A synaptic explanation of suppression in visual cortex

Responses to second-order texture modulations undergo surround suppression

First-order (contrast) surround suppression has been well characterized both psychophysically and physiologically,but relatively little is known as to whether the perception of second-order visual stimuli exhibits analogous center–surround interactions. Second-order surround suppression was characterized by requiring subjects to detect second-order modulation in stimuli presented alone or embedded in a surround.Both contrast- (CM) and orientation-modulated (OM) stimuli were used. For most subjects and both OM and CM stimuli, second-order surrounds caused thresholds to be higher, indicative of second-order suppression. For CM stimuli, suppression was orientation-specific, i.e., higher thresholds for parallel than for orthogonal surrounds. However, the evidence for orientation specificity of suppression for OM stimuli was weaker. These results suggest that normalization, leading to surround suppression, operates at multiple stages in cortical processing.

Dynamic causal modelling of precision and synaptic gain in visual perception - an EEG study

Estimating the precision or uncertainty associated with sensory signals is an important part of perception. Based on a previous computational model, we tested the hypothesis that increasing visual contrast increased the precision encoded in early visual areas by the gain or excitability of superficial pyramidal cells. This hypothesis was investigated using electroencephalography and dynamic causal modelling (DCM); a biologically constrained modelling of the cortical processes underlying EEG activity. Source localisation identified the electromagnetic sources of visually evoked responses and DCM was used to characterise the coupling among these sources. Bayesian model selection was used to select the most likely connectivity pattern and contrast-dependent changes in connectivity. As predicted, the model with the highest evidence entailed increased superficial pyramidal cell gain in higher-contrast trials. As predicted theoretically, contrast-dependent increases were reduced at higher levels of the hierarchy. These results demonstrate that increased signal-to-noise ratio in sensory signals produce (or are represented by) increased superficial pyramidal cell gain, and that synaptic parameters encoding statistical properties like sensory precision can be quantified using EEG and dynamic causal modelling.

Activity-dependent energy budget for neocortical signaling: effect of short-term synaptic plasticity on the energy expended by spiking and synaptic activity

The available estimate of the energy expended for signaling in rat neocortex is refined to examine the separate contribution of spiking and synaptic activity as a function of average neuronal firing rate. By taking into account a phenomenological model of short-term synaptic plasticity, we show that the transition from low to high cortical activity is accompanied by a substantial increase in relative energy consumed by action potentials vs. synaptic potentials. This consideration might be important for a deeper understanding of how information is represented in the cortex and which metabolic pathways are upregulated to sustain cortical activity.

Tuned normalization explains the size of attention modulations

The effect of attention on firing rates varies considerably within a single cortical area. The firing rate of some neurons is greatly modulated by attention while others are hardly affected. The reason for this variability across neurons is unknown. We found that the variability in attention modulation across neurons in area MT of macaques can be well explained by variability in the strength of tuned normalization across neurons. The presence of tuned normalization also explains a striking asymmetry in attention effects within neurons: when two stimuli are in a neuron's receptive field, directing attention to the preferred stimulus modulates firing rates more than directing attention to the nonpreferred stimulus. These findings show that much of the neuron-to-neuron variability in modulation of responses by attention depends on variability in the way the neurons process multiple stimuli, rather than differences in the influence of top-down signals related to attention.

Reciprocal inhibition of inhibition: a circuit motif for flexible categorization in stimulus selection

As a precursor to the selection of a stimulus for gaze and attention, a midbrain network categorizes stimuli into "strongest" and "others." The categorization tracks flexibly, in real time, the absolute strength of the strongest stimulus. In this study, we take a first-principles approach to computations that are essential for such categorization. We demonstrate that classical feedforward lateral inhibition cannot produce flexible categorization. However, circuits in which the strength of lateral inhibition varies with the relative strength of competing stimuli categorize successfully. One particular implementation--reciprocal inhibition of feedforward lateral inhibition--is structurally the simplest, and it outperforms others in flexibly categorizing rapidly and reliably. Strong predictions of this anatomically supported circuit model are validated by neural responses measured in the owl midbrain. The results demonstrate the extraordinary power of a remarkably simple, neurally grounded circuit motif in producing flexible categorization, a computation fundamental to attention, perception, and decision making.

Oscillatory synchronization model of attention to moving objects

The world is a dynamic environment hence it is important for the visual system to be able to deploy attention on moving objects and attentively track them. Psychophysical experiments indicate that processes of both attentional enhancement and inhibition are spatially focused on the moving objects; however the mechanisms of these processes are unknown. The studies indicate that the attentional selection of target objects is sustained via a feedforward-feedback loop in the visual cortical hierarchy and only the target objects are represented in attention-related areas. We suggest that feedback from the attention-related areas to early visual areas modulates the activity of neurons; establishes synchronization with respect to a common oscillatory signal for target items via excitatory feedback, and also establishes de-synchronization for distractor items via inhibitory feedback. A two layer computational neural network model with integrate-and-fire neurons is proposed and simulated for simple attentive tracking tasks. Consistent with previous modeling studies, we show that via temporal tagging of neural activity, distractors can be attentively suppressed from propagating to higher levels. However, simulations also suggest attentional enhancement of activity for distractors in the first layer which represents neural substrate dedicated for low level feature processing. Inspired by this enhancement mechanism, we developed a feature based object tracking algorithm with surround processing. Surround processing improved tracking performance by 57% in PETS 2001 dataset, via eliminating target features that are likely to suffer from faulty correspondence assignments.

Masking of figure-ground texture and single targets by surround inhibition: a computational spiking model

A visual stimulus can be made invisible, i.e. masked, by the presentation of a second stimulus. In the sensory cortex, neural responses to a masked stimulus are suppressed, yet how this suppression comes about is still debated. Inhibitory models explain masking by asserting that the mask exerts an inhibitory influence on the responses of a neuron evoked by the target. However, other models argue that the masking interferes with recurrent or reentrant processing. Using computer modeling, we show that surround inhibition evoked by ON and OFF responses to the mask suppresses the responses to a briefly presented stimulus in forward and backward masking paradigms. Our model results resemble several previously described psychophysical and neurophysiological findings in perceptual masking experiments and are in line with earlier theoretical descriptions of masking. We suggest that precise spatiotemporal influence of surround inhibition is relevant for visual detection.

Gain control in the response of human visual cortex to plaids

A recent intrinsic signal optical imaging study in tree shrew showed, surprisingly, that the population response of V1 to plaid patterns comprising grating components of equal contrast is predicted by the average of the responses to the individual components (MacEvoy SP, Tucker TR, Fitzpatrick D. Nat Neurosci 12: 637-645, 2009). This prompted us to compare responses to plaids and gratings in human visual cortex as a function of contrast and orientation. We found that the functional MRI (fMRI) blood oxygenation level-dependent (BOLD) responses of areas V1-V3 to a plaid comprising superposed grating components of equal contrast are significantly higher than the responses to a single component. Furthermore, the orientation response profile of a plaid is poorly predicted from a linear combination of the responses to its components. Together, these results indicate that the model of MacEvoy et al. (2009) cannot, without modification, account for the fMRI BOLD response to plaids in human visual cortex.

Decorrelation of spiking variability and improved information transfer through feedforward divisive normalization

Response variability is often positively correlated in pairs of similarly tuned neurons in the visual cortex. Many authors have considered correlated variability to prevent postsynaptic neurons from averaging across large groups of inputs to obtain reliable stimulus estimates. However, a simple average of variability ignores nonlinearities in cortical signal integration. This study shows that feedforward divisive normalization of a neuron's inputs effectively decorrelates their variability. Furthermore, we show that optimal linear estimates of a stimulus parameter that are based on normalized inputs are more accurate than those based on nonnormalized inputs, due partly to reduced correlations, and that these estimates improve with increasing population size up to several thousand neurons. This suggests that neurons may possess a simple mechanism for substantially decorrelating noise in their inputs. Further work is needed to reconcile this conclusion with past evidence that correlated noise impairs visual perception.

Local sensitivity to stimulus orientation and spatial frequency within the receptive fields of neurons in visual area 2 of macaque monkeys

We used dynamic dense noise stimuli and local spectral reverse correlation methods to reveal the local sensitivities of neurons in visual area 2 (V2) of macaque monkeys to orientation and spatial frequency within their receptive fields. This minimized the potentially confounding assumptions that are inherent in stimulus selections. The majority of neurons exhibited a relatively high degree of homogeneity for the preferred orientations and spatial frequencies in the spatial matrix of facilitatory subfields. However, about 20% of all neurons showed maximum orientation differences between neighboring subfields that were greater than 25 deg. The neurons preferring horizontal or vertical orientations showed less inhomogeneity in space than the neurons preferring oblique orientations. Over 50% of all units also exhibited suppressive profiles, and those were more heterogeneous than facilitatory profiles. The preferred orientation and spatial frequency of suppressive profiles differed substantially from those of facilitatory profiles, and the neurons with suppressive subfields had greater orientation selectivity than those without suppressive subfields. The peak suppression occurred with longer delays than the peak facilitation. These results suggest that the receptive field profiles of the majority of V2 neurons reflect the orderly convergence of V1 inputs over space, but that a subset of V2 neurons exhibit more complex response profiles having both suppressive and facilitatory subfields. These V2 neurons with heterogeneous subfield profiles could play an important role in the initial processing of complex stimulus features.

Normalization as a canonical neural computation

There is increasing evidence that the brain relies on a set of canonical neural computations, repeating them across brain regions and modalities to apply similar operations to different problems. A promising candidate for such a computation is normalization, in which the responses of neurons are divided by a common factor that typically includes the summed activity of a pool of neurons. Normalization was developed to explain responses in the primary visual cortex and is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions. Normalization may underlie operations such as the representation of odours, the modulatory effects of visual attention, the encoding of value and the integration of multisensory information. Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that it serves as a canonical neural computation.

Characterization of thalamocortical responses of regular-spiking and fast-spiking neurons of the mouse auditory cortex in vitro and in silico

We use a combination of in vitro whole cell recordings and computer simulations to characterize the cellular and synaptic properties that contribute to processing of auditory stimuli. Using a mouse thalamocortical slice preparation, we record the intrinsic membrane properties and synaptic properties of layer 3/4 regular-spiking (RS) pyramidal neurons and fast-spiking (FS) interneurons in primary auditory cortex (AI). We find that postsynaptic potentials (PSPs) evoked in FS cells are significantly larger and depress more than those evoked in RS cells after thalamic stimulation. We use these data to construct a simple computational model of the auditory thalamocortical circuit and find that the differences between FS and RS cells observed in vitro generate model behavior similar to that observed in vivo. We examine how feedforward inhibition and synaptic depression affect cortical responses to time-varying inputs that mimic sinusoidal amplitude-modulated tones. In the model, the balance of cortical inhibition and thalamic excitation evolves in a manner that depends on modulation frequency (MF) of the stimulus and determines cortical response tuning.

Unsupervised learning of generative and discriminative weights encoding elementary image components in a predictive coding model of cortical function

A method is presented for learning the reciprocal feedforward and feedback connections required by the predictive coding model of cortical function. When this method is used, feedforward and feedback connections are learned simultaneously and independently in a biologically plausible manner. The performance of the proposed algorithm is evaluated by applying it to learning the elementary components of artificial and natural images. For artificial images, the bars problem is employed, and the proposed algorithm is shown to produce state-of-the-art performance on this task. For natural images, components resembling Gabor functions are learned in the first processing stage, and neurons responsive to corners are learned in the second processing stage. The properties of these learned representations are in good agreement with neurophysiological data from V1 and V2. The proposed algorithm demonstrates for the first time that a single computational theory can explain the formation of cortical RFs and also the response properties of cortical neurons once those RFs have been learned.

Dependency reduction with divisive normalization: justification and effectiveness

Efficient coding transforms that reduce or remove statistical dependencies in natural sensory signals are important for both biology and engineering. In recent years, divisive normalization (DN) has been advocated as a simple and effective nonlinear efficient coding transform. In this work, we first elaborate on the theoretical justification for DN as an efficient coding transform. Specifically, we use the multivariate t model to represent several important statistical properties of natural sensory signals and show that DN approximates the optimal transforms that eliminate statistical dependencies in the multivariate t model. Second, we show that several forms of DN used in the literature are equivalent in their effects as efficient coding transforms. Third, we provide a quantitative evaluation of the overall dependency reduction performance of DN for both the multivariate t models and natural sensory signals. Finally, we find that statistical dependencies in the multivariate t model and natural sensory signals are increased by the DN transform with low-input dimensions. This implies that for DN to be an effective efficient coding transform, it has to pool over a sufficiently large number of inputs.

Contrast gain control in auditory cortex

The auditory system must represent sounds with a wide range of statistical properties. One important property is the spectrotemporal contrast in the acoustic environment: the variation in sound pressure in each frequency band, relative to the mean pressure. We show that neurons in ferret auditory cortex rescale their gain to partially compensate for the spectrotemporal contrast of recent stimulation. When contrast is low, neurons increase their gain, becoming more sensitive to small changes in the stimulus, although the effectiveness of contrast gain control is reduced at low mean levels. Gain is primarily determined by contrast near each neuron's preferred frequency, but there is also a contribution from contrast in more distant frequency bands. Neural responses are modulated by contrast over timescales of ∼100 ms. By using contrast gain control to expand or compress the representation of its inputs, the auditory system may be seeking an efficient coding of natural sounds.

Active data collection for efficient estimation and comparison of nonlinear neural models

The stimulus-response relationship of many sensory neurons is nonlinear, but fully quantifying this relationship by a complex nonlinear model may require too much data to be experimentally tractable. Here we present a theoretical study of a general two-stage computational method that may help to significantly reduce the number of stimuli needed to obtain an accurate mathematical description of nonlinear neural responses. Our method of active data collection first adaptively generates stimuli that are optimal for estimating the parameters of competing nonlinear models and then uses these estimates to generate stimuli online that are optimal for discriminating these models. We applied our method to simple hierarchical circuit models, including nonlinear networks built on the spatiotemporal or spectral-temporal receptive fields, and confirmed that collecting data using our two-stage adaptive algorithm was far more effective for estimating and comparing competing nonlinear sensory processing models than standard nonadaptive methods using random stimuli.

The impact of brief exposure to high contrast on the contrast response of neurons in primate lateral geniculate nucleus

Prolonged exposure to an effective stimulus generally reduces the sensitivity of neurons early in the visual pathway. Yet eye and head movements bring about frequent changes in the retinal image, and it is less clear that exposure to brief presentations will produce similar desensitization. To address this, we made extracellular recordings from single neurons in the lateral geniculate nucleus of anesthetized marmosets, a New World primate. We measured the contrast response for drifting gratings before and after 0.5-s exposure to a high-contrast drifting grating, a stationary grating, or a blank screen. Prior exposure to the drifting grating reduced the contrast sensitivity of cells in the magnocellular pathway, on average by 23%; this reduction remained strong when the adapting and test stimuli were separated by 0.4 s. Exposure to a stationary grating of the preferred spatial phase did not change the contrast response; exposure to the opposite spatial phase did. None of the brief adaptors reduced the sensitivity of parvocellular cells. We conclude that brief periods of high contrast, such as those that would be expected to occur during a normal visual fixation, are sufficient to reduce the sensitivity of magnocellular-pathway cells.

Neurometabolic coupling differs for suppression within and beyond the classical receptive field in visual cortex

Neurons in visual cortex exhibit two major types of stimulus elicited suppression. One, cross-orientation suppression, occurs within the classical receptive field (CRF) when an orthogonal grating is superposed on one at optimal orientation. The second, surround suppression, occurs when the size of an optimally oriented grating extends beyond the CRF. Previous proposals suggest that intracortical inhibition is responsible for surround suppression whereas feedforward processes may underlie cross-orientation suppression. To gain more insight concerning these types of suppression, we have included measurements of metabolic function in addition to neural responses. We made co-localized measurements of multiple unit neural activity and tissue oxygen concentrations in the striate cortex of anaesthetized cats while using visual stimuli to activate the two kinds of suppression. Results show that the amplitude of the initial negative oxygen response increases with stimulus size but neural responses decrease as size extends beyond the CRF. This shows that oxygen consumption increases with stimulus size regardless of reduced neural response. On the other hand, amplitudes of both the initial negative oxygen component and the neural responses are simultaneously attenuated by the orthogonal mask in cross-orientation suppression. These different neurometabolic response patterns are consistent with suggestions that the two types of suppressive processes arise from different neural mechanisms.

Short-term synaptic plasticity and intensity coding

Alterations in synaptic strength over short time scales, termed short-term synaptic plasticity, can gate the flow of information through neural circuits. Different information can be extracted from the same presynaptic spike train depending on the activity- and time-dependent properties of the plasticity at a given synapse. The parallel processing in the brain stem auditory pathways provides an excellent model system for investigating the functional implications of short-term plasticity in neural coding. We review recent evidence that short-term plasticity differs in different pathways with a special emphasis on the 'intensity' pathway. While short-term depression dominates the 'timing' pathway, the intensity pathway is characterized by a balance of short-term depression and facilitation that allows linear transmission of rate-coded intensity information. Target-specific regulation of presynaptic plasticity mechanisms underlies the differential expression of depression and facilitation. The potential contribution of short-term plasticity to different aspects of 'intensity'-related information processing, such as interaural level/intensity difference coding, amplitude modulation coding, and intensity-dependent gain control coding, is discussed.

A rapid form of activity-dependent recovery from short-term synaptic depression in the intensity pathway of the auditory brainstem

Short-term synaptic plasticity acts as a time- and firing rate-dependent filter that mediates the transmission of information across synapses. In the avian auditory brainstem, specific forms of plasticity are expressed at different terminals of the same auditory nerve fibers and contribute to the divergence of acoustic timing and intensity information. To identify key differences in the plasticity properties, we made patch-clamp recordings from neurons in the cochlear nucleus responsible for intensity coding, nucleus angularis, and measured the time course of the recovery of excitatory postsynaptic currents following short-term synaptic depression. These synaptic responses showed a very rapid recovery, following a bi-exponential time course with a fast time constant of approximately 40 ms and a dependence on the presynaptic activity levels, resulting in a crossing over of the recovery trajectories following high-rate versus low-rate stimulation trains. We also show that the recorded recovery in the intensity pathway differs from similar recordings in the timing pathway, specifically the cochlear nucleus magnocellularis, in two ways: (1) a fast recovery that was not due to recovery from postsynaptic receptor desensitization and (2) a recovery trajectory that was characterized by a non-monotonic bump that may be due in part to facilitation mechanisms more prevalent in the intensity pathway. We tested whether a previously proposed model of synaptic transmission based on vesicle depletion and sequential steps of vesicle replenishment could account for the recovery responses, and found it was insufficient, suggesting an activity-dependent feedback mechanism is present. We propose that the rapid recovery following depression allows improved coding of natural auditory signals that often consist of sound bursts separated by short gaps.

Power-law input-output transfer functions explain the contrast-response and tuning properties of neurons in visual cortex

We develop a unified model accounting simultaneously for the contrast invariance of the width of the orientation tuning curves (OT) and for the sigmoidal shape of the contrast response function (CRF) of neurons in the primary visual cortex (V1). We determine analytically the conditions for the structure of the afferent LGN and recurrent V1 inputs that lead to these properties for a hypercolumn composed of rate based neurons with a power-law transfer function. We investigate what are the relative contributions of single neuron and network properties in shaping the OT and the CRF. We test these results with numerical simulations of a network of conductance-based model (CBM) neurons and we demonstrate that they are valid and more robust here than in the rate model. The results indicate that because of the acceleration in the transfer function, described here by a power-law, the orientation tuning curves of V1 neurons are more tuned, and their CRF is steeper than those of their inputs. Last, we show that it is possible to account for the diversity in the measured CRFs by introducing heterogeneities either in single neuron properties or in the input to the neurons. We show how correlations among the parameters that characterize the CRF depend on these sources of heterogeneities. Comparison with experimental data suggests that both sources contribute nearly equally to the diversity of CRF shapes observed in V1 neurons.

Both the response and membrane potential of neurons in the primary visual cortex (V1) are selective to the orientation of elongated stimuli. The widths of the tuning curves, which characterize this selectivity, hardly depend on stimulus contrast whereas their amplitude does. The contrast dependence of this amplitude, the contrast response function (CRF), has a sigmoidal shape. Saturation of the spike response is substantially lower than the neurons' maximal firing rate. These well established facts constrain the possible mechanisms for orientation selectivity in V1. Furthermore, the single neuron CRFs in V1 display a broad diversity in their shape. This adds other constraints. Many theoretical works have tried to elaborate mechanisms of orientation selectivity that are compatible with the contrast invariant tuning widths. However, these mechanisms are usually incompatible with sigmoidal CRFs. We propose a mechanism which accounts simultaneously for contrast invariant tuning width for both rate and voltage response and for the shape and diversity of the CRFs. This mechanism relies on the interplay between power-law frequency-current transfer functions of single neurons, as measured in vivo in cortex, and on the recurrent interactions in the cortical circuit.

A single functional model accounts for the distinct properties of suppression in cortical area V1

Cross-orientation suppression and surround suppression have been extensively studied in primary visual cortex (V1). These two forms of suppression have some distinct properties which has led to the suggestion that they are generated by different underlying mechanisms. Furthermore, it has been suggested that mechanisms other than intracortical inhibition may be central to both forms of suppression. A simple computational model (PC/BC), in which intracortical inhibition is fundamental, is shown to simulate the distinct properties of cross-orientation and surround suppression. The same model has previously been shown to account for a large range of V1 response properties including orientation-tuning, spatial and temporal frequency tuning, facilitation and inhibition by flankers and textured surrounds as well as a range of other experimental results on cross-orientation suppression and surround suppression. The current results thus provide additional support for the PC/BC model of V1 and for the proposal that the diverse range of response properties observed in V1 neurons have a single computational explanation. Furthermore, these results demonstrate that current neurophysiological evidence is insufficient to discount intracortical inhibition as a central mechanism underlying both forms of suppression.

Sensory adaptation and short term plasticity as Bayesian correction for a changing brain

Neurons in the sensory system exhibit changes in excitability that unfold over many time scales. These fluctuations produce noise and could potentially lead to perceptual errors. However, to prevent such errors, postsynaptic neurons and synapses can adapt and counteract changes in the excitability of presynaptic neurons. Here we ask how neurons could optimally adapt to minimize the influence of changing presynaptic neural properties on their outputs. The resulting model, based on Bayesian inference, explains a range of physiological results from experiments which have measured the overall properties and detailed time-course of sensory tuning curve adaptation in the early visual cortex. We show how several experimentally measured short term plasticity phenomena can be understood as near-optimal solutions to this adaptation problem. This framework provides a link between high level computational problems, the properties of cortical neurons, and synaptic physiology.

Neuronal arithmetic

The vast computational power of the brain has traditionally been viewed as arising from the complex connectivity of neural networks, in which an individual neuron acts as a simple linear summation and thresholding device. However, recent studies show that individual neurons utilize a wealth of nonlinear mechanisms to transform synaptic input into output firing. These mechanisms can arise from synaptic plasticity, synaptic noise, and somatic and dendritic conductances. This tool kit of nonlinear mechanisms confers considerable computational power on both morphologically simple and more complex neurons, enabling them to perform a range of arithmetic operations on signals encoded ina variety of different ways.

Divisive normalization in olfactory population codes

In many regions of the visual system, the activity of a neuron is normalized by the activity of other neurons in the same region. Here we show that a similar normalization occurs during olfactory processing in the Drosophila antennal lobe. We exploit the orderly anatomy of this circuit to independently manipulate feedforward and lateral input to second-order projection neurons (PNs). Lateral inhibition increases the level of feedforward input needed to drive PNs to saturation, and this normalization scales with the total activity of the olfactory receptor neuron (ORN) population. Increasing total ORN activity also makes PN responses more transient. Strikingly, a model with just two variables (feedforward and total ORN activity) accurately predicts PN odor responses. Finally, we show that discrimination by a linear decoder is facilitated by two complementary transformations: the saturating transformation intrinsic to each processing channel boosts weak signals, while normalization helps equalize responses to different stimuli.

Feed-forward segmentation of figure-ground and assignment of border-ownership

Figure-ground is the segmentation of visual information into objects and their surrounding backgrounds. Two main processes herein are boundary assignment and surface segregation, which rely on the integration of global scene information. Recurrent processing either by intrinsic horizontal connections that connect surrounding neurons or by feedback projections from higher visual areas provide such information, and are considered to be the neural substrate for figure-ground segmentation. On the contrary, a role of feedforward projections in figure-ground segmentation is unknown. To have a better understanding of a role of feedforward connections in figure-ground organization, we constructed a feedforward spiking model using a biologically plausible neuron model. By means of surround inhibition our simple 3-layered model performs figure-ground segmentation and one-sided border-ownership coding. We propose that the visual system uses feed forward suppression for figure-ground segmentation and border-ownership assignment.

Contrast gain control and cortical TrkB signaling shape visual acuity

During development and aging and in amblyopia, visual acuity is far below the limitations set by the retina. Expression of brain-derived neurotrophic factor (BDNF) in the visual cortex is reduced in these situations. We asked whether neurotrophic tyrosine kinase receptor, type 2 (TrkB) regulates cortical visual acuity in adult mice. We found that genetically interfering with TrkB/BDNF signaling in pyramidal cells in the mature visual cortex reduced synaptic strength and resulted in a loss of neural responses to high spatial-frequency stimuli. Responses to low spatial-frequency stimuli were unaffected. This selective loss was not accompanied by a change in receptive field sizes or plasticity, but apparent contrast was reduced. Our results indicate that a dependence on spatial frequency in the Heeger normalization model explains this selective effect of contrast reduction on high-resolution vision and suggest that it involves contrast gain control operating in the visual cortex.

Response properties of neurons in primary somatosensory cortex of owl monkeys reflect widespread spatiotemporal integration

Receptive fields of neurons in somatosensory area 3b of monkeys are typically described as restricted to part of a single digit or palm pad. However, such neurons are likely involved in integrating stimulus information from across the hand. To evaluate this possibility, we recorded from area 3b neurons in anesthetized owl monkeys with 100-electrode arrays, stimulating two hand locations with electromechanical probes simultaneously or asynchronously. Response magnitudes and latencies of single- and multiunits varied with stimulus conditions, and multiunit responses were similar to single-unit responses. The mean peak firing rate for single neurons stimulated within the preferred location was estimated to be ∼26 spike/s. Simultaneous stimulation with a second probe outside the preferred location slightly decreased peak firing rates to ∼22 spike/s. When the nonpreferred stimulus preceded the preferred stimulus by 10-500 ms, peak firing rates were suppressed with greatest suppression when the nonpreferred stimulus preceded by 30 ms (∼7 spike/s). The mean latency for single neurons stimulated within the preferred location was ∼23 ms, and latency was little affected by simultaneous paired stimulation. However, when the nonpreferred stimulus preceded the preferred stimulus by 10 ms, latencies shortened to ∼16 ms. Response suppression occurred even when stimuli were separated by long distances (nonadjacent digits) or long times (500 ms onset asynchrony). Facilitation, though rare, occurred most often when the stimulus onsets were within 0-30 ms of each other. These findings quantify spatiotemporal interactions and support the hypothesis that area 3b is involved in widespread stimulus integration.

Representation of concurrent stimuli by population activity in visual cortex

How do neuronal populations represent concurrent stimuli? We measured population responses in cat primary visual cortex (V1) using electrode arrays. Population responses to two superimposed gratings were weighted sums of the individual grating responses. The weights depended strongly on the relative contrasts of the gratings. When the contrasts were similar, the population performed an approximately equal summation. When the contrasts differed markedly, however, the population performed approximately a winner-take-all competition. Stimuli that were intermediate to these extremes elicited intermediate responses. This entire range of behaviors was explained by a single model of contrast normalization. Normalization captured both the spike responses and the local field potential responses; it even predicted visually evoked currents source-localized to V1 in human subjects. Normalization has profound effects on V1 population responses and is likely to shape the interpretation of these responses by higher cortical areas.

Adaptive integration in the visual cortex by depressing recurrent cortical circuits

Neurons in the visual cortex receive a large amount of input from recurrent connections, yet the functional role of these connections remains unclear. Here we explore networks with strong recurrence in a computational model and show that short-term depression of the synapses in the recurrent loops implements an adaptive filter. This allows the visual system to respond reliably to deteriorated stimuli yet quickly to high-quality stimuli. For low-contrast stimuli, the model predicts long response latencies, whereas latencies are short for high-contrast stimuli. This is consistent with physiological data showing that in higher visual areas, latencies can increase more than 100 ms at low contrast compared to high contrast. Moreover, when presented with briefly flashed stimuli, the model predicts stereotypical responses that outlast the stimulus, again consistent with physiological findings. The adaptive properties of the model suggest that the abundant recurrent connections found in visual cortex serve to adapt the network's time constant in accordance with the stimulus and normalizes neuronal signals such that processing is as fast as possible while maintaining reliability.

Adaptive gain modulation in V1 explains contextual modifications during bisection learning

The neuronal processing of visual stimuli in primary visual cortex (V1) can be modified by perceptual training. Training in bisection discrimination, for instance, changes the contextual interactions in V1 elicited by parallel lines. Before training, two parallel lines inhibit their individual V1-responses. After bisection training, inhibition turns into non-symmetric excitation while performing the bisection task. Yet, the receptive field of the V1 neurons evaluated by a single line does not change during task performance. We present a model of recurrent processing in V1 where the neuronal gain can be modulated by a global attentional signal. Perceptual learning mainly consists in strengthening this attentional signal, leading to a more effective gain modulation. The model reproduces both the psychophysical results on bisection learning and the modified contextual interactions observed in V1 during task performance. It makes several predictions, for instance that imagery training should improve the performance, or that a slight stimulus wiggling can strongly affect the representation in V1 while performing the task. We conclude that strengthening a top-down induced gain increase can explain perceptual learning, and that this top-down signal can modify lateral interactions within V1, without significantly changing the classical receptive field of V1 neurons.

Contrast induced changes in response latency depend on stimulus specificity

Neurones in visual cortex show increasing response latency with decreasing stimulus contrast. Neurophysiological recordings from neurones in inferior temporal cortex (IT) and the superior temporal sulcus (STS), show that the increment in response latency with decreasing stimulus contrast is considerably greater in higher visual areas than that seen in primary visual cortex. This suggests that the majority of the latency change is not retinal or V1 in origin, instead each cortical processing area adds latency at low contrast. I show that, as in earlier visual areas, response latency is more strongly dependent on stimulus contrast than stimulus identity. There is large variation in the extent to which response latency increases with decreasing stimulus contrast. I show that this between cell variability is, at least in part, related to the stimulus specificity of the neurones: the increase in response latency as stimulus contrast decreases is greater for neurones that respond to few stimuli compared to neurones that respond to many stimuli.

Effects of aging on paired-pulse behavior of rat somatosensory cortical neurons

Aging affects all levels of neural processing including changes of intracortical inhibition and cortical excitability. The paired-pulse stimulation protocol, the application of 2 stimuli in close succession, is used to investigate cortical excitability. The paired-pulse behavior is characterized by the fact that the second response is significantly suppressed at short interstimulus intervals (ISIs) but approaches the first response with increasing ISIs. However, there are controversial reports about the influence of age on paired-pulse behavior. We therefore used pairs of tactile stimuli (ISIs from tens to hundreds of milliseconds) to record extracellular responses of somatosensory cortical neurons of young and aged rats. Paired-pulse behavior was quantified as the ratio of the amplitude of the second response divided by the first. For all ISIs, we found significantly higher ratios in the old animals indicating reduced paired-pulse suppression (PPS). Evaluation of the single response components revealed a significant reduction of the response to the first stimulus for old animals but no age-dependent decrement to the second. Changes in PPS are usually mediated by modulating the second response characteristics. Thus, our data demonstrate reduced PPS due to an overall reduction of the first response as a form of modified PPS developing at old age.

Aging affects the neural representation of speed in Macaque area MT

Human perception of speed declines with age. Much of the decline is probably mediated by changes in the middle temporal (MT) area, an extrastriate area whose neural activity is linked to the perception of speed. In the present study, we used random-dot patterns to study the effects of aging on speed-tuning curves in cortical area MT of macaque visual cortex. Our results provide evidence for a significant degradation of speed selectivity in MT. Cells in old animals preferred lower speeds than did those in young animals. Response modulation and discriminative capacity for speed in old monkeys were also significantly weaker than those in young ones. Concurrently, MT cells in old monkeys showed increased baseline responses, peak responses and response variability, and these changes were accompanied by decreased signal-to-noise ratios. We also found that speed discrimination thresholds in old animals were higher than in young ones. The foregoing neural changes may mediate the declines in visual motion perception that occur during senescence.

A precise form of divisive suppression supports population coding in the primary visual cortex

The responses of neurons in the primary visual cortex (V1) to an optimally-oriented grating are suppressed when a non-optimal grating is superimposed. Although cross-orientation suppression is thought to reflect mechanisms that maintain a distributed code for orientation, the impact of superimposed gratings upon V1 populations is unknown. Using intrinsic signal optical imaging, we find that patterns of tree shrew V1 activity evoked by superimposed equal-contrast gratings were predicted by the mean of patterns evoked by individual component gratings. This prediction held across contrasts, for summed sinusoidal gratings or non-summing square-wave gratings, and was reflected in single-unit extracellular recordings. Intracellular recordings revealed consistent levels of suppression throughout the evolution of subthreshold responses. These results indicate that divisive suppression powerfully governs population responses to multiple orientations. Moreover, the specific form of suppression we observe appears to support independent population codes for stimulus orientation and strength, and calls for a reassessment of mechanisms that underlie cross-orientation suppression.

The normalization model of attention

Attention has been found to have a wide variety of effects on the responses of neurons in visual cortex. We describe a model of attention that exhibits each of these different forms of attentional modulation, depending on the stimulus conditions and the spread (or selectivity) of the attention field in the model. The model helps reconcile proposals that have been taken to represent alternative theories of attention. We argue that the variety and complexity of the results reported in the literature emerge from the variety of empirical protocols that were used, such that the results observed in any one experiment depended on the stimulus conditions and the subject's attentional strategy, a notion that we define precisely in terms of the attention field in the model, but that has not typically been completely under experimental control.

Time course of cross-orientation suppression in the early visual cortex

Responses of a visual neuron to optimally oriented stimuli can be suppressed by a superposition of another grating with a different orientation. This effect is known as cross-orientation suppression. However, it is still not clear whether the effect is intracortical in origin or a reflection of subcortical processes. To address this issue, we measured spatiotemporal responses to a plaid pattern, a superposition of two gratings, as well as to individual component gratings (optimal and mask) using a subspace reverse-correlation method. Suppression for the plaid was evaluated by comparing the response to that for the optimal grating. For component stimuli, excitatory and negative responses were defined as responses more positive and negative, respectively, than that to a blank stimulus. The suppressive effect for plaids was observed in the vast majority of neurons. However, only approximately 30% of neurons showed the negative response to mask-only gratings. The magnitudes of negative responses to mask-only stimuli were correlated with the degree of suppression for plaid stimuli. Comparing the latencies, we found that the suppression for the plaids starts at about the same time or slightly later than the response onset for the optimal grating and reaches its maximum at about the same time as the peak latency for the mask-only grating. Based on these results, we propose that in addition to the suppressive effect originating at the subcortical stage, delayed suppressive signals derived from the intracortical networks act on the neuron to generate cross-orientation suppression.

Contextual modulation of V1 receptive fields depends on their spatial symmetry

The apparent receptive field characteristics of sensory neurons depend on the statistics of the stimulus ensemble--a nonlinear phenomenon often called contextual modulation. Since visual cortical receptive fields determined from simple stimuli typically do not predict responses to complex stimuli, understanding contextual modulation is crucial to understanding responses to natural scenes. To analyze contextual modulation, we examined how apparent receptive fields differ for two stimulus ensembles that are matched in first- and second-order statistics, but differ in their feature content: one ensemble is enriched in elongated contours. To identify systematic trends across the neural population, we used a multidimensional scaling method, the Procrustes transformation. We found that contextual modulation of receptive field components increases with their spatial extent. More surprisingly, we also found that odd-symmetric components change systematically, but even-symmetric components do not. This symmetry dependence suggests that contextual modulation is driven by oriented On/Off dyads, i.e., modulation of the strength of intracortically-generated signals.

Dynamics of tuning in the Fourier domain

Neurons in primary visual cortex (area V1) are jointly tuned to the orientation and spatial frequency of sinusoidal stimuli (the Fourier domain). The role that suppressive mechanisms play in shaping the tuning and dynamics of cortical responses remains the subject of debate. Here we used subspace reverse correlation to study the relationship between suppression by nonoptimal stimuli, the spectral-temporal separability of the responses, and their persistence in time. Two clear relationships emerged from our data. First, cells with inseparable responses were often accompanied by suppression to nonpreferred stimuli, while separable responses showed mostly enhancement by their preferred stimuli. Second, inseparable responses were characterized by a longer persistence in time compared with those with separable dynamics. A parametric model that assumes the additive combination of separable enhancement and suppression signals, with suppression constrained to be low-pass in spatial frequency and untuned for orientation, explained the data well. These new findings, in addition to an established correlation between selectivity and suppression for nonoptimal stimuli, clarify how the dynamics and selectivity of cortical responses are shaped by suppressive signals and how their interplay generates the large diversity of responses observed in primary visual cortex.

Postnatal development of onset transient responses in macaque V1 AND V2 neurons

Vision of newborn infants is limited by immaturities in their visual brain. In adult primates, the transient onset discharges of visual cortical neurons are thought to be intimately involved with capturing the rapid succession of brief images in visual scenes. Here we sought to determine the responsiveness and quality of transient responses in individual neurons of the primary visual cortex (V1) and visual area 2 (V2) of infant monkeys. We show that the transient component of neuronal firing to 640-ms stationary gratings was as robust and as reliable as in adults only 2 wk after birth, whereas the sustained component was more sluggish in infants than in adults. Thus the cortical circuitry supporting onset transient responses is functionally mature near birth, and our findings predict that neonates, known for their "impoverished vision," are capable of initiating relatively mature fixating eye movements and of performing in detection of simple objects far better than traditionally thought.

Retinal and cortical nonlinearities combine to produce masking in V1 responses to plaids

The visual response of a cell in the primary visual cortex (V1) to a drifting grating stimulus at the cell's preferred orientation decreases when a second, perpendicular, grating is superimposed. This effect is called masking. To understand the nonlinear masking effect, we model the response of Macaque V1 simple cells in layer 4Calpha to input from magnocellular Lateral Geniculate Nucleus (LGN) cells. The cortical model network is a coarse-grained reduction of an integrate-and-fire network with excitation from LGN input and inhibition from other cortical neurons. The input is modeled as a sum of LGN cell responses. Each LGN cell is modeled as the convolution of a spatio-temporal filter with the visual stimulus, normalized by a retinal contrast gain control, and followed by rectification representing the LGN spike threshold. In our model, the experimentally observed masking arises at the level of LGN input to the cortex. The cortical network effectively induces a dynamic threshold that forces the test grating to have high contrast before it can overcome the masking provided by the perpendicular grating. The subcortical nonlinearities and the cortical network together account for the masking effect.

Inhibition, spike threshold, and stimulus selectivity in primary visual cortex

Ever since Hubel and Wiesel described orientation selectivity in the visual cortex, the question of how precise selectivity emerges has been marked by considerable debate. There are essentially two views of how selectivity arises. Feed-forward models rely entirely on the organization of thalamocortical inputs. Feedback models rely on lateral inhibition to refine selectivity relative to a weak bias provided by thalamocortical inputs. The debate is driven by two divergent lines of evidence. On the one hand, many response properties appear to require lateral inhibition, including precise orientation and direction selectivity and crossorientation suppression. On the other hand, intracellular recordings have failed to find consistent evidence for lateral inhibition. Here we demonstrate a resolution to this paradox. Feed-forward models incorporating the intrinsic nonlinear properties of cortical neurons and feed-forward circuits (i.e., spike threshold, contrast saturation, and spike-rate rectification) can account for properties that have previously appeared to require lateral inhibition.

Level dependence of contextual modulation in auditory cortex

Responses of cortical neurons to sensory stimuli within their receptive fields can be profoundly altered by the stimulus context. In visual and somatosensory cortex, contextual interactions have been shown to change sign from facilitation to suppression depending on stimulus strength. Contextual modulation of high-contrast stimuli tends to be suppressive, but for low-contrast stimuli tends to be facilitative. This trade-off may optimize contextual integration by cortical cells and has been suggested to be a general feature of cortical processing, but it remains unknown whether a similar phenomenon occurs in auditory cortex. Here we used whole cell and single-unit recordings to investigate how contextual interactions in auditory cortical neurons depend on the relative intensity of masker and probe stimuli in a two-tone stimulus paradigm. We tested the hypothesis that relatively low-level probes should show facilitation, whereas relatively high-level probes should show suppression. We found that contextual interactions were primarily suppressive across all probe levels, and that relatively low-level probes were subject to stronger suppression than high-level probes. These results were virtually identical for spiking and subthreshold responses. This suggests that, unlike visual cortical neurons, auditory cortical neurons show maximal suppression rather than facilitation for relatively weak stimuli.

Thalamocortical transformations of periodic stimuli: the effect of stimulus velocity and synaptic short-term depression in the vibrissa-barrel system

Recent works on the response of barrel neurons to periodic deflections of the rat vibrissae have shown that the stimulus velocity is encoded in the corti cal spike rate (Pinto et al., Journal of Neurophysiology, 83(3), 1158-1166, 2000; Arabzadeh et al., Journal of Neuroscience, 23(27), 9146-9154, 2003). Other studies have reported that repetitive pulse stimulation produces band-pass filtering of the barrel response rate centered around 7-10 Hz (Garabedian et al., Journal of Neurophysiology, 90, 1379-1391, 2003) whereas sinusoidal stimulation gives an increasing rate up to 350 Hz (Arabzadeh et al., Journal of Neuroscience, 23(27), 9146-9154, 2003). To explore the mechanisms underlying these results we propose a simple computational model consisting in an ensemble of cells in the ventro-posterior medial thalamic nucleus (VPm) encoding the stimulus velocity in the temporal profile of their response, connected to a single barrel cell through synapses showing short-term depression. With sinusoidal stimulation, encoding the velocity in VPm facilitates the response as the stimulus frequency increases and it causes the velocity to be encoded in the cortical rate in the frequency range 20-100 Hz. Synaptic depression does not suppress the response with sinusoidal stimulation but it produces a band-pass behavior using repetitive pulses. We also found that the passive properties of the cell membrane eventually suppress the response to sinusoidal stimulation at high frequencies, something not observed experimentally. We argue that network effects not included here must be important in sustaining the response at those frequencies.

Temporal properties of surround suppression in cat primary visual cortex

The responses of neurons in primary visual cortex (V1) are suppressed by stimuli presented in the region surrounding the receptive field. There is debate as to whether this surround suppression is due to intracortical inhibition, is inherited from lateral geniculate nucleus (LGN), or is due to a combination of these factors. The mechanisms involved in surround suppression may differ from those involved in suppression within the receptive field, which is called cross-orientation suppression. To compare surround suppression to cross-orientation suppression, and to help elucidate its underlying mechanisms, we studied its temporal properties in anesthetized and paralyzed cats. We first measured the temporal resolution of suppression. While cat LGN neurons respond vigorously to drift rates up to 30 Hz, most cat V1 neurons stop responding above 10-15 Hz. If suppression originated in cortical responses, therefore, it should disappear above such drift rates. In a majority of cells, surround suppression decreased substantially when surround drift rate was above approximately 15 Hz, but some neurons demonstrated suppression with surround drift rates as high as 21 Hz. We then measured the susceptibility of suppression to contrast adaptation. Contrast adaptation reduces responses of cortical neurons much more than those of LGN neurons. If suppression originated in cortical responses, therefore, it should be reduced by adaptation. Consistent with this hypothesis, we found that prolonged exposure to the surround stimulus decreased the strength of surround suppression. The results of both experiments differ markedly from those previously obtained in a study of cross-orientation suppression, whose temporal properties were found to resemble those of LGN neurons. Our results provide further evidence that these two forms of suppression are due to different mechanisms. Surround suppression can be explained by a mixture of thalamic and cortical influences. It could also arise entirely from intracortical inhibition, but only if inhibitory neurons respond to somewhat higher drift rates than most cortical cells.

The emergence of contrast-invariant orientation tuning in simple cells of cat visual cortex

Simple cells in primary visual cortex exhibit contrast-invariant orientation tuning, in seeming contradiction to feed-forward models that rely on lateral geniculate nucleus (LGN) input alone. Contrast invariance has therefore been thought to depend on the presence of intracortical lateral inhibition. In vivo intracellular recordings instead suggest that contrast invariance can be explained by three properties of the excitatory pathway. (1) Depolarizations evoked by orthogonal stimuli are determined by the amount of excitation a cell receives from the LGN, relative to the excitation it receives from other cortical cells. (2) Depolarizations evoked by preferred stimuli saturate at lower contrasts than the spike output of LGN relay cells. (3) Visual stimuli evoke contrast-dependent changes in trial-to-trial variability, which lead to contrast-dependent changes in the relationship between membrane potential and spike rate. Thus, high-contrast, orthogonally oriented stimuli that evoke significant depolarizations evoke few spikes. Together these mechanisms, without lateral inhibition, can account for contrast-invariant stimulus selectivity.