of grid unit selectivity is entirely based on developmental self-organization, and as such it predicts that the metric it expresses shoul...

Many cognitive tasks involve transitions between distinct mental processes, which may range from discrete states to complex strategies. The ability of cortical networks to combine discrete jumps with continuous glides along ever changing trajectories, dubbed latching dynamics, may be essential for the emergence of the unique cognitive capacities of...

We collected a database of how 1,434 nouns are used with respect to the mass/count distinction in six languages; additional informants characterized the semantics of the underlying concepts. Results indicate only weak correlations between semantics and syntactic usage. In five out of the six languages, roughly half the nouns in the database are use...

To explore neurocognitive mechanisms underlying the human language faculty, cognitive scientists use artificial languages to control more precisely the language learning environment and to study selected aspects of natural languages. Artificial languages applied in cognitive studies are usually designed ad hoc, to only probe a specific hypothesis,...

This chapter focuses on the discovery of grid cells in the medial entorhinal cortex (MEC) of the rat which has helped to clarify the special hippocampal role for spatial representation and spatial memory. It also discusses the computational approach to hippocampal network design.

This chapter begins with a discussion of the evolutionary changes in the mammalian nervous system that distinguished it from reptilians and birds. It then discusses differentiation of the hippocampus and virtual rat simulations. It argues that hippocampal models require firing-rate adaptation for producing a time-shifted localization, i.e., the pre...

I will illustrate one example of neural computation which is beginning to be understood in detail, and which may inspire applications in synthetic systems: the storage and retrieval of memories in the mammalian hippocampus. The hippocampus is one part of the cortex that has, in all mammalian species, strictly the same organization in a few neural n...

This part presents four chapters on the concept of coding and representation. The first chapter focuses on the online coding and representation of information by means of neuronal activity. The second argues that the ability of the brain to segregate and integrate information, to make use of population and predictive coding, makes for a system that...

This chapter discusses information coding in higher sensory and memory areas. Neurons are vastly simpler than human beings are, but the metaphor is not completely silly because it illustrates the volatility of the notion of neural codes. Information theory has been developed precisely to quantify communication and is quintessential to an appraisal...

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Coexisting memory representations of the same information may differ in the amount of structure they embody, i.e. in the metric of relationships among individual memory items. Such an amount of structure may be quantified by the metric content index. We extract the metric content of the representation of spatial views in the monkey hippocampus and...

A quantification of the relation between neuronal responses and the events that have elicited them is important for understanding the brain. One way to do this in sensory systems is to treat a neuron as a communication channel3 and to measure the mutual information between a set of stimuli presented to the animal and the neuronal response. In such...

How the firing rate of a neuron carries information depends on the time over which rates are measured. For very short times, the amount of information conveyed depends, in a universal way, on the mean rates only (trial-to-trial variability is irrelevant) and the cell response can be taken to be binary (although an ideal binary response would convey...

Networks of threshold-linear neurons have previously been introduced and analysed as distributed associative memory systems. Here, results from simulations of pattern retrieval in a large-scale, sparsely connected network are presented. The storage capacity lies near a = 0.8 and 1.2 for binary and ternary patterns respectively, in reasonable accord...

Measuring the information carried by neuronal activity is made difficult, particularly when recording from mammalian cells, by the limited amount of data usually available, which results in a systematic error. While empirical ad hoc procedures have been used to correct for such error, we have recently proposed a direct procedure consisting of the a...

I consider a mean-field description of the dynamics of interacting intergrate-and-fire neuron-like units. The basic dynamical variables are the membrane potential of each (point-like) ‘cell’ and the conductance associated with each synaptic connection, both of which evolve discontinuously in time. In addition, an intrinsic potassium conductance, al...

I consider a mean-field description of the dynamics of interacting intergrate-and-fire neuron-like units. The basic dynamical variables are the membrane potential of each (point-like) ‘cell’ and the conductance associated with each synaptic connection, both of which evolve discontinuously in time. In addition, an intrinsic potassium conductance, al...

We examine the conditions under which a population of spiking neurons with all-to-all excitatory coupling can fire asynchronously. Synapses with time constants satisfying computed constraints assure the stability of an asynchronous firing state even in the absense of inhibition.

This paper considers the spatial functions of the primate hippocampus, their relation to the memory functions of the hippocampus, and how the hippocampus performs these functions. In addition to the evidence that is available from anatomical connections, the effects of lesions to the system, and single-unit recordings, we focus on neuronal network...

We study through computer simulations the motion in space of small networks consisting of a few sensory, intermediate, and motor units linked by feedforward connections of initially random strengths. Evolutionary pressure, exerted through random differentiation and selective reproduction, can force such objects to adapt to perform elementary naviga...

A general mean-field theory is presented for an attractor neural network in which each elementary unit is described by one input and one output real variable, and whose synaptic strengths are determined by a covariance imprinting rule. In the case of threshold-linear units, a single equation is shown to yield the storage capacity for the retrieval...

In the general framework of associative memory networks we focus our attention on a model of dynamical memory, in which the system hops spontaneously from a discrete attractor state to a correlated one. We call this process latching dynamics. The latching phenomenon is an interesting one either if studied from a semantic viewpoint, as the sequentia...

It is known that the Hippocampus holds a central role in the storage and in the retrieval of episodic memories. In particular the study of population dynamics in hippocampal place cells has emerged as one of the most powerful tools for understanding the encoding, storage and retrieval of episodic memories. Place cells are hippocampal neurons whose...

Hypothesized to be the neural basis for pattern separation, dentate gyrus (DG) has been proposed to separate similar cortical inputs into sparse representations before the input patterns are stored in memory in Hippocampus. This hypothesis has recently been confirmed experimentally by Leutgeb and colleagues. They showed that when the shape of the r...