Models and Measurements of Functional Maps in V1

Differential clustering of visual and choice- and saccade-related activity in macaque V3A and CIP

Neurons in sensory and motor cortices tend to aggregate in clusters with similar functional properties. Within the primate dorsal ("where") pathway, an important interface between three-dimensional (3-D) visual processing and motor-related functions consists of two hierarchically organized areas: V3A and the caudal intraparietal (CIP) area. In these areas, 3-D visual information, choice-related activity, and saccade-related activity converge, often at the single-neuron level. Characterizing the clustering of functional properties in areas with mixed selectivity, such as these, may help reveal organizational principles that support sensorimotor transformations. Here we quantified the clustering of visual feature selectivity, choice-related activity, and saccade-related activity by performing correlational and parametric comparisons of the responses of well-isolated, simultaneously recorded neurons in macaque monkeys. Each functional domain showed statistically significant clustering in both areas. However, there were also domain-specific differences in the strength of clustering across the areas. Visual feature selectivity and saccade-related activity were more strongly clustered in V3A than in CIP. In contrast, choice-related activity was more strongly clustered in CIP than in V3A. These differences in clustering may reflect the areas' roles in sensorimotor processing. Stronger clustering of visual and saccade-related activity in V3A may reflect a greater role in within-domain processing, as opposed to cross-domain synthesis. In contrast, stronger clustering of choice-related activity in CIP may reflect a greater role in synthesizing information across functional domains to bridge perception and action.NEW & NOTEWORTHY The occipital and parietal cortices of macaque monkeys are bridged by hierarchically organized areas V3A and CIP. These areas support 3-D visual transformations, carry choice-related activity during 3-D perceptual tasks, and possess saccade-related activity. This study quantifies the functional clustering of neuronal response properties within V3A and CIP for each of these domains. The findings reveal domain-specific cross-area differences in clustering that may reflect the areas' roles in sensorimotor processing.

Markov Blankets and Mirror Symmetries-Free Energy Minimization and Mesocortical Anatomy

A theoretical account of development in mesocortical anatomy is derived from the free energy principle, operating in a neural field with both Hebbian and anti-Hebbian neural plasticity. An elementary structural unit is proposed, in which synaptic connections at mesoscale are arranged in paired patterns with mirror symmetry. Exchanges of synaptic flux in each pattern form coupled spatial eigenmodes, and the line of mirror reflection between the paired patterns operates as a Markov blanket, so that prediction errors in exchanges between the pairs are minimized. The theoretical analysis is then compared to the outcomes from a biological model of neocortical development, in which neuron precursors are selected by apoptosis for cell body and synaptic connections maximizing synchrony and also minimizing axonal length. It is shown that this model results in patterns of connection with the anticipated mirror symmetries, at micro-, meso- and inter-arial scales, among lateral connections, and in cortical depth. This explains the spatial organization and functional significance of neuron response preferences, and is compatible with the structural form of both columnar and noncolumnar cortex. Multi-way interactions of mirrored representations can provide a preliminary anatomically realistic model of cortical information processing.

Causal evidence for the role of the sensory visual cortex in visual short-term memory maintenance

The role of the sensory visual cortex during visual short-term memory (VSTM) remains controversial. This controversy is possibly due to methodological issues in previous attempts to investigate the effects of transcranial magnetic stimulation (TMS) on VSTM. The aim of this study was to use TMS, while covering previous methodological deficits. Sixty-four young adults were recruited to participate in two experiments (Experiment 1: n = 36; Experiment 2: n = 28) using a VSTM orientation change-detection task under TMS. Monocular vision was ensured using red-blue goggles combined with red-blue stimuli. Double-pulse TMS was delivered at different times (Experiment 1: 0, 200 or 1000 ms; Experiment 2: 200, 1000 ms) during a 2 s maintenance phase, on one side of the occipital hemisphere. In Experiment 2, a sham TMS condition was introduced. Decreased detection sensitivity (d') in the ipsilateral occipital hemisphere to visual hemifield, and in the real TMS (compared with sham TMS) condition indicated inhibitory TMS effects, and thus, a causal involvement of the sensory visual cortex during early (200 ms) and late (1000 ms) maintenance in VSTM. These findings are aligned with sensory recruitment, which proposes that both perceptual and memory processes rely upon the same neural substrates in the sensory visual cortex. The methods used in this study were preregistered and had received in-principle acceptance on 6 June 2022 (Stage 1 protocol can be found in: https://doi.org/10.17605/OSF.IO/EMPDT).

Improving the validity of neuroimaging decoding tests of invariant and configural neural representation

Many research questions in sensory neuroscience involve determining whether the neural representation of a stimulus property is invariant or specific to a particular stimulus context (e.g., Is object representation invariant to translation? Is the representation of a face feature specific to the context of other face features?). Between these two extremes, representations may also be context-tolerant or context-sensitive. Most neuroimaging studies have used operational tests in which a target property is inferred from a significant test against the null hypothesis of the opposite property. For example, the popular cross-classification test concludes that representations are invariant or tolerant when the null hypothesis of specificity is rejected. A recently developed neurocomputational theory suggests two insights regarding such tests. First, tests against the null of context-specificity, and for the alternative of context-invariance, are prone to false positives due to the way in which the underlying neural representations are transformed into indirect measurements in neuroimaging studies. Second, jointly performing tests against the nulls of invariance and specificity allows one to reach more precise and valid conclusions about the underlying representations, particularly when the null of invariance is tested using the fine-grained information from classifier decision variables rather than only accuracies (i.e., using the decoding separability test). Here, we provide empirical and computational evidence supporting both of these theoretical insights. In our empirical study, we use encoding of orientation and spatial position in primary visual cortex as a case study, as previous research has established that these properties are encoded in a context-sensitive way. Using fMRI decoding, we show that the cross-classification test produces false-positive conclusions of invariance, but that more valid conclusions can be reached by jointly performing tests against the null of invariance. The results of two simulations further support both of these conclusions. We conclude that more valid inferences about invariance or specificity of neural representations can be reached by jointly testing against both hypotheses, and using neurocomputational theory to guide the interpretation of results.

Unification of free energy minimization, spatiotemporal energy, and dimension reduction models of V1 organization: Postnatal learning on an antenatal scaffold

Developmental selection of neurons and synapses so as to maximize pulse synchrony has recently been used to explain antenatal cortical development. Consequences of the same selection process—an application of the Free Energy Principle—are here followed into the postnatal phase in V1, and the implications for cognitive function are considered. Structured inputs transformed via lag relay in superficial patch connections lead to the generation of circumferential synaptic connectivity superimposed upon the antenatal, radial, “like-to-like” connectivity surrounding each singularity. The spatiotemporal energy and dimension reduction models of cortical feature preferences are accounted for and unified within the expanded model, and relationships of orientation preference (OP), space frequency preference (SFP), and temporal frequency preference (TFP) are resolved. The emergent anatomy provides a basis for “active inference” that includes interpolative modification of synapses so as to anticipate future inputs, as well as learn directly from present stimuli. Neurodynamic properties are those of heteroclinic networks with coupled spatial eigenmodes.

Sensory recruitment in visual short-term memory: A systematic review and meta-analysis of sensory visual cortex interference using transcranial magnetic stimulation

Sensory visual areas are involved in encoding information in visual short-term memory (VSTM). Yet it remains unclear whether sensory visual cortex is a necessary component of the brain network for maintenance of information in VSTM. Here, we aimed to systematically review studies that have investigated the role of the sensory visual cortex in VSTM using transcranial magnetic stimulation (TMS) and to quantitatively explore these effects using meta-analyses. Fourteen studies were identified and reviewed. Eight studies provided sufficient data for meta-analysis. Two meta-analyses, one regarding the VSTM encoding phase (17 effect sizes) and one regarding the VSTM maintenance phase (15 effect sizes), two meta-regressions (32 effect sizes in each), and one exploratory meta-analysis were conducted. Our results indicate that the sensory visual cortex is similarly involved in both the encoding and maintenance VSTM phase. We suggest that some cases where evidence did not show significant TMS effects was due to low memory or perceptual task demands. Overall, these findings support the idea that sensory visual areas are part of the brain network responsible for successfully maintaining information in VSTM.

Biological action at a distance: Correlated pattern formation in adjacent tessellation domains without communication

Tessellations emerge in many natural systems, and the constituent domains often contain regular patterns, raising the intriguing possibility that pattern formation within adjacent domains might be correlated by the geometry, without the direct exchange of information between parts comprising either domain. We confirm this paradoxical effect, by simulating pattern formation via reaction-diffusion in domains whose boundary shapes tessellate, and showing that correlations between adjacent patterns are strong compared to controls that self-organize in domains with equivalent sizes but unrelated shapes. The effect holds in systems with linear and non-linear diffusive terms, and for boundary shapes derived from regular and irregular tessellations. Based on the prediction that correlations between adjacent patterns should be bimodally distributed, we develop methods for testing whether a given set of domain boundaries constrained pattern formation within those domains. We then confirm such a prediction by analysing the development of ‘subbarrel’ patterns, which are thought to emerge via reaction-diffusion, and whose enclosing borders form a Voronoi tessellation on the surface of the rodent somatosensory cortex. In more general terms, this result demonstrates how causal links can be established between the dynamical processes through which biological patterns emerge and the constraints that shape them.

Patterns can form in biological systems as a net effect of dynamical interactions that are excitatory over short distances and inhibitory over larger distances. Patterns that form in this way are known to reflect the shape of the boundary conditions that contain them. But observing that a particular pattern is contained by a boundary is not enough to determine whether or not that boundary was a constraint on pattern formation. Here we develop a novel test for the influence of boundary shape on pattern formation, based on comparing patterns contained by boundaries whose shapes tessellate and thus are geometrically related. Applying this test to patterns of cell density measured in the developing neocortex confirms that cortical column boundaries constrain pattern formation during the first postnatal weeks. In more general terms, our analysis reveals that strong relationships between patterns that form in adjacent biological domains are to be expected based purely on geometrical effects, even if no information is exchanged between those domains during the process of pattern formation. Our analysis provides a means for testing current theories about the fundamental role that constraints play in organising biological systems.

Multi-Frequency Image Completion via a Biologically-Inspired Sub-Riemannian Model with Frequency and Phase

We present a novel cortically-inspired image completion algorithm. It uses five-dimensional sub-Riemannian cortical geometry, modeling the orientation, spatial frequency and phase-selective behavior of the cells in the visual cortex. The algorithm extracts the orientation, frequency and phase information existing in a given two-dimensional corrupted input image via a Gabor transform and represents those values in terms of cortical cell output responses in the model geometry. Then, it performs completion via a diffusion concentrated in a neighborhood along the neural connections within the model geometry. The diffusion models the activity propagation integrating orientation, frequency and phase features along the neural connections. Finally, the algorithm transforms the diffused and completed output responses back to the two-dimensional image plane.

Functional organization of spatial frequency tuning in macaque V1 revealed with two-photon calcium imaging

V1 neurons are functionally organized in orientation columns in primates. Whether spatial frequency (SF) columns also exist is less clear because mixed results have been reported. A definitive solution would be SF functional maps at single-neuron resolution. Here we used two-photon calcium imaging to construct first cellular SF maps in V1 superficial layers of five awake fixating macaques, and studied SF functional organization properties and neuronal tuning characteristics. The SF maps (850 × 850 μm²) showed weak horizontal SF clustering (median clustering index = 1.43 vs. unity baseline), about one sixth as strong as orientation clustering in the same sets of neurons, which argues against a meaningful orthogonal relationship between orientation and SF functional maps. These maps also displayed nearly absent vertical SF clustering between two cortical depths (150 & 300 μm), indicating a lack of SF columnar structures within the superficial layers. The underlying causes might be that most neurons were tuned to a narrow two-octave range of medium frequencies, and many neurons with different SF preferences were often spatially mixed, which disallowed finer grouping of SF tuning. In addition, individual SF tuning functions were often asymmetric, having wider lower frequency branches, which may help encode low SF information for later decoding.

A sub-Riemannian model of the visual cortex with frequency and phase

In this paper, we present a novel model of the primary visual cortex (V1) based on orientation, frequency, and phase selective behavior of V1 simple cells. We start from the first-level mechanisms of visual perception, receptive profiles. The model interprets V1 as a fiber bundle over the two-dimensional retinal plane by introducing orientation, frequency, and phase as intrinsic variables. Each receptive profile on the fiber is mathematically interpreted as rotated, frequency modulated, and phase shifted Gabor function. We start from the Gabor function and show that it induces in a natural way the model geometry and the associated horizontal connectivity modeling of the neural connectivity patterns in V1. We provide an image enhancement algorithm employing the model framework. The algorithm is capable of exploiting not only orientation but also frequency and phase information existing intrinsically in a two-dimensional input image. We provide the experimental results corresponding to the enhancement algorithm.

The growth of cognition: Free energy minimization and the embryogenesis of cortical computation

The assumption that during cortical embryogenesis neurons and synaptic connections are selected to form an ensemble maximising synchronous oscillation explains mesoscopic cortical development, and a mechanism for cortical information processing is implied by consistency with the Free Energy Principle and Dynamic Logic. A heteroclinic network emerges, with stable and unstable fixed points of oscillation corresponding to activity in symmetrically connected, versus asymmetrically connected, sets of neurons. Simulations of growth explain a wide range of anatomical observations for columnar and non-columnar cortex, superficial patch connections, and the organization and dynamic interactions of neurone response properties. An antenatal scaffold is created, upon which postnatal learning can establish continuously ordered neuronal representations, permitting matching of co-synchronous fields in multiple cortical areas to solve optimization problems as in Dynamic Logic. Fast synaptic competition partitions equilibria, minimizing "the curse of dimensionality", while perturbations between imperfectly partitioned synchronous fields, under internal reinforcement, enable the cortex to become adaptively self-directed. As learning progresses variational free energy is minimized and entropy bounded.

Different hemispheric specialization for face/word recognition: A high-density ERP study with hemifield visual stimulation

INTRODUCTION

The right fusiform face area (FFA) is important for face recognition, whereas the left visual word fusiform area (VWFA) is critical for word processing. Nevertheless, the early stages of unconscious and conscious face and word processing have not been studied systematically.

MATERIALS AND METHODS

To explore hemispheric differences for face and word recognition, we manipulated the visual field (left vs. right) and stimulus duration (subliminal [17 ms] versus supraliminal [300 ms]). We recorded P100 and N170 peaks with high-density ERPs in response to faces/objects or Japanese words/scrambled words in 18 healthy young subjects.

RESULTS

Contralateral P100 was larger than ipsilateral P100 for all stimulus types in the supraliminal, but not subliminal condition. The face- and word-N170s were not evoked in the subliminal condition. The N170 amplitude for the supraliminal face stimuli was significantly larger than that for the objects, and right hemispheric specialization was found for face recognition, irrespective of stimulus visual hemifield. Conversely, the supraliminal word-N170 amplitude was not significantly modulated by stimulus type, visual field, or hemisphere.

CONCLUSIONS

These results suggest that visual awareness is crucial for face and word recognition. Our study using hemifield stimulus presentation further demonstrates the robust right FFA for face recognition but not the left VWFA for word recognition in the Japanese brain.

A geometric attractor mechanism for self-organization of entorhinal grid modules

Grid cells in the medial entorhinal cortex (MEC) respond when an animal occupies a periodic lattice of 'grid fields' in the environment. The grids are organized in modules with spatial periods, or scales, clustered around discrete values separated on average by ratios in the range 1.4-1.7. We propose a mechanism that produces this modular structure through dynamical self-organization in the MEC. In attractor network models of grid formation, the grid scale of a single module is set by the distance of recurrent inhibition between neurons. We show that the MEC forms a hierarchy of discrete modules if a smooth increase in inhibition distance along its dorso-ventral axis is accompanied by excitatory interactions along this axis. Moreover, constant scale ratios between successive modules arise through geometric relationships between triangular grids and have values that fall within the observed range. We discuss how interactions required by our model might be tested experimentally.

A Potential VEP Biomarker for Mild Cognitive Impairment: Evidence from Selective Visual Deficit of Higher-Level Dorsal Pathway

Visual dysfunctions are common in Alzheimer's disease (AD). Our aim was to establish a neurophysiological biomarker for amnestic mild cognitive impairment (aMCI). Visual evoked potentials (VEPs) were recorded in aMCI patients who later developed AD (n = 15) and in healthy older (n = 15) and younger controls (n = 15). Visual stimuli were optimized to separately activate lower and higher levels of the ventral and dorsal streams. We compared VEP parameters across the three groups of participants and conducted a linear correlation analysis between VEPs and data from neuropsychological tests. We then used a receiver operating characteristic (ROC) analysis to discriminate those with aMCI from those who were healthy older adults. The latency and phase of VEPs to lower-level stimuli (chromatic and achromatic gratings) were significantly affected by age but not by cognitive decline. Conversely, VEP latencies for higher-ventral (faces and kanji-words) and dorsal (kana-words and optic flow motion) stimuli were not affected by age, but they were significantly prolonged in aMCI patients. Interestingly, VEPs for higher-dorsal stimuli were related to outcomes of neuropsychological tests. Furthermore, the ROC analysis showed that the highest areas under the curve were obtained for VEP latencies in response to higher-dorsal stimuli. These results suggest aMCI-related functional impairment specific to higher-level visual processing. Further, dysfunction in the higher-level of the dorsal stream could be an early indicator of cognitive decline. Therefore, we conclude that VEPs associated with higher-level dorsal stream activity can be a sensitive biomarker for early detection of aMCI.

Further Work on the Shaping of Cortical Development and Function by Synchrony and Metabolic Competition

This paper furthers our attempts to resolve two major controversies-whether gamma synchrony plays a role in cognition, and whether cortical columns are functionally important. We have previously argued that the configuration of cortical cells that emerges in development is that which maximizes the magnitude of synchronous oscillation and minimizes metabolic cost. Here we analyze the separate effects in development of minimization of axonal lengths, and of early Hebbian learning and selective distribution of resources to growing synapses, by showing in simulations that these effects are partially antagonistic, but their interaction during development produces accurate anatomical and functional properties for both columnar and non-columnar cortex. The resulting embryonic anatomical order can provide a cortex-wide scaffold for postnatal learning that is dimensionally consistent with the representation of moving sensory objects, and, as learning progressively overwrites the embryonic order, further associations also occur in a dimensionally consistent framework. The role ascribed to cortical synchrony does not demand specific frequency, amplitude or phase variation of pulses to mediate "feature linking." Instead, the concerted interactions of pulse synchrony with short-term synaptic dynamics, and synaptic resource competition can further explain cortical information processing in analogy to Hopfield networks and quantum computation.

Cortical Maps

In this article, we review functional organization in sensory cortical regions—how the cortex represents the world. We consider four interrelated aspects of cortical organization: (1) the set of receptive fields of individual cortical sensory neurons, (2) how lateral interaction between cortical neurons reflects the similarity of their receptive fields, (3) the spatial distribution of receptive-field properties across the horizontal extent of the cortical tissue, and (4) how the spatial distributions of different receptive-field properties interact with one another. We show how these data are generally well explained by the theory of input-driven self-organization, with a family of computational models of cortical maps offering a parsimonious account for a wide range of map-related phenomena. We then discuss important challenges to this explanation, with respect to the maps present at birth, maps present under activity blockade, the limits of adult plasticity, and the lack of some maps in rodents. Because there is not at present another credible general theory for cortical map development, we conclude by proposing key experiments to help uncover other mechanisms that might also be operating during map development.

Pinwheel-dipole configuration in cat early visual cortex

In the early visual cortex, information is processed within functional maps whose layouts are thought to underlie visual perception. However, the precise organization of these functional maps as well as their interrelationships remain unsettled. Here, we show that spatial frequency representation in cat early visual cortex exhibits singularities around which the map organizes like an electric dipole potential. These singularities are precisely co-located with singularities of the orientation map: the pinwheel centers. To show this, we used high resolution intrinsic optical imaging in cat areas 17 and 18. First, we show that a majority of pinwheel centers exhibit in their neighborhood both semi-global maximum and minimum in the spatial frequency map (i.e. extreme values of the spatial frequency in a hypercolumn). This contradicts pioneering studies suggesting that pinwheel centers are placed at the locus of a single spatial frequency extremum. Based on an analogy with electromagnetism, we proposed a mathematical model for a dipolar structure, accurately fitting optical imaging data. We conclude that a majority of orientation pinwheel centers form spatial frequency dipoles in cat early visual cortex. Given the functional specificities of neurons at singularities in the visual cortex, it is argued that the dipolar organization of spatial frequency around pinwheel centers could be fundamental for visual processing.

Parsimony, Exhaustivity and Balanced Detection in Neocortex

The layout of sensory brain areas is thought to subtend perception. The principles shaping these architectures and their role in information processing are still poorly understood. We investigate mathematically and computationally the representation of orientation and spatial frequency in cat primary visual cortex. We prove that two natural principles, local exhaustivity and parsimony of representation, would constrain the orientation and spatial frequency maps to display a very specific pinwheel-dipole singularity. This is particularly interesting since recent experimental evidences show a dipolar structures of the spatial frequency map co-localized with pinwheels in cat. These structures have important properties on information processing capabilities. In particular, we show using a computational model of visual information processing that this architecture allows a trade-off in the local detection of orientation and spatial frequency, but this property occurs for spatial frequency selectivity sharper than reported in the literature. We validated this sharpening on high-resolution optical imaging experimental data. These results shed new light on the principles at play in the emergence of functional architecture of cortical maps, as well as their potential role in processing information.

Möbius-strip-like columnar functional connections are revealed in somato-sensory receptive field centroids

Receptive fields of neurons in the forelimb region of areas 3b and 1 of primary somatosensory cortex, in cats and monkeys, were mapped using extracellular recordings obtained sequentially from nearly radial penetrations. Locations of the field centroids indicated the presence of a functional system in which cortical homotypic representations of the limb surfaces are entwined in three-dimensional Möbius-strip-like patterns of synaptic connections. Boundaries of somatosensory receptive field in nested groups irregularly overlie the centroid order, and are interpreted as arising from the superposition of learned connections upon the embryonic order. Since the theory of embryonic synaptic self-organization used to model these results was devised and earlier used to explain findings in primary visual cortex, the present findings suggest the theory may be of general application throughout cortex and may reveal a modular functional synaptic system, which, only in some parts of the cortex, and in some species, is manifest as anatomical ordering into columns.

Neurobiology of continuous spike-wave in slow-wave sleep and Landau-Kleffner syndromes

BACKGROUND

Several pediatric seizure disorders have common electrophysiological features during slow-wave sleep that produce different syndromes based on which part of the developing brain is involved. These disorders, of which continuous spike-wave in slow-wave sleep and Landau-Kleffner are the most common, are characterized by continuous spike-wave activity during slow-wave sleep, developmentally regulated onset and termination of abnormal electrical activity, and loss of previously acquired skills. Over the last 20 years, a variety of basic science findings suggest how spike-wave activity during sleep can cause the observed clinical outcomes.

METHODS

Literature review and analysis.

RESULTS

The role of slow-wave sleep in normal cortical plasticity during developmental critical periods, how disruption of slow-wave sleep by electrographic seizures could affect cortical maps and development, and the organization and functional connectivity of the thalamic structures that when damaged are thought to produce these seizure disorders are reviewed.

CONCLUSIONS

Potential therapeutic directions are proposed based on the mechanisms of plasticity and anatomical structures involved in cortical plasticity during slow-wave sleep.

BOLD signal change and contrast reversing frequency: an event-related fMRI study in human primary visual cortex

It is believed that human primary visual cortex (V1) increases activity with increasing temporal frequency of a visual stimulus. Two kinds of visual stimulus were used in the previous studies, one is patterned-flash stimulus with a fixed onset period and an increasing average luminance with the increase of temporal frequency, the other is contrast reversing flickering checkerboard or grating with a constant average luminance across different temporal frequencies. That hemodynamic responses change as a function of reversal frequency of contrast reversing checkerboard is at odds with neurophysiological studies in animals and neuroimaging studies in humans. In the present study, we addressed the relationship between reversal frequency of contrast reversing checkerboard and hemodynamic response in human V1 using an event-related experimental paradigm and found that the transient characteristics of blood oxygenation level dependent response in human V1 depended very little on the reversal frequency of a contrast reversing checkerboard.

Diagnosing developmental dyscalculia on the basis of reliable single case FMRI methods: promises and limitations

FMRI-studies are mostly based on a group study approach, either analyzing one group or comparing multiple groups, or on approaches that correlate brain activation with clinically relevant criteria or behavioral measures. In this study we investigate the potential of fMRI-techniques focusing on individual differences in brain activation within a test-retest reliability context. We employ a single-case analysis approach, which contrasts dyscalculic children with a control group of typically developing children. In a second step, a support-vector machine analysis and cluster analysis techniques served to investigate similarities in multivariate brain activation patterns. Children were confronted with a non-symbolic number comparison and a non-symbolic exact calculation task during fMRI acquisition. Conventional second level group comparison analysis only showed small differences around the angular gyrus bilaterally and the left parieto-occipital sulcus. Analyses based on single-case statistical procedures revealed that developmental dyscalculia is characterized by individual differences predominantly in visual processing areas. Dyscalculic children seemed to compensate for relative under-activation in the primary visual cortex through an upregulation in higher visual areas. However, overlap in deviant activation was low for the dyscalculic children, indicating that developmental dyscalculia is a disorder characterized by heterogeneous brain activation differences. Using support vector machine analysis and cluster analysis, we tried to group dyscalculic and typically developing children according to brain activation. Fronto-parietal systems seem to qualify for a distinction between the two groups. However, this was only effective when reliable brain activations of both tasks were employed simultaneously. Results suggest that deficits in number representation in the visual-parietal cortex get compensated for through finger related aspects of number representation in fronto-parietal cortex. We conclude that dyscalculic children show large individual differences in brain activation patterns. Nonetheless, the majority of dyscalculic children can be differentiated from controls employing brain activation patterns when appropriate methods are used.

Organization and origin of spatial frequency maps in cat visual cortex

It remains controversial whether and how spatial frequency (SF) is represented tangentially in cat visual cortex. Several models were proposed, but there is no consensus. Worse still, some data indicate that the SF organization previously revealed by optical imaging techniques simply reflects non-stimulus-specific responses. Instead, stimulus-specific responses arise from the homogeneous distribution of geniculo-cortical afferents representing X and Y pathways. To clarify this, we developed a new imaging method allowing rapid stimulation with a wide range of SFs covering more than 6 octaves with only 0.2 octave resolution. A benefit of this method is to avoid error of high-pass filtering methods which systematically under-represent dominant selectivity features near pinwheel centers. We show unequivocally that SF is organized into maps in cat area 17 (A17) and area 18 (A18). The SF organization in each area displays a global anteroposterior SF gradient and local patches. Its layout is constrained to that of the orientation map, and it is suggested that both maps share a common functional architecture. A17 and A18 are bound at the transition zone by another SF gradient involving the geniculo-cortical and the callosal pathways. A model based on principal component analysis shows that SF maps integrate three different SF-dependent channels. Two of these reflect the segregated excitatory input from X and Y geniculate cells to A17 and A18. The third one conveys a specific combination of excitatory and suppressive inputs to the visual cortex. In a manner coherent with anatomical and electrophysiological data, it is interpreted as originating from a subtype of Y geniculate cells.

On the dynamics of cortical development: synchrony and synaptic self-organization

We describe a model for cortical development that resolves long-standing difficulties of earlier models. It is proposed that, during embryonic development, synchronous firing of neurons and their competition for limited metabolic resources leads to selection of an array of neurons with ultra-small-world characteristics. Consequently, in the visual cortex, macrocolumns linked by superficial patchy connections emerge in anatomically realistic patterns, with an ante-natal arrangement which projects signals from the surrounding cortex onto each macrocolumn in a form analogous to the projection of a Euclidean plane onto a Möbius strip. This configuration reproduces typical cortical response maps, and simulations of signal flow explain cortical responses to moving lines as functions of stimulus velocity, length, and orientation. With the introduction of direct visual inputs, under the operation of Hebbian learning, development of mature selective response “tuning” to stimuli of given orientation, spatial frequency, and temporal frequency would then take place, overwriting the earlier ante-natal configuration. The model is provisionally extended to hierarchical interactions of the visual cortex with higher centers, and a general principle for cortical processing of spatio-temporal images is sketched.

Distinct functional organizations for processing different motion signals in V1, V2, and V4 of macaque

Motion perception is qualitatively invariant across different objects and forms, namely, the same motion information can be conveyed by many different physical carriers, and it requires the processing of motion signals consisting of direction, speed, and axis or trajectory of motion defined by a moving object. Compared with the representation of orientation, the cortical processing of these different motion signals within the early ventral visual pathway of the primate remains poorly understood. Using drifting full-field noise stimuli and intrinsic optical imaging, along with cytochrome-oxidase staining, we found that the orientation domains in macaque V1, V2, and V4 that processed orientation signals also served to process motion signals associated with the axis and speed of motion. In contrast, direction domains within the thick stripes of V2 demonstrated preferences that were independent of motion speed. The population responses encoding the orientation and motion axis could be precisely reproduced by a spatiotemporal energy model. Thus, our observation of orientation domains with dual functions in V1, V2, and V4 directly support the notion that the linear representation of the temporal series of retinotopic activations may serve as another motion processing strategy in primate ventral visual pathway, contributing directly to fine form and motion analysis. Our findings further reveal that different types of motion information are differentially processed in parallel and segregated compartments within primate early visual cortices, before these motion features are fully combined in high-tier visual areas.

Equivalent representation of real and illusory contours in macaque V4

The cortical processing of illusory contours provides a unique window for exploring the brain mechanisms underlying visual perception. Previous electrophysiological single-cell recordings demonstrate that a subgroup of cells in macaque V1 and V2 signal the presence of illusory contours, whereas recent human brain imaging studies reveal higher-order visual cortices playing a central role in illusory figure processing. It seems that the processing of illusory contours/figures may engage multiple cortical interactions between hierarchically organized processing stages in the ventral visual pathway of primates. However, it is not yet known in which brain areas illusory contours are represented in the same manner as real contours at both the population and single-cell levels. Here, by combining intrinsic optical imaging in anesthetized rhesus macaques with single-cell recordings in awake ones, we found a complete overlap of orientation domains in visual cortical area V4 for processing real and illusory contours. In contrast, the orientation domains mapped in early visual areas V1 and V2 mainly encoded the local physical stimulus features inducing the subjective perception of global illusory contours. Our results indicate that real and illusory contours are encoded equivalently by the same functional domains in V4, suggesting that V4 is a key cortical locus for integration of local features into global contours.

BOLD responses to different temporal frequency stimuli in the lateral geniculate nucleus and visual cortex: insights into the neural basis of fMRI

The neural basis of the blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) remains largely unknown after decades of research. To investigate this issue, the unique property of the temporal frequency tuning that could separate neural input and output in the primary visual cortex was used as a model. During moving grating stimuli of 1, 2, 10 and 20Hz temporal frequencies, we measured 9.4-T BOLD fMRI responses simultaneously in the primary visual cortex of area 17 (A17) and area 18 (A18), and the lateral geniculate nucleus (LGN) of isoflurane-anesthetized cat. Our results showed that preferred temporal frequencies of the BOLD responses for A17, A18 and LGN were 3.1Hz, 4.5Hz and 6.0Hz, respectively, which were comparable to the previously reported electrophysiological data. Additionally, the difference of BOLD response onset time between LGN and A17 was 0.5s, which is 18 times larger than the difference of neural activity onset time between these areas. We then compared the frequency-dependent BOLD fMRI response of A17 with tissue partial pressure of oxygen (pO(2)) and electrophysiological data of the same animal model reported by Viswanathan and Freeman (Nature Neuroscience, 2007). The BOLD tuning curve resembled the low frequency band (<12Hz) of local field potential (LFP) tuning curve rather than spiking activity, gamma band (25-90Hz) of LFP, and tissue pO(2) tuning curves, suggesting that the BOLD fMRI signal relates closer to low frequency LFP.

Modulation of activity in human visual area V1 during memory masking

Neurons in the primary visual cortex, V1, are specialized for the processing of elemental features of the visual stimulus, such as orientation and spatial frequency. Recent fMRI evidence suggest that V1 neurons are also recruited in visual perceptual memory; a number of studies using multi-voxel pattern analysis have successfully decoded stimulus-specific information from V1 activity patterns during the delay phase in memory tasks. However, consistent fMRI signal modulations reflecting the memory process have not yet been demonstrated. Here, we report evidence, from three subjects, that the low V1 BOLD activity during retention of low-level visual features is caused by competing interactions between neural populations coding for different values along the spectrum of the dimension remembered. We applied a memory masking paradigm in which the memory representation of a masker stimulus interferes with a delayed spatial frequency discrimination task when its frequency differs from the discriminanda with ±1 octave and found that impaired behavioral performance due to masking is reflected in weaker V1 BOLD signals. This cross-channel inhibition in V1 only occurs with retinotopic overlap between the masker and the sample stimulus of the discrimination task. The results suggest that memory for spatial frequency is a local process in the retinotopically organized visual cortex.

Neural plasticity: the biological substrate for neurorehabilitation

Decades of basic science have clearly demonstrated the capacity of the central nervous system (CNS) to structurally and functionally adapt in response to experience. The field of neurorehabilitation has begun to use this body of work to develop neurobiologically informed therapies that harness the key behavioral and neural signals that drive neural plasticity. The present review describes how neural plasticity supports both learning in the intact CNS and functional improvement in the damaged or diseased CNS. A pragmatic, interdisciplinary definition of neural plasticity is presented that may be used by both clinical and basic scientists studying neurorehabilitation. Furthermore, a description of how neural plasticity may act to drive different neural strategies underlying functional improvement after CNS injury or disease is provided. The understanding of the relationship between these different neural strategies, mechanisms of neural plasticity, and changes in behavior may facilitate the development of novel, more effective rehabilitation interventions.

Independent encoding of grating motion across stationary feature maps in primary visual cortex visualized with voltage-sensitive dye imaging

In early visual cortex different stimulus parameters are represented in overlaid feature maps. Such functioning was extensively explored by the use of drifting gratings characterized by orientation, spatial-temporal frequency, and direction of motion. However surprisingly, the direct cortical visuotopic drift of the gratings' stripy pattern has never been detected simultaneously to these stationary feature maps. It therefore remains to be demonstrated how physical signals of grating motion across the cortex are represented independently of other parametric maps and thus, how multi-dimensional input is processed independently to enable effective read-out further downstream. Taking advantage of the high spatial and temporal resolution of voltage-sensitive dye imaging, we here show the real-time encoding of position and orientation. By decomposing the cortical responses to drifting gratings we visualize the typical emergence of stationary orientation maps in which specific domains exhibited highest amplitudes. Simultaneously to these patchy maps, we demonstrate coherently propagating waves of activity that precisely matched the actual movement of the gratings in space and time, most dominantly for spatial frequencies lower than the preferred range. Thus, the primary visual cortex multiplexes information about retinotopic motion by additional temporal modulation of stationary orientation signals. These signals may be used to variably extract coarse-grained object motion and form information at higher visual processing stages.

In vivo retinotopic mapping of superior colliculus using manganese-enhanced magnetic resonance imaging

The superior colliculus (SC) is a dome-shaped subcortical laminar structure in the mammalian midbrain, whose superficial layers receive visual information from the retina in a topological order. Despite the increasing number of studies investigating retinotopic projection in visual brain development and disorders, in vivo, high-resolution 3D mapping of topographic organization in the subcortical visual nuclei has not yet been available. This study explores the capability of 3D manganese-enhanced MRI (MEMRI) at 200 μm isotropic resolution for in vivo retinotopic mapping of the rat SC upon partial transection of the intraorbital optic nerve. One day after intravitreal Mn(2+) injection into both eyes, animals with partial transection at the right superior intraorbital optic nerve in Group 1 (n=8) exhibited a significantly lower T1-weighted signal intensity in the lateral region of the left SC compared to the left medial SC and right control SC. Partial transection toward the temporal or nasal region of the right intraorbital optic nerve in Group 2 (n=7) led to T1-weighted hypointensity in the rostral or caudal region of the left SC, whereas a clear border was observed separating 2 halves of the left SC in all groups. Previous histological and electrophysiological studies showed that the retinal ganglion cell axons emanating from superior, inferior, nasal and temporal retina projected respectively to the contralateral lateral, medial, caudal and rostral SC in rodents. While this topological pattern is preserved in the intraorbital optic nerve, it was shown that partial transection of the superior intraorbital optic nerve led to primary injury predominantly in the superior but not inferior retina and optic nerve. The results of this study demonstrated the sensitivity of submillimeter-resolution MEMRI for in vivo, 3D mapping of the precise retinotopic projections in SC upon reduced anterograde axonal transport of Mn(2+) ions from localized regions of the anterior visual pathways to the subcortical midbrain nuclei. Future MEMRI studies are envisioned that measure the topographic changes in brain development, diseases, plasticity and regeneration therapies in a global and longitudinal setting.

Dominant vertical orientation processing without clustered maps: early visual brain dynamics imaged with voltage-sensitive dye in the pigeon visual Wulst

The pigeon is a widely established behavioral model of visual cognition, but the processes along its most basic visual pathways remain mostly unexplored. Here, we report the neuronal population dynamics of the visual Wulst, an assumed homolog of the mammalian striate cortex, captured for the first time with voltage-sensitive dye imaging. Responses to drifting gratings were characterized by focal emergence of activity that spread extensively across the entire Wulst, followed by rapid adaptation that was most effective in the surround. Using additional electrophysiological recordings, we found cells that prefer a variety of orientations. However, analysis of the imaged spatiotemporal activation patterns revealed no clustered orientation map-like arrangements as typically found in the primary visual cortices of many mammalian species. Instead, the vertical orientation was overrepresented, both in terms of the imaged population signal, as well as the number of neurons preferring the vertical orientation. Such enhanced selectivity for the vertical orientation may result from horizontal motion vectors that trigger adaptation to the extensive flow field input during natural behavior. Our findings suggest that, although the avian visual Wulst is homologous to the primary visual cortex in terms of its gross anatomical connectivity and topology, its detailed operation and internal organization is still shaped according to specific input characteristics.

Gaussian process methods for estimating cortical maps

A striking feature of cortical organization is that the encoding of many stimulus features, for example orientation or direction selectivity, is arranged into topographic maps. Functional imaging methods such as optical imaging of intrinsic signals, voltage sensitive dye imaging or functional magnetic resonance imaging are important tools for studying the structure of cortical maps. As functional imaging measurements are usually noisy, statistical processing of the data is necessary to extract maps from the imaging data. We here present a probabilistic model of functional imaging data based on Gaussian processes. In comparison to conventional approaches, our model yields superior estimates of cortical maps from smaller amounts of data. In addition, we obtain quantitative uncertainty estimates, i.e. error bars on properties of the estimated map. We use our probabilistic model to study the coding properties of the map and the role of noise-correlations by decoding the stimulus from single trials of an imaging experiment.

Neural computation of visual imaging based on Kronecker product in the primary visual cortex

BACKGROUND

What kind of neural computation is actually performed by the primary visual cortex and how is this represented mathematically at the system level? It is an important problem in the visual information processing, but has not been well answered. In this paper, according to our understanding of retinal organization and parallel multi-channel topographical mapping between retina and primary visual cortex V1, we divide an image into orthogonal and orderly array of image primitives (or patches), in which each patch will evoke activities of simple cells in V1. From viewpoint of information processing, this activated process, essentially, involves optimal detection and optimal matching of receptive fields of simple cells with features contained in image patches. For the reconstruction of the visual image in the visual cortex V1 based on the principle of minimum mean squares error, it is natural to use the inner product expression in neural computation, which then is transformed into matrix form.

RESULTS

The inner product is carried out by using Kronecker product between patches and function architecture (or functional column) in localized and oriented neural computing. Compared with Fourier Transform, the mathematical description of Kronecker product is simple and intuitive, so is the algorithm more suitable for neural computation of visual cortex V1. Results of computer simulation based on two-dimensional Gabor pyramid wavelets show that the theoretical analysis and the proposed model are reasonable.

CONCLUSIONS

Our results are: 1. The neural computation of the retinal image in cortex V1 can be expressed to Kronecker product operation and its matrix form, this algorithm is implemented by the inner operation between retinal image primitives and primary visual cortex's column. It has simple, efficient and robust features, which is, therefore, such a neural algorithm, which can be completed by biological vision. 2. It is more suitable that the function of cortical column in cortex V1 is considered as the basic unit of visual image processing (such unit can implement basic multiplication of visual primitives, such as contour, line, and edge), rather than a set of tiled array filter. Fourier Transformation is replaced with Kronecker product, which greatly reduces the computational complexity. The neurobiological basis of this idea is that a visual image can be represented as a linear combination of orderly orthogonal primitive image containing some local feature. In the visual pathway, the image patches are topographically mapped onto cortex V1 through parallel multi-channels and then are processed independently by functional columns. Clearly, the above new perspective has some reference significance to exploring the neural mechanisms on the human visual information processing.

Subcortical representation of non-Fourier image features

A fundamental goal of visual neuroscience is to identify the neural pathways representing different image features. It is widely argued that the early stages of these pathways represent linear features of the visual scene and that the nonlinearities necessary to represent complex visual patterns are introduced later in cortex. We tested this by comparing the responses of subcortical and cortical neurons to interference patterns constructed by summing sinusoidal gratings. Although a linear mechanism can detect the component gratings, a nonlinear mechanism is required to detect an interference pattern resulting from their sum. Consistent with in vitro retinal ganglion cell recordings, we found that interference patterns are represented subcortically by cat LGN Y-cells, but not X-cells. Linear and nonlinear tuning properties of LGN Y-cells were then characterized and compared quantitatively with those of cortical area 18 neurons responsive to interference patterns. This comparison revealed a high degree of similarity between the two neural populations, including the following: (1) the representation of similar spatial frequencies in both their linear and nonlinear responses, (2) comparable orientation selectivity for the high spatial frequency carrier of interference patterns, and (3) the same difference in their temporal frequency selectivity for drifting gratings versus the envelope of interference patterns. The present findings demonstrate that the nonlinear subcortical Y-cell pathway represents complex visual patterns and likely underlies cortical responses to interference patterns. We suggest that linear and nonlinear mechanisms important for encoding visual scenes emerge in parallel through distinct pathways originating at the retina.