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Widespread Periodic Intrinsic Connections in the Tree Shrew Visual Cortex
Abstract
Intrinsic connections within the tree shrew (Tupaia glis) visual cortex (area 17) are organized in periodic stripelike patterns within layers I, II, and III. This anatomical network resembles the regularly organized stripes of 2-deoxyglucose accumulation seen after stimulation of alert animals with uniformly oriented lines. Such connections imply that widespread lateral interactions are superimposed on the retinotopic organization of area 17 and suggest alternative interpretations of cortical columns.
... The underlying neural underpinnings have been characterized as an association field (2), which links contour elements that are part of smooth contours. Neurophysiological studies in monkeys have identified that the primary visual cortex (V1) makes a fundamental contribution to contour integration (3)(4)(5)(6), and anatomical studies have shown that the topology of horizontal connections in V1 is well suited for mediating interactions between neurons with a similar orientation preference (7)(8)(9)(10). Such intracortical circuitry in V1 has been implemented in many computational models to account for the successful process of contour integration (11)(12)(13). ...
... Functional influences between V4 and V1 can be mediated by a number of anatomical routes, including direct connections between V4 and V1 and indirect connections passing through V2 or even pulvinar (33,36). Nonetheless, the interactions within V1 are likely mediated by a plexus of horizontal connections that run between columns of similar orientation preference (7)(8)(9)(10)37). The columnar specificity of these horizontal connections, as well as their extent, is consonant with the functional and perceptual characteristics of the putative association field that links contour elements belonging to a smooth contour (2,38,39). ...
Significance
One of the fundamental tasks of vision is to group the image elements that belong to one object and to segregate them from other objects and the background. Such a process, known as contour integration, is thought of as involving both long-range horizontal connections in the primary visual cortex (V1) and feedback influences from higher cortical areas such as V4. Using conditional Granger causality analysis of simultaneously recorded neurons in monkey visual cortical areas V1 and V4, we are able to dissect the respective contributions of intraareal and interareal interactions during contour integration, indicating that feedback and lateral connections work synergistically to group and segment visual image components.
... In higher mammals, the pyramidal cells of the superficial cortical layers form a distinctive network consisting of a circular arrangement of clusters of synaptic boutons arranged around a core of cells, dendrites, and axon (Rockland and Lund 1982). Viewed en face, the network appears flower-like and has been referred to as the cortical 'daisy' . ...
... As previous studies have shown, the majority of bouton clusters were located in the superficial layers (Rockland and Lund 1982;Binzegger et al. 2004;Levitt et al. 1994) with a smaller, but consistent innervation of layer 5 (Martin and Whitteridge 1984; Gilbert and Wiesel 1979;Gilbert 1983;Stepanyants et al. 2009;Binzegger et al. 2004Binzegger et al. , 2007Karube and Kisvarday 2011;Buzas et al. 2006). In the current study, we discovered a distinct sublaminar organization of the clusters that had not been detected in previous studies, probably because so few such neurons have been reconstructed in 3D until now. ...
Pyramidal cells in the superficial layers of neocortex of higher mammals form a lateral network of axon clusters known as the 'daisy' network. The role of these axon clusters remains speculative and we still lack a comprehensive quantitative description of the single neurons forming the daisy or their heterogeneity. We filled intracellularly 50 superficial layer pyramidal neurons in the cat primary visual cortex and reconstructed the axonal tree and their synaptic boutons in 3D. Individual bouton clusters were identified using an objective mean-shift algorithm. By parameterizing the morphology of these 50 axonal trees and the 217 bouton clusters they formed, we were able to extract one set of relatively constant parameters and another set of variable parameters. Both sets combined allowed us to outline a comprehensive biological blueprint of superficial layer pyramidal neurons. Overall, our detailed analysis supports the hypothesis that pyramidal neurons use their lateral clusters to combine differential contextual cues, required for context-dependent processing of natural scenes.
... In the so-called ice cube model, V1 is continuously divided into full-range orientation hypercolumns, each associated with a different image (or retinal) position [8]. The orientation-selective neurons in two hypercolumns are able to interact through long-range horizontal connections [9,10] to facilitate contextual computations. ...
... As has been described in recent neurophysiological studies, each dominant point of a boundary segment in an image space forms a "pixel" in the visual field; it corresponds to an orientationselective neuron. The orientation-selective neurons in two hypercolumns interact through long-range horizontal connections [9,10]. These neurons and the connections between them make up a graph structure. ...
Visual curve completion is a fundamental problem in understanding the principles of the human visual system. This problem is usually divided into two problems: a grouping problem and a shape problem. On one hand, though perception of the visually completed curve is clearly a global task (for example, a human perceives the Kanizsa triangle only when seeing all three black objects), conventional methods for solving the grouping problem are generally based on local Gestalt laws. On the other hand, the shape of the visually completed curve is usually recovered by minimizing shape energy in existing methods. However, not only do these methods lack mechanisms to adjust the shape of the recovered visual curve using perceptual, psychophysical, and neurophysiological knowledge, but it is also difficult to calculate an explicit representation of the visually completed curve. In this paper, we present a systematic computational model for generating a visually completed curve. Firstly, based on recent studies of perception, psychophysics, and neurophysiology, we formulate a grouping procedure based on the human visual system by seeking a minimum Hamiltonian cycle in a graph, solving the grouping problem in a global manner. Secondly, we employ a Bézier curve-based model to represent the visually completed curve. Not only is an explicit representation deduced, but we also present a means to integrate knowledge from related areas, such as perception, psychophysics, and neurophysiology, and so on. The proposed computational model has been validated using many modal and amodal completion examples, and desirable results were obtained.
... Patchy horizontal intra-areal projections are well-established networks of V1 in monkey, cat, and tree shrew (Rockland and Lund, 1982;Rockland and Lund, 1983;Martin and Whitteridge, 1984;Blasdel et al., 1985;Gilbert and Wiesel, 1989;Bosking et al., 1997). Such networks are thought to play a role in the integration of locally encoded stimulus features into a global multidimensional representations of space (Martin et al., 2014;Chavane et al., 2022). ...
Interactions between feedback connections from higher cortical areas and local horizontal connections within primary visual cortex (V1) were shown to play a role in contextual processing in different behavioral states. Layer 1 (L1) is an important part of the underlying network. This cell-sparse layer is a target of feedback and local inputs, and nexus for contacts onto apical dendrites of projection neurons in the layers below. Importantly, L1 is a site for coupling inputs from the outside world with internal information. To determine whether all of these circuit elements overlap in L1, we labeled the horizontal network within mouse V1 with anterograde and retrograde viral tracers. We found two types of local horizontal connections: short ones that were tangentially limited to the representation of the point image, and long ones which reached beyond the receptive field center, deep into its surround. The long connections were patchy and terminated preferentially in M2 muscarinic acetylcholine receptor-negative (M2-) interpatches. Anterogradely labeled inputs overlapped in M2-interpatches with apical dendrites of retrogradely labeled L2/3 and L5 cells, forming module-selective loops between topographically distant locations. Previous work showed that L1 of M2-interpatches receive inputs from the lateral posterior thalamic nucleus (LP) and from a feedback network from areas of the medial dorsal stream, including the secondary motor cortex. Together, these findings suggest that interactions in M2-interpatches play a role in processing visual inputs produced by object-and self-motion.
... Wide-field optical imaging using voltage-sensitive dye (VSD) (see Box 2) permits the depiction of the ongoing state of the cortex through measurements of changes in membrane voltage across millions of neurons under varying input conditions (Onat et al. 2011a). Furthermore, as the emitted fluorescent signals reflect a continuum of membrane potentials, gradual changes in subthreshold activity that spread via long-range cortical connections (Creutzfeldt et al. 1977;Fisken et al. 1975;Gilbert and Wiesel 1979;Rockland and Lund 1982) become unmasked. Consequently, reorganization processes across widely interconnected neurons, including their nonlinear interactions that are not apparent in extracellular spiking, can be tracked over a wide spatial range as postsynaptic activity at mesoscopic population level (Freeman and Barrie 2000; Jancke et al. 1999;Jancke 2000Jancke , 2017Onat et al. 2011aOnat et al. , 2013. ...
Adult visual plasticity underlying local remodeling of the cortical circuitry in vivo appears to be associated with a spatiotemporal pattern of strongly increased spontaneous and evoked activity of populations of cells. Here we review and discuss pioneering work by us and others about principles of plasticity in the adult visual cortex, starting with our study which showed that a confined lesion in the cat retina causes increased excitability in the affected region in the primary visual cortex accompanied by fine-tuned restructuring of neuronal function. The underlying remodeling processes was further visualized with voltage-sensitive dye (VSD) imaging that allowed a direct tracking of retinal lesion-induced reorganization across horizontal cortical circuitries. Nowadays, application of noninvasive stimulation methods pursues the idea further of increased cortical excitability along with decreased inhibition as key factors for the induction of adult cortical plasticity. We used high-frequency transcranial magnetic stimulation (TMS), for the first time in combination with VSD optical imaging, and provided evidence that TMS-amplified excitability across large pools of neurons forms the basis for noninvasively targeting reorganization of orientation maps in the visual cortex. Our review has been compiled on the basis of these four own studies, which we discuss in the context of historical developments in the field of visual cortical plasticity and the current state of the literature. Overall, we suggest markers of LTP-like cortical changes at mesoscopic population level as a main driving force for the induction of visual plasticity in the adult. Elevations in excitability that predispose towards cortical plasticity are most likely a common property of all cortical modalities. Thus, interventions that increase cortical excitability are a promising starting point to drive perceptual and potentially motor learning in therapeutic applications.
... First, ocular dominance columns have also been shown to exist in animals with mixed geniculocortical projections, i.e., owl monkeys [Kaskan et al., 2007]. Secondly, certain types of columns in the visual cortex (with clustered horizontal connections) have been demonstrated in galagos and tupaia [Rockland and Lund, 1982;Sesma et al., 1984] which are phylogenetically closer to the orders Rodentia and Lagomorpha, which have no columns in the visual cortex at all [Kaschube et al., 2010]. ...
... In addition, we hypothesized that these horizontal connections are the main contributor to the early cortical responses to ICMS recorded in the somatosensory cortex. Horizontal connections are a prominent feature of cortical intrinsic circuitry (Gilbert and Wiesel, 1979;Rockland and Lund 1982;Jones et al 1979). These connections originate primarily from pyramidal cells, extend for 2-6 mm parallel to the cortical surface, and terminate in a highly selective and patchy manner targeting predominately (80%) excitatory cells (McGuire et al 1991). ...
Objective
Intuitively providing touch feedback from artificial hands to users with sensory loss remains a challenge. Although localized fingertip sensations can be evoked via intracortical microstimulation (ICMS), feedback is generally optimized using psychometric tasks rather than mimicking the cortical response to touch.
Approach
We created an anatomically-informed and participant-specific model of the human somatosensory cortex (S1) region with an implanted microelectrode array (MEA). We performed simultaneous stimulation-and-recording from the study participant S1 region to characterize cortical responses elicited by single ICMS pulses. Pulses were delivered to a set of pre-selected electrodes mapped to tactile receptive fields. We next performed a 2D (i.e., in the plane of the MEA probe tips) current source density (CSD) analysis of recorded cortical responses to inform cortical network model parameters on how ICMS activates neurons and lateral synaptic connections in the area of the S1 sampled by MEA electrodes. Using information from planar CSD profiles obtained from ground truth data, we reconstructed lateral connections in the S1 model needed to produce the desired responses to single ICMS pulses. The effect of multiple ICMS was then simulated in the biologically realistic cortical model and the results were validated against ground truth cortical responses from the study participant.
Main results
A high-resolution cortical network model, calibrated to produce the known cortical responses to single ICMS pulses delivered to individual electrodes, predicted with a reasonable accuracy the cortical response to ICMS pulses delivered simultaneously to multiple electrodes.
Significance
These preliminary results suggest that high-resolution biologically realistic cortical network models can potentially be reliable predictors of cortical response to a given pattern of ICMS presentations and therefore useful in designing biomimetic stimulation patterns.
... Furthermore, tree shrews are close relatives to primates because of their high degree of similarities in both molecular and physiological aspects. 14,15 Moreover, recent studies successively revealed the reference genomes for tree shrews. 14,[16][17][18] For PSGs, the orthologs in tree shrews have more similarities than these identified in mice. ...
Primate-specific genes (PSGs) tend to be expressed in the brain and testis. This phenomenon is consistent with brain evolution in primates but is seemingly contradictory to the similarity of spermatogenesis among mammals. Here, using whole-exome sequencing, we identified deleterious variants of X-linked SSX1 in six unrelated men with asthenoteratozoospermia. SSX1 is a PSG expressed predominantly in the testis, and the SSX family evolutionarily expanded independently in rodents and primates. As the mouse model could not be used for studying SSX1, we used a non-human primate model and tree shrews, which are phylogenetically similar to primates, to knock down (KD) Ssx1 expression in the testes. Consistent with the phenotype observed in humans, both Ssx1-KD models exhibited a reduced sperm motility and abnormal sperm morphology. Further, RNA sequencing indicated that Ssx1 deficiency influenced multiple biological processes during spermatogenesis. Collectively, our experimental observations in humans and cynomolgus monkey and tree shrew models highlight the crucial role of SSX1 in spermatogenesis. Notably, three of the five couples who underwent intra-cytoplasmic sperm injection treatment achieved a successful pregnancy. This study provides important guidance for genetic counseling and clinical diagnosis and, significantly, describes the approaches for elucidating the functions of testis-enriched PSGs in spermatogenesis.
... Numerous studies have characterized the structural and functional properties of the mammalian brain. This has resulted in a treasure-trove of knowledge on types of neuronal (DeFelipe and Fariñas 1992;Freund and Buzsáki 1996;Peters and Kaiserman-Abramof 1970), axonal and dendritic morphologies (Helmstaedter and Feldmeyer 2010;Larkman 1991;Lübke and Feldmeyer 2010;Spruston 2008;Thomson et al. 1996), laminar organization (DeFelipe et al. 2002;Kätzel et al. 2011;Mountcastle 1997;Rockland 2019;Rockland and Lund 1982;Woolsey and Van der Loos 1970), their gene expression profiles (Kawaguchi and Kubota 1997;Rudy et al. 2011;Toledo-Rodriguez et al. 2005;Yuste et al. 2020) and ion channel kinetics (Bekkers 2000;Kole et al. 2006;Korngreen and Sakmann 2000;Lai and Jan 2006;Markram and Sakmann 1994;Ranjan et al. 2011), morphological and electrophysiological properties (Connors et al. 1982;Hestrin and Armstrong 1996;Kasper et al. 1994;Larkman 1991;Ramaswamy and Markram 2015;Steriade 2004;Zhu 2000), synaptic connections (Feldmeyer et al. 1999;Gupta et al. 2000;Jiang et al. 2015;Mason et al. 1991;Szabadics et al. 2006;Thomson and Lamy 2007), microcircuit anatomy (Avermann et al. 2012;DeFelipe et al. 2002;Lefort et al. 2009;Martin 2002;Rockland 2010), and physiology and function (Haider et al. 2006;McCormick et al. 2003;Petersen 2007;Traub 2005). Schematic illustration of the core steps to reconstruct and simulate brain tissue as previously described in and for which this chapter elaborates the underlying computational concepts The approach described in aims to make sense of these multi-modal and multi-scale datasets by using a data-driven model as an integration framework. ...
Whole-Brain Modelling is a scientific field with a short history and a long past. Its various disciplinary roots and conceptual ingredients extend back to as early as the 1940s. It was not until the late 2000s, however, that a nascent paradigm emerged in roughly its current form-concurrently, and in many ways joined at the hip, with its sister field of macro-connectomics. This period saw a handful of seminal papers authored by a certain motley crew of notable theoretical and cognitive neuroscientists, which have served to define much of the landscape of whole-brain modelling as it stands at the start of the 2020s. At the same time, the field has over the past decade expanded in a dozen or more fascinating new methodological, theoretical, and clinical directions. In this chapter we offer a potted Past, Present, and Future of whole-brain modelling, noting what we take to be some of its greatest successes, hardest challenges, and most exciting opportunities.
... This perceptual task has been used to assess the integrity of low-level spatial vision and, by inference, the underlying neural mechanism in healthy older ageing (Chan, Battista, & McKendrick, 2012;McKendrick, Weymouth, & Battista, 2013) as well as in diseases and developmental disorders, such as schizophrenia (Must, Janka, Benedek, & Kéri, 2004;Schütze, Bongard, Marbach, Brand, & Herzog, 2007) and autism (Jachim, Warren, McLoughlin, & Gowen, 2015). The neural mechanisms underpinning the perceptual phenomenon of collinear facilitation are believed to originate from two types of neural connections: feed-forward facilitation between cell layers in V1 (Gilbert & Wiesel, 1983, 1989Livingstone & Hubel, 1984;Polat & Sagi, 1993;Rockland & Lund, 1982) and feedback facilitation from extrastriate visual areas to V1 (Angelucci et al., 2002;Freeman, Driver, Sagi, & Zhaoping, 2003;Huang & Hess, 2008;Hupé et al., 1998). Current available work in the older human population can only point to a possible change in the spatial interactions underlying collinear facilitation (Chan et al., 2012;McKendrick et al., 2013) but are unable to differentially pinpoint if one or both types of neural connections are affected in the ageing process. ...
Collinear facilitation is a visual phenomenon by which the contrast detection threshold of a central target is reduced (facilitation) when placed equidistant between two high-contrast flankers. The neural mechanisms underpinning this phenomenon originate from feed-forward lateral facilitation between cell layers in V1 (slower) and feedback facilitation from extrastriate visual areas to V1 (faster). The strength of these contributions has been explored in younger adults by presenting the central target and flankers at varying timing offsets. Here, we investigated the effects of older age on collinear facilitation with flankers presented in sync, before, and after target onset, to allow the inference of any characteristic effect of older age on feed-forward and feedback facilitatory mechanisms. Seventeen older and 19 younger observers participated. Our data confirms previous findings of an age-related reduction in facilitation when flankers and target occur at synchrony, but no age difference was found at other timings. Marked interindividual variability in facilitation for the different flanker onset timings was present, which was repeatable within individuals. Further research is required to ascertain the mechanistic underpinnings for different facilitation profiles between individuals. Longitudinal study across an individual's life span is needed to determine whether an individual's facilitation profile changes with age.
... Thus, the nature of V2 feedback to V1 during contextual modulation is still unclear in humans as in non-human primates. Collinear facilitation, the increase in contrast sensitivity for a target embedded in between two iso-oriented flankers (Polat and Sagi 1993), is another widely studied contextual modulation effect, observed both in fovea and near periphery (Maniglia et al. 2011(Maniglia et al. , 2015a, thought to rely on similar early neural substrate as surround suppression, specifically the horizontal connections in V1 (Rockland and Lund 1982;Wiesel 1983, 1985;Polat and Sagi 1993). On the other hand, attention seems necessary for this effect to emerge (Freeman et al. 2001), and its range spans over several degrees of visual angle (Maniglia et al. 2015a, b) beyond the anatomical range of horizontal connections (Angelucci and Bressloff 2006), implying possible feedback from higher visual areas. ...
The interaction between the primary visual cortex (V1) and extrastriate visual areas provides the first building blocks in our perception of the world. V2, in particular, seems to play a crucial role in shaping contextual modulation information through feedback projections to V1. However, whether this feedback is inhibitory or excitatory is still unclear. In order to test the nature of V2 feedback to V1, we used neuronavigation-guided offline inhibitory transcranial magnetic stimulation (TMS) on V2 before testing participants on collinear facilitation, a contrast detection task with lateral masking. This contextual modulation task is thought to rely on horizontal connections in V1 and possibly extrastriate feedback. Results showed that when inhibitory TMS was delivered over V2, contrast thresholds decreased for targets presented in the contralateral hemifield, consistent with the retinotopic mapping of this area, while having no effect for targets presented in the ipsilateral hemifield or after control (CZ) stimulation. These results suggest that feedback from V2 to V1 during contextual modulation is mostly inhibitory, corroborating recent observations in monkey electrophysiology and extending this mechanism to human visual system. Moreover, we provide for the first time direct evidence of the involvement of extrastriate visual areas in collinear facilitation.
... A much larger number of contacts (>60%) (Binzegger et al., 2004;Stepanyants, Martinez, Ferecskó, & Kisvárday, 2009) arises from the massive network of horizontal connections (HCs) through which cortical PNs exchange contextual information (Angelucci et al., 2002;Bosking, Zhang, Schofield, & Fitzpatrick, 1997;Boucsein, 2011;Chisum, Mooser, & Fitzpatrick, 2003;McGuire, Gilbert, Rivlin, & Wiesel, 1991;Rockland & Lund, 1982). Despite their large numbers and undoubted importance, relatively little is known regarding the HC's contributions to behavior, the functional form(s) of the classical-contextual interactions they give rise to, or the biophysical mechanisms that underlie their modulatory effects. ...
A signature feature of the neocortex is the dense network of horizontal connections (HCs) through which pyramidal neurons (PNs) exchange “contextual” information. In primary visual cortex (V1), HCs are thought to facilitate boundary detection, a crucial operation for object recognition, but how HCs modulate PN responses to boundary cues within their classical receptive fields (CRF) remains unknown. We began by “asking” natural images, through a structured data collection and ground truth labeling process, what function a V1 cell should use to compute boundary probability from aligned edge cues within and outside its CRF. The “answer” was an asymmetric 2-D sigmoidal function, whose nonlinear form provides the first normative account for the “multiplicative” center-flanker interactions previously reported in V1 neurons (Kapadia et al. 1995, 2000; Polat et al. 1998). Using a detailed compartmental model, we then show that this boundary-detecting classical-contextual interaction function can be computed with near perfect accuracy by NMDAR-dependent spatial synaptic interactions within PN dendrites – the site where classical and contextual inputs first converge in the cortex. In additional simulations, we show that local interneuron circuitry activated by HCs can powerfully leverage the nonlinear spatial computing capabilities of PN dendrites, providing the cortex with a highly flexible substrate for integration of classical and contextual information.
Significance Statement
In addition to the driver inputs that establish their classical receptive fields, cortical pyramidal neurons (PN) receive a much larger number of “contextual” inputs from other PNs through a dense plexus of horizontal connections (HCs). However by what mechanisms, and for what behavioral purposes, HC’s modulate PN responses remains unclear. We pursued these questions in the context of object boundary detection in visual cortex, by combining an analysis of natural boundary statistics with detailed modeling PNs and local circuits. We found that nonlinear synaptic interactions in PN dendrites are ideally suited to solve the boundary detection problem. We propose that PN dendrites provide the core computing substrate through which cortical neurons modulate each other’s responses depending on context.
... An additional feature of V1 is that regions of similar OP are preferentially linked within and between unit 42 cells by lateral connections, forming a patchy network ( Gilbert and Wiesel, 1983;Rockland and Lund, 1982). 2 . ...
Neural field theory is used to quantitatively analyze the two-dimensional spatiotemporal correlation properties of gamma-band (30 - 70 Hz) oscillations evoked by stimuli arriving at the primary visual cortex (V1), and modulated by patchy connectivities that depend on orientation preference (OP). Correlation functions are derived analytically under different stimulus and measurement conditions. The predictions reproduce a range of published experimental results, including the existence of two-point oscillatory temporal cross-correlations with zero time-lag between neurons with similar OP, the influence of spatial separation of neurons on the strength of the correlations, and the effects of differing stimulus orientations.
... Since these studies, the repertoire of model species used in visual neuroscience has been expanded greatly. Smaller primate species, including the new world monkeys such as the marmoset, offer a several advantages including a smooth cortical surface, reduced size and shorter lifespan (and thus quicker development) (Solomon and Rosa, 2014), factors which may also motivate, in part, the use of non-primate species such as the ferret (Chapman et al., 1996;Coppola et al., 1998;White et al., 2001b) and tree shrew (Rockland and Lund, 1982;Fitzpatrick, 1996;Bosking et al., 1997). The apparent advantage of rodent species are similar in nature but even more acute. ...
Neurons in Primary Visual Cortex (V1) are known to respond strongly to visual stimuli. Studies of neuronal responses in V1, carried out first in cats, but later primates and other mammals, have demonstrated that bars of light at particular orientations evoke strong, reliable responses in terms of increased firing rate of action potentials. Tuning of neuronal responses to certain stimulus parameters, such as orientation but also spatial and temporal frequencies, as well as the apparent dichotomy between simple and complex responses, have given rise to a number of influential models not just of V1 function, but more generally in the field of cortical physiology and computer vision. Owing to its small size and the plethora of available molecular and genetic tools, the visual cortex of the mouse may be a more tractable model system than that of much larger animals. Recent studies of neuronal responses in mouse V1 have shown that these are broadly similar to those of primates and carnivores, although not identical in all aspects. My thesis aims firstly to characterise intrinsic and sensory-evoked properties in regularspiking, putative pyramidal neurons in L2/3 of the mouse visual cortex using whole-cell patch clamp recording in vivo . In addition, the anatomical connectivity of individual neurons is characterised using virus-assisted circuit mapping. The majority of these neurons are found to be simple cells. Orientation tuning (the degree to which neuronal responses are selective to stimuli of a preferred orientation) is found to be quite variable, even within this singular group of neurons. The potential roles of intrinsic diversity, functional connectivity, and sensory experience in setting the orientation tuning of a particular neuron are investigated. These findings provide an insight in to how diverse responses to sensory stimuli can be generated in an apparently homogenous group of neurons.
... For example, a high density of labeled cells was seen in adjacent cortical regions in the present study (data not shown) and in thalamic nuclei previously (Conte et al., 2009). Clustering is a common hallmark of long-range cortico-cortical connections in the visual cortex of tree shrews, cats, monkeys and rats (Rockland and Lund, 1982;Livingstone and Hubel, 1984;Burkhalter, 1989;Gilbert and Wiesel, 1989). This type of organization appears when two cortical territories interact in a precise manner. ...
Acetylcholine is an important neurotransmitter for the regulation of visual attention, plasticity, and perceptual learning. It is released in the visual cortex predominantly by cholinergic projections from the basal forebrain, where stimulation may produce potentiation of visual processes. However, little is known about the fine organization of these corticopetal projections, such as whether basal forebrain neurons projecting to the primary and secondary visual cortical areas (V1 and V2, respectively) are organized retinotopically. The aim of this study was to map these basal forebrain-V1/V2 projections. Microinjections of the fluorescent retrograde tracer cholera toxin b fragment in different sites within V1 and V2 in Long–Evans rats were performed. Retrogradely labeled cell bodies in the horizontal and vertical limbs of the diagonal band of Broca (HDB and VDB, respectively), nucleus basalis magnocellularis, and substantia innominata (SI), were mapped ex vivo with a computer-assisted microscope stage controlled by stereological software. Choline acetyltranferase immunohistochemistry was used to identify cholinergic cells. Our results showed a predominance of cholinergic projections coming from the HDB. These projections were not retinotopically organized but projections to V1 arised from neurons located in the anterior HDB/SI whereas projections to V2 arised from neurons located throughout the whole extent of HDB/SI. The absence of a clear topography of these projections suggests that BF activation can stimulate visual cortices broadly.
... Francis's next two papers were co-authored with GJM. The first was based on an observation that a pattern of stripes is produced when horseradish peroxidase is injected into the primary visual cortex of the tree shrew (Rockland & Lund 1982). They explained this pattern by positing a particular kind of long-range connection that would allow the receptive fields of neurons with similar orientation preferences to be 'stitched together' to make long receptive fields (25), a conjecture which now has strong supporting evidence (Bosking et al. 1997). ...
The first half of the twentieth century saw a profound change in our understanding of the chemistry underlying biology. We came to learn in detail how the small molecules upon which life is based are interconverted by specific enzymes, a web which increased in complexity and became modern biochemistry. Intellectually, a quite separate development—molecular biology—arose from physicists and chemists studying the structure of proteins with X-rays, and biologists studying viruses that infect bacteria. Its intellectual thrust was to discover how information in genes is expressed and controlled. This led to a revolution in our understanding of biology, and no person was more influential in shaping and guiding this emerging field than Francis Crick.
... Horizontal connections in V1 are millimeters-long, intralaminar axonal projections most prominent in lower layers 2/3 and in layer 5 in many mammalian species (Rockland & Lund 1982Gilbert & Wiesel 1983). Their features, at least in layers 2/3 (where they have been characterized most extensively), are well suited to generate orientation-tuned near-SM, including both suppressive and facilitatory modulations. ...
Surround modulation (SM) is a fundamental property of sensory neurons in many species and sensory modalities. SM is the ability of stimuli in the surround of a neuron's receptive field (RF) to modulate (typically suppress) the neuron's response to stimuli simultaneously presented inside the RF, a property thought to underlie optimal coding of sensory information and important perceptual functions. Understanding the circuit and mechanisms for SM can reveal fundamental principles of computations in sensory cortices, from mouse to human. Current debate is centered over whether feedforward or intracortical circuits generate SM, and whether this results from increased inhibition or reduced excitation. Here we present a working hypothesis, based on theoretical and experimental evidence, that SM results from feedforward, horizontal, and feedback interactions with local recurrent connections, via synaptic mechanisms involving both increased inhibition and reduced recurrent excitation. In particular, strong and balanced recurrent excitatory and inhibitory circuits play a crucial role in the computation of SM. Expected final online publication date for the Annual Review of Neuroscience Volume 40 is July 8, 2017. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
... The tree shrew (Tupaia belangeri chinensis) belongs to Order Scandentia and is similar to primates in many biological features (Fan et al., 2013;Rockland & Lund, 1982;Xu et al., 2012). Moreover, its high brain-to-body mass ratio makes it a promising non-human primate animal model in brain and biomedical research (Cao et al., 2003;Li et al., 2017). ...
Brain development and aging are associated with alterations in multiple epigenetic systems, including DNA methylation and demethylation patterns. Here, we observed that the levels of the 5-hydroxymethylcytosine (5hmC) ten-eleven translocation (TET) enzyme-mediated active DNA demethylation products were dynamically changed and involved in postnatal brain development and aging in tree shrews (Tupaia belangeri chinensis). The levels of 5hmC in multiple anatomic structures showed a gradual increase throughout postnatal development, whereas a significant decrease in 5hmC was found in several brain regions in aged tree shrews, including in the prefrontal cortex and hippocampus, but not the cerebellum. Active changes in Tet mRNA levels indicated that TET2 and TET3 predominantly contributed to the changes in 5hmC levels. Our findings provide new insight into the dynamic changes in 5hmC levels in tree shrew brains during postnatal development and aging processes.
... For Hubel and Wiesel (Hubel and Wiesel 1962), the radial cortical column is the 'functional unit of cortex' that most economically achieves the highly specific wiring needed to generate simple and complex cells in different layers. Linking these 'columns' are lateral connections that form a patchy network (Rockland and Lund 1982), which appears to be ubiquitous across all cortical areas in non-rodent species, including cat, tree shrew, monkey, and human (Douglas and . A common view is that the lateral connections link patches of common orientation preference, thus expressing a 'like-to-like' connection rule, achieved by means of a 'fire-together-wire together' mechanism (Gilbert and Wiesel 1989;Malach et al. 1994;Bosking et al. 1997;Sincich and Blasdel 2001). ...
The present study is the first to describe quantitatively the patterns of synaptic connections made by the patchy network of pyramidal cell axons in the superficial layers of cat V1 in relation to the orientation map. Intrinsic signal imaging of the orientation map was combined with 3D morphological reconstructions of physiologically-characterized neurons at light and electron microscope levels. A Similarity Index (SI) expressed the similarity of the orientation domain of a given bouton cluster to that of its parent dendritic tree. Six pyramidal cells whose axons had a wide range of SIs were examined. Boutons were sampled from five local and five distal clusters, and from the linear segments that link the clusters. The synaptic targets were reconstructed by serial section electron microscopy. Of the 233 synapses examined, 182 synapses were formed with spiny neurons, the remainder with smooth neurons. The proportion of smooth neurons that were synaptic targets varied greatly (from 0 to 50%) between the cluster samples, but was not correlated with the SI. The postsynaptic density sizes were similar for synapses in local and distal clusters, regardless of their SI. This heterogeneity in the synaptic targets of single cells within the superficial layers is a network feature well-suited for context-dependent processing.
... Using this technique, Grinvald and colleagues could, for the first time, visualize at the functional level how a small visual stimulus (a square of light) produces far-spreading activity in primary visual cortex (V1), much beyond the region of thalamic input (Fig. 1). Hence, the method provided direct evidence of the impact of dendritic integration and the functional properties of longrange horizontal connections [5][6][7][8] at the neuronal population level. Because from then on voltage-sensitive dye imaging (VSDI) was shown to allow for recordings along a continuum of membrane potentials, far spread interactions of neuronal populations across long-range connections, constituting gradual input from outside the classical receptive field, 9 became optically accessible. ...
Wide-field voltage imaging is unique in its capability to capture snapshots of activity-across the full gradient of average changes in membrane potentials from subthreshold to suprathreshold levels-of hundreds of thousands of superficial cortical neurons that are simultaneously active. Here, I highlight two examples where voltage-sensitive dye imaging (VSDI) was exploited to track gradual space-time changes of activity within milliseconds across several millimeters of cortex at submillimeter resolution: the line-motion condition, measured in Amiram Grinvald's Laboratory more than 10 years ago and-coming full circle running VSDI in my laboratory-another motion-inducing condition, in which two neighboring stimuli counterchange luminance simultaneously. In both examples, cortical spread is asymmetrically boosted, creating suprathreshold activity drawn out over primary visual cortex. These rapidly propagating waves may integrate brain signals that encode motion independent of direction-selective circuits.
... Of particular relevance for fMRI, relating to the expected signal changes and spatial patterns obtained, is that columns generally do not have distinct borders but are rather comprised by a "core" set of neurons with the same functional properties, surrounded by neurons that share functional properties with neighbouring columns. Therefore, the spatial pattern of activity of neighbouring columns as detected by fMRI is expected to partially overlap not only because of the presumably wider spatial point-spread function of the hemodynamic response with respect to column width, but also because of the neuronal activity pattern within a column and neuronal communications between columns (Gilbert and Wiesel, 1983;Rockland and Lund, 1982). ...
Human MRI scanners at ultra-high magnetic field strengths of 7 T and higher are increasingly available to the neuroscience community. A key advantage brought by ultra-high field MRI is the possibility to increase the spatial resolution at which data is acquired, with little reduction in image quality. This opens a new set of opportunities for neuroscience, allowing investigators to map the human cortex at an unprecedented level of detail. In this review, we present recent work that capitalizes on the increased signal-to-noise ratio available at ultra-high field and discuss the theoretical advances with a focus on sensory and motor systems neuroscience. Further, we review research performed at sub-millimeter spatial resolution and discuss the limits and the potential of ultra-high field imaging for structural and functional imaging in human cortex. The increased spatial resolution achievable at ultra-high field has the potential to unveil the fundamental computations performed within a given cortical area, ultimately allowing the visualization of the mesoscopic organization of human cortex at the functional and structural level.
... China. It belongs to the order Scandentia and shares a high degree of similarity to primates in many of its molecular and physiological aspects [1][2][3]. Moreover, it has a small adult body size, a high brain-to-body mass ratio, a short reproductive cycle and life span, and a low cost of maintenance. ...
Tree shrews have a close relationship to primates and have many advantages over rodents in biomedical research. However, the lack of gene manipulation methods has hindered the wider use of this animal. Spermatogonial stem cells (SSCs) have been successfully expanded in culture to permit sophisticated gene editing in the mouse and rat. Here, we describe a culture system for the long-term expansion of tree shrew SSCs without the loss of stem cell properties. In our study, thymus cell antigen 1 was used to enrich tree shrew SSCs. RNA-sequencing analysis revealed that the Wnt/β-catenin signaling pathway was active in undifferentiated SSCs, but was downregulated upon the initiation of SSC differentiation. Exposure of tree shrew primary SSCs to recombinant Wnt3a protein during the initial passages of culture enhanced the survival of SSCs. Use of tree shrew Sertoli cells, but not mouse embryonic fibroblasts, as feeder was found to be necessary for tree shrew SSC proliferation, leading to a robust cell expansion and long-term culture. The expanded tree shrew SSCs were transfected with enhanced green fluorescent protein (EGFP)-expressing lentiviral vectors. After transplantation into sterilized adult male tree shrew's testes, the EGFP-tagged SSCs were able to restore spermatogenesis and successfully generate transgenic offspring. Moreover, these SSCs were suitable for the CRISPR/Cas9-mediated gene modification. The development of a culture system to expand tree shrew SSCs in combination with a gene editing approach paves the way for precise genome manipulation using the tree shrew.Cell Research advance online publication 23 December 2016; doi:10.1038/cr.2016.156.
... In the mammalian visual cortex, boutons of many superficial layer (L2/3) pyramidal cells are known to terminate in distinct clusters forming patchy projection of the axons (Rockland and Lund 1982;Gilbert and Wiesel 1983;Rockland and Lund 1983;Martin and Whitteridge 1984;Kisvárday and Eysel 1992;Binzegger et al. 2007). L4 neurons also provide clustered projections although with different spatial constraints compared to their superficial layer counterparts (Karube and Kisvárday 2011). ...
To uncover the functional topography of layer 6 neurons, optical imaging was combined with three-dimensional neuronal reconstruction. Apical dendrite morphology of 23 neurons revealed three distinct types. Type Aa possessed a short apical dendrite with many oblique branches, Type Ab was characterized by a short and less branched apical dendrite, whereas Type B had a long apical dendrite with tufts in layer 2. Each type had a similar number of boutons, yet their spatial distribution differed from each other in both radial and horizontal extent. Boutons of Type Aa and Ab were almost restricted to the column of the parent soma with a laminar preference to layer 4 and 5/6, respectively. Only Type B contributed to long horizontal connections (up to 1.5 mm) mostly in deep layers. For all types, bouton distribution on orientation map showed an almost equal occurrence at iso- (52.6 ± 18.8 %) and non-iso-orientation (oblique, 27.7 ± 14.9 % and cross-orientation 19.7 ± 10.9 %) sites. Spatial convergence of axons of nearby layer 6 spiny neurons depended on soma separation of the parent cells, but only weakly on orientation preference, contrary to orientation dependence of converging axons of layer 4 spiny cells. The results show that layer 6 connections have only a weak dependence on orientation preference compared with those of layers 2/3 (Buzás et al., J Comp Neurol 499:861–881, 2006) and 4 (Karube and Kisvárday, Cereb Cortex 21:1443–1458, 2011).
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The online version of this article (doi:10.1007/s00429-016-1284-z) contains supplementary material, which is available to authorized users.
... Adjacent groups with the same orientation specificity are reciprocally interconnected; each excitatory neuron receives 32 weak connections from excitatory neurons in those adjacent groups. Anatomical and physiological evidence in primary visual cortex has revealed the existence of a system of short-range corticocortical connections (Rockland and Lund, 1982;Gilbert and Wiesel, 1983; l 990a) which preferentially links cell groups with similar orientation specificity (Ts'o et al., 1986;Gilbert and Wiesel, 1989;Luhmann et al., 1990b). functionally observable interactions between columns of different orientation specificity exist (Matsubara et al., 1985;Hara et al., 1988) but are probably of inhibitory character and would thus exert a decorrelating influence. ...
... order to build this columnar architecture requires the ability to visualize the receptive fields of large numbers of simple cells, determine the spatial arrangement of their ON and OFF subfields, and how this relates to the columnar maps of orientation and visual space. We have achieved this by using two-photon calcium imaging to map the receptive fields of large numbers of single neurons in layer 2/3 of the tree shrew, a species with a close phylogenetic relation to primates 8 , and a visual cortex with a well-developed columnar architecture 5,[9][10][11] . ...
Circuits in the visual cortex integrate the information derived from separate ON (light-responsive) and OFF (dark-responsive) pathways to construct orderly columnar representations of stimulus orientation and visual space. How this transformation is achieved to meet the specific topographic constraints of each representation remains unclear. Here we report several novel features of ON-OFF convergence visualized by mapping the receptive fields of layer 2/3 neurons in the tree shrew (Tupaia belangeri) visual cortex using two-photon imaging of GCaMP6 calcium signals. We show that the spatially separate ON and OFF subfields of simple cells in layer 2/3 exhibit topologically distinct relationships with the maps of visual space and orientation preference. The centres of OFF subfields for neurons in a given region of cortex are confined to a compact region of visual space and display a smooth visuotopic progression. By contrast, the centres of the ON subfields are distributed over a wider region of visual space, display substantial visuotopic scatter, and have an orientation-specific displacement consistent with orientation preference map structure. As a result, cortical columns exhibit an invariant aggregate receptive field structure: an OFF-dominated central region flanked by ON-dominated subfields. This distinct arrangement of ON and OFF inputs enables continuity in the mapping of both orientation and visual space and the generation of a columnar map of absolute spatial phase.
Intrinsic, ongoing fluctuations of cortical activity form traveling waves that modulate the gain of sensory-evoked responses and perceptual sensitivity. Several lines of evidence suggest that intrinsic traveling waves (iTWs) may arise, in part, from the coordination of synaptic activity through the recurrent horizontal connectivity within cortical areas, which include long range patchy connections that link neurons with shared feature preferences. In a spiking network model with anatomical topology that incorporates feature-selective patchy connections, which we call the Balanced Patchy Network (BPN), we observe repeated iTWs, which we refer to as motifs. In the model, motifs stem from fluctuations in the excitability of like-tuned neurons that result from shifts in E/I balance as action potentials traverse these patchy connections. To test if feature-selective motifs occur in vivo, we examined data previously recorded using multielectrode arrays in Area MT of marmosets trained to perform a threshold visual detection task. Using a newly developed method for comparing the similarity of wave patterns we found that some iTWs can be grouped into motifs. As predicted by the BPN, many of these motifs are feature selective, exhibiting direction-selective modulations in ongoing spiking activity. Further, motifs modulate the gain of the response evoked by a target and perceptual sensitivity to the target if the target matches the preference of the motif. These results provide evidence that iTWs are shaped by the patterns of horizontal fiber projections in the cortex and that patchy connections enable iTWs to regulate neural and perceptual sensitivity in a feature selective manner.
An examination of how widely distributed and specialized activities of the brain are flexibly and effectively coordinated.
A fundamental shift is occurring in neuroscience and related disciplines. In the past, researchers focused on functional specialization of the brain, discovering complex processing strategies based on convergence and divergence in slowly adapting anatomical architectures. Yet for the brain to cope with ever-changing and unpredictable circumstances, it needs strategies with richer interactive short-term dynamics. Recent research has revealed ways in which the brain effectively coordinates widely distributed and specialized activities to meet the needs of the moment. This book explores these findings, examining the functions, mechanisms, and manifestations of distributed dynamical coordination in the brain and mind across different species and levels of organization. The book identifies three basic functions of dynamic coordination: contextual disambiguation, dynamic grouping, and dynamic routing. It considers the role of dynamic coordination in temporally structured activity and explores these issues at different levels, from synaptic and local circuit mechanisms to macroscopic system dynamics, emphasizing their importance for cognition, behavior, and psychopathology.
ContributorsEvan Balaban, György Buzsáki, Nicola S. Clayton, Maurizio Corbetta, Robert Desimone, Kamran Diba, Shimon Edelman, Andreas K. Engel, Yves Fregnac, Pascal Fries, Karl Friston, Ann Graybiel, Sten Grillner, Uri Grodzinski, John-Dylan Haynes, Laurent Itti, Erich D. Jarvis, Jon H. Kaas, J.A. Scott Kelso, Peter König, Nancy J. Kopell, Ilona Kovács, Andreas Kreiter, Anders Lansner, Gilles Laurent, Jörg Lücke, Mikael Lundqvist, Angus MacDonald, Kevan Martin, Mayank Mehta, Lucia Melloni, Earl K. Miller, Bita Moghaddam, Hannah Monyer, Edvard I. Moser, May-Britt Moser, Danko Nikolic, William A. Phillips, Gordon Pipa, Constantin Rothkopf, Terrence J. Sejnowski, Steven M. Silverstein, Wolf Singer, Catherine Tallon-Baudry, Roger D. Traub, Jochen Triesch, Peter Uhlhaas, Christoph von der Malsburg, Thomas Weisswange, Miles Whittington, Matthew Wilson
It has previously been shown that it is possible to derive a new class of biophysically detailed brain tissue models when one computationally analyzes and exploits the interdependencies or the multi-modal and multi-scale organization of the brain. These reconstructions, sometimes referred to as digital twins, enable a spectrum of scientific investigations. Building such models has become possible because of increase in quantitative data but also advances in computational capabilities, algorithmic and methodological innovations. This chapter presents the computational science concepts that provide the foundation to the data-driven approach to reconstructing and simulating brain tissue as developed by the EPFL Blue Brain Project, which was originally applied to neocortical microcircuitry and extended to other brain regions. Accordingly, the chapter covers aspects such as a knowledge graph-based data organization and the importance of the concept of a dataset release. We illustrate algorithmic advances in finding suitable parameters for electrical models of neurons or how spatial constraints can be exploited for predicting synaptic connections. Furthermore, we explain how in silico experimentation with such models necessitates specific addressing schemes or requires strategies for an efficient simulation. The entire data-driven approach relies on the systematic validation of the model. We conclude by discussing complementary strategies that not only enable judging the fidelity of the model but also form the basis for its systematic refinements.
A signature feature of the neocortex is the dense network of horizontal connections (HCs) through which pyramidal neurons (PNs) exchange “contextual” information. In primary visual cortex (V1), HCs are thought to facilitate boundary detection, a crucial operation for object recognition, but how HCs modulate PN responses to boundary cues within their classical receptive fields (CRF) remains unknown. We began by “asking” natural images, through a structured data collection and ground truth labeling process, what function a V1 cell should use to compute boundary probability from aligned edge cues within and outside its CRF. The “answer” was an asymmetric 2-D sigmoidal function, whose nonlinear form provides the first normative account for the “multiplicative” center-flanker interactions previously reported in V1 neurons (Kapadia et al. 1995, 2000; Polat et al. 1998). Using a detailed compartmental model, we then show that this boundary-detecting classical-contextual interaction function can be computed by NMDAR-dependent spatial synaptic interactions within PN dendrites – the site where classical and contextual inputs first converge in the cortex. In additional simulations, we show that local interneuron circuitry activated by HCs can powerfully leverage the nonlinear spatial computing capabilities of PN dendrites, providing the cortex with a highly flexible substrate for integration of classical and contextual information.
Most neurons in the primary visual cortex (V1) of mammals show sharp orientation selectivity and band-pass spatial frequency tuning. Here, we examine whether sharpening of the broad tuning that exists subcortically, namely in the retina and the lateral geniculate nucleus (LGN), underlie the sharper tuning seen for both the above features in tree shrew V1. Since the transition from poor feature selectivity to sharp tuning occurs entirely within V1 in tree shrews, we examined the orientation selectivity and spatial frequency tuning of neurons within individual electrode penetrations. We found that most layer 4 and layer 2/3 neurons in the same cortical column preferred the same stimulus orientation. However, a subset of layer 3c neurons close to the layer 4 border preferred near orthogonal orientations, suggesting that layer 2/3 neurons may inherit the orientation preferences of their layer 4 input neurons and also receive cross-orientation inhibition from layer 3c neurons. We also found that layer 4 neurons showed sharper orientation selectivity at higher spatial frequencies, suggesting that attenuation of low spatial frequency responses by spatially broad inhibition acting on layer 4 inputs to layer 2/3 neurons can enhance both orientation and spatial frequency selectivities. However, in a proportion of layer 2/3 neurons, the sharper tuning of layer 2/3 neurons appeared to arise also or even mainly from inhibition specific to high spatial frequencies acting on the layer 4 inputs to layer 2/3. Overall, our results are consistent with the suggestion that in tree shrews, sharp feature selectivity in layer 2/3 can be established by intracortical mechanisms that sharpen biases observed in layer 4, which are in turn inherited presumably from thalamic afferents.
The edges of an image contains rich visual cognitive cues. However, the edge information of a natural scene usually is only a set of disorganized unorganized pixels for a computer. In psychology, the phenomenon of quickly perceiving global information from a complex pattern is called the global precedence effect (GPE). For example, when one observes the edge map of an image, some contours seem to automatically “pop out” from the complex background. This is a manifestation of GPE on edge information and is called global contour precedence (GCP). The primary visual cortex (V1) is closely related to the processing of edges. In this article, a neural computational model to simulate GCP based on the mechanisms of V1 is presented. There are three layers in the proposed model: the representation of line segments, organization of edges, and perception of global contours. In experiments, the ability to group edges is tested on the public dataset BSDS500. The results show that the grouping performance, robustness, and time cost of the proposed model are superior to those of other methods. In addition, the outputs of the proposed model can also be applied to the generation of object proposals, which indicates that the proposed model can contribute significantly to high-level visual tasks.
Spatial integration is a fundamental, context-dependent neural operation that involves extensive neural circuits across cortical layers of V1. To better understand how spatial integration is dynamically coordinated across layers we recorded single- and multi-unit activity and local field potentials across V1 layers of awake mice, and used dynamic Bayesian model comparisons to identify when laminar activity and inter-laminar functional interactions showed surround suppression, the hallmark of spatial integration. We found that surround suppression is strongest in layer 3 (L3) and L4 activity, showing rapidly sharpening receptive fields and increasing suppression strength. Importantly, we also found that specific directed functional connections were strongest for intermediate stimulus sizes and suppressed for larger ones, particularly for the L3->L5 and L3->L1 connections. Taken together, the results shed light on the different functional roles of cortical layers in spatial integration and show how L3 dynamically coordinates activity across a cortical column depending on spatial context.
Alongside difficulties with communication and social interaction, autism is often accompanied by unusual sensory and perceptual experiences including enhanced visual performance on tasks that involve separating local parts from global context. This superiority may be the result of atypical integrative processing, involving feedback and lateral connections between visual neurons. The current study investigated the integrity of these connections in autistic adults by examining two psychophysics tasks that rely on these processes - collinear facilitation and contour integration. The relative contribution of feedback and lateral connectivity was studied by altering the timing of the target relative to the flankers in the collinear facilitation task, in 16 autistic and 16 non-autistic adults. There were no significant differences in facilitation between the autistic and non-autistic groups, indicating that for this task and participant sample, lateral and feedback connectivity appear relatively intact in autistic individuals. Contour integration was examined in a different group of 20 autistic and 18 non-autistic individuals, for open and closed contours to assess the closure effect (improved detection of closed compared to open contours). Autistic individuals showed a reduced closure effect at both short (150 ms) and longer (500 ms) stimulus presentation durations that was driven by better performance of the autistic group for the open contours. These results suggest that reduced closure in a simple contour detection paradigm is unlikely to be due to slower global processing. Reduced closure has implications for understanding sensory overload by contributing to reduced figure-ground segregation of salient visual features.
The morphological characteristics of the basal dendritic fields of layer III pyramidal neurones were determined in visual areas in the occipital, parietal, and temporal lobes of adult marmoset monkeys by means of intracellular iontophoretic injection of Lucifer yellow. Neurones in the primary visual area (V1) had the least extensive and least complex (as determined by Sholl analysis) dendritic trees, followed by those in the second visual area (V2). There was a progressive increase in size and complexity of dendritic trees with rostral progression from V1 and V2, through the “ventral stream,” including the dorsolateral area (DL) and the caudal and rostral subdivisions of inferotemporal cortex (ITc and ITr, respectively). Neurones in areas of the dorsal stream, including the dorsomedial (DM), dorsoanterior (DA), middle temporal (MT), and posterior parietal (PP) areas, were similar in size and complexity but were larger and more complex than those in V1 and V2. Neurones in V1 had the lowest spine density, whereas neurones in V2, DM, DA, and PP had similar spine densities. Neurones in MT and inferotemporal cortex had relatively high spine densities, with those in ITr having the highest spine density of all neurones studied. Calculations based on the size, number of branches, and spine densities revealed that layer III pyramidal neurones in ITr have 7.4 times more spines on their basal dendritic fields than those in V1. The differences in the extent of, and the number of spines in, the basal dendritic fields of layer III pyramidal neurones in the different visual areas suggest differences in the ability of neurones to integrate excitatory and inhibitory inputs. The differences in neuronal morphology between visual areas, and the consistency in these differences across New World and Old World monkey species, suggest that they reflect fundamental organisational principles in primate visual cortical structure. J. Comp. Neurol. 415:33–51, 1999. © 1999 Wiley‐Liss, Inc.
This paper generalizes and extends previous work on using neural field theory to quantitatively analyze the two-dimensional (2D) spatiotemporal correlation properties of gamma-band (30–70 Hz) oscillations evoked by stimuli arriving at the primary visual cortex, and modulated by patchy connectivities that depend on orientation preference (OP). Correlation functions are derived analytically for general stimulus and measurement conditions. The theoretical results reproduce a range of published experimental results. These include (i) the existence of two-point oscillatory temporal cross correlations with zero time lag between neurons with similar OP; (ii) the influence of spatial separation of neurons on the strength of the correlations; and (iii) the effects of differing stimulus orientations. They go beyond prior work by incorporating experimentally observed patchy projection patterns to predict the 2D correlation structure including both OP and ocular dominance effects, thereby relaxing assumptions of translational invariance implicit in prior one-dimensional analysis.
To reduce statistical redundancy of natural inputs and increase the sparseness of coding, neurons in primary visual cortex (V1) show tuning for stimulus size and surround suppression. This integration of spatial information is a fundamental, context-dependent neural operation involving extensive neural circuits that span across all cortical layers of a V1 column, and reflects both feedforward and feedback processing. However, how spatial integration is dynamically coordinated across cortical layers remains poorly understood. We recorded single- and multiunit activity and local field potentials across V1 layers of awake mice (both sexes) while they viewed stimuli of varying size and used dynamic Bayesian model comparisons to identify when laminar activity and interlaminar functional interactions showed surround suppression, the hallmark of spatial integration. We found that surround suppression is strongest in layer 3 (L3) and L4 activity, where suppression is established within ∼10 ms after response onset, and receptive fields dynamically sharpen while suppression strength increases. Importantly, we also found that specific directed functional connections were strongest for intermediate stimulus sizes and suppressed for larger ones, particularly for connections from L3 targeting L5 and L1. Together, the results shed light on the different functional roles of cortical layers in spatial integration and on how L3 dynamically coordinates activity across a cortical column depending on spatial context.SIGNIFICANCE STATEMENT Neurons in primary visual cortex (V1) show tuning for stimulus size, where responses to stimuli exceeding the receptive field can be suppressed (surround suppression). We demonstrate that functional connectivity between V1 layers can also have a surround-suppressed profile. A particularly prominent role seems to have layer 3, the functional connections to layers 5 and 1 of which are strongest for stimuli of optimal size and decreased for large stimuli. Our results therefore point toward a key role of layer 3 in coordinating activity across the cortical column according to spatial context.
In the primary visual cortex (V1), neuronal responses to stimuli within the receptive field (RF) are modulated by stimuli in the RF surround. A common effect of surround modulation is surround suppression, which is dependent on the feature difference between stimuli within and surround the RF and is suggested to be involved in the perceptual phenomenon of figure-ground segregation. In this study, we examined the relationship between feature-specific surround suppression of V1 neurons and figure detection behavior based on figure-ground feature difference. We trained freely moving mice to perform a figure detection task using figure and ground gratings that differed in spatial phase. The performance of figure detection increased with the figure-ground phase difference, and was modulated by stimulus contrast. Electrophysiological recordings from V1 in head-fixed mice showed that the increase in phase difference between stimuli within and surround the RF caused a reduction in surround suppression, which was associated with an increase in V1 neural discrimination between stimuli with and without RF-surround phase difference. Consistent with the behavioral performance, the sensitivity of V1 neurons to RF-surround phase difference could be influenced by stimulus contrast. Furthermore, inhibiting V1 by optogenetically activating either parvalbumin (PV)- or somatostatin (SOM)-expressing inhibitory neurons both decreased the behavioral performance of figure detection. Thus, the phase-specific surround suppression in V1 represents a neural correlate of figure detection behavior based on figure-ground phase discontinuity.
This chapter studies the second component of the functional architecture of primary visual areas, namely what are called cortico-cortical ‘horizontal’ connections. They join together neurons that detect orientations at different points which are parallel, and even approximately coaxial. This coaxial ‘parallel transport’ has been confirmed by psychophysical experiments on what David Field, Anthony Hayes,, and Robert Hess called the association field. To a first approximation, coaxial parallel transport implements what is known in differential geometry as the contact structure of the fibre bundle \(\mathbb {V}_\mathrm{J}\) of 1 -jets of curves in the plane. It is invariant under the action of the group SE(2) of isometries of the Euclidean plane. The contact structure is associated with a non-commutative group structure on \(\mathbb {V}_\mathrm{J}\), the action of SE(2) then being identified with the left-translations of \(\mathbb {V}_\mathrm{J}\) on itself. This group is isomorphic to the ‘polarized’ Heisenberg group. It is a nilpotent group belonging to the class of what are called Carnot groups. The definition of an SE(2)-invariant metric on the contact planes thus defines what is called a sub-Riemannian geometry. Using this, one obtains a natural explanation for the phenomenon whereby the visual system constructs long-range illusory contours. For illusory contours with curvature, this leads to variational models. At the end of the 1980s, David Mumford already proposed a first model, defined in the plane \(\mathbb {R}^{2}\) of the visual field, which minimized a certain functional of curve length and curvature. We propose a model in the contact bundle \(\mathbb {V}_\mathrm{J}\) that rests on the hypothesis that illusory contours are sub-Riemannian geodesics. The Cartan ‘prolongation’ of this structure, called the Engel structure, corresponds to the 2 -jets of curves in the plane \(\mathbb {R}^{2}\). It must be taken into account if we want to report on the experimental data showing that, in the primary visual system, there exist not only orientation detectors (tangents and 1-jets), but also curvature detectors (osculating circles and 2-jets). We then point out a few properties of the functional architecture of areas V2, V4 (for colour), V5, and MT (for motion). We also discuss Swindale’s model for directions. Finally, we briefly describe the genetic control of the neural morphogenesis and axon guidance of the functional architectures.
Voltage-sensitive dye imaging experiments in primary visual cortex (V1) have shown that local, oriented visual stimuli elicit stable orientation-selective activation within the stimulus retinotopic footprint. The cortical activation dynamically extends far beyond the retinotopic footprint, but the peripheral spread stays non-selective—a surprising finding given a number of anatomo-functional studies showing the orientation specificity of long-range connections. Here we use a computational model to investigate this apparent discrepancy by studying the expected population response using known published anatomical constraints. The dynamics of input-driven localized states were simulated in a planar neural field model with multiple sub-populations encoding orientation. The realistic connectivity profile has parameters controlling the clustering of long-range connections and their orientation bias. We found substantial overlap between the anatomically relevant parameter range and a steep decay in orientation selective activation that is consistent with the imaging experiments. In this way our study reconciles the reported orientation bias of long-range connections with the functional expression of orientation selective neural activity. Our results demonstrate this sharp decay is contingent on three factors, that long-range connections are sufficiently diffuse, that the orientation bias of these connections is in an intermediate range (consistent with anatomy) and that excitation is sufficiently balanced by inhibition. Conversely, our modelling results predict that, for reduced global inhibition strength, spurious orientation selective activation could be generated through long-range lateral connections. Furthermore, if the orientation bias of lateral connections is very strong, or if inhibition is particularly weak, the network operates close to an instability leading to unbounded cortical activation.
Poincaré observed that the perception of space is based on active movements, and relies on the notions of invariance, covariation between sensors and environment, and active compensation ( [179], [180], [181], [182]). The research of Piaget has proved the importance of various kinds of geometrical invariance in cognitive and behaviorial development ( [173], [177], [176]). To him intelligence is a form of adaptation, the continuous process of using the environment for learning ( [174]). Adaptation is a process that can happen at the scale of evolution, development or functioning. In ecology, or in population biology and genetics, it means the adjustment or change in behavior, physiology, and structure of an organism to become more suited to an environment, thus better fitted to survive and passing their genes on to the next generation (Darwin plus Mendel, [45]).
The set of neural connections in an organism is now called the connectome. Using recent noninvasive techniques such as diffusion tensor imaging and traditional invasive techniques for tract tracing has uncovered a wide range of connectomes from Caenorhabditis elegans and Drosophila melanogaster to cat, mouse, rat, macaque, and human. We can therefore start to look at organisational changes during evolution. At the same time cell lineage information and measurements at different time steps allow us to observe network changes during individual, ontogenetic development. We find that the structure of a network is closely linked to its function, with distinct functional components first leading to network modules and, after the rise of further specialisation, to a hierarchical architecture with modules at different levels of network organisation. We first describe concepts that are used to characterize complex networks, then move on to briefly discuss computational models for development and evolution, before showing how network features change during the evolution and development of brain networks. We conclude with future challenges in the field of connectome development and evolution.
Collinear facilitation refers to the increase in sensitivity found for a target when aligned between nearby, brighter flankers, and is thought to underpin the ability to integrate fragmented contours to form higher order global shapes. Many studies have explored the spatial and temporal aspects of this arrangement, and there is a consensus that two mechanisms could be responsible for this phenomenon; lateral excitation within V1 and extra-striate feedback to V1. There is some debate as to whether facilitation can still occur if the target is presented before the flankers, a manipulation known as backward masking, which could rely on feedback to V1. We shed light on this debate by using forward, simultaneous and backward masking with a relatively large sample of 26 participants. We used short stimulus presentation times (35 ms) and a range of SOAs (stimulus onset asynchronies) (-70, -35, 0, 35 and 70 ms) in order to isolate any feedback facilitation that may occur. We found that collinear facilitation occurred with forward masking (+ve SOAs) in all participants. However, facilitation with backward masking (-ve SOAs) only occurred in 54% of participants. We present a basic model of facilitation that simulates the results of our experiment and could account for differences between previous studies. The model indicates that facilitation with backward masking arises primarily from feedback excitation. Our findings suggest that both lateral connectivity and extra-striate feedback contribute to target facilitation, but in fundamentally different ways and that feedback may be absent in some participants.
Anatomy and function of long-range intrinsic and callosal axons in primary visual cortex are reviewed. In cats, both arborize in a patchy manner, in an orderly relationship to the visuotopic map and visual stimulus features. Patches tend to link neurons with similar contour and direction preference aligned along a collinear visual field axis. Direct investigation of callosal action on visual responses reveals a multiplicative shift without changing neuronal selectivity. Both gain and bias toward excitation or inhibition depend on global stimulus attributes. Interactions are more pronounced for neurons processing similar, in particular cardinal, visual features. As feature selectivity emerges already in ongoing neuronal activity, it is hypothesized that perceptual grouping is anticipated via the feature bias in patchy connections. By comparing data from lateral and feedback circuits, we conclude that visual callosal connections are more similar to intrinsic connections and can be interpreted as extending this circuit across the hemispheres.
There is growing evidence of significant plasticity in neuronal receptive fields and functional architecture in adult primary sensory cortex. Surgical lesions or rewiring of nerves in the periphery lead to large-scale changes in the corresponding cortical maps. Such changes are also seen after protracted training on sensory discrimination tasks, in a manner that reflects the subjects' improved discriminative abilities after training and is governed by their attentional state during training. More rapid and dynamic changes in cortical receptive field properties are seen with selective visual stimulation and during conditioning experiments. In the visual system, adult plasticity is clearly attributable to changes in cortex and not subcortical changes; moreover, the evidence suggests that the network of horizontal collaterals in primary visual cortex (V1) may play a significant role in V1 plasticity, both long-term and rapid. The same network is also likely to underlie some aspects of routine visual integration in V1. This leads to the speculation that plastic processes could form a part of routine cortical processing. At a cellular level, neurons in adult cortex possess the synaptic machinery that could underlie much of the observed adult plasticity. This includes short- as well as long-term activity-dependent processes for synaptic modification, as well as the modulation of such effects by the context of a task.
The encephalization which accompanies the phylogenetic emergence of mammals has led to a dramatic increase of nerve cells and nervous connections that exceeds by far the disproportionally small increase of the genom. This implies that the information stored in the genom cannot alone suffice to specify the connectivity of higher nervous systems. The following numbers illustrate the magnitude of the specification problems that have to be solved during brain development.
In the macaque monkey striate (primary visual) cortex, the grouping of cells into ocular dominance and orientation columns leads to the prediction of highly specific spatial patterns of cellular activity in response to stimulation by lines through one or both eyes. In the pesent paper these paterns have been examined by the 2-deoxyuglucose autoradiographic method developed by Sokoloff and his group (Kennedy et al, '76). An anesthetized monkey was given an injection of 14C 2-deoxyglucose and then visually stimulated for 45 minues with a large array of moving vertical stripes, with both eyes open. The 14C autoradiographs of striate cortex showed vertical bands of label extending through the full cortical thickness. Layer I was at most only lightly labelled, and layers IV b and VI wee the most dense. Layer IV c (the site of terminations of most geniculate afferents) was labelled uniformly along its length, as expected from the lack of orientation specificity of units recorded in that leyer. In the other layers the pattern seen in tangential sections was complex, consisting of swirling stripes with many bifurcations and blind endings, but with occasional more regular regions whee the stripes wee roughly parallel. Interstripe distance was rather constant, at 570 μm. Ocular dominance columns were examined in this same monkey, in the same region, by injecting one eye with 3H-proline two weeks before the deoxyglucose experiment, and preparing a second set of autoradiographs of the sections after prolonged washing to remove the 14C-deoxyglucose. As seen in tangential sections through layer IV c, these columns had the usual stripe-like form, with a period of 770 μm, but were simpler in their pattern than the orientation stripes, with fewer bifurcations and less swirling. A comparison of the two sets of columns in the same area showed many intersections, but no strict or consistent relationships: angles of intersection showed a distribution that was not obviously different from that expected for any two randomly superimposed sets of lines.
Another monkey was stimulated with vertical stripes, but with only one eye open. Deoxyglucose autoradiographs of tangential sections showed regular uniform rows of label in layer IV c, with all the characteristic features of eye dominance columns. In the layers above and below IV c the rows in tangential view were broken up into regularly spaced patches of label, presumably representing aggregations of cells responsive to vertically oriented stimuli. The patches showed no consistent alignment across the ocular dominance rows, and indeed no such tendency would be expected, considering the complexity of the orientation columns. This pattern of labelling is again predicted from and confirms the previous physiological studies.
Single cell recordings in monkey striate cortex have shown differences in response properties from one cell layer to the next and have also shown that the IVth layer, which receives most of its input from the geniculate, is subdivided into a mosaic of regions, some connected to the left eye, others to the right. In the present study small lesions were made in single layers or pairs of layers in the lateral geniculate body, and the striate cortex was later examined with a Fink‐Heimer modification of the Nauta method. We hoped to correlate the laminar distribution of axon terminals in the cortex with functional differences between layers, and to demonstrate the IVth‐layer mosaic anatomically.
After lesions in either of the two most dorsal (parvocellular) layers, terminal degeneration was found mainly in layer IVc, with a second minor input to a narrow band in the upper part of IVa. A very few degenerating fibers ascended to layer I. In contrast, lesions in either of the two ventral (magnocellular) layers were followed by terminal degeneration confined, apparently, to IVb, or at times extending for a short distance into the upper part of IVc; no degeneration was seen in layer IVa or in layer I.
After a lesion confined to a single geniculate layer, a section through the corresponding region of striate cortex showed discrete areas or bands of degeneration in layer IV, usually 0.5–1.0 mm long, separated by interbands of about the same extent in which there was no terminal degeneration. When serial sections were reconstructed to obtain a face‐on view of the layer‐IV mosaic, it appeared as a series of regular, parallel, alternating degeneration‐rich and degeneration‐poor stripes. When a geniculate lesion involved both layer VI (the most dorsal, with input from the contralateral eye) and the part of layer V directly below (ipsilateral eye), the cortical degeneration, as expected, occupied a virtually continuous strip in layer IVc and the reconstructed face‐on view of this layer showed a large confluent region of degeneration.
In some of the reconstructions the cortical stripes seemed highly regular; in others there was a variable amount of cross connection between stripes. The stripes varied in width from 0.25 to 0.50 mm, and width did not seem to correlate with region of retinal representation.
It is concluded that the long narrow stripes of alternating left‐eye and right‐eye input to layer IV are an anatomical counterpart of the physiologically observed ocular‐dominance columns. Because of this segregation of inputs, cells of layer IV are almost invariably influenced by one eye only. A cell above or below layer IV will be dominated by the eye supplying the nearest IVth layer stripe, but will generally, though not always, receive a subsidiary input from the other eye, presumably by diagonal connections from the nearest stripes supplied by that eye.
Of the many possible functions of the macaque monkey primary visual cortex (striate cortex, area 17) two are now fairly well understood. First, the incoming information from the lateral geniculate bodies is rearranged so that most cells in the striate cortex respond to specifically oriented line segments, and, second, information originating from the two eyes converges upon single cells. The rearrangement and convergence do not take place immediately, however: in layer IVc, where the bulk of the afferents terminate, virtually all cells have fields with circular symmetry and are strictly monocular, driven from the left eye or from the right, but not both; at subsequent stages, in layers above and below IVc, most cells show orientation specificity, and about half are binocular. In a binocular cell the receptive fields in the two eyes are on corresponding regions in the two retinas and are identical in structure, but one eye is usually more effective than the other in influencing the cell; all shades of ocular dominance are seen. These two functions are strongly reflected in the architecture of the cortex, in that cells with common physiological properties are grouped together in vertically organized systems of columns. In an ocular dominance column all cells respond preferentially to the same eye. By four independent anatomical methods it has been shown that these columns have the from of vertically disposed alternating left-eye and right-eye slabs, which in horizontal section form alternating stripes about 400 mu m thick, with occasional bifurcations and blind endings. Cells of like orientation specificity are known from physiological recordings to be similarly grouped in much narrower vertical sheeet-like aggregations, stacked in orderly sequences so that on traversing the cortex tangentially one normally encounters a succession of small shifts in orientation, clockwise or counterclockwise; a 1 mm traverse is usually accompanied by one or several full rotations through 180 degrees, broken at times by reversals in direction of rotation and occasionally by large abrupt shifts. A full complement of columns, of either type, left-plus-right eye or a complete 180 degrees sequence, is termed a hypercolumn. Columns (and hence hypercolumns) have roughly the same width throughout the binocular part of the cortex. The two independent systems of hypercolumns are engrafted upon the well known topographic representation of the visual field. The receptive fields mapped in a vertical penetration through cortex show a scatter in position roughly equal to the average size of the fields themselves, and the area thus covered, the aggregate receptive field, increases with distance from the fovea. A parallel increase is seen in reciprocal magnification (the number of degrees of visual field corresponding to 1 mm of cortex). Over most or all of the striate cortex a movement of 1-2 mm, traversing several hypercolumns, is accompanied by a movement through the visual field about equal in size to the local aggregate receptive field. Thus any 1-2 mm block of cortex contains roughly the machinery needed to subserve an aggregate receptive field. In the cortex the fall-off in detail with which the visual field is analysed, as one moves out from the foveal area, is accompanied not by a reduction in thickness of layers, as is found in the retina, but by a reduction in the area of cortex (and hence the number of columnar units) devoted to a given amount of visual field: unlike the retina, the striate cortex is virtually uniform morphologically but varies in magnification. In most respects the above description fits the newborn monkey just as well as the adult, suggesting that area 17 is largely genetically programmed. The ocular dominance columns, however, are not fully developed at birth, since the geniculate terminals belonging to one eye occupy layer IVc throughout its length, segregating out into separate columns only after about the first 6 weeks, whether or not the animal has visual experience. If one eye is sutured closed during this early period the columns belonging to that eye become shrunken and their companions correspondingly expanded. This would seem to be at least in part the result of interference with normal maturation, though sprouting and retraction of axon terminals are not excluded.
Sixty lesions were placed in the pulvinar nucleus or the lateral geniculate nucleus of the tree shrew, and degenerated axons and their terminals were traced to the cortex. In all but two of the animals the electrode approached the thalamic target through the cerebellum and midbrain, thus sparing the cortex and thalamic nuclei other than the target nuclei. The results show that the pulvinar nucleus projects in a topographic fashion to an extensive cortical zone that includes areas 18, 19 and several temporal areas below 19. While there are several architectonic areas in its cortical target, no corresponding subdivisions could be established within the pulvinar nucleus, and its projections are best explained in terms of a single topographic organization. Further, since the pulvinar nucleus receives fibers from the superficial layers of the superior colliculus, its extensive cortical target can be regarded as primary visual cortex. The lateral geniculate nucleus projects in a precisely topographic fashion to area 17. Further, our evidence suggests that each layer of the lateral geniculate nucleus projects to a horizontal strip within the fourth or granular layer of area striata. With respect to the question of the relation between ocular dominance and location in area 17, the pattern of projections from the lateral geniculate nucleus does not reveal ocular dominance columns in layer IV of the tree shrew. In contrast to our results Hubel and Wiesel ('68, '69) have shown that in the monkey there are vertical columns of cells in layer IV driven by either the homolateral or the contralateral eye. The case for the cat (Hubel and Wiesel, '62, '65) may be different from either of the other two species, thus posing the problem of discovering the mammalian plan and departures from the prototypical organization.
1. The striate cortex was studied in lightly anaesthetized macaque and spider monkeys by recording extracellularly from single units and stimulating the retinas with spots or patterns of light. Most cells can be categorized as simple, complex, or hypercomplex, with response properties very similar to those previously described in the cat. On the average, however, receptive fields are smaller, and there is a greater sensitivity to changes in stimulus orientation. A small proportion of the cells are colour coded.
2. Evidence is presented for at least two independent systems of columns extending vertically from surface to white matter. Columns of the first type contain cells with common receptive‐field orientations. They are similar to the orientation columns described in the cat, but are probably smaller in cross‐sectional area. In the second system cells are aggregated into columns according to eye preference. The ocular dominance columns are larger than the orientation columns, and the two sets of boundaries seem to be independent.
3. There is a tendency for cells to be grouped according to symmetry of responses to movement; in some regions the cells respond equally well to the two opposite directions of movement of a line, but other regions contain a mixture of cells favouring one direction and cells favouring the other.
4. A horizontal organization corresponding to the cortical layering can also be discerned. The upper layers (II and the upper two‐thirds of III) contain complex and hypercomplex cells, but simple cells are virtually absent. The cells are mostly binocularly driven. Simple cells are found deep in layer III, and in IV A and IV B. In layer IV B they form a large proportion of the population, whereas complex cells are rare. In layers IV A and IV B one finds units lacking orientation specificity; it is not clear whether these are cell bodies or axons of geniculate cells. In layer IV most cells are driven by one eye only; this layer consists of a mosaic with cells of some regions responding to one eye only, those of other regions responding to the other eye. Layers V and VI contain mostly complex and hypercomplex cells, binocularly driven.
5. The cortex is seen as a system organized vertically and horizontally in entirely different ways. In the vertical system (in which cells lying along a vertical line in the cortex have common features) stimulus dimensions such as retinal position, line orientation, ocular dominance, and perhaps directionality of movement, are mapped in sets of superimposed but independent mosaics. The horizontal system segregates cells in layers by hierarchical orders, the lowest orders (simple cells monocularly driven) located in and near layer IV, the higher orders in the upper and lower layers.
The topographic organization of the orientation column system in tree shrew striate cortex was examined by using 2–deoxyglucose autoradiography to map the cortical sites of increased metabolic activity produced by visual stimulation with stripes of a single orientation. Awake experimental tree shrews (freely moving, restrained, or paralyzed) were given injections of deoxyglucose label and then stimulated with vertical, horizontal, or oblique stripes for 45–75 min. Autoradiographs of coronal sections through the striate cortex revealed regularly spaced radial zones of increased deoxyglucose uptake 150–350 μm wide, extending from the cortical surface to the white matter, separated by interzone regions of lower uptake. The radial zones were most densely labeled and distinct in layers I–IIIb and least distinct in layer IV, which was continuously and densely labeled throughout both the radial zone and interzone regions. These radial zones, which were not present in control animals that viewed many orientations, reflect the locations of cortical cells activated by a single stimulus orientation.
Microelectrode recordings were made in the binocular portion of the tree shrew striate cortex to determine how orientation selective cells are distributed topographically in area 17 of this species. Seventy-five percent of the cells sampled were activated well by elongated visual stimuli and were quite selective for stimulus orientation. Ninety-five percent of the orientation-selective cells had orientation tuning ranges (Wilson and Sherman, '76) between ± 5° and ± 40° from their optimal orientation.