Columns In Visual Cortex Research Articles

A Framework for Intelligence and Cortical Function Based on Grid Cells in the Neocortex.

How the neocortex works is a mystery. In this paper we propose a novel framework for understanding its function. Grid cells are neurons in the entorhinal cortex that represent the location of an animal in its environment. Recent evidence suggests that grid cell-like neurons may also be present in the neocortex. We propose that grid cells exist throughout the neocortex, in every region and in every cortical column. They define a location-based framework for how the neocortex functions. Whereas grid cells in the entorhinal cortex represent the location of one thing, the body relative to its environment, we propose that cortical grid cells simultaneously represent the location of many things. Cortical columns in somatosensory cortex track the location of tactile features relative to the object being touched and cortical columns in visual cortex track the location of visual features relative to the object being viewed. We propose that mechanisms in the entorhinal cortex and hippocampus that evolved for learning the structure of environments are now used by the neocortex to learn the structure of objects. Having a representation of location in each cortical column suggests mechanisms for how the neocortex represents object compositionality and object behaviors. It leads to the hypothesis that every part of the neocortex learns complete models of objects and that there are many models of each object distributed throughout the neocortex. The similarity of circuitry observed in all cortical regions is strong evidence that even high-level cognitive tasks are learned and represented in a location-based framework.

3D topology of orientation columns in visual cortex revealed by functional optical coherence tomography.

Orientation tuning is a canonical neuronal response property of six-layer visual cortex that is encoded in pinwheel structures with center orientation singularities. Optical imaging of intrinsic signals enables us to map these surface two-dimensional (2D) structures, whereas lack of appropriate techniques has not allowed us to visualize depth structures of orientation coding. In the present study, we performed functional optical coherence tomography (fOCT), a technique capable of acquiring a 3D map of the intrinsic signals, to study the topology of orientation coding inside the cat visual cortex. With this technique, for the first time, we visualized columnar assemblies in orientation coding that had been predicted from electrophysiological recordings. In addition, we found that the columnar structures were largely distorted around pinwheel centers: center singularities were not rigid straight lines running perpendicularly to the cortical surface but formed twisted string-like structures inside the cortex that turned and extended horizontally through the cortex. Looping singularities were observed with their respective termini accessing the same cortical surface via clockwise and counterclockwise orientation pinwheels. These results suggest that a 3D topology of orientation coding cannot be fully anticipated from 2D surface measurements. Moreover, the findings demonstrate the utility of fOCT as an in vivo mesoscale imaging method for mapping functional response properties of cortex in the depth axis. NEW & NOTEWORTHY We used functional optical coherence tomography (fOCT) to visualize three-dimensional structure of the orientation columns with millimeter range and micrometer spatial resolution. We validated vertically elongated columnar structure in iso-orientation domains. The columnar structure was distorted around pinwheel centers. An orientation singularity formed a string with tortuous trajectories inside the cortex and connected clockwise and counterclockwise pinwheel centers in the surface orientation map. The results were confirmed by comparisons with conventional optical imaging and electrophysiological recordings.

Probabilistic computation underlying sequence learning in a spiking attractor memory network

Many cognitive and motor functions are enabled by the temporal representation and processing of stimuli but it remains an open issue how neuronal circuits could reliably encode such sequences of information. We consider the task of generating and learning spatiotemporal spike patterns in the context of an attractor memory network, in which each memory is stored in a distributed fashion represented by increased firing in pools of excitatory neurons. Excitatory activity is locally modulated by inhibitory neurons representing lateral inhibition that generates a type of winner-take-all dynamics. Networks of this type have previously been shown to exhibit switching between a non-coding ground state and low-rate memory state activations displaying gamma oscillations [1]; however, stable sequential associations between different attractors were not present. Assuming a probabilistic framework in which local neuron populations discretely encode uncertainty about an attribute in the external world (e.g. a column in visual cortex tuned to a specific edge orientation), we model inter-module synapses using the Bayesian Confidence Propagation Neural Network (BCPNN) plasticity rule [2]. We use a spike-based version of BCPNN in which synaptic weights are statistically inferred by estimating the posterior likelihood of activation for the postsynaptic cell upon presentation of evidence in the form of presynaptic activity patterns. Probabilities are estimated on-line using local exponentially weighted moving averages, with time scales that are biologically motivated by the cascade of events involved in the induction and maintenance of long-term plasticity. Modulating the kinetics of these traces is shown to shape the width of the STDP kernel, which in turn allows attractors to be learned forwards or backwards through time. Stable learning is confirmed by aunimodal stationary weight distribution. Inference additionally requires modification of a distinct neuronal component, which we interpret as a correlate of intrinsic excitability. Such synaptic [3] and nonsynaptic [4] mechanisms were specifically shown to be relevant for learning and inference. In broader terms, our model instead suggests the presence of and interaction between all of these processes in approximating Bayesian computation. Introducing plastic BCPNN synaptic projections into the attractor network model allows for stable associations between distinct network states. Associations are mediated by different synaptic timescales [5] with fast (AMPA type) and slower (NMDA type) dynamics that in conjunction with the spiking BCPNN rule produce sequences of attractor activations. We demonstrate the feasibility of our model using network simulations of integrate-and-fire neurons, and find that the ability to learn sequences depends on the specific structure of the inhibitory microcircuitry and on the local balance of excitation and inhibition in the network. Preliminary results show that the network can reliably store spatiotemporal patterns consisting of hundreds of discrete network states using just a few thousand neurons. Moreover, excitatory pools can participate multiple times in the sequence, suggesting that spiking attractor networks of this type could support an efficient combinatorial code. Our model provides novel insights into how local and global computations found throughout neocortex and hippocampus, framed in the context of probabilistic inference, could contribute to generating and learning sequential neural activity.

Layer dependent neural modulation of a realistic layered-microcircuit model in visual cortex based on bottom-up and top-down signals

Visual attention allocates the information processing resources of the brain to selected sensory inputs to reduce the processing load. Here, we carried out a large-scale simulation with a layered-microcircuit model of the visual cortex based on current knowledge of cortical neurobiology to explore the complex interaction between bottom-up visual input and top-down attentional signals. The microcircuit model corresponds to two columns of visual cortex. Each column consists of about 40,000 integrate-and-fire neurons comprising layers 2/3, 4, 5 and 6 [1]. These columns interact via lateral inhibition from layer 2/3 excitatory neurons in one column to layer 2/3 inhibitory neurons in the other, so that the full network comprises in total around 80,000 neurons and 300 million synapses. Excitatory and inhibitory neurons in layer 4 of the model receive visual inputs mimicking vertical and horizontal bars. Top-down attention was projected to layers 2/3 and 5 to facilitate the visual processing. In order to investigate the mechanism of visual processing and the attentional effect in the layered-microcircuit model, we compared the response of the model to physiological results for neural and attentional modulation [2]. Our model successfully reproduced previous experimental observations of stimulus presentation and attentional effects on visual neuronal responses in layers 2/3 and 5 (Figure ​(Figure1).1). Moreover, the model predicts contrasting differences in the effects of attention between cortical layers: attention to a preferred stimulus of a column enhances neuronal responses of layers 2/3 and 5, the output station of cortical microcircuits, whereas attention suppresses neuronal activities of layer 4, the input station of cortical microcircuits. Further simulations with our model suggest that the specific attentional modulation pattern of layer 4 activity emerges from inter-laminar synaptic connections within the cortical microcircuit and is crucial for the microcircuit to rapidly shift attention to a stimulus different from the one currently attended to. Our multicolumnar model is a canonical microcircuit model for the dynamic selection of multiple sensory inputs to the visual cortices, and makes several testable predictions about the layer-dependence of the response modulations. Figure 1 The population firing rates of excitatory (filled bars) and inhibitory (empty bars) neurons are shown for each layer of a column for various combinations of visual and attentional inputs. The preferred stimulus of the column is bordered white. An attended ...

Population receptive fields of ON and OFF thalamic inputs to an orientation column in visual cortex

The primary visual cortex of primates and carnivores is organized into columns of neurons with similar preferences for stimulus orientation, but the developmental origin and function of this organization are still matters of debate. We found that the orientation preference of a cortical column is closely related to the population receptive field of its ON and OFF thalamic inputs. The receptive field scatter from the thalamic inputs was more limited than previously thought and matched the average receptive field size of neurons at the input layers of cortex. Moreover, the thalamic population receptive field (calculated as ON - OFF average) had separate ON and OFF subregions, similar to cortical neurons in layer 4, and provided an accurate prediction of the preferred orientation of the column. These results support developmental models of orientation maps that are based on the receptive field arrangement of ON and OFF visual inputs to cortex.

Predicting the orientation of invisible stimuli from activity in human primary visual cortex

Humans can experience aftereffects from oriented stimuli that are not consciously perceived, suggesting that such stimuli receive cortical processing. Determining the physiological substrate of such effects has proven elusive owing to the low spatial resolution of conventional human neuroimaging techniques compared to the size of orientation columns in visual cortex. Here we show that even at conventional resolutions it is possible to use fMRI to obtain a direct measure of orientation-selective processing in V1. We found that many parts of V1 show subtle but reproducible biases to oriented stimuli, and that we could accumulate this information across the whole of V1 using multivariate pattern recognition. Using this information, we could then successfully predict which one of two oriented stimuli a participant was viewing, even when masking rendered that stimulus invisible. Our findings show that conventional fMRI can be used to reveal feature-selective processing in human cortex, even for invisible stimuli.

High-field fMRI unveils orientation columns in humans

Functional (f)MRI has revolutionized the field of human brain research. fMRI can noninvasively map the spatial architecture of brain function via localized increases in blood flow after sensory or cognitive stimulation. Recent advances in fMRI have led to enhanced sensitivity and spatial accuracy of the measured signals, indicating the possibility of detecting small neuronal ensembles that constitute fundamental computational units in the brain, such as cortical columns. Orientation columns in visual cortex are perhaps the best known example of such a functional organization in the brain. They cannot be discerned via anatomical characteristics, as with ocular dominance columns. Instead, the elucidation of their organization requires functional imaging methods. However, because of insufficient sensitivity, spatial accuracy, and image resolution of the available mapping techniques, thus far, they have not been detected in humans. Here, we demonstrate, by using high-field (7-T) fMRI, the existence and spatial features of orientation- selective columns in humans. Striking similarities were found with the known spatial features of these columns in monkeys. In addition, we found that a larger number of orientation columns are devoted to processing orientations around 90 degrees (vertical stimuli with horizontal motion), whereas relatively similar fMRI signal changes were observed across any given active column. With the current proliferation of high-field MRI systems and constant evolution of fMRI techniques, this study heralds the exciting prospect of exploring unmapped and/or unknown columnar level functional organizations in the human brain.

Non-linear dynamics of columns of cat visual cortex revealed by simulation and experiment.

Correlation images were derived from simultaneous recordings of 12 signals representing the synaptic activity at different layers of a column in cat visual cortex (area 18) and 12 signals representing the local average spiking activity at the same locations. Because the ongoing activity and the activity evoked by stroboscopic flashes yielded the same correlation image, ongoing activity is caused by an input to a column similar to flash-evoked activity and is thus not endogenous. Moving bar stimuli evoked bursts of oscillations (25-75 Hz band) in the correlation image. The rhythm of these oscillations was not related to any frequency component in the stimulus. In all correlation images we observed that synaptic activity in one layer resulted in simultaneous spiking activity in all layers with latency differences smaller than 2 ms (the sample interval used). Similar behaviour was observed in a simulation experiment where we 'realistically' modelled one column of visual cortex with 1000 three-compartmental neurons in 11 functional layers. When such a model column was tuned to yield a stable and excitable system with low ongoing activity, activation of any of the layers caused simultaneous activity in all 11 layers. Both the simulation and the experimental results suggest that a column can be regarded as a basic processing element sending the same information over all its outputs to other columns within the same cortical region, other visual areas and subcortical structures.

Properties of Persistent Postnatal Cortical Subplate Neurons

Subplate (SP) neurons are important for the proper development of thalamocortical innervation. They are necessary for formation of ocular dominance and orientation columns in visual cortex. During the perinatal period, many SP neurons die. The surviving cohort forms interstitial cells in the white matter (WM) and a band of horizontally oriented cells below layer VI (layer VIb, layer VII, or subplate cells). Although the function of embryonic SP neurons has been well established, the functional roles of WM and postnatal SP cells are not known. We used a combination of anatomical, immunohistochemical, and electrophysiological techniques to explore the dendritic morphology, neurotransmitter phenotype, intrinsic electrophysiological, and synaptic input properties of these surviving cells in the rat visual cortex. The density of SP and WM cells significantly decreases during the first month of life. Both populations express neuronal markers and have extensive dendritic arborizations within the SP, WM, and to the overlying visual cortex. Some intrinsic electrophysiological properties of SP and WM cells are similar: each generates high-frequency slowly adapting trains of action potentials in response to a sustained depolarization. However, SP cells exhibit greater frequency-dependent action potential broadening than WM neurons. Both cell types receive predominantly AMPA/kainate receptor-mediated excitatory synaptic input that undergoes paired-pulse facilitation as well as NMDA receptor and GABAergic input. Synaptic inputs to these cells can also undergo long-term synaptic plasticity. Thus, surviving SP and WM cells are functional electrogenic neurons integrated within the postnatal visual cortical circuit.

Subplate Neurons Regulate Maturation of Cortical Inhibition and Outcome of Ocular Dominance Plasticity

Synaptic plasticity during critical periods of development requires intact inhibitory circuitry. We report that subplate neurons are needed both for maturation of inhibition and for the proper sign of ocular dominance (OD) plasticity. Removal of subplate neurons prevents the developmental upregulation of genes involved in mature, fast GABAergic transmission in cortical layer 4, including GABA receptor subunits and KCC2, and thus prevents the switch to a hyperpolarizing effect of GABA. To understand the implications of these changes, a realistic circuit model was formulated. Simulations predicted that without subplate neurons, monocular deprivation (MD) paradoxically favors LGN axons representing the deprived (less active) eye, exactly what was then observed experimentally. Simulations also account for published results showing that OD plasticity requires mature inhibition. Thus, subplate neurons regulate molecular machinery required to establish an adult balance of excitation and inhibition in layer 4, and thereby influence the outcome of OD plasticity.

Predicting the orientation of invisible stimuli from activity in human primary visual cortex

Humans can experience aftereffects from oriented stimuli that are not consciously perceived, suggesting that such stimuli receive cortical processing. Determining the physiological substrate of such effects has proven elusive owing to the low spatial resolution of conventional human neuroimaging techniques compared to the size of orientation columns in visual cortex. Here we show that even at conventional resolutions it is possible to use fMRI to obtain a direct measure of orientation-selective processing in V1. We found that many parts of V1 show subtle but reproducible biases to oriented stimuli, and that we could accumulate this information across the whole of V1 using multivariate pattern recognition. Using this information, we could then successfully predict which one of two oriented stimuli a participant was viewing, even when masking rendered that stimulus invisible. Our findings show that conventional fMRI can be used to reveal feature-selective processing in human cortex, even for invisible stimuli.

Brain-Derived Neurotrophic Factor Expands Ocular Dominance Columns in Visual Cortex in Monocularly Deprived and Nondeprived Kittens But Does Not in Adult Cats

Segregation and stabilization of thalamocortical afferents to eye-specific patches, so-called "ocular dominance (OD) columns," in visual cortex are hypothesized to be based on activity-dependent competition for trophic factors such as brain-derived neurotrophic factor (BDNF) between afferents representing the two eyes during the critical period of postnatal development. To test this hypothesis we observed effects of an intracortical infusion of BDNF on OD columns in monocularly deprived kittens and also compared effects between normal kittens and adult cats. BDNF had a hypertrophic action on afferents irrespective of visual inputs so that it desegregated OD columns in the visual cortex of deprived and normal kittens, but this action was not seen in the adults, substantiating its hypothesized trophic role in plasticity of OD columns in the developing visual cortex.

Development of ocular dominance columns in the absence of retinal input.

The initial establishment of ocular dominance columns in visual cortex is believed to involve the segregation of overlapping geniculocortical axons into eye-specific patches based on patterns of correlated activity. However, we found that total removal of retinal influence early in visual development did not prevent segregation of geniculocortical axons into alternating stripes with periodicity normal for ocular dominance columns. Because the patterning of geniculocortical afferents resists this dramatic change in the level, source and pattern of spontaneous activity, we propose that formation of ocular dominance columns relies on molecular cues present on thalamic axons, cortical cells or both.

Two input systems for body representations in the primate striatal matrix: experimental evidence in the squirrel monkey

The striatum is important in basal ganglia motor control and movement disorders. In this study we demonstrate the existence of two distinct sensorimotor cortical input systems to the striatum of the squirrel monkey. The first is a group of discrete zones in the extrastriosomal matrix of the putamen ("matrisomes") that receive somatotopically organized projections from both the body map in ipsilateral primary motor cortex (MI) and maps in ipsilateral primary somatosensory cortex (SI). The second system is a group of matrisomes in largely different locations that receive somatotopically organized inputs from contralateral MI but not SI. Intracortical microstimulation and multiunit recording were used to guide deposits of multiple anterograde tracers in MI and SI. Striosome/matrix architecture was demonstrated by enkephalin immunohistochemistry. We found that inputs from regions of ipsilateral MI and SI that represented the same body parts sent projections to the same matrisomes of the ipsilateral putamen. Contralateral MI sent its strongest inputs to matrisomes that tended to interdigitate with those receiving inputs from ipsilateral SI and MI, except the contralateral MI face region, which sent projections that overlapped those from the ipsilateral MI face region. MI regions representing axial body parts (trunk and face) sent stronger representations to the contralateral putamen than did those representing distal parts (hand and foot). SI sent no contralateral projection. Thus, with the exception of the face representation, inputs from contralateral and ipsilateral body representations may alternate in the primate striatal matrix, an arrangement reminiscent of the alternating ocular dominance columns in visual cortex. Ipsilateral SI and MI and contralateral MI all innervated matrisomes intermingled with striosomes and with matrisomes not receiving sensorimotor cortical input. The patchiness of these maps is thus unlike the smoother somatotopic maps of sensorimotor cortex, and is also unlike the fractured somatotopy reported for the cerebellum.

A mathematical model for the self-organization of orientation columns in visual cortex.

The visual cortex contains regular arrangements of neurons responding to specific types of visual stimulation, such as ocular dominance columns and orientation columns. These columnar structures can be considered as the functional architecture for early visual information processing. The model of activity-dependent self-organization reported here demonstrates that both response properties of neurons to visual stimulation and the related columnar organization can be reproduced based on the competition between ON- and OFF-center inputs. Furthermore, the relationships between anatomical neural organization and its physiological response properties are clarified. This model also predicts new columnar organization linking the symmetry of receptive fields, which has never been examined. A hypercolumn, composed of orientation columns and symmetry columns, is suggested to serve as a basis for the representation of visual information.

Experimental and Theoretical Studies of the Organization of Afferents to Single Orientation Columns in Visual Cortex

Experimental and Theoretical Studies of the Organization of Afferents to Single Orientation Columns in Visual Cortex

Continuity or incontinuity of orientation columns in visual cortex: A critical evaluation of published and unpublished data

Orientation columns in the visual cortex of cat and monkey were originally defined as small areas where all cells from layer 2 to 6 had the same preferred stimulus orientation. Large variation in preferred orientation, occasionally observed, were interpreted as biological scatter or artefacts. In contrast to this view, recent experiments revealed frequent abrupt shifts in preferred orientations at the transition from middle to lower layers. This controversial issue is of considerable relevance for models of cortical wiring. Therefore, in this report new and previously published data are quantitatively evaluated. The comparison shows that the large orientation shifts cannot be reconciled as mainly due to deviation of penetrations from the radial cell columns. The present data suggest that, in middle and lower layers of the cat's cortex, two groups of cells with approximately orthogonal orientations coexist. Comparison of results from different authors supports our evidence for the occurrence of orientation shifts. The controversy is reduced to the difference in the proportions of penetrations with and without shifts in different laboratories. A possible explanation for this remaining difference is the lower relative frequency of shifts in heavily sedated animals. Our own data were collected from awake, behaving or lightly anesthetized animals in chronic preparations.

WGA-HRP as a transneuronal marker in the visual pathways of monkey and rat

Wheat germ agglutinin conjugated to horseradish peroxidase (WGA-HRP) was injected intraocularly in monkeys and rats. All known primary visual pathways were labeled and, in addition, ocular dominance columns in visual cortex were labeled in monkey, and in rat, parabigeminal, oculomotor, thalamic reticular, and visual cortical areas were labeled as well as neuronal soma in superior colliculus. We conclude that WGA-HRP is a useful transneuronal marker for visual pathways.

Restriction of visual experience to a single orientation affects the organization of orientation columns in cat visual cortex. A study with deoxyglucose.

In six dark reared, 4-weak-old kittens visual experience was restricted to contours of a single orientation, horizontal or vertical, using cylindrical lenses. Subsequently, the deoxyglucose method was used to determine whether these artificial raising conditions had affected the development of orientation columns in the visual cortex. After application of the deoxyglucose pulse one hemifield was stimulated with vertical, the other with horizontal contours. Thus, from interhemispheric comparison, changes in columnar systems corresponding to experienced and inexperienced orientations could be determined. The following results were obtained: (1) Irrespective of the restrictions in visual experience, orientation columns develop in areas 17, 18, 19 and in the visual areas of the posterior suprasylvian sulcus. (2) Within area 17, spacing between columns encoding the same orientations is remarkably regular (1 mm), is not influenced by selective experience and shows only slight interindividual variation. (3) In non-striate areas the spacing of columns is less regular and the spatial frequency of the periodicity is lower. (4) The modifiability of this columnar pattern by selective experience is small within the granular layer of striate cortex but substantial in non-granular layers: Within layer IV columns whose preference corresponds to the experienced orientation are wider and more active than those encoding the orthogonal orientation but the columnar grid remains basically unaltered. Outside layer IV the columnar system is maintained only for columns encoding the experienced orientations. The deprived columns by contrast frequently fail to extend into non-granular layers and remain confined to the vicinity of layer IV. (5) These modifications in the columnar arrangement are more pronounced in striate cortex than in nonstriate visual areas and, within the former, more conspicuous in the central than in the peripheral representation of the visual field. It is concluded that within layer IV the blue print for the system of orientation columns is determined by genetic instructions: first order cells in layer IV develop orientation selectivity irrespective of experience whereby the preference for a particular orientation is predetermined by the position in the columnar grid. Dependent on experience is, however, the expansion of the columnar system from layer IV into non-granular layers. It is argued that all distortions following selective rearing can be accounted for by competitive interactions between intracortical pathways, the mechanisms being identical to those established for competitive processes in the domain of ocular dominance columns. It is proposed that such experience dependent modifiability of connections between first and second order cells is a necessary prerequisite for the development of orientation selectivity in cells with large and complex receptive fields.