Surround suppression and sparse coding in visual and barrel cortices

Visual surround suppression at the neural and perceptual levels

Surround suppression was initially identified as a phenomenon at the neural level in which stimuli outside the neuron's receptive field alone cannot activate responses but can modulate neural responses to stimuli covered inside the receptive field. Subsequent studies showed that surround suppression is not only a critical property of neurons across species and brain areas but also has been found in visual perceptions. More importantly, surround suppression varies across individuals and shows significant differences between normal controls and patients with certain mental disorders. Here, we combined results from related literature and summarized the findings derived from physiological and psychophysical evidence. We first outline the basic properties of surround suppression in the visual system and perceptions. Then, we mainly summarize the differences in perceptual surround suppression among different human subjects. Our review suggests that there is no consensus regarding whether the strength of perceptual surround suppression could be used as an effective index to distinguish particular populations. Then, we summarized the similar mechanisms for surround suppression and cognitive impairments to further explore the potential clinical applications of surround suppression. A clearer understanding of the mechanisms of surround suppression in neural responses and perceptions is necessary for facilitating its clinical applications.

Synthetic surprise as the foundation of the psychedelic experience

Psychedelic agents, such as LSD and psilocybin, induce marked alterations in consciousness via activation of the 5-HT2A receptor (5-HT2ARs). We hypothesize that psychedelics enforce a state of synthetic surprise through the biased activation of the 5-HTRs system. This idea is informed by recent insights into the role of 5-HT in signaling surprise. The effects on consciousness, explained by the cognitive penetrability of perception, can be described within the predictive coding framework where surprise corresponds to prediction error, the mismatch between predictions and actual sensory input. Crucially, the precision afforded to the prediction error determines its effect on priors, enabling a dynamic interaction between top-down expectations and incoming sensory data. By integrating recent findings on predictive coding circuitry and 5-HT2ARs transcriptomic data, we propose a biological implementation with emphasis on the role of inhibitory interneurons. Implications arise for the clinical use of psychedelics, which may rely primarily on their inherent capacity to induce surprise in order to disrupt maladaptive patterns.

No Evidence of Cross-Orientation Suppression Differences in Migraine with Aura Compared to Healthy Controls

It has been suggested that there may be an imbalance of excitation and inhibitory processes in the visual areas of the brain in people with migraine aura (MA). One idea is thalamocortical dysrhythmia, characterized by disordered oscillations, and thus disordered communication between the lateral geniculate nucleus and the cortex. Cross-orientation suppression is a visual task thought to rely on inhibitory processing, possibly originating in the lateral geniculate nucleus. We measured both resting-state oscillations and cross-orientation suppression using EEG over occipital areas in people with MA and healthy volunteers. We found evidence of cross-orientation suppression in the SSVEP responses, but no evidence of any group difference. Therefore, inhibitory processes related to cross-orientation suppression do not appear to be impaired in MA.

Layer 1 of somatosensory cortex: an important site for input to a tiny cortical compartment

Neocortical layer 1 has been proposed to be at the center for top-down and bottom-up integration. It is a locus for interactions between long-range inputs, layer 1 interneurons, and apical tuft dendrites of pyramidal neurons. While input to layer 1 has been studied intensively, the level and effect of input to this layer has still not been completely characterized. Here we examined the input to layer 1 of mouse somatosensory cortex with retrograde tracing and optogenetics. Our assays reveal that local input to layer 1 is predominantly from layers 2/3 and 5 pyramidal neurons and interneurons, and that subtypes of local layers 5 and 6b neurons project to layer 1 with different probabilities. Long-range input from sensory-motor cortices to layer 1 of somatosensory cortex arose predominantly from layers 2/3 neurons. Our optogenetic experiments showed that intra-telencephalic layer 5 pyramidal neurons drive layer 1 interneurons but have no effect locally on layer 5 apical tuft dendrites. Dual retrograde tracing revealed that a fraction of local and long-range neurons was both presynaptic to layer 5 neurons and projected to layer 1. Our work highlights the prominent role of local inputs to layer 1 and shows the potential for complex interactions between long-range and local inputs, which are both in position to modify the output of somatosensory cortex.

Lateral inhibition in V1 controls neural & perceptual contrast sensitivity

Lateral inhibition is a central principle for sensory system function. It is thought to operate by the activation of inhibitory neurons that restrict the spatial spread of sensory excitation. Much work on the role of inhibition in sensory systems has focused on visual cortex; however, the neurons, computations, and mechanisms underlying cortical lateral inhibition remain debated, and its importance for visual perception remains unknown. Here, we tested how lateral inhibition from PV or SST neurons in mouse primary visual cortex (V1) modulates neural and perceptual sensitivity to stimulus contrast. Lateral inhibition from PV neurons reduced neural and perceptual sensitivity to visual contrast in a uniform subtractive manner, whereas lateral inhibition from SST neurons more effectively changed the slope (or gain) of neural and perceptual contrast sensitivity. A neural circuit model identified spatially extensive lateral projections from SST neurons as the key factor, and we confirmed this with direct subthreshold measurements of a larger spatial footprint for SST versus PV lateral inhibition. Together, these results define cell-type specific computational roles for lateral inhibition in V1, and establish their unique consequences on sensitivity to contrast, a fundamental aspect of the visual world.

Surround suppression in mouse auditory cortex underlies auditory edge detection

Surround suppression (SS) is a fundamental property of sensory processing throughout the brain. In the auditory system, the early processing stream encodes sounds using a one dimensional physical space-frequency. Previous studies in the auditory system have shown SS to manifest as bandwidth tuning around the preferred frequency. We asked whether bandwidth tuning can be found around frequencies away from the preferred frequency. We exploited the simplicity of spectral representation of sounds to study SS by manipulating both sound frequency and bandwidth. We recorded single unit spiking activity from the auditory cortex (ACx) of awake mice in response to an array of broadband stimuli with varying central frequencies and bandwidths. Our recordings revealed that a significant portion of neuronal response profiles had a preferred bandwidth that varied in a regular way with the sound's central frequency. To gain insight into the possible mechanism underlying these responses, we modelled neuronal activity using a variation of the "Mexican hat" function often used to model SS. The model accounted for response properties of single neurons with high accuracy. Our data and model show that these responses in ACx obey simple rules resulting from the presence of lateral inhibitory sidebands, mostly above the excitatory band of the neuron, that result in sensitivity to the location of top frequency edges, invariant to other spectral attributes. Our work offers a simple explanation for auditory edge detection and possibly other computations of spectral content in sounds.

Mechanisms of Surround Suppression Effect on the Contrast Sensitivity of V1 Neurons in Cats

Surround suppression (SS) is a phenomenon that a neuron’s response to visual stimuli within the classical receptive field (cRF) is suppressed by a concurrent stimulation in the surrounding receptive field (sRF) beyond the cRF. Studies show that SS affects neuronal response contrast sensitivity in the primary visual cortex (V1). However, the underlying mechanisms remain unclear. Here, we examined SS effect on the contrast sensitivity of cats’ V1 neurons with different preferred SFs using external noise-masked visual stimuli and perceptual template model (PTM) analysis at the system level. The contrast sensitivity was evaluated by the inverted threshold contrast of neurons in response to circular gratings of different contrasts in the cRF with or without an annular grating in the sRF. Our results showed that SS significantly reduced the contrast sensitivity of cats’ V1 neurons. The SS-induced reduction of contrast sensitivity was not correlated with SS strength but was dependent on neuron’s preferred SF, with a larger reduction for neurons with low preferred SFs than those with high preferred SFs. PTM analysis of threshold versus external noise contrast (TvC) functions indicated that SS decreased contrast sensitivity by increasing both the internal additive noise and impact of external noise for neurons with low preferred SFs, but improving only internal additive noise for neurons with high preferred SFs. Furthermore, the SS effect on the contrast-response function of low- and high-SF neurons also exhibited different mechanisms in contrast gain and response gain. Collectively, these results suggest that the mechanisms of SS effect on neuronal contrast sensitivity may depend on neuronal populations with different SFs.

Corticothalamic feedback sculpts visual spatial integration in mouse thalamus

En route from the retina to the cortex, visual information passes through the dorsolateral geniculate nucleus (dLGN) of the thalamus, where extensive corticothalamic (CT) feedback has been suggested to modulate spatial processing. How this modulation arises from direct excitatory and indirect inhibitory CT feedback pathways remains enigmatic. Here, we show that in awake mice, retinotopically organized cortical feedback sharpens receptive fields (RFs) and increases surround suppression in the dLGN. Guided by a network model indicating that widespread inhibitory CT feedback is necessary to reproduce these effects, we targeted the visual sector of the thalamic reticular nucleus (visTRN) for recordings. We found that visTRN neurons have large RFs, show little surround suppression and exhibit strong feedback-dependent responses to large stimuli. These features make them an ideal candidate for mediating feedback-enhanced surround suppression in the dLGN. We conclude that cortical feedback sculpts spatial integration in the dLGN, likely via recruitment of neurons in the visTRN.

Synthesis of a comprehensive population code for contextual features in the awake sensory cortex

How cortical circuits build representations of complex objects is poorly understood. Individual neurons must integrate broadly over space, yet simultaneously obtain sharp tuning to specific global stimulus features. Groups of neurons identifying different global features must then assemble into a population that forms a comprehensive code for these global stimulus properties. Although the logic for how single neurons summate over their spatial inputs has been well explored in anesthetized animals, how large groups of neurons compose a flexible population code of higher-order features in awake animals is not known. To address this question, we probed the integration and population coding of higher-order stimuli in the somatosensory and visual cortices of awake mice using two-photon calcium imaging across cortical layers. We developed a novel tactile stimulator that allowed the precise measurement of spatial summation even in actively whisking mice. Using this system, we found a sparse but comprehensive population code for higher-order tactile features that depends on a heterogeneous and neuron-specific logic of spatial summation beyond the receptive field. Different somatosensory cortical neurons summed specific combinations of sensory inputs supra-linearly, but integrated other inputs sub-linearly, leading to selective responses to higher-order features. Visual cortical populations employed a nearly identical scheme to generate a comprehensive population code for contextual stimuli. These results suggest that a heterogeneous logic of input-specific supra-linear summation may represent a widespread cortical mechanism for the synthesis of sparse higher-order feature codes in neural populations. This may explain how the brain exploits the thalamocortical expansion of dimensionality to encode arbitrary complex features of sensory stimuli.

Voltage-Sensitive Dye versus Intrinsic Signal Optical Imaging: Comparison of Tactile Responses in Primary and Secondary Somatosensory Cortices of Rats

Studies using functional magnetic resonance imaging assume that hemodynamic responses have roughly linear relationships with underlying neural activity. However, to accurately investigate the neurovascular transfer function and compare its variability across brain regions, it is necessary to obtain full-field imaging of both electrophysiological and hemodynamic responses under various stimulus conditions with superior spatiotemporal resolution. Optical imaging combined with voltage-sensitive dye (VSD) and intrinsic signals (IS) is a powerful tool to address this issue. We performed VSD and IS imaging in the primary (S1) and secondary (S2) somatosensory cortices of rats to obtain optical maps of whisker-evoked responses. There were characteristic differences in sensory responses between the S1 and S2 cortices: VSD imaging revealed more localized excitatory and stronger inhibitory neural activity in S1 than in S2. IS imaging revealed stronger metabolic responses in S1 than in S2. We calculated the degree of response to compare the sensory responses between cortical regions and found that the ratio of the degree of response of S2 to S1 was similar, irrespective of whether the ratio was determined by VSD or IS imaging. These results suggest that neurovascular coupling does not vary between the S1 and S2 cortices.

Recurrent dynamics in the cerebral cortex: Integration of sensory evidence with stored knowledge

Current concepts of sensory processing in the cerebral cortex emphasize serial extraction and recombination of features in hierarchically structured feed-forward networks in order to capture the relations among the components of perceptual objects. These concepts are implemented in convolutional deep learning networks and have been validated by the astounding similarities between the functional properties of artificial systems and their natural counterparts. However, cortical architectures also display an abundance of recurrent coupling within and between the layers of the processing hierarchy. This massive recurrence gives rise to highly complex dynamics whose putative function is poorly understood. Here a concept is proposed that assigns specific functions to the dynamics of cortical networks and combines, in a unifying approach, the respective advantages of recurrent and feed-forward processing. It is proposed that the priors about regularities of the world are stored in the weight distributions of feed-forward and recurrent connections and that the high-dimensional, dynamic space provided by recurrent interactions is exploited for computations. These comprise the ultrafast matching of sensory evidence with the priors covertly represented in the correlation structure of spontaneous activity and the context-dependent grouping of feature constellations characterizing natural objects. The concept posits that information is encoded not only in the discharge frequency of neurons but also in the precise timing relations among the discharges. Results of experiments designed to test the predictions derived from this concept support the hypothesis that cerebral cortex exploits the high-dimensional recurrent dynamics for computations serving predictive coding.

The Role of Interhemispheric Interactions in Cortical Plasticity

Despite the fact that there is a growing awareness to the callosal connections between hemispheres the two hemispheres of the brain are commonly treated as independent structures when peripheral or cortical manipulations are applied to one of them. The contralateral hemisphere is often used as a within-animal control of plastic changes induced onto the other side of the brain. This ensures uniform conditions for producing experimental and control data, but it may overlook possible interhemispheric interactions. In this paper we provide, for the first time, direct proof that cortical, experience-dependent plasticity is not a unilateral, independent process. We mapped metabolic brain activity in rats with 2-[¹⁴C] deoxyglucose (2DG) following experience-dependent plasticity induction after a month of unilateral (left), partial whiskers deprivation (only row B was left). This resulted in ∼45% widening of the cortical sensory representation of the spared whiskers in the right, contralateral barrel field (BF). We show that the width of 2DG visualized representation is less than 20% when only contralateral stimulation of the spared row of whiskers is applied in immobilized animals. This means that cortical map remodeling, which is induced by experience-dependent plasticity mechanisms, depends partially on the contralateral hemisphere. The response, which is observed by 2DG brain mapping in the partially deprived BF after standard synchronous bilateral whiskers stimulation, is therefore the outcome of at least two separately activated plasticity mechanisms. A focus on the integrated nature of cortical plasticity, which is the outcome of the emergent interactions between deprived and non-deprived areas in both hemispheres may have important implications for learning and rehabilitation. There is also a clear implication that there is nothing like “control hemisphere” since any plastic changes in one hemisphere have to have influence on functioning of the opposite one.

Functional and Structural Properties of Highly Responsive Somatosensory Neurons in Mouse Barrel Cortex

Sparse population activity is a well-known feature of supragranular sensory neurons in neocortex. The mechanisms underlying sparseness are not well understood because a direct link between the neurons activated in vivo, and their cellular properties investigated in vitro has been missing. We used two-photon calcium imaging to identify a subset of neurons in layer L2/3 (L2/3) of mouse primary somatosensory cortex that are highly active following principal whisker vibrotactile stimulation. These high responders (HRs) were then tagged using photoconvertible green fluorescent protein for subsequent targeting in the brain slice using intracellular patch-clamp recordings and biocytin staining. This approach allowed us to investigate the structural and functional properties of HRs that distinguish them from less active control cells. Compared to less responsive L2/3 neurons, HRs displayed increased levels of stimulus-evoked and spontaneous activity, elevated noise and spontaneous pairwise correlations, and stronger coupling to the population response. Intrinsic excitability was reduced in HRs, while we found no evidence for differences in other electrophysiological and morphological parameters. Thus, the choice of which neurons participate in stimulus encoding may be determined largely by network connectivity rather than by cellular structure and function.

Modulation of Coordinated Activity across Cortical Layers by Plasticity of Inhibitory Synapses

In the neocortex, synaptic inhibition shapes all forms of spontaneous and sensory evoked activity. Importantly, inhibitory transmission is highly plastic, but the functional role of inhibitory synaptic plasticity is unknown. In the mouse barrel cortex, activation of layer (L) 2/3 pyramidal neurons (PNs) elicits strong feedforward inhibition (FFI) onto L5 PNs. We find that FFI involving parvalbumin (PV)-expressing cells is strongly potentiated by postsynaptic PN burst firing. FFI plasticity modifies the PN excitation-to-inhibition (E/I) ratio, strongly modulates PN gain, and alters information transfer across cortical layers. Moreover, our LTPi-inducing protocol modifies firing of L5 PNs and alters the temporal association of PN spikes to γ-oscillations both in vitro and in vivo. All of these effects are captured by unbalancing the E/I ratio in a feedforward inhibition circuit model. Altogether, our results indicate that activity-dependent modulation of perisomatic inhibitory strength effectively influences the participation of single principal cortical neurons to cognition-relevant network activity.

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Feedforward inhibition (FFI) of layer 5 pyramidal neurons (PNs) is highly plastic

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Long-term potentiation of FFI modulates spiking activity of layer 5 PNs

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LTPi affects information transfer across cortical layers

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The strength of LTPi determines the phase locking of PN firing to γ-oscillations

Pseudosparse neural coding in the visual system of primates

When measuring sparseness in neural populations as an indicator of efficient coding, an implicit assumption is that each stimulus activates a different random set of neurons. In other words, population responses to different stimuli are, on average, uncorrelated. Here we examine neurophysiological data from four lobes of macaque monkey cortex, including V1, V2, MT, anterior inferotemporal cortex, lateral intraparietal cortex, the frontal eye fields, and perirhinal cortex, to determine how correlated population responses are. We call the mean correlation the pseudosparseness index, because high pseudosparseness can mimic statistical properties of sparseness without being authentically sparse. In every data set we find high levels of pseudosparseness ranging from 0.59-0.98, substantially greater than the value of 0.00 for authentic sparseness. This was true for synthetic and natural stimuli, as well as for single-electrode and multielectrode data. A model indicates that a key variable producing high pseudosparseness is the standard deviation of spontaneous activity across the population. Consistently high values of pseudosparseness in the data demand reconsideration of the sparse coding literature as well as consideration of the degree to which authentic sparseness provides a useful framework for understanding neural coding in the cortex.

Seasonal plasticity in the adult somatosensory cortex

To survive, animals need to adapt to changes of their ecosystem by changing their behaviors or even morphing the organs responsible for generating these behaviors. Small mammals have a high metabolic rate, and to balance energy deficits during winter they can decrease their brain and body size, a phenomenon termed Dehnel’s effect. We find specific seasonal changes in the brain of the smallest terrestrial mammal, the Etruscan shrew. Their cortex shrinks in the winter, with layer-width and neuron number reduction in the energetically expensive somatosensory cortical layer 4. Imaging of neural activity revealed reduced suppressive responses to whisker touch during winter, indicating that such cortical adaptation may have synergistic functional and behavioral effects in addition to direct metabolic benefits.

Seasonal cycles govern life on earth, from setting the time for the mating season to influencing migrations and governing physiological conditions like hibernation. The effect of such changing conditions on behavior is well-appreciated, but their impact on the brain remains virtually unknown. We investigate long-term seasonal changes in the mammalian brain, known as Dehnel’s effect, where animals exhibit plasticity in body and brain sizes to counter metabolic demands in winter. We find large seasonal variation in cellular architecture and neuronal activity in the smallest terrestrial mammal, the Etruscan shrew, Suncus etruscus. Their brain, and specifically their neocortex, shrinks in winter. Shrews are tactile hunters, and information from whiskers first reaches the somatosensory cortex layer 4, which exhibits a reduced width (−28%) in winter. Layer 4 width (+29%) and neuron number (+42%) increase the following summer. Activity patterns in the somatosensory cortex show a prominent reduction of touch-suppressed neurons in layer 4 (−55%), the most metabolically active layer. Loss of inhibitory gating occurs with a reduction in parvalbumin-positive interneurons, one of the most active neuronal subtypes and the main regulators of inhibition in layer 4. Thus, a reduction in neurons in layer 4 and particularly parvalbumin-positive interneurons may incur direct metabolic benefits. However, changes in cortical balance can also affect the threshold for detecting sensory stimuli and impact prey choice, as observed in wild shrews. Thus, seasonal neural adaptation can offer synergistic metabolic and behavioral benefits to the organism and offer insights on how neural systems show adaptive plasticity in response to ecological demands.

Up and Down States and Memory Consolidation Across Somatosensory, Entorhinal, and Hippocampal Cortices

In the course of a day, brain states fluctuate, from conscious awake information-acquiring states to sleep states, during which previously acquired information is further processed and stored as memories. One hypothesis is that memories are consolidated and stored during "offline" states such as sleep, a process thought to involve transfer of information from the hippocampus to other cortical areas. Up and Down states (UDS), patterns of activity that occur under anesthesia and sleep states, are likely to play a role in this process, although the nature of this role remains unclear. Here we review what is currently known about these mechanisms in three anatomically distinct but interconnected cortical areas: somatosensory cortex, entorhinal cortex, and the hippocampus. In doing so, we consider the role of this activity in the coordination of "replay" during sleep states, particularly during hippocampal sharp-wave ripples. We conclude that understanding the generation and propagation of UDS may provide key insights into the cortico-hippocampal dialogue linking archi- and neocortical areas during memory formation.

Morphological and Functional Characterization of Non-fast-Spiking GABAergic Interneurons in Layer 4 Microcircuitry of Rat Barrel Cortex

GABAergic interneurons are notorious for their heterogeneity, despite constituting a small fraction of the neuronal population in the neocortex. Classification of interneurons is crucial for understanding their widespread cortical functions as they provide a complex and dynamic network, balancing excitation and inhibition. Here, we investigated different types of non-fast-spiking (nFS) interneurons in Layer 4 (L4) of rat barrel cortex using whole-cell patch-clamp recordings with biocytin-filling. Based on a quantitative analysis on a combination of morphological and electrophysiological parameters, we identified 5 distinct types of L4 nFS interneurons: 1) trans-columnar projecting interneurons, 2) locally projecting non-Martinotti-like interneurons, 3) supra-granular projecting Martinotti-like interneurons, 4) intra-columnar projecting VIP-like interneurons, and 5) locally projecting neurogliaform-like interneurons. Trans-columnar projecting interneurons are one of the most striking interneuron types, which have not been described so far in Layer 4. They feature extensive axonal collateralization not only in their home barrel but also in adjacent barrels. Furthermore, we identified that most of the L4 nFS interneurons express somatostatin, while few are positive for the transcription factor Prox1. The morphological and electrophysiological characterization of different L4 nFS interneuron types presented here provides insights into their synaptic connectivity and functional role in cortical information processing.

Optogenetic study of the response interaction among multi-afferent inputs in the barrel cortex of rats

We investigated the relationship between whisker mechanoreceptive inputs and the neural responses to optical stimulation in layer 2/upper 3 (L2/U3) of the barrel cortex using optogenetics since, ideally, we should investigate interactions among inputs with spatiotemporal acuity. Sixteen whisker points of a transgenic rat (W-TChR2V4), that expresses channelrhodopsin 2 (ChR2)-Venus conjugate (ChR2V) in the peripheral nerve endings surrounding the whisker follicles, were respectively connected one-by-one with 16 LED-coupled optical fibres, which illuminated the targets according to a certain pattern in order to evaluate interactions among the inputs in L2/U3. We found that the individual L2/U3 neurons frequently received excitatory inputs from multiple whiskers that were arrayed in a row. Although the interactions among major afferent inputs (MAIs) were negligible, negative interactions with the surrounding inputs suggest that the afferent inputs were integrated in the cortical networks to enhance the contrast of an array to its surroundings. With its simplicity, reproducibility and spatiotemporal acuity, the optogenetic approach would provide an alternative way to understand the principles of afferent integration in the cortex and should complement knowledge obtained by experiments using more natural stimulations.

Layer 3 Dynamically Coordinates Columnar Activity According to Spatial Context

To reduce statistical redundancy of natural inputs and increase the sparseness of coding, neurons in primary visual cortex (V1) show tuning for stimulus size and surround suppression. This integration of spatial information is a fundamental, context-dependent neural operation involving extensive neural circuits that span across all cortical layers of a V1 column, and reflects both feedforward and feedback processing. However, how spatial integration is dynamically coordinated across cortical layers remains poorly understood. We recorded single- and multiunit activity and local field potentials across V1 layers of awake mice (both sexes) while they viewed stimuli of varying size and used dynamic Bayesian model comparisons to identify when laminar activity and interlaminar functional interactions showed surround suppression, the hallmark of spatial integration. We found that surround suppression is strongest in layer 3 (L3) and L4 activity, where suppression is established within ∼10 ms after response onset, and receptive fields dynamically sharpen while suppression strength increases. Importantly, we also found that specific directed functional connections were strongest for intermediate stimulus sizes and suppressed for larger ones, particularly for connections from L3 targeting L5 and L1. Together, the results shed light on the different functional roles of cortical layers in spatial integration and on how L3 dynamically coordinates activity across a cortical column depending on spatial context.SIGNIFICANCE STATEMENT Neurons in primary visual cortex (V1) show tuning for stimulus size, where responses to stimuli exceeding the receptive field can be suppressed (surround suppression). We demonstrate that functional connectivity between V1 layers can also have a surround-suppressed profile. A particularly prominent role seems to have layer 3, the functional connections to layers 5 and 1 of which are strongest for stimuli of optimal size and decreased for large stimuli. Our results therefore point toward a key role of layer 3 in coordinating activity across the cortical column according to spatial context.

Neural coding: A single neuron's perspective

What any sensory neuron knows about the world is one of the cardinal questions in Neuroscience. Information from the sensory periphery travels across synaptically coupled neurons as each neuron encodes information by varying the rate and timing of its action potentials (spikes). Spatiotemporally correlated changes in this spiking regimen across neuronal populations are the neural basis of sensory representations. In the somatosensory cortex, however, spiking of individual (or pairs of) cortical neurons is only minimally informative about the world. Recent studies showed that one solution neurons implement to counteract this information loss is adapting their rate of information transfer to the ongoing synaptic activity by changing the membrane potential at which spike is generated. Here we first introduce the principles of information flow from the sensory periphery to the primary sensory cortex in a model sensory (whisker) system, and subsequently discuss how the adaptive spike threshold gates the intracellular information transfer from the somatic post-synaptic potential to action potentials, controlling the information content of communication across somatosensory cortical neurons.

Bidirectional encoding of motion contrast in the mouse superior colliculus

Detection of salient objects in the visual scene is a vital aspect of an animal's interactions with its environment. Here, we show that neurons in the mouse superior colliculus (SC) encode visual saliency by detecting motion contrast between stimulus center and surround. Excitatory neurons in the most superficial lamina of the SC are contextually modulated, monotonically increasing their response from suppression by the same-direction surround to maximal potentiation by an oppositely-moving surround. The degree of this potentiation declines with depth in the SC. Inhibitory neurons are suppressed by any surround at all depths. These response modulations in both neuronal populations are much more prominent to direction contrast than to phase, temporal frequency, or static orientation contrast, suggesting feature-specific saliency encoding in the mouse SC. Together, our findings provide evidence supporting locally generated feature representations in the SC, and lay the foundations towards a mechanistic and evolutionary understanding of their emergence.

Parallel Computations in Insect and Mammalian Visual Motion Processing

Sensory systems use receptors to extract information from the environment and neural circuits to perform subsequent computations. These computations may be described as algorithms composed of sequential mathematical operations. Comparing these operations across taxa reveals how different neural circuits have evolved to solve the same problem, even when using different mechanisms to implement the underlying math. In this review, we compare how insect and mammalian neural circuits have solved the problem of motion estimation, focusing on the fruit fly Drosophila and the mouse retina. Although the two systems implement computations with grossly different anatomy and molecular mechanisms, the underlying circuits transform light into motion signals with strikingly similar processing steps. These similarities run from photoreceptor gain control and spatiotemporal tuning to ON and OFF pathway structures, motion detection, and computed motion signals. The parallels between the two systems suggest that a limited set of algorithms for estimating motion satisfies both the needs of sighted creatures and the constraints imposed on them by metabolism, anatomy, and the structure and regularities of the visual world.

Differential receptive field organizations give rise to nearly identical neural correlations across three parallel sensory maps in weakly electric fish

Understanding how neural populations encode sensory information thereby leading to perception and behavior (i.e., the neural code) remains an important problem in neuroscience. When investigating the neural code, one must take into account the fact that neural activities are not independent but are actually correlated with one another. Such correlations are seen ubiquitously and have a strong impact on neural coding. Here we investigated how differences in the antagonistic center-surround receptive field (RF) organization across three parallel sensory maps influence correlations between the activities of electrosensory pyramidal neurons. Using a model based on known anatomical differences in receptive field center size and overlap, we initially predicted large differences in correlated activity across the maps. However, in vivo electrophysiological recordings showed that, contrary to modeling predictions, electrosensory pyramidal neurons across all three segments displayed nearly identical correlations. To explain this surprising result, we incorporated the effects of RF surround in our model. By systematically varying both the RF surround gain and size relative to that of the RF center, we found that multiple RF structures gave rise to similar levels of correlation. In particular, incorporating known physiological differences in RF structure between the three maps in our model gave rise to similar levels of correlation. Our results show that RF center overlap alone does not determine correlations which has important implications for understanding how RF structure influences correlated neural activity.

Growing evidence across nervous systems and species shows that the activities of neighboring neurons are not independent but are correlated with one another, which has important implications for neural coding. Such correlations are generally thought to be due to shared input. However, how this shared input is integrated by neurons in order to give rise to correlated activity is not well understood in general. Here we investigated how receptive field structure determines correlations between the activities of electrosensory pyramidal neurons in weakly electric fish. To do so, we used a combination of mathematical modeling of the known antagonistic center-surround RF structure as well as in vivo electrophysiological recordings. Our results show that the amount of receptive field center overlap alone is not sufficient to explain experimentally observed neural correlations in general. This is because our experimental data shows that pyramidal neurons with very different amounts of receptive field center overlap display almost identical correlations between their activities. Further, our modeling shows that both receptive field center and surround play important roles in determining correlated activity, such that very different combinations of relative RF surround strength and size can generate nearly identical correlations between neural activities. We discuss the implications of our results for sensory processing.

Striatal Network Models of Huntington's Disease Dysfunction Phenotypes

We present a network model of striatum, which generates “winnerless” dynamics typical for a network of sparse, unidirectionally connected inhibitory units. We observe that these dynamics, while interesting and a good match to normal striatal electrophysiological recordings, are fragile. Specifically, we find that randomly initialized networks often show dynamics more resembling “winner-take-all,” and relate this “unhealthy” model activity to dysfunctional physiological and anatomical phenotypes in the striatum of Huntington's disease animal models. We report plasticity as a potent mechanism to refine randomly initialized networks and create a healthy winnerless dynamic in our model, and we explore perturbations to a healthy network, modeled on changes observed in Huntington's disease, such as neuron cell death and increased bidirectional connectivity. We report the effect of these perturbations on the conversion risk of the network to an unhealthy state. Finally we discuss the relationship between structural and functional phenotypes observed at the level of simulated network dynamics as a promising means to model disease progression in different patient populations.

Circuits and Mechanisms for Surround Modulation in Visual Cortex

Surround modulation (SM) is a fundamental property of sensory neurons in many species and sensory modalities. SM is the ability of stimuli in the surround of a neuron's receptive field (RF) to modulate (typically suppress) the neuron's response to stimuli simultaneously presented inside the RF, a property thought to underlie optimal coding of sensory information and important perceptual functions. Understanding the circuit and mechanisms for SM can reveal fundamental principles of computations in sensory cortices, from mouse to human. Current debate is centered over whether feedforward or intracortical circuits generate SM, and whether this results from increased inhibition or reduced excitation. Here we present a working hypothesis, based on theoretical and experimental evidence, that SM results from feedforward, horizontal, and feedback interactions with local recurrent connections, via synaptic mechanisms involving both increased inhibition and reduced recurrent excitation. In particular, strong and balanced recurrent excitatory and inhibitory circuits play a crucial role in the computation of SM.

Reduced Lateral Inhibition Impairs Olfactory Computations and Behaviors in a Drosophila Model of Fragile X Syndrome

Fragile X syndrome (FXS) patients present neuronal alterations that lead to severe intellectual disability, but the underlying neuronal circuit mechanisms are poorly understood. An emerging hypothesis postulates that reduced GABAergic inhibition of excitatory neurons is a key component in the pathophysiology of FXS. Here, we directly test this idea in a FXS Drosophila model. We show that FXS flies exhibit strongly impaired olfactory behaviors. In line with this, olfactory representations are less odor specific due to broader response tuning of excitatory projection neurons. We find that impaired inhibitory interactions underlie reduced specificity in olfactory computations. Finally, we show that defective lateral inhibition across projection neurons is caused by weaker inhibition from GABAergic interneurons. We provide direct evidence that deficient inhibition impairs sensory computations and behavior in an in vivo model of FXS. Together with evidence of impaired inhibition in autism and Rett syndrome, these findings suggest a potentially general mechanism for intellectual disability.

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Lack of dFMRP leads to reduced olfactory attraction and aversion in fruit flies

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Odor selectivity of antennal lobe projection neurons is impaired in dfmr1⁻ flies

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GABAergic lateral inhibition within the antennal lobe is weaker in dfmr1⁻ flies

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Deficient lateral inhibition impairs sensory computations and animal behavior

The neurogenesis of P1 and N1: A concurrent EEG/LFP study

It is generally recognised that event related potentials (ERPs) of electroencephalogram (EEG) primarily reflect summed post-synaptic activity of the local pyramidal neural population(s). However, it is still not understood how the positive and negative deflections (e.g. P1, N1 etc) observed in ERP recordings are related to the underlying excitatory and inhibitory post-synaptic activity. We investigated the neurogenesis of P1 and N1 in ERPs by pharmacologically manipulating inhibitory post-synaptic activity in the somatosensory cortex of rodent, and concurrently recording EEG and local field potentials (LFPs). We found that the P1 wave in the ERP and LFP of the supragranular layers is determined solely by the excitatory post-synaptic activity of the local pyramidal neural population, as is the initial segment of the N1 wave across cortical depth. The later part of the N1 wave was modulated by inhibitory post-synaptic activity, with its peak and the pulse width increasing as inhibition was reduced. These findings suggest that the temporal delay of inhibition with respect to excitation observed in intracellular recordings is also reflected in extracellular field potentials (FPs), resulting in a temporal window during which only excitatory post-synaptic activity and leak channel activity are recorded in the ERP and evoked LFP time series. Based on these findings, we provide clarification on the interpretation of P1 and N1 in terms of the excitatory and inhibitory post-synaptic activities of the local pyramidal neural population(s).

Attention operates uniformly throughout the classical receptive field and the surround

Shifting attention among visual stimuli at different locations modulates neuronal responses in heterogeneous ways, depending on where those stimuli lie within the receptive fields of neurons. Yet how attention interacts with the receptive-field structure of cortical neurons remains unclear. We measured neuronal responses in area V4 while monkeys shifted their attention among stimuli placed in different locations within and around neuronal receptive fields. We found that attention interacts uniformly with the spatially-varying excitation and suppression associated with the receptive field. This interaction explained the large variability in attention modulation across neurons, and a non-additive relationship among stimulus selectivity, stimulus-induced suppression and attention modulation that has not been previously described. A spatially-tuned normalization model precisely accounted for all observed attention modulations and for the spatial summation properties of neurons. These results provide a unified account of spatial summation and attention-related modulation across both the classical receptive field and the surround.

DOI:http://dx.doi.org/10.7554/eLife.17256.001

At any moment, our brain receives an enormous amount of information from our senses. However, we are not aware of all of this information; only the information we decide to focus on is perceived in detail. This ability to focus our attention is important for survival.

The neurons involved in vision respond best to information that comes from a small ‘window’ in what is being seen. When something appears in this window (known as the neuron’s receptive field), the activity of the neuron either increases or decreases. How does focusing attention on an object change the neuron’s response? Verhoef and Maunsell investigated this question by recording electrical activity in an area of the brain called V4 in monkeys as they focused their attention on objects in different locations of the neuron’s receptive field.

The recordings show that a single rule determines when attention influences a neuron’s activity. If an object inside the neuron’s receptive field decreases the activity of the neuron, then attention can change that neuron’s activity. Attention then changes the activity of the neuron by either removing or further boosting the influence of these objects.

Verhoef and Maunsell then developed a mathematical model based on these results, and found that the model could explain why the activity of a neuron changes when attention is focused on objects at different locations in its receptive field. The next step is to understand exactly how the brain works to either remove or boost the influence of an object that causes a neuron’s activity to decrease.

DOI:http://dx.doi.org/10.7554/eLife.17256.002

Altered excitatory-inhibitory balance within somatosensory cortex is associated with enhanced plasticity and pain sensitivity in a mouse model of multiple sclerosis

BACKGROUND

Chronic neuropathic pain is a common symptom of multiple sclerosis (MS). MOG35-55-induced experimental autoimmune encephalomyelitis (EAE) has been used as an animal model to investigate the mechanisms of pain in MS. Previous studies have implicated sensitization of spinal nociceptive networks in the pathogenesis of pain in EAE. However, the involvement of supraspinal sites of nociceptive integration, such as the primary somatosensory cortex (S1), has not been defined. We therefore examined functional, structural, and immunological alterations in S1 during the early stages of EAE, when pain behaviors first appear. We also assessed the effects of the antidepressant phenelzine (PLZ) on S1 alterations and nociceptive (mechanical) sensitivity in early EAE. PLZ has been shown to restore central nervous system (CNS) tissue concentrations of GABA and the monoamines (5-HT, NA) in EAE. We hypothesized that PLZ treatment would also normalize nociceptive sensitivity in EAE by restoring the balance of excitation and inhibition (E-I) in the CNS.

METHODS

We used in vivo flavoprotein autofluorescence imaging (FAI) to assess neural ensemble responses in S1 to vibrotactile stimulation of the limbs in early EAE. We also used immunohistochemistry (IHC), and Golgi-Cox staining, to examine synaptic changes and neuroinflammation in S1. Mechanical sensitivity was assessed at the clinical onset of EAE with Von Frey hairs.

RESULTS

Mice with early EAE exhibited significantly intensified and expanded FAI responses in S1 compared to controls. IHC revealed increased vesicular glutamate transporter (VGLUT1) expression and disrupted parvalbumin+ (PV+) interneuron connectivity in S1 of EAE mice. Furthermore, peri-neuronal nets (PNNs) were significantly reduced in S1. Morphological analysis of excitatory neurons in S1 revealed increased dendritic spine densities. Iba-1+ cortical microglia were significantly elevated early in the disease. Chronic PLZ treatment was found to normalize mechanical thresholds in EAE. PLZ also normalized S1 FAI responses, neuronal morphologies, and cortical microglia numbers and attenuated VGLUT1 reactivity-but did not significantly attenuate the loss of PNNs.

CONCLUSIONS

These findings implicate a pro-excitatory shift in the E-I balance of the somatosensory CNS, arising early in the pathogenesis EAE and leading to large-scale functional and structural plasticity in S1. They also suggest a novel antinociceptive effect of PLZ treatment.

More Gamma More Predictions: Gamma-Synchronization as a Key Mechanism for Efficient Integration of Classical Receptive Field Inputs with Surround Predictions

During visual stimulation, neurons in visual cortex often exhibit rhythmic and synchronous firing in the gamma-frequency (30–90 Hz) band. Whether this phenomenon plays a functional role during visual processing is not fully clear and remains heavily debated. In this article, we explore the function of gamma-synchronization in the context of predictive and efficient coding theories. These theories hold that sensory neurons utilize the statistical regularities in the natural world in order to improve the efficiency of the neural code, and to optimize the inference of the stimulus causes of the sensory data. In visual cortex, this relies on the integration of classical receptive field (CRF) data with predictions from the surround. Here we outline two main hypotheses about gamma-synchronization in visual cortex. First, we hypothesize that the precision of gamma-synchronization reflects the extent to which CRF data can be accurately predicted by the surround. Second, we hypothesize that different cortical columns synchronize to the extent that they accurately predict each other’s CRF visual input. We argue that these two hypotheses can account for a large number of empirical observations made on the stimulus dependencies of gamma-synchronization. Furthermore, we show that they are consistent with the known laminar dependencies of gamma-synchronization and the spatial profile of intercolumnar gamma-synchronization, as well as the dependence of gamma-synchronization on experience and development. Based on our two main hypotheses, we outline two additional hypotheses. First, we hypothesize that the precision of gamma-synchronization shows, in general, a negative dependence on RF size. In support, we review evidence showing that gamma-synchronization decreases in strength along the visual hierarchy, and tends to be more prominent in species with small V1 RFs. Second, we hypothesize that gamma-synchronized network dynamics facilitate the emergence of spiking output that is particularly information-rich and sparse.

Chronic recordings reveal tactile stimuli can suppress spontaneous activity of neurons in somatosensory cortex of awake and anesthetized primates

In somatosensory cortex, tactile stimulation within the neuronal receptive field (RF) typically evokes a transient excitatory response with or without postexcitatory inhibition. Here, we describe neuronal responses in which stimulation on the hand is followed by suppression of the ongoing discharge. With the use of 16-channel microelectrode arrays implanted in the hand representation of primary somatosensory cortex of New World monkeys and prosimian galagos, we recorded neuronal responses from single units and neuron clusters. In 66% of our sample, neuron activity tended to display suppression of firing when regions of skin outside of the excitatory RF were stimulated. In a small proportion of neurons, single-site indentations suppressed firing without initial increases in response to any of the tested sites on the hand. Latencies of suppressive responses to skin indentation (usually 12-34 ms) were similar to excitatory response latencies. The duration of inhibition varied across neurons. Although most observations were from anesthetized animals, we also found similar neuron response properties in one awake galago. Notably, suppression of ongoing neuronal activity did not require conditioning stimuli or multi-site stimulation. The suppressive effects were generally seen following single-site skin indentations outside of the neuron's minimal RF and typically on different digits and palm pads, which have not often been studied in this context. Overall, the characteristics of widespread suppressive or inhibitory response properties with and without initial facilitative or excitatory responses add to the growing evidence that neurons in primary somatosensory cortex provide essential processing for integrating sensory stimulation from across the hand.

Limitations of short range Mexican hat connection for driving target selection in a 2D neural field: activity suppression and deviation from input stimuli

Dynamic Neural Field models (DNF) often use a kernel of connection with short range excitation and long range inhibition. This organization has been suggested as a model for brain structures or for artificial systems involved in winner-take-all processes such as saliency localization, perceptual decision or target/action selection. A good example of such a DNF is the superior colliculus (SC), a key structure for eye movements. Recent results suggest that the superficial layers of the SC (SCs) exhibit relatively short range inhibition with a longer time constant than excitation. The aim of the present study was to further examine the properties of a DNF with such an inhibition pattern in the context of target selection. First we tested the effects of stimulus size and shape on when and where self-maintained clusters of firing neurons appeared, using three variants of the model. In each model variant, small stimuli led to rapid formation of a spiking cluster, a range of medium sizes led to the suppression of any activity on the network and hence to no target selection, while larger sizes led to delayed selection of multiple loci. Second, we tested the model with two stimuli separated by a varying distance. Again single, none, or multiple spiking clusters could occur, depending on distance and relative stimulus strength. For short distances, activity attracted toward the strongest stimulus, reminiscent of well-known behavioral data for saccadic eye movements, while for larger distances repulsion away from the second stimulus occurred. All these properties predicted by the model suggest that the SCs, or any other neural structure thought to implement a short range MH, is an imperfect winner-take-all system. Although, those properties call for systematic testing, the discussion gathers neurophysiological and behavioral data suggesting that such properties are indeed present in target selection for saccadic eye movements.

Long, intrinsic horizontal axons radiating through and beyond rat barrel cortex have spatial distributions similar to horizontal spreads of activity evoked by whisker stimulation

Stimulation of a single whisker evokes a peak of activity that is centered over the associated barrel in rat primary somatosensory cortex, and yet the evoked local field potential and the intrinsic signal optical imaging response spread symmetrically away from this barrel for over 3.5 mm to cross cytoarchitectonic borders into other "unimodal" sensory cortical areas. To determine whether long horizontal axons have the spatial distribution necessary to underlie this activity spread, we injected adeno-associated viral vectors into barrel cortex and characterized labeled axons extending from the injection site in transverse sections of flattened cortex. Combined qualitative and quantitative analyses revealed labeled axons radiating diffusely in all directions for over 3.5 mm from supragranular injection sites, with density declining over distance. The projection pattern was similar at four different cortical depths, including infragranular laminae. Infragranular vector injections produced patterns similar to the supragranular injections. Long horizontal axons were detected both using a vector with a permissive cytomegalovirus promoter to label all neuronal subtypes and using a calcium/calmodulin-dependent protein kinase II α vector to restrict labeling to excitatory cortical pyramidal neurons. Individual axons were successfully reconstructed from series of supragranular sections, indicating that they traversed gray matter only. Reconstructed axons extended from the injection site, left the barrel field, branched, and sometimes crossed into other sensory cortices identified by cytochrome oxidase staining. Thus, radiations of long horizontal axons indeed have the spatial characteristics necessary to explain horizontal activity spreads. These axons may contribute to multimodal cortical responses and various forms of cortical neural plasticity.

The stabilized supralinear network: a unifying circuit motif underlying multi-input integration in sensory cortex

Neurons in sensory cortex integrate multiple influences to parse objects and support perception. Across multiple cortical areas, integration is characterized by two neuronal response properties: (1) surround suppression--modulatory contextual stimuli suppress responses to driving stimuli; and (2) "normalization"--responses to multiple driving stimuli add sublinearly. These depend on input strength: for weak driving stimuli, contextual influences facilitate or more weakly suppress and summation becomes linear or supralinear. Understanding the circuit operations underlying integration is critical to understanding cortical function and disease. We present a simple, general theory. A wealth of integrative properties, including the above, emerge robustly from four cortical circuit properties: (1) supralinear neuronal input/output functions; (2) sufficiently strong recurrent excitation; (3) feedback inhibition; and (4) simple spatial properties of intracortical connections. Integrative properties emerge dynamically as circuit properties, with excitatory and inhibitory neurons showing similar behaviors. In new recordings in visual cortex, we confirm key model predictions.

Noradrenergic plasticity of olfactory sensory neuron inputs to the main olfactory bulb

Sensory responses are modulated by internal factors including attention, experience, and brain state. This is partly due to fluctuations in neuromodulatory input from regions such as the noradrenergic locus ceruleus (LC) in the brainstem. LC activity changes with arousal and modulates sensory processing, cognition, and memory. The main olfactory bulb (MOB) is richly targeted by LC fibers and noradrenaline profoundly influences MOB circuitry and odor-guided behavior. Noradrenaline-dependent plasticity affects the output of the MOB; however. it is unclear whether noradrenergic plasticity also affects the input to the MOB from olfactory sensory neurons (OSNs) in the glomerular layer. Noradrenergic terminals are found in the glomerular layer, but noradrenaline receptors do not seem to acutely modulate OSN terminals in vitro. We investigated whether noradrenaline induces plasticity at the glomerulus. We used wide-field optical imaging to measure changes in odor responses following electrical stimulation of LC in anesthetized mice. Surprisingly, odor-evoked intrinsic optical signals at the glomerulus were persistently weakened after LC activation. Calcium imaging selectively from OSNs confirmed that this effect was due to suppression of presynaptic input and was prevented by noradrenergic antagonists. Finally, suppression of responses to an odor did not require precise coincidence of the odor with LC activation. However, suppression was intensified by LC activation in the absence of odors. We conclude that noradrenaline release from LC has persistent effects on odor processing already at the first synapse of the main olfactory system. This mechanism could contribute to arousal-dependent memories.

Physiology and Impact of Horizontal Connections in Rat Neocortex

Cortical information processing at the cellular level has predominantly been studied in local networks, which are dominated by strong vertical connectivity between layers. However, recent studies suggest that the bulk of axons targeting pyramidal neurons most likely originate from outside this local range, emphasizing the importance of horizontal connections. We mapped a subset of these connections to L5B pyramidal neurons in rat somatosensory cortex with photostimulation, identifying intact projections up to a lateral distance of 2 mm. Our estimates of the spatial distribution of cells presynaptic to L5B pyramids support the idea that the majority is located outside the local volume. The synaptic physiology of horizontal connections does not differ markedly from that of local connections, whereas the layer and cell-type-dependent pattern of innervation does. Apart from L2/3, L6A provides a strong source of horizontal connections. Implementing our data into a spiking neuronal network model shows that more horizontal connections promote robust asynchronous ongoing activity states and reduce noise correlations in stimulus-induced activity.

Experience-dependent specialization of receptive field surround for selective coding of natural scenes

At eye opening, neurons in primary visual cortex (V1) are selective for stimulus features, but circuits continue to refine in an experience-dependent manner for some weeks thereafter. How these changes contribute to the coding of visual features embedded in complex natural scenes remains unknown. Here we show that normal visual experience after eye opening is required for V1 neurons to develop a sensitivity for the statistical structure of natural stimuli extending beyond the boundaries of their receptive fields (RFs), which leads to improvements in coding efficiency for full-field natural scenes (increased selectivity and information rate). These improvements are mediated by an experience-dependent increase in the effectiveness of natural surround stimuli to hyperpolarize the membrane potential specifically during RF-stimulus epochs triggering action potentials. We suggest that neural circuits underlying surround modulation are shaped by the statistical structure of visual input, which leads to more selective coding of features in natural scenes.

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V1 firing is more selective to natural than phase-scrambled surround stimuli

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Improved selectivity is caused by Vm hyperpolarisation prior to RF-spiking events

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Natural surround sensitivity is experience dependent, absent in immature/deprived V1

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Vision shapes circuits to improve V1 coding of natural scenes across RF and surround

Multiple components of surround modulation in primary visual cortex: multiple neural circuits with multiple functions?

The responses of neurons in primary visual cortex (V1) to stimulation of their receptive field (RF) are modulated by stimuli in the RF surround. This modulation is suppressive when the stimuli in the RF and surround are of similar orientation, but less suppressive or facilitatory when they are cross-oriented. Similarly, in human vision surround stimuli selectively suppress the perceived contrast of a central stimulus. Although the properties of surround modulation have been thoroughly characterized in many species, cortical areas and sensory modalities, its role in perception remains unknown. Here we argue that surround modulation in V1 consists of multiple components having different spatio-temporal and tuning properties, generated by different neural circuits and serving different visual functions. One component arises from LGN afferents, is fast, untuned for orientation, and spatially restricted to the surround region nearest to the RF (the near-surround); its function is to normalize V1 cell responses to local contrast. Intra-V1 horizontal connections contribute a slower, narrowly orientation-tuned component to near-surround modulation, whose function is to increase the coding efficiency of natural images in manner that leads to the extraction of object boundaries. The third component is generated by topdown feedback connections to V1, is fast, broadly orientation-tuned, and extends into the far-surround; its function is to enhance the salience of behaviorally relevant visual features. Far- and near-surround modulation, thus, act as parallel mechanisms: the former quickly detects and guides saccades/attention to salient visual scene locations, the latter segments object boundaries in the scene.

Neural representation of ambiguous visual objects in the inferior temporal cortex

Inferior temporal (IT) cortex as the final stage of the ventral visual pathway is involved in visual object recognition. In our everyday life we need to recognize visual objects that are degraded by noise. Psychophysical studies have shown that the accuracy and speed of the object recognition decreases as the amount of visual noise increases. However, the neural representation of ambiguous visual objects and the underlying neural mechanisms of such changes in the behavior are not known. Here, by recording the neuronal spiking activity of macaque monkeys’ IT we explored the relationship between stimulus ambiguity and the IT neural activity. We found smaller amplitude, later onset, earlier offset and shorter duration of the response as visual ambiguity increased. All of these modulations were gradual and correlated with the level of stimulus ambiguity. We found that while category selectivity of IT neurons decreased with noise, it was preserved for a large extent of visual ambiguity. This noise tolerance for category selectivity in IT was lost at 60% noise level. Interestingly, while the response of the IT neurons to visual stimuli at 60% noise level was significantly larger than their baseline activity and full (100%) noise, it was not category selective anymore. The latter finding shows a neural representation that signals the presence of visual stimulus without signaling what it is. In general these findings, in the context of a drift diffusion model, explain the neural mechanisms of perceptual accuracy and speed changes in the process of recognizing ambiguous objects.

Visual nonclassical receptive field effects emerge from sparse coding in a dynamical system

Extensive electrophysiology studies have shown that many V1 simple cells have nonlinear response properties to stimuli within their classical receptive field (CRF) and receive contextual influence from stimuli outside the CRF modulating the cell's response. Models seeking to explain these non-classical receptive field (nCRF) effects in terms of circuit mechanisms, input-output descriptions, or individual visual tasks provide limited insight into the functional significance of these response properties, because they do not connect the full range of nCRF effects to optimal sensory coding strategies. The (population) sparse coding hypothesis conjectures an optimal sensory coding approach where a neural population uses as few active units as possible to represent a stimulus. We demonstrate that a wide variety of nCRF effects are emergent properties of a single sparse coding model implemented in a neurally plausible network structure (requiring no parameter tuning to produce different effects). Specifically, we replicate a wide variety of nCRF electrophysiology experiments (e.g., end-stopping, surround suppression, contrast invariance of orientation tuning, cross-orientation suppression, etc.) on a dynamical system implementing sparse coding, showing that this model produces individual units that reproduce the canonical nCRF effects. Furthermore, when the population diversity of an nCRF effect has also been reported in the literature, we show that this model produces many of the same population characteristics. These results show that the sparse coding hypothesis, when coupled with a biophysically plausible implementation, can provide a unified high-level functional interpretation to many response properties that have generally been viewed through distinct mechanistic or phenomenological models.

Simple cells in the primary visual cortex (V1) demonstrate many response properties that are either nonlinear or involve response modulations (i.e., stimuli that do not cause a response in isolation alter the cell's response to other stimuli). These non-classical receptive field (nCRF) effects are generally modeled individually and their collective role in biological vision is not well understood. Previous work has shown that classical receptive field (CRF) properties of V1 cells (i.e., the spatial structure of the visual field responsive to stimuli) could be explained by the sparse coding hypothesis, which is an optimal coding model that conjectures a neural population should use the fewest number of cells simultaneously to represent each stimulus. In this paper, we have performed extensive simulated physiology experiments to show that many nCRF response properties are simply emergent effects of a dynamical system implementing this same sparse coding model. These results suggest that rather than representing disparate information processing operations themselves, these nCRF effects could be consequences of an optimal sensory coding strategy that attempts to represent each stimulus most efficiently. This interpretation provides a potentially unifying high-level functional interpretation to many response properties that have generally been viewed through distinct models.

Top-down beta rhythms support selective attention via interlaminar interaction: a model

Cortical rhythms have been thought to play crucial roles in our cognitive abilities. Rhythmic activity in the beta frequency band, around 20 Hz, has been reported in recent studies that focused on neural correlates of attention, indicating that top-down beta rhythms, generated in higher cognitive areas and delivered to earlier sensory areas, can support attentional gain modulation. To elucidate functional roles of beta rhythms and underlying mechanisms, we built a computational model of sensory cortical areas. Our simulation results show that top-down beta rhythms can activate ascending synaptic projections from L5 to L4 and L2/3, responsible for biased competition in superficial layers. In the simulation, slow-inhibitory interneurons are shown to resonate to the 20 Hz input and modulate the activity in superficial layers in an attention-related manner. The predicted critical roles of these cells in attentional gain provide a potential mechanism by which cholinergic drive can support selective attention.

Top-down signals originate from higher cognitive areas such as parietal and prefrontal cortex and propagate to earlier stages of the brain. They have been thought to be associated with selective attention, and recent physiological studies suggest that top-down signals in the beta frequency band can support selective attention. In this study, we employ a computational model to investigate potential mechanisms by which top-down beta rhythms can influence neural responses induced by presentation of stimuli. The model includes several cell types, reportedly crucial for generating cortical rhythmic activity in the gamma and beta frequency bands, and the simulation results show that top-down beta rhythms are capable of reproducing experimentally observed attentional effects on neural responses to visual stimuli. These modulatory effects of top-down beta rhythms are mainly induced via activation of ascending inhibition originating from deep layer slow inhibitory interneurons. Since the excitability of slow interneurons can be increased by cholinergic neuromodulators, these interneurons may mediate the effects of cholinergic tone on attention.

Extensive excitatory network interactions shape temporal processing of communication signals in a model sensory system

Many sensory brain regions are characterized by extensive local network interactions. However, we know relatively little about the contribution of this microcircuitry to sensory coding. Detailed analyses of neuronal microcircuitry are usually performed in vitro, whereas sensory processing is typically studied by recording from individual neurons in vivo. The electrosensory pathway of mormyrid fish provides a unique opportunity to link in vitro studies of synaptic physiology with in vivo studies of sensory processing. These fish communicate by actively varying the intervals between pulses of electricity. Within the midbrain posterior exterolateral nucleus (ELp), the temporal filtering of afferent spike trains establishes interval tuning by single neurons. We characterized pairwise neuronal connectivity among ELp neurons with dual whole cell recording in an in vitro whole brain preparation. We found a densely connected network in which single neurons influenced the responses of other neurons throughout the network. Similarly tuned neurons were more likely to share an excitatory synaptic connection than differently tuned neurons, and synaptic connections between similarly tuned neurons were stronger than connections between differently tuned neurons. We propose a general model for excitatory network interactions in which strong excitatory connections both reinforce and adjust tuning and weak excitatory connections make smaller modifications to tuning. The diversity of interval tuning observed among this population of neurons can be explained, in part, by each individual neuron receiving a different complement of local excitatory inputs.

Spatial integration in mouse primary visual cortex

Responses of many neurons in primary visual cortex (V1) are suppressed by stimuli exceeding the classical receptive field (RF), an important property that might underlie the computation of visual saliency. Traditionally, it has proven difficult to disentangle the underlying neural circuits, including feedforward, horizontal intracortical, and feedback connectivity. Since circuit-level analysis is particularly feasible in the mouse, we asked whether neural signatures of spatial integration in mouse V1 are similar to those of higher-order mammals and investigated the role of parvalbumin-expressing (PV+) inhibitory interneurons. Analogous to what is known from primates and carnivores, we demonstrate that, in awake mice, surround suppression is present in the majority of V1 neurons and is strongest in superficial cortical layers. Anesthesia with isoflurane-urethane, however, profoundly affects spatial integration: it reduces the laminar dependency, decreases overall suppression strength, and alters the temporal dynamics of responses. We show that these effects of brain state can be parsimoniously explained by assuming that anesthesia affects contrast normalization. Hence, the full impact of suppressive influences in mouse V1 cannot be studied under anesthesia with isoflurane-urethane. To assess the neural circuits of spatial integration, we targeted PV+ interneurons using optogenetics. Optogenetic depolarization of PV+ interneurons was associated with increased RF size and decreased suppression in the recorded population, similar to effects of lowering stimulus contrast, suggesting that PV+ interneurons contribute to spatial integration by affecting overall stimulus drive. We conclude that the mouse is a promising model for circuit-level mechanisms of spatial integration, which relies on the combined activity of different types of inhibitory interneurons.

Splenium of corpus callosum: patterns of interhemispheric interaction in children and adults

The splenium of the corpus callosum connects the posterior cortices with fibers varying in size from thin late-myelinating axons in the anterior part, predominantly connecting parietal and temporal areas, to thick early-myelinating fibers in the posterior part, linking primary and secondary visual areas. In the adult human brain, the function of the splenium in a given area is defined by the specialization of the area and implemented via excitation and/or suppression of the contralateral homotopic and heterotopic areas at the same or different level of visual hierarchy. These mechanisms are facilitated by interhemispheric synchronization of oscillatory activity, also supported by the splenium. In postnatal ontogenesis, structural MRI reveals a protracted formation of the splenium during the first two decades of human life. In doing so, the slow myelination of the splenium correlates with the formation of interhemispheric excitatory influences in the extrastriate areas and the EEG synchronization, while the gradual increase of inhibitory effects in the striate cortex is linked to the local inhibitory circuitry. Reshaping interactions between interhemispherically distributed networks under various perceptual contexts allows sparsification of responses to superfluous information from the visual environment, leading to a reduction of metabolic and structural redundancy in a child's brain.