Anatomical substrates for early stages in cortical processing of visual information in the macaque monkey

A laminar model for the joint development of ocular dominance columns and CO blobs in the primary visual cortex

In this paper, we present a multi-layer, activity-dependent model for the joint development of ocular dominance (OD) columns and cytochrome oxidase (CO) blobs in primate V1. For simplicity, we focus on layers 4C and 2/3 with both layers receiving direct thalamic inputs and layer 4C sending vertical projections to layer 2/3. Both the thalamic and the vertical connections are taken to be modifiable by activity. Using a correlation-based Hebbian learning rule with subtractive normalization, we show how the formation of an OD map in layer 4C is inherited by layer 2/3 via the vertical projections. Competition between these feedforward projections and the direct thalamic input to layer 2/3 then results in the formation of CO blobs superimposed upon the ocular dominance map. The spacing of the OD columns is determined by the spatial profile of the intralaminar connections within layer 4, while the spacing of CO blobs depends both on the width of the OD columns inherited from layer 4 and the spatial distribution of intralaminar connections within the superficial layer. The resulting CO blob distribution is shown to be consistent with experimental data. In addition, we numerically simulate monocular deprivation and find that while the CO blob distribution is unaltered, the OD pattern undergoes modification. The OD stripes of the deprived eye narrow, whereas the OD stripes for the remaining open eye widen.

Anatomy and Physiology of Macaque Visual Cortical Areas V1, V2, and V5/MT: Bases for Biologically Realistic Models

The cerebral cortex of primates encompasses multiple anatomically and physiologically distinct areas processing visual information. Areas V1, V2, and V5/MT are conserved across mammals and are central for visual behavior. To facilitate the generation of biologically accurate computational models of primate early visual processing, here we provide an overview of over 350 published studies of these three areas in the genus Macaca, whose visual system provides the closest model for human vision. The literature reports 14 anatomical connection types from the lateral geniculate nucleus of the thalamus to V1 having distinct layers of origin or termination, and 194 connection types between V1, V2, and V5, forming multiple parallel and interacting visual processing streams. Moreover, within V1, there are reports of 286 and 120 types of intrinsic excitatory and inhibitory connections, respectively. Physiologically, tuning of neuronal responses to 11 types of visual stimulus parameters has been consistently reported. Overall, the optimal spatial frequency (SF) of constituent neurons decreases with cortical hierarchy. Moreover, V5 neurons are distinct from neurons in other areas for their higher direction selectivity, higher contrast sensitivity, higher temporal frequency tuning, and wider SF bandwidth. We also discuss currently unavailable data that could be useful for biologically accurate models.

Attentional Gating in Primary Visual Cortex: A Physiological Basis for Dyslexia

The visual magnocellular pathway is known to play a central part in visuospatial attention and in directing attention to specific parts of the visual world in serial search. It is proposed that, in the case of reading, this mechanism is trained to perform a sequential gating of visual information coming into the primary visual cortex to enable further orderly processing by the ventral stream. This scheme, taken together with the potential for plasticity between the different afferent channels in the case of a relative impairment of the magnocellular system, can provide some limited rationale for the beneficial effects that have been claimed for the use of coloured overlays and glasses.

Towards a unified scheme of cortical lamination for primary visual cortex across primates: insights from NeuN and VGLUT2 immunoreactivity

Primary visual cortex (V1) is clearly distinguishable from other cortical areas by its distinctive pattern of neocortical lamination across mammalian species. In some mammals, primates in particular, the layers of V1 are further divided into a number of sublayers based on their anatomical and functional characteristics. While these sublayers are easily recognizable across a range of primates, the exact number of divisions in each layer and their relative position within the depth of V1 has been inconsistently reported, largely due to conflicting schemes of nomenclature for the V1 layers. This conflict centers on the definition of layer 4 in primate V1, and the subdivisions of layer 4 that can be consistently identified across primate species. Brodmann’s (1909) laminar scheme for V1 delineates three subdivisions of layer 4 in primates, based on cellular morphology and geniculate inputs in anthropoid monkeys. In contrast, Hässler’s (1967) laminar scheme delineates a single layer 4 and multiple subdivisions of layer 3, based on comparisons of V1 lamination across the primate lineage. In order to clarify laminar divisions in primate visual cortex, we performed NeuN and VGLUT2 immunohistochemistry in V1 of chimpanzees, Old World macaque monkeys, New World squirrel, owl, and marmoset monkeys, prosimian galagos and mouse lemurs, and non-primate, but highly visual, tree shrews. By comparing the laminar divisions identified by each method across species, we find that Hässler’s (1967) laminar scheme for V1 provides a more consistent representation of neocortical layers across all primates, including humans, and facilitates comparisons of V1 lamination with non-primate species. These findings, along with many others, support the consistent use of Hässler’s laminar scheme in V1 research.

Differential expression of vesicular glutamate transporters 1 and 2 may identify distinct modes of glutamatergic transmission in the macaque visual system

Glutamate is the primary neurotransmitter utilized by the mammalian visual system for excitatory neurotransmission. The sequestration of glutamate into synaptic vesicles, and the subsequent transport of filled vesicles to the presynaptic terminal membrane, is regulated by a family of proteins known as vesicular glutamate transporters (VGLUTs). Two VGLUT proteins, VGLUT1 and VGLUT2, characterize distinct sets of glutamatergic projections between visual structures in rodents and prosimian primates, yet little is known about their distributions in the visual system of anthropoid primates. We have examined the mRNA and protein expression patterns of VGLUT1 and VGLUT2 in the visual system of macaque monkeys, an Old World anthropoid primate, in order to determine their relative distributions in the superior colliculus, lateral geniculate nucleus, pulvinar complex, V1 and V2. Distinct expression patterns for both VGLUT1 and VGLUT2 identified architectonic boundaries in all structures, as well as anatomical subdivisions of the superior colliculus, pulvinar complex, and V1. These results suggest that VGLUT1 and VGLUT2 clearly identify regions of glutamatergic input in visual structures, and may identify common architectonic features of visual areas and nuclei across the primate radiation. Additionally, we find that VGLUT1 and VGLUT2 characterize distinct subsets of glutamatergic projections in the macaque visual system; VGLUT2 predominates in driving or feedforward projections from lower order to higher order visual structures while VGLUT1 predominates in modulatory or feedback projections from higher order to lower order visual structures. The distribution of these two proteins suggests that VGLUT1 and VGLUT2 may identify class 1 and class 2 type glutamatergic projections within the primate visual system (Sherman and Guillery, 2006).

Maximum decoding abilities of temporal patterns and synchronized firings: application to auditory neurons responding to click trains and amplitude modulated white noise

Simultaneous recordings of an increasing number of neurons have recently become available, but few methods have been proposed to handle this activity. Here, we extract and investigate all the possible temporal neural activity patterns based on synchronized firings of neurons recorded on multiple electrodes, or based on bursts of single-electrode activity in cat primary auditory cortex. We apply this to responses to periodic click trains or sinusoïdal amplitude modulated noise by obtaining for each pattern its temporal modulation transfer function. An algorithm that maximizes the mutual information between all patterns and stimuli subsequently leads to the identification of patterns that optimally decode modulation frequency (MF). We show that stimulus information contained in multi-electrode synchronized firing is not redundant with single-electrode firings and leads to improved efficiency of MF decoding. We also show that the combined use of firing rate and temporal codes leads to a better discrimination of the MF.

Physiological differences between neurons in layer 2 and layer 3 of primary visual cortex (V1) of alert macaque monkeys

The physiological literature does not distinguish between the superficial layers 2 and 3 of the primary visual cortex even though these two layers differ in their cytoarchitecture and anatomical connections. To distinguish layer 2 from layer 3, we have analysed the response characteristics of neurons recorded during microelectrode penetrations perpendicular to the cortical surface. Extracellular responses of single neurons to sweeping bars were recorded while macaque monkeys performed a fixation task. Data were analysed from penetrations where cells could be localized to specific depths in the cortex. Although the most superficial cells (depth, 145-371 microm; presumably layer 2) responded preferentially to particular stimulus orientations, they were less selective than cells encountered immediately beneath them (depth, 386-696 microm; presumably layer 3). Layer 2 cells had smaller spikes, higher levels of ongoing activity, larger receptive field activating regions, and less finely tuned selectivity for stimulus orientation and length than layer 3 cells. Direction selectivity was found only in layer 3. These data suggest that layer 3 is involved in generating and transmitting precise, localized information about image features, while the lesser selectivity of layer 2 cells may participate in top-down influences from higher cortical areas, as well as modulatory influences from subcortical brain regions.

Processing of first-order motion in marmoset visual cortex is influenced by second-order motion

We measured the responses of single neurons in marmoset visual cortex (V1, V2, and the third visual complex) to moving first-order stimuli and to combined first- and second-order stimuli in order to determine whether first-order motion processing was influenced by second-order motion. Beat stimuli were made by summing two gratings of similar spatial frequency, one of which was static and the other was moving. The beat is the product of a moving sinusoidal carrier (first-order motion) and a moving low-frequency contrast envelope (second-order motion). We compared responses to moving first-order gratings alone with responses to beat patterns with first-order and second-order motion in the same direction as each other, or in opposite directions to each other in order to distinguish first-order and second-order direction-selective responses. In the majority (72%, 67/93) of cells (V1 73%, 45/62; V2 70%, 16/23; third visual complex 75%, 6/8), responses to first-order motion were significantly influenced by the addition of a second-order signal. The second-order envelope was more influential when moving in the opposite direction to the first-order stimulus, reducing first-order direction sensitivity in V1, V2, and the third visual complex. We interpret these results as showing that first-order motion processing through early visual cortex is not separate from second-order motion processing; suggesting that both motion signals are processed by the same system.

Contribution of feedforward, lateral and feedback connections to the classical receptive field center and extra-classical receptive field surround of primate V1 neurons

A central question in visual neuroscience is what circuits generate the responses of neurons in the primary visual cortex (V1). V1 neurons respond best to oriented stimuli of optimal size within their receptive field (RF) center. This size tuning is contrast dependent, i.e. a neuron's optimal stimulus size measured at high contrast (the high-contrast summation RF, or hsRF) is smaller than when measured using low-contrast stimuli (the low-contrast summation RF, or lsRF). Responses to stimuli in the RF center are usually suppressed by iso-oriented stimuli in the extra-classical RF surround. Iso-orientation surround suppression is fast and long range, extending well beyond the size of V1 cells' lsRF. Geniculocortical feedforward (FF), V1 lateral and extrastriate feedback (FB) connections to V1 could all contribute to generating the RF center and surround of V1 neurons. Studies on the spatio-temporal properties and functional organization of these connections can help disclose their specific contributions to the responses of V1 cells. These studies, reviewed in this chapter, have shown that FF afferents to V1 integrate signals within the hsRF of V1 cells; V1 lateral connections are commensurate with the size of the lsRF and may, thus, underlie contrast-dependent changes in spatial summation, and modulatory effects arising from the surround region closer to the RF center (the "near" surround). The spatial and temporal properties of lateral connections cannot account for the dimensions and onset latency of modulation arising from more distant regions of the surround (the "far" surround). Inter-areal FB connections to V1, instead, are commensurate with the full spatial range of center and surround responses, and show fast conduction velocity consistent with the short onset latency of modulation arising from the "far" surround. We review data showing that a subset of FB connections terminate in a patchy fashion in V1, and show modular and orientation specificity, consistent with their proposed role in orientation-specific center-surround interactions. We propose specific mechanisms by which each connection type contributes to the RF center and surround of V1 neurons, and implement these hypotheses into a recurrent network model. We show physiological data in support of the model's predictions, revealing that modulation from the "far" surround is not always suppressive, but can be facilitatory under specific stimulus conditions.

Peaked Encoding of Relative Luminance in Macaque Areas V1 and V2

It is widely presumed that throughout the primate visual pathway neurons encode the relative luminance of objects (at a given light adaptation level) using two classes of monotonic function, one positively and the other negatively sloped. Based on computational considerations, we hypothesized that early visual cortex also contains neurons preferring intermediate relative luminance values. We tested this hypothesis by recording from single neurons in areas V1 and V2 of alert, fixating macaque monkeys during presentation of a large, spatially uniform patch oscillating slowly in luminance and surrounded by a static texture background. A substantial subset of neurons responsive to such low spatial frequency luminance stimuli in both areas exhibited prominent and statistically reliable response peaks to intermediate rather than minimal or maximal luminance values. When presented with static patches of different luminance but of the same spatial configuration, most neurons tested retained a preference for intermediate relative luminance. Control experiments using luminance modulation at multiple low temporal frequencies or reduced amplitude indicate that in the slow luminance-oscillating paradigm, responses were more strongly modulated by the luminance level than the rate of luminance change. These results strongly support our hypothesis and reveal a striking cortical transformation of luminance-related information that may contribute to the perception of surface brightness and lightness. In addition, we tested many luminance-sensitive neurons with large chromatic patches oscillating slowly in luminance. Many cells, including the gray-preferring neurons, exhibited strong color preferences, suggesting a role of luminance-sensitive cells in encoding information in three-dimensional color space.

Attentional modulation of visual processing

Single-unit recording studies in the macaque have carefully documented the modulatory effects of attention on the response properties of visual cortical neurons. Attention produces qualitatively different effects on firing rate, depending on whether a stimulus appears alone or accompanied by distracters. Studies of contrast gain control in anesthetized mammals have found parallel patterns of results when the luminance contrast of a stimulus increases. This finding suggests that attention has co-opted the circuits that mediate contrast gain control and that it operates by increasing the effective contrast of the attended stimulus. Consistent with this idea, microstimulation of the frontal eye fields, one of several areas that control the allocation of spatial attention, induces spatially local increases in sensitivity both at the behavioral level and among neurons in area V4, where endogenously generated attention increases contrast sensitivity. Studies in the slice have begun to explain how modulatory signals might cause such increases in sensitivity.

Anatomical origins of the classical receptive field and modulatory surround field of single neurons in macaque visual cortical area V1

From the analyses of our own and others' anatomical and physiological data for the macaque visual system, we arrive at a conclusion that three pathways can provide the V1 neuron with access to information from the visual field and affect its response. First, direct thalamic input can determine the size of the initial activating RF at high contrast. Second, lateral connections can enlarge the RF at low contrast by pooling information from larger regions of cortex that are otherwise ineffective when high contrast thalamic input is driving the cortical neuron. Thirdly, feedback from extrastriate cortex (possibly together with overlap or interdigitation of coactive lateral connectional fields within V1) can provide a large and stimulus specific surround modulatory field. The stimulus specificity of the interactions between the center and surround fields, may be due to the orderly, matching structure and different scales of intra-areal and feedback projection excitatory pathways. The observed activity changes of single recorded excitatory neurons could be a result of the relative weight of excitation on the excitatory neurons themselves and on local inhibitory interneurons that synapse on them. Inhibitory basket neurons, driven by the local excitatory neurons, could govern local interactions between cortical patches of different tuning properties, resulting in more distant changes in excitatory input in the laterally connected intra-areal neuronal pools.

Convergence of parvocellular and magnocellular information channels in the primary visual cortex of the macaque

We investigated whether responses of single cells in the striate cortex of anaesthetized macaque monkeys exhibit signatures of both parvocellular (P) and magnocellular (M) inputs from the dorsal lateral geniculate nucleus (dLGN). We used a palette of 128 isoluminant hues at four different saturation levels to test responses to chromatic stimuli against a white background. Spectral selectivity with these isoluminant stimuli was taken as an indication of P inputs. The presence of magnocellular inputs to a given cortical cell was deduced from its responses to a battery of tests, including assessment of achromatic contrast sensitivity, relative strengths of chromatic and luminance borders in driving the cell at different velocities and conduction velocity of their retino-geniculo-cortical afferents. At least a quarter of the cells in our cortical sample appear to receive convergent P and M inputs. We cannot however, exclude the possibility that some of these cells could be receiving a convergent input from the third parallel channel from the dLGN, namely the koniocellular (K) rather than the P channel. The neurons with convergent P and M inputs were recorded not only from supragranular and infragranular layers but also from the principal geniculate input recipient layer 4. Thus, our results challenge classical ideas of strict parallelism between different information streams at the level of the primate striate cortex.

What geometric visual hallucinations tell us about the visual cortex

Many observers see geometric visual hallucinations after taking hallucinogens such as LSD, cannabis, mescaline or psilocybin; on viewing bright flickering lights; on waking up or falling asleep; in "near-death" experiences; and in many other syndromes. Klüver organized the images into four groups called form constants: (I) tunnels and funnels, (II) spirals, (III) lattices, including honeycombs and triangles, and (IV) cobwebs. In most cases, the images are seen in both eyes and move with them. We interpret this to mean that they are generated in the brain. Here, we summarize a theory of their origin in visual cortex (area V1), based on the assumption that the form of the retino-cortical map and the architecture of V1 determine their geometry. (A much longer and more detailed mathematical version has been published in Philosophical Transactions of the Royal Society B, 356 [2001].) We model V1 as the continuum limit of a lattice of interconnected hypercolumns, each comprising a number of interconnected iso-orientation columns. Based on anatomical evidence, we assume that the lateral connectivity between hypercolumns exhibits symmetries, rendering it invariant under the action of the Euclidean group E(2), composed of reflections and translations in the plane, and a (novel) shift-twist action. Using this symmetry, we show that the various patterns of activity that spontaneously emerge when V1's spatially uniform resting state becomes unstable correspond to the form constants when transformed to the visual field using the retino-cortical map. The results are sensitive to the detailed specification of the lateral connectivity and suggest that the cortical mechanisms that generate geometric visual hallucinations are closely related to those used to process edges, contours, surfaces, and textures.

The spatial transformation of color in the primary visual cortex of the macaque monkey

Perceptually, color is used to discriminate objects by hue and to identify color boundaries. The primate retina and the lateral geniculate nucleus (LGN) have cell populations sensitive to color modulation, but the role of the primary visual cortex (V1) in color signal processing is uncertain. We re-evaluated color processing in V1 by studying single-neuron responses to luminance and to equiluminant color patterns equated for cone contrast. Many neurons respond robustly to both equiluminant color and luminance modulation (color-luminance cells). Also, there are neurons that prefer luminance (luminance cells), and a few neurons that prefer color (color cells). Surprisingly, most color-luminance cells are spatial-frequency tuned, with approximately equal selectivity for chromatic and achromatic patterns. Therefore, V1 retains the color sensitivity provided by the LGN, and adds spatial selectivity for color boundaries.

Response latency of macaque area MT/V5 neurons and its relationship to stimulus parameters

A total of 310 MT/V5 single cells were tested in anesthetized, paralyzed macaque monkeys with moving random-dot stimuli. At optimum stimulus parameters, latencies ranged from 35 to 325 ms with a mean of 87+/-45 (SD) ms. By examining the relationship between latency and response levels, stimulus parameters, and stimulus selectivities, we attempted to isolate the contributions of these factors to latency and to identify delays representing intervening synapses (circuitry) and signal processing (flow of information through that circuitry). First, the relationship between stimulus parameters and latency was investigated by varying stimulus speed and direction for individual cells. Resulting changes in latencies were explainable in terms of response levels corresponding to how closely the actual stimulus matched the preferred stimulus of the cell. Second, the relationship between stimulus selectivity and latency across the population of cells was examined using the optimum speed and direction of each neuron. A weak tendency for cells tuned for slow speeds to have longer latencies was explainable by lower response rates among slower-tuned neurons. In contrast, sharper direction tuning was significantly associated with short latencies even after taking response rate into account, (P = 0.002, ANCOVA). Accordingly, even the first 10 ms of the population response fully demonstrates direction tuning. A third study, which examined the relationship between antagonistic surrounds and latency, revealed a significant association between the strength of the surround and the latency that was independent of response levels (P < 0.002, ANCOVA). Neurons having strong surrounds exhibited latencies averaging 20 ms longer than those with little or no surround influence, suggesting that neurons with surrounds represent a later stage in processing with one or more intervening synapses. The laminar distribution of latencies closely followed the average surround antagonism in each layer, increasing with distance from input layer IV but precisely mirroring response levels, which were highest near the input layer and gradually decreased with distance from input layer IV. Layer II proved the exception with unexpectedly shorter latencies (P< 0.02, ANOVA) yet showing only modest response levels. The short latency and lack of strong direction tuning in layer II is consistent with input from the superior colliculus. Finally, experiments with static stimuli showed that latency does not vary with response rate for such stimuli, suggesting a fundamentally different mode of processing than that for a moving stimulus.

Recurrent sampling models for the Helmholtz machine

Many recent analysis-by-synthesis density estimation models of cortical learning and processing have made the crucial simplifying assumption that units within a single layer are mutually independent given the states of units in the layer below or the layer above. In this article, we suggest using either a Markov random field or an alternative stochastic sampling architecture to capture explicitly particular forms of dependence within each layer. We develop the architectures in the context of real and binary Helmholtz machines. Recurrent sampling can be used to capture correlations within layers in the generative or the recognition models, and we also show how these can be combined.

Anatomical comparison of the macaque and marsupial visual cortex: common features that may reflect retention of essential cortical elements

This study identifies fundamental anatomical features of primary visual cortex, area V1 of macaque monkey cerebral cortex, i.e., features that are present in area V1 of phylogenetically distant mammals of quite different lifestyle and features that are common to other regions of cortex. We compared anatomical constituents of macaque V1 with V1 of members of the two principal marsupial lines, the dunnart and the quokka, that diverged from the eutherian mammalian line over 135 million years ago. Features of V1 common to both macaque and marsupials were then compared with anatomical features we have previously described for macaque prefrontal cortex. Despite large differences in overall area and thickness of V1 cortex between these animals, the absolute size of pyramidal neurons is remarkably similar, as are their specific dendritic branch patterns and patterns of distribution of intrinsic axons. Pyramidal neuron patchy connections exist in the supragranular V1 in both the marsupial quokka and macaque as well as in macaque prefrontal cortex. Several specific types of aspinous interneurons are common to area V1 in both marsupial and macaque and are also present in macaque prefrontal cortex. Spiny stellate cells are a common feature of the thalamic-recipient, mid-depth lamina 4 of V1 in all three species. Because these similarities exist despite the very different lifestyles and evolutionary histories of the animals compared, this finding argues for a highly conserved framework of cellular detail in macaque primary visual cortex rather than convergent evolution of these features.

Constraints on long range interactions mediating contour detection

Contour detection may be mediated by lateral interactions between neighboring cortical neurons whose receptive fields have collinear axes of preferred orientation. This hypothesis was tested in psychophysical experiments and computer simulations using a contour detection task in which observers searched for groups of Gabor patches that followed spatially extended contour paths embedded in noise consisting of several hundred Gabor patches with random positions and orientations. The orientation-selective units in the simulated neural network were linked by facilitatory interconnections whose strength depended on the geometry (distance, curvature, change in curvature) of smooth curves connecting the orientation axes of units in a pairwise fashion. Psychophysical detection performance was much higher for contour signal groups that followed closed rather than open-ended paths. However, just two sudden changes in orientation of neighboring Gabor patch elements in closed-path contours reduced detection performance to the same levels obtained with open-ended contours. These psychophysical data agreed with the results of the neural network simulations. Furthermore, the simulations also accounted for previous findings that removal of a single Gabor patch element from a closed-path contour group significantly degraded detection performance. We conclude that closure alone is not sufficient to enhance the visibility of a contour. However, if a closed contour meets certain geometric constraints, then lateral interactions based on these constraints can generate facilitation that reverberates around the closed path, thereby enhancing the contour's visibility.

The brain as a symbol-processing machine

The knowledge accumulated about the biochemistry of the synapsis in the last decades completely changes the notion of brain processing founded exclusively over an electrical mechanism, toward that supported by a complex chemical message exchange occurring both locally, at the synaptic site, as well as at other localities, depending on the solubility of the involved chemical substances in the extracellular compartment. These biochemical transactions support a rich symbolic processing of the information both encoded by the genes and provided by actual data collected from the surrounding environment, by means of either special molecular or cellular receptor systems. In this processing, molecules play the role of symbols and chemical affinity shared by them specifies the syntax for symbol manipulation in order to process and to produce chemical messages. In this context, neurons are conceived as message-exchanging agents. Chemical strings are produced and stored at defined places, and ionic currents are used to speed up message delivery. Synaptic transactions can no longer be assumed to correspond to a simple process of propagating numbers powered by a factor measuring the presynaptic capacity to influence the postsynaptic electrical activity, but they must be modeled by more powerful formal tools supporting both numerical and symbolic calculations. It is proposed here that formal language theory is the adequate mathematical tool to handle such symbolic processing. The purpose of the present review is therefore: (a) to discuss the relevant and recent literature about trophic factors, signal transduction mechanisms, neuromodulators and neurotransmitters in order (b) to point out the common features of these correlated processes; and (c) to show how they may be organized into a formal model supported by the theory of fuzzy formal languages (d) to model the brain as a distributed intelligent problem solver.