The contribution of vertical and horizontal connections to the receptive field center and surround in V1

Reduced influence of perceptual context in mild traumatic brain injury is not an illusion

Perceptual grouping is impaired following mild traumatic brain injury (mTBI). This may affect visual size perception, a process influenced by perceptual grouping abilities. We conducted two experiments to evaluate visual size perception in people with self-reported history of mTBI, using two different size-contrast illusions: the Ebbinghaus Illusion (Experiment 1) and the Müller-Lyer illusion (Experiment 2). In Experiment 1, individuals with mTBI and healthy controls were asked to compare the size of two target circles that were either the same size or different sizes. The target circles appeared by themselves (no-context condition), or were surrounded by smaller or larger circles (context condition). Similar levels of accuracy were evident between the groups in the no-context condition. However, size judgements by mTBI participants were more accurate in the context condition, suggesting that they processed the target circles separately from the surrounding circles. In Experiment 2, individuals with mTBI and healthy controls judged the length of parallel lines that appeared with arrowheads (context condition) or without arrowheads (no context condition). Consistent with Experiment 1, size judgements by mTBI participants were more accurate than size judgements by control participants in the context condition. These findings suggest that mTBI influences size perception by impairing perceptual grouping of visual stimuli in near proximity.

Generalizing biological surround suppression based on center surround similarity via deep neural network models

Sensory perception is dramatically influenced by the context. Models of contextual neural surround effects in vision have mostly accounted for Primary Visual Cortex (V1) data, via nonlinear computations such as divisive normalization. However, surround effects are not well understood within a hierarchy, for neurons with more complex stimulus selectivity beyond V1. We utilized feedforward deep convolutional neural networks and developed a gradient-based technique to visualize the most suppressive and excitatory surround. We found that deep neural networks exhibited a key signature of surround effects in V1, highlighting center stimuli that visually stand out from the surround and suppressing responses when the surround stimulus is similar to the center. We found that in some neurons, especially in late layers, when the center stimulus was altered, the most suppressive surround surprisingly can follow the change. Through the visualization approach, we generalized previous understanding of surround effects to more complex stimuli, in ways that have not been revealed in visual cortices. In contrast, the suppression based on center surround similarity was not observed in an untrained network. We identified further successes and mismatches of the feedforward CNNs to the biology. Our results provide a testable hypothesis of surround effects in higher visual cortices, and the visualization approach could be adopted in future biological experimental designs.

Horizontal connectivity in V1: Prediction of coherence in contour and motion integration

This study demonstrates the functional importance of the Surround context relayed laterally in V1 by the horizontal connectivity, in controlling the latency and the gain of the cortical response to the feedforward visual drive. We report here four main findings: 1) a centripetal apparent motion sequence results in a shortening of the spiking latency of V1 cells, when the orientation of the local inducer and the global motion axis are both co-aligned with the RF orientation preference; 2) this contextual effects grows with visual flow speed, peaking at 150–250°/s when it matches the propagation speed of horizontal connectivity (0.15–0.25 mm/ms); 3) For this speed range, the axial sensitivity of V1 cells is tilted by 90° to become co-aligned with the orientation preference axis; 4) the strength of modulation by the surround context correlates with the spatiotemporal coherence of the apparent motion flow. Our results suggest an internally-generated binding process, linking local (orientation /position) and global (motion/direction) features as early as V1. This long-range diffusion process constitutes a plausible substrate in V1 of the human psychophysical bias in speed estimation for collinear motion. Since it is demonstrated in the anesthetized cat, this novel form of contextual control of the cortical gain and phase is a built-in property in V1, whose expression does not require behavioral attention and top-down control from higher cortical areas. We propose that horizontal connectivity participates in the propagation of an internal “prediction” wave, shaped by visual experience, which links contour co-alignment and global axial motion at an apparent speed in the range of saccade-like eye movements.

Classical-Contextual Interactions in V1 May Rely on Dendritic Computations

A signature feature of the neocortex is the dense network of horizontal connections (HCs) through which pyramidal neurons (PNs) exchange "contextual" information. In primary visual cortex (V1), HCs are thought to facilitate boundary detection, a crucial operation for object recognition, but how HCs modulate PN responses to boundary cues within their classical receptive fields (CRF) remains unknown. We began by "asking" natural images, through a structured data collection and ground truth labeling process, what function a V1 cell should use to compute boundary probability from aligned edge cues within and outside its CRF. The "answer" was an asymmetric 2-D sigmoidal function, whose nonlinear form provides the first normative account for the "multiplicative" center-flanker interactions previously reported in V1 neurons (Kapadia et al., 1995, 2000; Polat et al., 1998). Using a detailed compartmental model, we then show that this boundary-detecting classical-contextual interaction function can be computed by NMDAR-dependent spatial synaptic interactions within PN dendrites - the site where classical and contextual inputs first converge in the cortex. In additional simulations, we show that local interneuron circuitry activated by HCs can powerfully leverage the nonlinear spatial computing capabilities of PN dendrites, providing the cortex with a highly flexible substrate for integration of classical and contextual information.

Neural coding of image structure and contrast polarity of Cartesian, hyperbolic, and polar gratings in the primary and secondary visual cortex of the tree shrew

We comprehensively characterize spiking and visual evoked potential (VEP) activity in tree shrew V1 and V2 using Cartesian, hyperbolic, and polar gratings. Neural selectivity to structure of Cartesian gratings was higher than other grating classes in both visual areas. From V1 to V2, structure selectivity of spiking activity increased, whereas corresponding VEP values tended to decrease, suggesting that single-neuron coding of Cartesian grating attributes improved while the cortical columnar organization of these neurons became less precise from V1 to V2. We observed that neurons in V2 generally exhibited similar selectivity for polar and Cartesian gratings, suggesting that structure of polar-like stimuli might be encoded as early as in V2. This hypothesis is supported by the preference shift from V1 to V2 toward polar gratings of higher spatial frequency, consistent with the notion that V2 neurons encode visual scene borders and contours. Neural sensitivity to modulations of polarity of hyperbolic gratings was highest among all grating classes and closely related to the visual receptive field (RF) organization of ON- and OFF-dominated subregions. We show that spatial RF reconstructions depend strongly on grating class, suggesting that intracortical contributions to RF structure are strongest for Cartesian and polar gratings. Hyperbolic gratings tend to recruit least cortical elaboration such that the RF maps are similar to those generated by sparse noise, which most closely approximate feedforward inputs. Our findings complement previous literature in primates, rodents, and carnivores and highlight novel aspects of shape representation and coding occurring in mammalian early visual cortex.

Optogenetic Activation of Normalization in Alert Macaque Visual Cortex

Normalization has been proposed as a canonical computation that accounts for a variety of nonlinear neuronal response properties associated with sensory processing and higher cognitive functions. A key premise of normalization is that the excitability of a neuron is inversely proportional to the overall activity level of the network. We tested this by optogenetically activating excitatory neurons in alert macaque primary visual cortex and measuring changes in neuronal activity as a function of stimulation intensity, with or without variable-contrast visual stimulation. Optogenetic depolarization of excitatory neurons either facilitated or suppressed baseline activity, consistent with indirect recruitment of inhibitory networks. As predicted by the normalization model, neurons exhibited sub-additive responses to optogenetic and visual stimulation, which depended lawfully on stimulation intensity and luminance contrast. We conclude that the normalization computation persists even under the artificial conditions of optogenetic stimulation, underscoring the canonical nature of this form of neural computation.

A model for attentional information routing through coherence predicts biased competition and multistable perception

Selective attention allows to focus on relevant information and to ignore distracting features of a visual scene. These principles of information processing are reflected in response properties of neurons in visual area V4: if a neuron is presented with two stimuli in its receptive field, and one is attended, it responds as if the nonattended stimulus was absent (biased competition). In addition, when the luminance of the two stimuli is temporally and independently varied, local field potentials are correlated with the modulation of the attended stimulus and not, or much less, correlated with the nonattended stimulus (information routing). To explain these results in one coherent framework, we present a two-layer spiking cortical network model with distance-dependent lateral connectivity and converging feed-forward connections. With oscillations arising inherently from the network structure, our model reproduces both experimental observations. Hereby, lateral interactions and shifts of relative phases between sending and receiving layers (communication through coherence) are identified as the main mechanisms underlying both biased competition as well as selective routing. Exploring the parameter space, we show that the effects are robust and prevalent over a broad range of parameters. In addition, we identify the strength of lateral inhibition in the first model layer as crucial for determining the working regime of the system: increasing lateral inhibition allows a transition from a network configuration with mixed representations to one with bistable representations of the competing stimuli. The latter is discussed as a possible neural correlate of multistable perception phenomena such as binocular rivalry.

Modulation of orientation-selective neurons by motion: when additive, when multiplicative?

The recurrent interaction among orientation-selective neurons in the primary visual cortex (V1) is suited to enhance contours in a noisy visual scene. Motion is known to have a strong pop-up effect in perceiving contours, but how motion-sensitive neurons in V1 support contour detection remains vastly elusive. Here we suggest how the various types of motion-sensitive neurons observed in V1 should be wired together in a micro-circuitry to optimally extract contours in the visual scene. Motion-sensitive neurons can be selective about the direction of motion occurring at some spot or respond equally to all directions (pandirectional). We show that, in the light of figure-ground segregation, direction-selective motion neurons should additively modulate the corresponding orientation-selective neurons with preferred orientation orthogonal to the motion direction. In turn, to maximally enhance contours, pandirectional motion neurons should multiplicatively modulate all orientation-selective neurons with co-localized receptive fields. This multiplicative modulation amplifies the local V1-circuitry among co-aligned orientation-selective neurons for detecting elongated contours. We suggest that the additive modulation by direction-specific motion neurons is achieved through synaptic projections to the somatic region, and the multiplicative modulation by pandirectional motion neurons through projections to the apical region of orientation-specific pyramidal neurons. For the purpose of contour detection, the V1-intrinsic integration of motion information is advantageous over a downstream integration as it exploits the recurrent V1-circuitry designed for that task.

A high-density, high-channel count, multiplexed μECoG array for auditory-cortex recordings

Our understanding of the large-scale population dynamics of neural activity is limited, in part, by our inability to record simultaneously from large regions of the cortex. Here, we validated the use of a large-scale active microelectrode array that simultaneously records 196 multiplexed micro-electrocortigraphical (μECoG) signals from the cortical surface at a very high density (1,600 electrodes/cm(2)). We compared μECoG measurements in auditory cortex using a custom "active" electrode array to those recorded using a conventional "passive" μECoG array. Both of these array responses were also compared with data recorded via intrinsic optical imaging, which is a standard methodology for recording sound-evoked cortical activity. Custom active μECoG arrays generated more veridical representations of the tonotopic organization of the auditory cortex than current commercially available passive μECoG arrays. Furthermore, the cortical representation could be measured efficiently with the active arrays, requiring as little as 13.5 s of neural data acquisition. Next, we generated spectrotemporal receptive fields from the recorded neural activity on the active μECoG array and identified functional organizational principles comparable to those observed using intrinsic metabolic imaging and single-neuron recordings. This new electrode array technology has the potential for large-scale, temporally precise monitoring and mapping of the cortex, without the use of invasive penetrating electrodes.

Transformation of receptive field properties from lateral geniculate nucleus to superficial V1 in the tree shrew

Tree shrew primary visual cortex (V1) exhibits a pronounced laminar segregation of inputs from different classes of relay neurons in the lateral geniculate nucleus (LGN). We examined how several receptive field (RF) properties were transformed from LGN to V1 layer 4 to V1 layer 2/3. The progression of RF properties across these stages differed markedly from that found in the cat. V1 layer 4 cells are largely similar to the the LGN cells that provide their input, being dominated by a single sign (ON or OFF) and being strongly modulated by sinusoidal gratings. Some layer 4 neurons, notably those near the edges of layer 4, exhibited increased orientation selectivity, and most layer 4 neurons exhibited a preference for lower temporal frequencies. Neurons in cortical layer 2/3 differ significantly from those in the LGN; most exhibited strong orientation tuning and both ON and OFF responses. The strength of orientation selectivity exhibited a notable sublaminar organization, with the strongest orientation tuned neurons in the most superficial parts of layer 2/3. Modulation indexes provide evidence for simple and complex cells in both layer 4 and layer 2/3. However, neurons with high modulation indexes were heterogenous in the spatial organization of ON and OFF responses, with many of them exhibiting unbalanced ON and OFF responses rather than well-segregated ON and OFF subunits. When compared to the laminar organization of V1 in other mammals, these data show that the process of natural selection can result in significantly altered structure/function relationships in homologous cortical circuits.

On the relation between receptive field structure and stimulus selectivity in the tree shrew primary visual cortex

There are notable differences in functional properties of primary visual cortex (V1) neurons among mammalian species, particularly those concerning the occurrence of simple and complex cells and the generation of orientation selectivity. Here, we present quantitative data on receptive field (RF) structure, response modulation, and orientation tuning for single neurons in V1 of the tree shrew, a close relative of primates. We find that spatial RF subfield segregation, a criterion for identifying simple cells, was exceedingly small in the tree shrew V1. In contrast, many neurons exhibited elevated F1/F0 modulation that is often used as a simple cell marker. This apparent discrepancy can be explained by the robust stimulus polarity preference in tree shrew V1, which inflates F1/F0 ratio values. RF structure mapped with sparse-noise-which is spatially restricted and emphasizes thalamo-cortical feed-forward inputs-appeared unrelated to orientation selectivity. However, RF structure mapped using the Hartley subspace stimulus-which covers a large area of the visual field and recruits considerable intracortical processing-did predict orientation preference. Our findings reveal a number of striking similarities in V1 functional organization between tree shrews and primates, emphasizing the important role of intracortical recurrent processing in shaping V1 response properties in these species.

Perceptual learning in Williams syndrome: looking beyond averages

Williams Syndrome is a genetically determined neurodevelopmental disorder characterized by an uneven cognitive profile and surprisingly large neurobehavioral differences among individuals. Previous studies have already shown different forms of memory deficiencies and learning difficulties in WS. Here we studied the capacity of WS subjects to improve their performance in a basic visual task. We employed a contour integration paradigm that addresses occipital visual function, and analyzed the initial (i.e. baseline) and after-learning performance of WS individuals. Instead of pooling the very inhomogeneous results of WS subjects together, we evaluated individual performance by expressing it in terms of the deviation from the average performance of the group of typically developing subjects of similar age. This approach helped us to reveal information about the possible origins of poor performance of WS subjects in contour integration. Although the majority of WS individuals showed both reduced baseline and reduced learning performance, individual analysis also revealed a dissociation between baseline and learning capacity in several WS subjects. In spite of impaired initial contour integration performance, some WS individuals presented learning capacity comparable to learning in the typically developing population, and vice versa, poor learning was also observed in subjects with high initial performance levels. These data indicate a dissociation between factors determining initial performance and perceptual learning.

Context matters: the illusive simplicity of macaque V1 receptive fields

Even in V1, where neurons have well characterized classical receptive fields (CRFs), it has been difficult to deduce which features of natural scenes stimuli they actually respond to. Forward models based upon CRF stimuli have had limited success in predicting the response of V1 neurons to natural scenes. As natural scenes exhibit complex spatial and temporal correlations, this could be due to surround effects that modulate the sensitivity of the CRF. Here, instead of attempting a forward model, we quantify the importance of the natural scenes surround for awake macaque monkeys by modeling it non-parametrically. We also quantify the influence of two forms of trial to trial variability. The first is related to the neuron’s own spike history. The second is related to ongoing mean field population activity reflected by the local field potential (LFP). We find that the surround produces strong temporal modulations in the firing rate that can be both suppressive and facilitative. Further, the LFP is found to induce a precise timing in spikes, which tend to be temporally localized on sharp LFP transients in the gamma frequency range. Using the pseudo R² as a measure of model fit, we find that during natural scene viewing the CRF dominates, accounting for 60% of the fit, but that taken collectively the surround, spike history and LFP are almost as important, accounting for 40%. However, overall only a small proportion of V1 spiking statistics could be explained (R²∼5%), even when the full stimulus, spike history and LFP were taken into account. This suggests that under natural scene conditions, the dominant influence on V1 neurons is not the stimulus, nor the mean field dynamics of the LFP, but the complex, incoherent dynamics of the network in which neurons are embedded.

Visual experience modulates spatio-temporal dynamics of circuit activation

Persistent reduction in sensory drive in early development results in multiple plastic changes of different cortical synapses. How these experience-dependent modifications affect the spatio-temporal dynamics of signal propagation in neocortical circuits is poorly understood. Here we demonstrate that brief visual deprivation significantly affects the propagation of electrical signals in the primary visual cortex. The spatio-temporal spread of circuit activation upon direct stimulation of its input layer (Layer 4) is reduced, as is the activation of L2/3 – the main recipient of the output from L4. Our data suggest that the decrease in spatio-temporal activation of L2/3 depends on reduced L4 output, and is not intrinsically generated within L2/3. The data shown here suggest that changes in the synaptic components of the visual cortical circuit result not only in alteration of local integration of excitatory and inhibitory inputs, but also in a significant decrease in overall circuit activation. Furthermore, our data indicate a differential effect of visual deprivation on L4 and L2/3, suggesting that while feedforward activation of L2/3 is reduced, its activation by long range, within layer inputs is unaltered. Thus, brief visual deprivation induces experience-dependent circuit re-organization by modulating not only circuit excitability, but also the spatio-temporal patterns of cortical activation within and between layers.

Orientation tuning of the suppressive extraclassical surround depends on intrinsic organization of V1

The intrinsic functional architecture of early cortical areas in highly visual mammals is characterized by the presence of domains and pinwheels, with orientation preference of the inputs to these regions being more and less selective, respectively. We exploited this organizational feature to investigate mechanisms supporting extraclassical surround suppression, a process thought to be critical for figure ground segregation and form vision. Combining intrinsic signal optical imaging and single-unit recording in V1 of anesthetized cats, we show for the first time that the orientation tuning of the suppressive surround is sharper for domain than for pinwheel neurons. This difference depends on high center gain and is more pronounced in superficial cortex. In addition, when we remove the near component of the surround stimulus, the strength of suppression induced by the iso-oriented surround is significantly reduced for domain neurons but is unchanged for orthogonal oriented surrounds. This leads to broader orientation tuning of suppression that renders domain cells indistinguishable from pinwheel cells. Because the limited receptive field of the near surround can be accounted for by the lateral spread of long-range connections in V1, our findings suggest that intrinsic V1 circuits play a key role in the orientation tuning of extraclassical surround suppression.

Development of maps of simple and complex cells in the primary visual cortex

Hubel and Wiesel (1962) classified primary visual cortex (V1) neurons as either simple, with responses modulated by the spatial phase of a sine grating, or complex, i.e., largely phase invariant. Much progress has been made in understanding how simple-cells develop, and there are now detailed computational models establishing how they can form topographic maps ordered by orientation preference. There are also models of how complex cells can develop using outputs from simple cells with different phase preferences, but no model of how a topographic orientation map of complex cells could be formed based on the actual connectivity patterns found in V1. Addressing this question is important, because the majority of existing developmental models of simple-cell maps group neurons selective to similar spatial phases together, which is contrary to experimental evidence, and makes it difficult to construct complex cells. Overcoming this limitation is not trivial, because mechanisms responsible for map development drive receptive fields (RF) of nearby neurons to be highly correlated, while co-oriented RFs of opposite phases are anti-correlated. In this work, we model V1 as two topographically organized sheets representing cortical layer 4 and 2/3. Only layer 4 receives direct thalamic input. Both sheets are connected with narrow feed-forward and feedback connectivity. Only layer 2/3 contains strong long-range lateral connectivity, in line with current anatomical findings. Initially all weights in the model are random, and each is modified via a Hebbian learning rule. The model develops smooth, matching, orientation preference maps in both sheets. Layer 4 units become simple cells, with phase preference arranged randomly, while those in layer 2/3 are primarily complex cells. To our knowledge this model is the first explaining how simple cells can develop with random phase preference, and how maps of complex cells can develop, using only realistic patterns of connectivity.

Asymmetric temporal integration of layer 4 and layer 2/3 inputs in visual cortex

Neocortical neurons in vivo receive concurrent synaptic inputs from multiple sources, including feedforward, horizontal, and feedback pathways. Layer 2/3 of the visual cortex receives feedforward input from layer 4 and horizontal input from layer 2/3. Firing of the pyramidal neurons, which carries the output to higher cortical areas, depends critically on the interaction of these pathways. Here we examined synaptic integration of inputs from layer 4 and layer 2/3 in rat visual cortical slices. We found that the integration is sublinear and temporally asymmetric, with larger responses if layer 2/3 input preceded layer 4 input. The sublinearity depended on inhibition, and the asymmetry was largely attributable to the difference between the two inhibitory inputs. Interestingly, the asymmetric integration was specific to pyramidal neurons, and it strongly affected their spiking output. Thus via cortical inhibition, the temporal order of activation of layer 2/3 and layer 4 pathways can exert powerful control of cortical output during visual processing.

Axon topography of layer IV spiny cells to orientation map in the cat primary visual cortex (area 18)

Our aim was to reveal the relationship between layer IV horizontal connections and the functional architecture of the cat primary visual cortex because these connections play important roles in the first cortical stage of visual signals integration. We investigated bouton distribution of spiny neurons over an orientation preference map using in vivo optical imaging, unit recordings, and single neuron reconstructions. The radial extent of reconstructed axons (14 star pyramidal and 9 spiny stellate cells) was ~1.5 mm. In the vicinity of the parent somata (<400 μm), boutons occupied chiefly iso-orientations, however, more distally, 7 cells projected preferentially to non-iso-orientations. Boutons of each cell were partitioned into 1-15 distinct clusters based on the mean-shift algorithm, of which 57 clusters preferred iso-orientations and 43 clusters preferred cross-orientations, each showing sharp orientation preference "tuning." However, unlike layer III/V pyramidal cells preferring chiefly iso-orientations, layer IV cells were engaged with broad orientations because each bouton cluster from the same cell could show different orientation preference. These results indicate that the circuitry of layer IV spiny cells is organized differently from that of iso-orientation dominant layer III/V cells and probably processes visual signals in a different manner from that of the superficial and deeper layers.

Presynaptic development at L4 to l2/3 excitatory synapses follows different time courses in visual and somatosensory cortex

Visual and somatosensory cortices exhibit profound experience-dependent plasticity during development and adulthood and are common model systems for probing the synaptic and molecular mechanisms of plasticity. However, comparisons between the two areas may be confounded by a lack of accurate information on their relative rates of development. In this study, we used whole-cell recording in acute brain slices to study synaptic development in mouse barrel and visual cortex. We found that short-term plasticity (STP) switched from strong depression at postnatal day (P)12 to weaker depression and facilitation in mature cortex. However, presynaptic maturation was delayed by ∼2 weeks at layer (L)4 to L2/3 excitatory synapses in visual cortex relative to barrel cortex. This developmental delay was pathway-specific; maturation of L2/3 to L2/3 synapses occurred over similar timescales in barrel and visual cortex. The developmental increase in the paired-pulse ratio to values greater than unity was mirrored by a developmental decrease in presynaptic release probability. Therefore, L4 to L2/3 excitatory synapses had lower release probabilities and showed greater short-term facilitation in barrel cortex than in visual cortex at P28. Postsynaptic mechanisms could not account for the delayed maturation of STP in visual cortex. These findings indicate that synaptic development is delayed in the L4 to L2/3 pathway in visual cortex, and emphasize the need to take into account the changes in synaptic properties that occur during development when comparing plasticity mechanisms in different cortical areas.

Neocortical axon arbors trade-off material and conduction delay conservation

The brain contains a complex network of axons rapidly communicating information between billions of synaptically connected neurons. The morphology of individual axons, therefore, defines the course of information flow within the brain. More than a century ago, Ramón y Cajal proposed that conservation laws to save material (wire) length and limit conduction delay regulate the design of individual axon arbors in cerebral cortex. Yet the spatial and temporal communication costs of single neocortical axons remain undefined. Here, using reconstructions of in vivo labelled excitatory spiny cell and inhibitory basket cell intracortical axons combined with a variety of graph optimization algorithms, we empirically investigated Cajal's conservation laws in cerebral cortex for whole three-dimensional (3D) axon arbors, to our knowledge the first study of its kind. We found intracortical axons were significantly longer than optimal. The temporal cost of cortical axons was also suboptimal though far superior to wire-minimized arbors. We discovered that cortical axon branching appears to promote a low temporal dispersion of axonal latencies and a tight relationship between cortical distance and axonal latency. In addition, inhibitory basket cell axonal latencies may occur within a much narrower temporal window than excitatory spiny cell axons, which may help boost signal detection. Thus, to optimize neuronal network communication we find that a modest excess of axonal wire is traded-off to enhance arbor temporal economy and precision. Our results offer insight into the principles of brain organization and communication in and development of grey matter, where temporal precision is a crucial prerequisite for coincidence detection, synchronization and rapid network oscillations.

Within the grey matter of cerebral cortex is a complex network formed by a dense tangle of individual branching axons mostly of cortical origin. Yet remarkably when presented with a barrage of complex, noisy sensory stimuli this convoluted network architecture computes accurately and rapidly. How does such a highly interconnected though jumbled forest of axonal trees process vital information so quickly? Pioneering neuroscientist Ramón y Cajal thought the size and shape of individual neurons was governed by simple rules to save cellular material and to reduce signal conduction delay. In this study, we investigated how these rules applied to whole axonal trees in neocortex by comparing their 3D structure to equivalent artificial arbors optimized for these rules. We discovered that neocortical axonal trees achieve a balance between these two rules so that a little more cellular material than necessary was used to substantially reduce conduction delays. Importantly, we suggest the nature of arbor branching balances time and material so that neocortical axons may communicate with a high degree of temporal precision, enabling accurate and rapid computation within local cortical networks. This approach could be applied to other neural structures to better understand the functional principles of brain design.

Normal susceptibility to visual illusions in abnormal development: evidence from Williams syndrome

The perception of visual illusions is a powerful diagnostic of implicit integration of global information. Many illusions occur when length, size, orientation, or luminance are misjudged because neighboring visuospatial information cannot be ignored. We asked if people with Williams syndrome (WS), a rare genetic disorder that results in severely impaired global visuospatial construction abilities, are also susceptible to the context of visual illusions. Remarkably, we found that illusions influenced WS individuals to the same degree as normal adults, although size discrimination was somewhat impaired in WS. Our results are evidence that illusions are a consequence of the brain's bias to implicitly integrate visual information, even in a population known to have difficulty in explicitly representing spatial relationships among objects. Moreover, these results suggest that implicit and non-implicit integration of spatial information have different vulnerabilities in abnormal development.

Models of cortical networks with long-range patchy projections

The cortex exhibits an intricate vertical and horizontal architecture, the latter often featuring spatially clustered projection patterns, so-called patches. Many network studies of cortical dynamics ignore such spatial structures and assume purely random wiring. Here, we focus on non-random network structures provided by long-range horizontal (patchy) connections that remain inside the gray matter. We investigate how the spatial arrangement of patchy projections influences global network topology and predict its impact on the activity dynamics of the network. Since neuroanatomical data on horizontal projections is rather sparse, we suggest and compare four candidate scenarios of how patchy connections may be established. To identify a set of characteristic network properties that enables us to pin down the differences between the resulting network models, we employ the framework of stochastic graph theory. We find that patchy projections provide an exceptionally efficient way of wiring, as the resulting networks tend to exhibit small-world properties with significantly reduced wiring costs. Furthermore, the eigenvalue spectra, as well as the structure of common in- and output of the networks suggest that different spatial connectivity patterns support distinct types of activity propagation.

Flexible learning of natural statistics in the human brain

The ability to detect and identify targets in cluttered scenes is a critical skill for survival and interactions. To solve this challenge the brain has optimized mechanisms for capitalizing on frequently occurring regularities in the environment. Although evolution and development have been suggested to shape the brain's architecture in a manner that resembles these natural statistics, we provide novel evidence that short-term experience in adulthood may modify the brain's functional organization to support integration of signals atypical of shape contours in natural scenes. Although collinearity is a prevalent principle for perceptual integration in natural scenes, we show that observers learn to exploit other image regularities (i.e., orthogonal alignments of segments at an angle to the contour path) that typically signify discontinuities. Combining behavioral and functional MRI measurements, we demonstrate that this flexible learning is mediated by changes in the neural representations of behaviorally relevant image regularities primarily in dorsal visual areas. These changes in neural sensitivity are in line with changes in perceptual sensitivity for the detection of orthogonal contours and are evident only in observers that show significant performance improvement. In contrast, changes in the activation extent in frontoparietal regions are evident independent of performance changes, may support the detection of salient regions, and modulate perceptual integration in occipitotemporal areas in a top-down manner. Thus experience at shorter timescales in adulthood supports the adaptive functional optimization of visual circuits for flexible interpretation of natural scenes.

Orientation perception in Williams Syndrome: discrimination and integration

Williams Syndrome (WS) is a rare neurodevelopmental disorder, which stems from a genetic deletion on chromosome 7 and causes a profound weakness in visuospatial cognition. Our current study explores how orientation perception may contribute to the visuospatial deficits in WS. In Experiment 1, we found that WS individuals and normal 3-4 year olds had similar orientation discrimination thresholds and had similar prevalence of mirror-reversal errors for diagonal targets (+/-45 deg). In Experiment 2, we asked whether this immaturity in orientation discrimination would also be reflected in a task requiring integration of oriented elements. We found that sensitivities of WS individuals for detecting orientation-defined contours were higher than sensitivities of normal 3-4 year olds, and were not significantly different from sensitivities of normal adults. Together, these results suggest that orientation discrimination and orientation integration have different maturational trajectories in normal development and different susceptibilities to damage in WS. These may reflect largely separate visuospatial mechanisms.

Experience shapes the utility of natural statistics for perceptual contour integration

Segmenting meaningful targets from cluttered scenes is a fundamental function of the visual system. Evolution and development have been suggested to optimize the brain's solution to this computationally challenging task by tuning the visual system to features that co-occur frequently in natural scenes (e.g., collinear edges) [1, 2, 3]. However, the role of shorter-term experience in shaping the utility of scene statistics remains largely unknown. Here, we ask whether collinearity is a specialized case, or whether the brain can learn to recruit any image regularity for the purpose of target identification. Consistent with long-term optimization for typical scene statistics, observers were better at detecting collinear contours than configurations of elements oriented at orthogonal or acute angles to the contour path. However, training resulted in improved detection of orthogonal contours that lasted for several months, suggesting retuning rather than transient changes of visual sensitivity. Improvement was also observed for acute contours but only after longer training. These results demonstrate that the brain flexibly exploits image regularities and learns to use discontinuities typically associated with surface boundaries (orthogonal, acute alignments) for contour linking and target identification. Thus, short-term experience in adulthood shapes the interpretation of scenes by assigning new statistical utility to image regularities.

Visuospatial interpolation in typically developing children and in people with Williams Syndrome

Visuospatial interpolation is the estimation of object position or contour shape computed from known "anchor" positions. We characterized the developmental profile of interpolation by measuring positional thresholds as a function of inter-element separation without (Experiment 1) and with (Experiment 2) the context of illusory contours in typically developing children, typical adults and individuals with Williams Syndrome (WS), a genetic disorder that causes impaired global visuospatial abilities. We found that typically developing children and WS individuals had more difficulty integrating information across distant elements than typical adults. However, illusory contours improved thresholds in all participant groups in a similar way. Our results suggest that in WS individuals, and in typically developing children, the grouping mechanisms that enable long-range spatial integration are immature. We hypothesize that WS individuals and young children can use stimulus-driven grouping cues for bottom-up integration, but have immature mechanisms for top-down integration of spatial information.

Spatio-temporal prediction and inference by V1 neurons

In normal vision, visual scenes are predictable, as they are both spatially and temporally redundant. Evidence suggests that the visual system may use the spatio-temporal regularities of the external world, available in the retinal signal, to extract information from the visual environment and better reconstruct current and future stimuli. We studied this by recording neuronal responses of primary visual cortex (area V1) in anaesthetized and paralysed macaques during the presentation of dynamic sequences of bars, in which spatio-temporal regularities and local information were independently manipulated. Most V1 neurons were significantly modulated by events prior to and distant from stimulation of their classical receptive fields (CRFs); many were more strongly tuned to prior and distant events than they were to CRFs bars; and several showed tuning to prior information without any CRF stimulation. Hence, V1 neurons do not simply analyse local contours, but impute local features to the visual world, on the basis of prior knowledge of a visual world in which useful information can be distributed widely in space and time.

Similarity and diversity in visual cortex: is there a unifying theory of cortical computation?

The cerebral cortex, with its conserved 6-layer structure, has inspired many unifying models of function. However, recent comparative studies of primary visual cortex have revealed considerable structural diversity, raising doubts about the possibility of an all-encompassing theory. This review examines similarities and differences in V1 across mammals. Gross laminar interconnections are relatively conserved. Major functional response classes are found universally or nearly universally. Orientation and spatial frequency tuning bandwidths are quite similar despite an enormous range of visual resolution across species, and orientation tuning is contrast-invariant. Nevertheless, there is considerable diversity in the abundance of different cell classes, laminar organization, functional architecture, and functional connectivity. Orientation-selective responses arise in different layers in different species. Some mammals have elaborate columnar architecture like orientation maps and ocular dominance bands, but others lack this organization with no apparent impact on single cell properties. Finally, local functional connectivity varies according to map structure: similar cells are connected in smooth map regions but dissimilar cells are linked in animals without maps. If there is a single structure/function relation for cortex, it must accommodate significant variations in cortical circuitry. Alternatively, natural selection may craft unique circuits that function differently in each species.

Layout of transcallosal activity in cat visual cortex revealed by optical imaging

The contribution of interhemispheric connections to functional maps in cat visual cortex was investigated by using optical imaging of intrinsic signals. In order to isolate the functional inputs arriving via the corpus callosum (CC) from other inputs, we used the split-chiasm preparation. The regions activated through the CC in visual areas 17 (A17) and 18 (A18) were localized and characterized by stimulating monocularly split-chiasm cats with moving, high contrast oriented gratings. We found that the CC mediates the activation of orientation selective domains in the transition zone (TZ) between A17 and A18 and occasionally within portions of both of these areas. We observed transcallosally activated orientation domains all along the TZ without any obvious interruption, and these domains were arranged around "pinwheel" centers. Interestingly, the TZ was divided in two parallel regions, which resemble A17 and A18 in their preferred temporal and spatial frequencies. Finally, we demonstrated that orientation maps evoked through the transcallosal and geniculo-cortical pathways were similar within the TZ, indicating a convergence of inputs of matching orientations in this region. These results contribute to a better understanding of the role of the CC in visual perception of orientations and shapes, at the level of the visual cortex.

A model of V4 shape selectivity and invariance

Object recognition in primates is mediated by the ventral visual pathway and is classically described as a feedforward hierarchy of increasingly sophisticated representations. Neurons in macaque monkey area V4, an intermediate stage along the ventral pathway, have been shown to exhibit selectivity to complex boundary conformation and invariance to spatial translation. How could such a representation be derived from the signals in lower visual areas such as V1? We show that a quantitative model of hierarchical processing, which is part of a larger model of object recognition in the ventral pathway, provides a plausible mechanism for the translation-invariant shape representation observed in area V4. Simulated model neurons successfully reproduce V4 selectivity and invariance through a nonlinear, translation-invariant combination of locally selective subunits, suggesting that a similar transformation may occur or culminate in area V4. Specifically, this mechanism models the selectivity of individual V4 neurons to boundary conformation stimuli, exhibits the same degree of translation invariance observed in V4, and produces observed V4 population responses to bars and non-Cartesian gratings. This work provides a quantitative model of the widely described shape selectivity and invariance properties of area V4 and points toward a possible canonical mechanism operating throughout the ventral pathway.

Maplike representation of celestial E-vector orientations in the brain of an insect

For many insects, the polarization pattern of the blue sky serves as a compass cue for spatial navigation. E-vector orientations are detected by photoreceptors in a dorsal rim area of the eye. Polarized-light signals from both eyes are finally integrated in the central complex, a brain area consisting of two subunits, the protocerebral bridge and the central body. Here we show that a topographic representation of zenithal E-vector orientations underlies the columnar organization of the protocerebral bridge in a locust. The maplike arrangement is highly suited to signal head orientation under the open sky.

Morphological, electrophysiological, and synaptic properties of corticocallosal pyramidal cells in the neonatal rat neocortex

Neocortical pyramidal cells (PCs) project to various cortical and subcortical targets. In layer V, the population of thick tufted PCs (TTCs) projects to subcortical targets such as the tectum, brainstem, and spinal cord. Another population of layer V PCs projects via the corpus callosum to the contralateral neocortical hemisphere mediating information transfer between the hemispheres. This subpopulation (corticocallosally projecting cells [CCPs]) has been previously described in terms of their morphological properties, but less is known about their electrophysiological properties, and their synaptic connectivity is unknown. We studied the morphological, electrophysiological, and synaptic properties of CCPs by retrograde labeling with fluorescent microbeads in P13-P16 Wistar rats. CCPs were characterized by shorter, untufted apical dendrites, which reached only up to layers II/III, confirming previous reports. Synaptic connections between CCPs were different from those observed between TTCs, both in probability of occurrence and dynamic properties. We found that the CCP network is about 4 times less interconnected than the TTC network and the probability of release is 24% smaller, resulting in a more linear synaptic transmission. The study shows that layer V pyramidal neurons projecting to different targets form subnetworks with specialized connectivity profiles, in addition to the specialized morphological and electrophysiological intrinsic properties.

Primary visual cortex neurons that contribute to resolve the aperture problem

It is traditional to believe that neurons in primary visual cortex are sensitive only or principally to stimulation within a spatially restricted receptive field (classical receptive field). It follows from this that they should only be capable of encoding the direction of stimulus movement orthogonal to the local contour, since this is the only information available in their classical receptive field "aperture." This direction is not necessarily the same as the motion of the entire object, as the direction cue within an aperture is ambiguous to the global direction of motion, which can only be derived by integrating with unambiguous components of the object. Recent results, however, show that primary visual cortex neurons can integrate spatially and temporally distributed cues outside the classical receptive field, and so we reexamined whether primary visual cortex neurons suffer the "aperture problem." With the stimulation of an optimally oriented bar drifting across the classical receptive field in different global directions, here we show that a subpopulation of primary visual cortex neurons (25/81) recorded from anesthetized and paralyzed marmosets is capable of integrating informative unambiguous direction cues presented by the bar ends, well outside their classical receptive fields, to encode global motion direction. Although the stimuli within the classical receptive field were identical, their directional responses were significantly modulated according to the global direction of stimulus movement. Hence, some primary visual cortex neurons are not local motion energy filters, but may encode signals that contribute directly to global motion processing.

Do we know what the early visual system does?

We can claim that we know what the visual system does once we can predict neural responses to arbitrary stimuli, including those seen in nature. In the early visual system, models based on one or more linear receptive fields hold promise to achieve this goal as long as the models include nonlinear mechanisms that control responsiveness, based on stimulus context and history, and take into account the nonlinearity of spike generation. These linear and nonlinear mechanisms might be the only essential determinants of the response, or alternatively, there may be additional fundamental determinants yet to be identified. Research is progressing with the goals of defining a single "standard model" for each stage of the visual pathway and testing the predictive power of these models on the responses to movies of natural scenes. These predictive models represent, at a given stage of the visual pathway, a compact description of visual computation. They would be an invaluable guide for understanding the underlying biophysical and anatomical mechanisms and relating neural responses to visual perception.

Functional organization of visual cortex in the prosimian bush baby revealed by optical imaging of intrinsic signals

Cells in primary visual cortex (V1) of primates and carnivores respond most strongly to a visual stimulus presented to one eye, in a particular visual field location, and at a particular orientation. Each of these stimulus attributes is mapped across the cortical surface, and, in macaque monkeys and cats, strong geometrical relationships exist between these feature maps. In macaque V1 and V2, correlations between feature maps and cytochrome oxidase (CO)-rich modules have also been observed. To see if such relationships reflect a conserved principle of V1 functional architecture among primate species, we examined these maps in the prosimian bush baby, a species that has been proposed to represent the ancestral primate organization. We found that the layout of individual feature maps in bush baby V1 is similar to that of other primates, but we found an entirely different organization of orientation preference in bush baby V2 compared with that reported in simian primates. Another striking distinction between bush baby and simian species is that we observed no strong relationships among maps of orientation, ocular dominance, and CO blobs in V1. Thus our findings suggest that precise relationships between feature maps are not a common element of the functional organization in all primates and that such relationships are not necessary for achieving basic coverage of stimulus feature combinations. In addition, our results suggest that specific relationships between feature maps in V1, and the subdivision of V2 into functional compartments, may have arisen comparatively late in the evolution of primates.

Single-neuron responses and neuronal decisions in a vernier task

Vernier acuity is a measure of the smallest horizontal offset between two vertical lines that can be behaviorally discriminated. To examine the link between the neuronal responses in a retinotopic mosaic and vernier acuity, we recorded the responses of single cells in cat lateral geniculate nucleus to a vertical bar stimulus that was stepped in small increments through the receptive fields of cells. Based on the single-trial responses evoked by stimuli at different positions, we calculated the spatial resolution that could be achieved. If the stimulus could fall anywhere in their receptive fields, single neurons had spatial resolutions two times worse than previously reported vernier thresholds. Given the known coverage factor in a cat retina, we developed a two-stage decision model to examine how the responses of neurons in a retinotopic mosaic could be processed to achieve vernier acuity. In order for psychophysical thresholds to be accounted for by the responses of a single cell, the stimulus must fall in the quarter of the receptive field that provides the most information about stimulus position. Alternatively, both the absolute psychophysical threshold for vernier acuity and its dependence on stimulus length can be realized by pooling the responses of a few neurons, all located on one side of the bar stimulus.