Complex dynamics of V1 population responses explained by a simple gain-control model

Disparate nonlinear neural dynamics measured with different techniques in macaque and human V1

Diverse neuro-imaging techniques measure different aspects of neural responses with distinct spatial and temporal resolutions. Relating measured neural responses across different methods has been challenging. Here, we take a step towards overcoming this challenge, by comparing the nonlinearity of neural dynamics measured across methods. We used widefield voltage-sensitive dye imaging (VSDI) to measure neural population responses in macaque V1 to visual stimuli with a wide range of temporal waveforms. We found that stimulus-evoked VSDI responses are surprisingly near-additive in time. These results are qualitatively different from the strong sub-additive dynamics previously measured using fMRI and electrocorticography (ECoG) in human visual cortex with a similar set of stimuli. To test whether this discrepancy is specific to VSDI-a signal dominated by subthreshold neural activity, we repeated our measurements using widefield imaging of a genetically encoded calcium indicator (GcaMP6f)-a signal dominated by spiking activity, and found that GCaMP signals in macaque V1 are also near-additive. Therefore, the discrepancies in the extent of sub-additivity between the macaque and the human measurements are unlikely due to differences between sub- and supra-threshold neural responses. Finally, we use a simple yet flexible delayed normalization model to capture these different dynamics across measurements (with different model parameters). The model can potentially generalize to a broader set of stimuli, which aligns with previous suggestion that dynamic gain-control is a canonical computation contributing to neural processing in the brain.

A dynamic neural resource model bridges sensory and working memory

Probing memory of a complex visual image within a few hundred milliseconds after its disappearance reveals significantly greater fidelity of recall than if the probe is delayed by as little as a second. Classically interpreted, the former taps into a detailed but rapidly decaying visual sensory or 'iconic' memory (IM), while the latter relies on capacity-limited but comparatively stable visual working memory (VWM). While iconic decay and VWM capacity have been extensively studied independently, currently no single framework quantitatively accounts for the dynamics of memory fidelity over these time scales. Here, we extend a stationary neural population model of VWM with a temporal dimension, incorporating rapid sensory-driven accumulation of activity encoding each visual feature in memory, and a slower accumulation of internal error that causes memorized features to randomly drift over time. Instead of facilitating read-out from an independent sensory store, an early cue benefits recall by lifting the effective limit on VWM signal strength imposed when multiple items compete for representation, allowing memory for the cued item to be supplemented with information from the decaying sensory trace. Empirical measurements of human recall dynamics validate these predictions while excluding alternative model architectures. A key conclusion is that differences in capacity classically thought to distinguish IM and VWM are in fact contingent upon a single resource-limited WM store.

Neural correlates of perceptual similarity masking in primate V1

Visual detection is a fundamental natural task. Detection becomes more challenging as the similarity between the target and the background in which it is embedded increases, a phenomenon termed 'similarity masking'. To test the hypothesis that V1 contributes to similarity masking, we used voltage sensitive dye imaging (VSDI) to measure V1 population responses while macaque monkeys performed a detection task under varying levels of target-background similarity. Paradoxically, we find that during an initial transient phase, V1 responses to the target are enhanced, rather than suppressed, by target-background similarity. This effect reverses in the second phase of the response, so that in this phase V1 signals are positively correlated with the behavioral effect of similarity. Finally, we show that a simple model with delayed divisive normalization can qualitatively account for our findings. Overall, our results support the hypothesis that a nonlinear gain control mechanism in V1 contributes to perceptual similarity masking.

Induction of excitatory brain state governs plastic functional changes in visual cortical topology

Adult visual plasticity underlying local remodeling of the cortical circuitry in vivo appears to be associated with a spatiotemporal pattern of strongly increased spontaneous and evoked activity of populations of cells. Here we review and discuss pioneering work by us and others about principles of plasticity in the adult visual cortex, starting with our study which showed that a confined lesion in the cat retina causes increased excitability in the affected region in the primary visual cortex accompanied by fine-tuned restructuring of neuronal function. The underlying remodeling processes was further visualized with voltage-sensitive dye (VSD) imaging that allowed a direct tracking of retinal lesion-induced reorganization across horizontal cortical circuitries. Nowadays, application of noninvasive stimulation methods pursues the idea further of increased cortical excitability along with decreased inhibition as key factors for the induction of adult cortical plasticity. We used high-frequency transcranial magnetic stimulation (TMS), for the first time in combination with VSD optical imaging, and provided evidence that TMS-amplified excitability across large pools of neurons forms the basis for noninvasively targeting reorganization of orientation maps in the visual cortex. Our review has been compiled on the basis of these four own studies, which we discuss in the context of historical developments in the field of visual cortical plasticity and the current state of the literature. Overall, we suggest markers of LTP-like cortical changes at mesoscopic population level as a main driving force for the induction of visual plasticity in the adult. Elevations in excitability that predispose towards cortical plasticity are most likely a common property of all cortical modalities. Thus, interventions that increase cortical excitability are a promising starting point to drive perceptual and potentially motor learning in therapeutic applications.

Perceptual Cycles Travel Across Retinotopic Space

Visual perception waxes and wanes periodically over time at low frequencies (theta: 4-7 Hz; alpha: 8-13 Hz), creating "perceptual cycles." These perceptual cycles can be induced when stimulating the brain with a flickering visual stimulus at the theta or alpha frequency. Here, we took advantage of the well-known organization of the visual system into retinotopic maps (topographic correspondence between visual and cortical spaces) to assess the spatial organization of induced perceptual cycles. Specifically, we tested the hypothesis that they can propagate across the retinotopic space. A disk oscillating in luminance (inducer) at 4, 6, 8, or 10 Hz was presented in the periphery of the visual field to induce perceptual cycles at specific frequencies. EEG recordings verified that the brain responded at the corresponding inducer frequencies and their first harmonics. Perceptual cycles were assessed with a concurrent detection task-target stimuli were displayed at threshold contrast (50% detection) at random times during the inducer. Behavioral results confirmed that perceptual performance was modulated periodically by the inducer at each frequency. We additionally manipulated the distance between the target and the inducer (three possible positions) and showed that the optimal phase, that is, moment of highest target detection, shifted across target distance to the inducer, specifically when its flicker frequency was in the alpha range (8 and 10 Hz). These results demonstrate that induced alpha perceptual cycles travel across the retinotopic space in humans at a propagation speed of 0.3-0.5 m/sec, consistent with the speed of unmyelinated horizontal connections in the visual cortex.

Cascaded normalizations for spatial integration in the primary visual cortex of primates

Spatial integration of visual information is an important function in the brain. However, neural computation for spatial integration in the visual cortex remains unclear. In this study, we recorded laminar responses in V1 of awake monkeys driven by visual stimuli with grating patches and annuli of different sizes. We find three important response properties related to spatial integration that are significantly different between input and output layers: neurons in output layers have stronger surround suppression, smaller receptive field (RF), and higher sensitivity to grating annuli partially covering their RFs. These interlaminar differences can be explained by a descriptive model composed of two global divisions (normalization) and a local subtraction. Our results suggest suppressions with cascaded normalizations (CNs) are essential for spatial integration and laminar processing in the visual cortex. Interestingly, the features of spatial integration in convolutional neural networks, especially in lower layers, are different from our findings in V1.

Visual cortex responds to sound onset and offset during passive listening

Sounds enhance our ability to detect, localize, and respond to co-occurring visual targets. Research suggests that sounds improve visual processing by resetting the phase of ongoing oscillations in visual cortex. However, it remains unclear what information is relayed from the auditory system to visual areas and if sounds modulate visual activity even in the absence of visual stimuli (e.g., during passive listening). Using intracranial electroencephalography (iEEG) in humans, we examined the sensitivity of visual cortex to three forms of auditory information during a passive listening task: auditory onset responses, auditory offset responses, and rhythmic entrainment to sounds. Because some auditory neurons respond to both sound onsets and offsets, visual timing and duration processing may benefit from each. Additionally, if auditory entrainment information is relayed to visual cortex, it could support the processing of complex stimulus dynamics that are aligned between auditory and visual stimuli. Results demonstrate that in visual cortex, amplitude-modulated sounds elicited transient onset and offset responses in multiple areas, but no entrainment to sound modulation frequencies. These findings suggest that activity in visual cortex (as measured with iEEG in response to auditory stimuli) may not be affected by temporally fine-grained auditory stimulus dynamics during passive listening (though it remains possible that this signal may be observable with simultaneous auditory-visual stimuli). Moreover, auditory responses were maximal in low-level visual cortex, potentially implicating a direct pathway for rapid interactions between auditory and visual cortices. This mechanism may facilitate perception by time-locking visual computations to environmental events marked by auditory discontinuities.

A dynamic normalization model of temporal attention

Vision is dynamic, handling a continuously changing stream of input, yet most models of visual attention are static. Here, we develop a dynamic normalization model of visual temporal attention and constrain it with new psychophysical human data. We manipulated temporal attention-the prioritization of visual information at specific points in time-to a sequence of two stimuli separated by a variable time interval. Voluntary temporal attention improved perceptual sensitivity only over a specific interval range. To explain these data, we modelled voluntary and involuntary attentional gain dynamics. Voluntary gain enhancement took the form of a limited resource over short time intervals, which recovered over time. Taken together, our theoretical and experimental results formalize and generalize the idea of limited attentional resources across space at a single moment to limited resources across time at a single location.

Nearby contours abolish the binocular advantage

That binocular viewing confers an advantage over monocular viewing for detecting isolated low luminance or low contrast objects, has been known for well over a century; however, the processes involved in combining the images from the two eyes are still not fully understood. Importantly, in natural vision, objects are rarely isolated but appear in context. It is well known that nearby contours can either facilitate or suppress detection, depending on their distance from the target and the global configuration. Here we report that at close distances collinear (but not orthogonal) flanking contours suppress detection more under binocular compared to monocular viewing, thus completely abolishing the binocular advantage, both at threshold and suprathreshold levels. In contrast, more distant flankers facilitate both monocular and binocular detection, preserving a binocular advantage up to about four times the detection threshold. Our results for monocular and binocular viewing, for threshold contrast discrimination without nearby flankers, can be explained by a gain control model with uncertainty and internal multiplicative noise adding additional constraints on detection. However, in context with nearby flankers, both contrast detection threshold and suprathreshold contrast appearance matching require the addition of both target-to-target and flank-to-target interactions occurring before the site of binocular combination. To test an alternative model, in which the interactions occur after the site of binocular combination, we performed a dichoptic contrast matching experiment, with the target presented to one eye, and the flanks to the other eye. The two models make very different predictions for abutting flanks under dichoptic conditions. Interactions after the combination site predict that the perceived contrast of the flanked target will be strongly suppressed, while interactions before the site predict the perceived contrast will be more or less veridical. The data are consistent with the latter model, strongly suggesting that the interactions take place before the site of binocular combination.

A recurrent circuit implements normalization, simulating the dynamics of V1 activity

The normalization model has been applied to explain neural activity in diverse neural systems including primary visual cortex (V1). The model's defining characteristic is that the response of each neuron is divided by a factor that includes a weighted sum of activity of a pool of neurons. Despite the success of the normalization model, there are three unresolved issues. 1) Experimental evidence supports the hypothesis that normalization in V1 operates via recurrent amplification, i.e., amplifying weak inputs more than strong inputs. It is unknown how normalization arises from recurrent amplification. 2) Experiments have demonstrated that normalization is weighted such that each weight specifies how one neuron contributes to another's normalization pool. It is unknown how weighted normalization arises from a recurrent circuit. 3) Neural activity in V1 exhibits complex dynamics, including gamma oscillations, linked to normalization. It is unknown how these dynamics emerge from normalization. Here, a family of recurrent circuit models is reported, each of which comprises coupled neural integrators to implement normalization via recurrent amplification with arbitrary normalization weights, some of which can recapitulate key experimental observations of the dynamics of neural activity in V1.

Dynamic Patterns of Spontaneous Ongoing Activity in the Visual Cortex of Anesthetized and Awake Monkeys are Different

Ongoing internal cortical activity plays a major role in perception and behavior both in animals and humans. Previously we have shown that spontaneous patterns resembling orientation-maps appear over large cortical areas in the primary visual-cortex of anesthetized cats. However, it remains unknown 1) whether spontaneous-activity in the primate also displays similar patterns and 2) whether a significant difference exists between cortical ongoing-activity in the anesthetized and awake primate. We explored these questions by combining voltage-sensitive-dye imaging with multiunit and local-field-potential recordings. Spontaneously emerging orientation and ocular-dominance maps, spanning up to 6 × 6 mm2, were readily observed in anesthetized but not in awake monkeys. Nevertheless, spontaneous correlated-activity involving orientation-domains was observed in awake monkeys. Under both anesthetized and awake conditions, spontaneous correlated-activity coincided with traveling waves. We found that spontaneous activity resembling orientation-maps in awake animals spans smaller cortical areas in each instance, but over time it appears across all of V1. Furthermore, in the awake monkey, our results suggest that the synaptic strength had been completely reorganized including connections between dissimilar elements of the functional architecture. These findings lend support to the notion that ongoing-activity has many more fast switching representations playing an important role in cortical function and behavior.

Interaction between steady-state visually evoked potentials at nearby flicker frequencies

Steady-state visually evoked potential (SSVEP) studies routinely employ simultaneous presentation of two temporally modulated stimuli, with SSVEP amplitude modulations serving to index top-down cognitive processes. However, the nature of SSVEP amplitude modulations as a function of competing temporal frequency (TF) has not been systematically studied, especially in relation to the normalization framework which has been extensively used to explain visual responses to multiple stimuli. We recorded spikes and local field potential (LFP) from the primary visual cortex (V1) as well as EEG from two awake macaque monkeys while they passively fixated plaid stimuli with components counterphasing at different TFs. We observed asymmetric SSVEP response suppression by competing TFs (greater suppression for lower TFs), which further depended on the relative orientations of plaid components. A tuned normalization model, adapted to SSVEP responses, provided a good account of the suppression. Our results provide new insights into processing of temporally modulated visual stimuli.

Predicting neuronal dynamics with a delayed gain control model

Visual neurons respond to static images with specific dynamics: neuronal responses sum sub-additively over time, reduce in amplitude with repeated or sustained stimuli (neuronal adaptation), and are slower at low stimulus contrast. Here, we propose a simple model that predicts these seemingly disparate response patterns observed in a diverse set of measurements-intracranial electrodes in patients, fMRI, and macaque single unit spiking. The model takes a time-varying contrast time course of a stimulus as input, and produces predicted neuronal dynamics as output. Model computation consists of linear filtering, expansive exponentiation, and a divisive gain control. The gain control signal relates to but is slower than the linear signal, and this delay is critical in giving rise to predictions matched to the observed dynamics. Our model is simpler than previously proposed related models, and fitting the model to intracranial EEG data uncovers two regularities across human visual field maps: estimated linear filters (temporal receptive fields) systematically differ across and within visual field maps, and later areas exhibit more rapid and substantial gain control. The model is further generalizable to account for dynamics of contrast-dependent spike rates in macaque V1, and amplitudes of fMRI BOLD in human V1.

Nonlinear Lateral Interactions in V1 Population Responses Explained by a Contrast Gain Control Model

How do cortical responses to local image elements combine to form a spatial pattern of population activity in primate V1? Here, we used voltage-sensitive dye imaging, which measures summed membrane potential activity, to examine the rules that govern lateral interactions between the representations of two small local-oriented elements in macaque (Macaca mulatta) V1. We find strong subadditive and mostly orientation-independent interactions for nearby elements [2-4 mm interelement cortical distance (IED)] that gradually become linear at larger separations (>6 mm IED). These results are consistent with a population gain control model describing nonlinear V1 population responses to single oriented elements. However, because of the membrane potential-to-spiking accelerating nonlinearity, the model predicts supra-additive lateral interactions of spiking responses for intermediate separations at a range of locations between the two elements, consistent with some prior facilitatory effects observed in electrophysiology and psychophysics. Overall, our results suggest that population-level lateral interactions in V1 are primarily explained by a simple orientation-independent contrast gain control mechanism.SIGNIFICANCE STATEMENT Interactions between representations of simple visual elements such as oriented edges in primary visual cortex (V1) are thought to contribute to our ability to easily integrate contours and segment surfaces, but the mechanisms that govern these interactions are primarily unknown. Our study provides novel evidence that lateral interactions at the population level are governed by a simple contrast gain-control mechanism, and we show how this divisive gain-control mechanism can give rise to apparently facilitatory spiking responses.

Classification of Spatiotemporal Neural Activity Patterns in Brain Imaging Data

Various patterns of neural activity are observed in dynamic cortical imaging data. Such patterns may reflect how neurons communicate using the underlying circuitry to perform appropriate functions; thus it is crucial to investigate the spatiotemporal characteristics of the observed neural activity patterns. In general, however, neural activities are highly nonlinear and complex, so it is a demanding job to analyze them quantitatively or to classify the patterns of observed activities in various types of imaging data. Here, we present our implementation of a novel method that successfully addresses the above issues for precise comparison and classification of neural activity patterns. Based on two-dimensional representations of the geometric structure and temporal evolution of activity patterns, our method successfully classified a number of computer-generated sample patterns created from combinations of various spatial and temporal patterns. In addition, we validated our method with voltage-sensitive dye imaging data of Alzheimer's disease (AD) model mice. Our analysis algorithm successfully distinguished the activity data of AD mice from that of wild type with significantly higher performance than previously suggested methods. Our result provides a pragmatic solution for precise analysis of spatiotemporal patterns of neural imaging data.

Cortical travelling waves: mechanisms and computational principles

Multichannel recording technologies have revealed travelling waves of neural activity in multiple sensory, motor and cognitive systems. These waves can be spontaneously generated by recurrent circuits or evoked by external stimuli. They travel along brain networks at multiple scales, transiently modulating spiking and excitability as they pass. Here, we review recent experimental findings that have found evidence for travelling waves at single-area (mesoscopic) and whole-brain (macroscopic) scales. We place these findings in the context of the current theoretical understanding of wave generation and propagation in recurrent networks. During the large low-frequency rhythms of sleep or the relatively desynchronized state of the awake cortex, travelling waves may serve a variety of functions, from long-term memory consolidation to processing of dynamic visual stimuli. We explore new avenues for experimental and computational understanding of the role of spatiotemporal activity patterns in the cortex.

Visual Motion Discrimination by Propagating Patterns in Primate Cerebral Cortex

Visual stimuli can evoke waves of neural activity that propagate across the surface of visual cortical areas. The relevance of these waves for visual processing is unknown. Here, we measured the phase and amplitude of local field potentials (LFPs) in electrode array recordings from the motion-processing medial temporal (MT) area of anesthetized male marmosets. Animals viewed grating or dot-field stimuli drifting in different directions. We found that, on individual trials, the direction of LFP wave propagation is sensitive to the direction of stimulus motion. Propagating LFP patterns are also detectable in trial-averaged activity, but the trial-averaged patterns exhibit different dynamics and behaviors from those in single trials and are similar across motion directions. We show that this difference arises because stimulus-sensitive propagating patterns are present in the phase of single-trial oscillations, whereas the trial-averaged signal is dominated by additive amplitude effects. Our results demonstrate that propagating LFP patterns can represent sensory inputs at timescales relevant to visually guided behaviors and raise the possibility that propagating activity patterns serve neural information processing in area MT and other cortical areas.SIGNIFICANCE STATEMENT Propagating wave patterns are widely observed in the cortex, but their functional relevance remains unknown. We show here that visual stimuli generate propagating wave patterns in local field potentials (LFPs) in a movement-sensitive area of the primate cortex and that the propagation direction of these patterns is sensitive to stimulus motion direction. We also show that averaging LFP signals across multiple stimulus presentations (trial averaging) yields propagating patterns that capture different dynamic properties of the LFP response and show negligible direction sensitivity. Our results demonstrate that sensory stimuli can modulate propagating wave patterns reliably in the cortex. The relevant dynamics are normally masked by trial averaging, which is a conventional step in LFP signal processing.

Noisy Spiking in Visual Area V2 of Amblyopic Monkeys

Interocular decorrelation of input signals in developing visual cortex can cause impaired binocular vision and amblyopia. Although increased intrinsic noise is thought to be responsible for a range of perceptual deficits in amblyopic humans, the neural basis for the elevated perceptual noise in amblyopic primates is not known. Here, we tested the idea that perceptual noise is linked to the neuronal spiking noise (variability) resulting from developmental alterations in cortical circuitry. To assess spiking noise, we analyzed the contrast-dependent dynamics of spike counts and spiking irregularity by calculating the square of the coefficient of variation in interspike intervals (CV²) and the trial-to-trial fluctuations in spiking, or mean matched Fano factor (m-FF) in visual area V2 of monkeys reared with chronic monocular defocus. In amblyopic neurons, the contrast versus response functions and the spike count dynamics exhibited significant deviations from comparable data for normal monkeys. The CV² was pronounced in amblyopic neurons for high-contrast stimuli and the m-FF was abnormally high in amblyopic neurons for low-contrast gratings. The spike count, CV², and m-FF of spontaneous activity were also elevated in amblyopic neurons. These contrast-dependent spiking irregularities were correlated with the level of binocular suppression in these V2 neurons and with the severity of perceptual loss for individual monkeys. Our results suggest that the developmental alterations in normalization mechanisms resulting from early binocular suppression can explain much of these contrast-dependent spiking abnormalities in V2 neurons and the perceptual performance of our amblyopic monkeys.

SIGNIFICANCE STATEMENT

Amblyopia is a common developmental vision disorder in humans. Despite the extensive animal studies on how amblyopia emerges, we know surprisingly little about the neural basis of amblyopia in humans and nonhuman primates. Although the vision of amblyopic humans is often described as being noisy by perceptual and modeling studies, the exact nature or origin of this elevated perceptual noise is not known. We show that elevated and noisy spontaneous activity and contrast-dependent noisy spiking (spiking irregularity and trial-to-trial fluctuations in spiking) in neurons of visual area V2 could limit the visual performance of amblyopic primates. Moreover, we discovered that the noisy spiking is linked to a high level of binocular suppression in visual cortex during development.

Catching the voltage gradient-asymmetric boost of cortical spread generates motion signals across visual cortex: a brief review with special thanks to Amiram Grinvald

Wide-field voltage imaging is unique in its capability to capture snapshots of activity-across the full gradient of average changes in membrane potentials from subthreshold to suprathreshold levels-of hundreds of thousands of superficial cortical neurons that are simultaneously active. Here, I highlight two examples where voltage-sensitive dye imaging (VSDI) was exploited to track gradual space-time changes of activity within milliseconds across several millimeters of cortex at submillimeter resolution: the line-motion condition, measured in Amiram Grinvald's Laboratory more than 10 years ago and-coming full circle running VSDI in my laboratory-another motion-inducing condition, in which two neighboring stimuli counterchange luminance simultaneously. In both examples, cortical spread is asymmetrically boosted, creating suprathreshold activity drawn out over primary visual cortex. These rapidly propagating waves may integrate brain signals that encode motion independent of direction-selective circuits.

Mammalian cortical voltage imaging using genetically encoded voltage indicators: a review honoring professor Amiram Grinvald

The pioneering work of Amiram Grinvald established voltage-sensitive dye imaging (VSDI) in the mammalian cortex in the 1980s and inspired decades of cortical voltage imaging and the associated technological developments. The recent conception and development of genetically encoded voltage indicators (GEVIs) overcome many of the limitations of classical VSDI, and open experimental approaches that provide accruing support for orchestrated neuronal circuit dynamics of spatially distributed neuronal circuit underlying behaviors. We will review recent achievements using GEVIs to optically monitor the cortical activity in mammalian brains in vivo and provide a perspective for potential future directions.

Improving voltage-sensitive dye imaging: with a little help from computational approaches

Voltage-sensitive dye imaging (VSDI) is a key neurophysiological recording tool because it reaches brain scales that remain inaccessible to other techniques. The development of this technique from in vitro to the behaving nonhuman primate has only been made possible thanks to the long-lasting, visionary work of Amiram Grinvald. This work has opened new scientific perspectives to the great benefit to the neuroscience community. However, this unprecedented technique remains largely under-utilized, and many future possibilities await for VSDI to reveal new functional operations. One reason why this tool has not been used extensively is the inherent complexity of the signal. For instance, the signal reflects mainly the subthreshold neuronal population response and is not linked to spiking activity in a straightforward manner. Second, VSDI gives access to intracortical recurrent dynamics that are intrinsically complex and therefore nontrivial to process. Computational approaches are thus necessary to promote our understanding and optimal use of this powerful technique. Here, we review such approaches, from computational models to dissect the mechanisms and origin of the recorded signal, to advanced signal processing methods to unravel new neuronal interactions at mesoscopic scale. Only a stronger development of interdisciplinary approaches can bridge micro- to macroscales.

Sensory noise predicts divisive reshaping of receptive fields

In order to respond reliably to specific features of their environment, sensory neurons need to integrate multiple incoming noisy signals. Crucially, they also need to compete for the interpretation of those signals with other neurons representing similar features. The form that this competition should take depends critically on the noise corrupting these signals. In this study we show that for the type of noise commonly observed in sensory systems, whose variance scales with the mean signal, sensory neurons should selectively divide their input signals by their predictions, suppressing ambiguous cues while amplifying others. Any change in the stimulus context alters which inputs are suppressed, leading to a deep dynamic reshaping of neural receptive fields going far beyond simple surround suppression. Paradoxically, these highly variable receptive fields go alongside and are in fact required for an invariant representation of external sensory features. In addition to offering a normative account of context-dependent changes in sensory responses, perceptual inference in the presence of signal-dependent noise accounts for ubiquitous features of sensory neurons such as divisive normalization, gain control and contrast dependent temporal dynamics.

Effects of Stimulus Size and Contrast on the Initial Primary Visual Cortical Response in Humans

Decades of intracranial electrophysiological investigation into the primary visual cortex (V1) have produced many fundamental insights into the computations carried out in low-level visual circuits of the brain. Some of the most important work has been simply concerned with the precise measurement of neural response variations as a function of elementary stimulus attributes such as contrast and size. Surprisingly, such simple but fundamental characterization of V1 responses has not been carried out in human electrophysiology. Here we report such a detailed characterization for the initial "C1" component of the scalp-recorded visual evoked potential (VEP). The C1 is known to be dominantly generated by initial afferent activation in V1, but is difficult to record reliably due to interindividual anatomical variability. We used pattern-pulse multifocal VEP mapping to identify a stimulus position that activates the left lower calcarine bank in each individual, and afterwards measured robust negative C1s over posterior midline scalp to gratings presented sequentially at that location. We found clear and systematic increases in C1 peak amplitude and decreases in peak latency with increasing size as well as with increasing contrast. With a sample of 15 subjects and ~180 trials per condition, reliable C1 amplitudes of -0.46 µV were evoked at as low a contrast as 3.13% and as large as -4.82 µV at 100% contrast, using stimuli of 3.33° diameter. A practical implication is that by placing sufficiently-sized stimuli to target favorable calcarine cortical loci, robust V1 responses can be measured at contrasts close to perceptual thresholds, which could greatly facilitate principled studies of early visual perception and attention.

Temporal Asymmetry in Dark-Bright Processing Initiates Propagating Activity across Primary Visual Cortex

Differences between visual pathways representing darks and lights have been shown to affect spatial resolution and detection timing. Both psychophysical and physiological studies suggest an underlying retinal origin with amplification in primary visual cortex (V1). Here we show that temporal asymmetries in the processing of darks and lights create motion in terms of propagating activity across V1. Exploiting the high spatiotemporal resolution of voltage-sensitive dye imaging, we captured population responses to abrupt local changes of luminance in cat V1. For stimulation we used two neighboring small squares presented on either bright or dark backgrounds. When a single square changed from dark to bright or vice versa, we found coherent population activity emerging at the respective retinal input locations. However, faster rising and decay times were obtained for the bright to dark than the dark to bright changes. When the two squares changed luminance simultaneously in opposite polarities, we detected a propagating wave front of activity that originated at the cortical location representing the darkened square and rapidly expanded toward the region representing the brightened location. Thus, simultaneous input led to sequential activation across cortical retinotopy. Importantly, this effect was independent of the squares' contrast with the background. We suggest imbalance in dark-bright processing as a driving force in the generation of wave-like activity. Such propagation may convey motion signals and influence perception of shape whenever abrupt shifts in visual objects or gaze cause counterchange of luminance at high-contrast borders.

SIGNIFICANCE STATEMENT

An elementary process in vision is the detection of darks and lights through the retina via ON and OFF channels. Psychophysical and physiological studies suggest that differences between these channels affect spatial resolution and detection thresholds. Here we show that temporal asymmetries in the processing of darks and lights create motion signals across visual cortex. Using two neighboring squares, which simultaneously counterchanged luminance, we discovered propagating activity that was strictly drawn out from cortical regions representing the darkened location. Thus, a synchronous stimulus event translated into sequential wave-like brain activation. Such propagation may convey motion signals accessible in higher brain areas, whenever abrupt shifts in visual objects or gaze cause counterchange of luminance at high-contrast borders.

Relating normalization to neuronal populations across cortical areas

Normalization, which divisively scales neuronal responses to multiple stimuli, is thought to underlie many sensory, motor, and cognitive processes. In every study where it has been investigated, neurons measured in the same brain area under identical conditions exhibit a range of normalization, ranging from suppression by nonpreferred stimuli (strong normalization) to additive responses to combinations of stimuli (no normalization). Normalization has been hypothesized to arise from interactions between neuronal populations, either in the same or different brain areas, but current models of normalization are not mechanistic and focus on trial-averaged responses. To gain insight into the mechanisms underlying normalization, we examined interactions between neurons that exhibit different degrees of normalization. We recorded from multiple neurons in three cortical areas while rhesus monkeys viewed superimposed drifting gratings. We found that neurons showing strong normalization shared less trial-to-trial variability with other neurons in the same cortical area and more variability with neurons in other cortical areas than did units with weak normalization. Furthermore, the cortical organization of normalization was not random: neurons recorded on nearby electrodes tended to exhibit similar amounts of normalization. Together, our results suggest that normalization reflects a neuron's role in its local network and that modulatory factors like normalization share the topographic organization typical of sensory tuning properties.

Effects of GABAA kinetics on cortical population activity: computational studies and physiological confirmations

Voltage-sensitive dye (VSD) imaging produces an unprecedented real-time and high-resolution mesoscopic signal to measure the cortical population activity. We have previously shown that the neuronal compartments contributions to the signal are dynamic and stimulus-dependent (Chemla S, Chavane F. Neuroimage 53: 420-438, 2010). Moreover, the VSD signal can also be strongly affected by the network state, such as in anesthetized vs. awake preparations. Here, we investigated the impact of the network state, through GABAA receptors modulation, on the VSD signal using a computational approach. We therefore systematically measured the effect of the GABAA-mediated inhibitory postsynaptic potentials (IPSPs) decay time constant (τG) on our modeled VSD response to an input stimulus of increasing strength. Our simulations suggest that τG strongly modulates the dynamics of the VSD signal, affecting the amplitude, input response function, and the transient balance of excitation and inhibition. We confirmed these predictions experimentally on awake and anesthetized monkeys, comparing VSD responses to drifting gratings stimuli of various contrasts. Lastly, one in vitro study has suggested that GABAA receptors may also be directly affected by the VSDs themselves (Mennerick S, Chisari M, Shu H, Taylor A, Vasek M, Eisenman L, Zorumski C. J Neurosci 30: 2871-2879, 2010). Our modeling approach suggests that the type of modulation described in this study would actually have a negligible influence on the population response. This study highlights that functional results acquired with different techniques and network states must be compared with caution. Biophysical models are proposed here as an adequate tool to delineate the domain of VSD data interpretation.

In Vivo Voltage-Sensitive Dye Study of Lateral Spreading of Cortical Activity in Mouse Primary Visual Cortex Induced by a Current Impulse

In the mammalian primary visual cortex (V1), lateral spreading of excitatory potentials is believed to be involved in spatial integrative functions, but the underlying cortical mechanism is not well understood. Visually-evoked population-level responses have been shown to propagate beyond the V1 initial activation site in mouse, similar to higher mammals. Visually-evoked responses are, however, affected by neuronal circuits prior to V1 (retina, LGN), making the separate analysis of V1 difficult. Intracortical stimulation eliminates these initial processing steps. We used in vivo RH1691 voltage-sensitive dye (VSD) imaging and intracortical microstimulation in adult C57BL/6 mice to elucidate the spatiotemporal properties of population-level signal spreading in V1 cortical circuits. The evoked response was qualitatively similar to that measured in single-cell electrophysiological experiments in rodents: a fast transient fluorescence peak followed by a fast and a slow decrease or hyperpolarization, similar to EPSP and fast and slow IPSPs in single cells. The early cortical response expanded at speeds commensurate with long horizontal projections (at 5% of the peak maximum, 0.08–0.15 m/s) however, the bulk of the VSD signal propagated slowly (at half-peak maximum, 0.05–0.08 m/s) suggesting an important role of regenerative multisynaptic transmission through short horizontal connections in V1 spatial integrative functions. We also found a tendency for a widespread and fast cortical response suppression in V1, which was eliminated by GABA_A-antagonists gabazine and bicuculline methiodide. Our results help understand the neuronal circuitry involved in lateral spreading in V1.

Mechanisms for Rapid Adaptive Control of Motion Processing in Macaque Visual Cortex

A key feature of neural networks is their ability to rapidly adjust their function, including signal gain and temporal dynamics, in response to changes in sensory inputs. These adjustments are thought to be important for optimizing the sensitivity of the system, yet their mechanisms remain poorly understood. We studied adaptive changes in temporal integration in direction-selective cells in macaque primary visual cortex, where specific hypotheses have been proposed to account for rapid adaptation. By independently stimulating direction-specific channels, we found that the control of temporal integration of motion at one direction was independent of motion signals driven at the orthogonal direction. We also found that individual neurons can simultaneously support two different profiles of temporal integration for motion in orthogonal directions. These findings rule out a broad range of adaptive mechanisms as being key to the control of temporal integration, including untuned normalization and nonlinearities of spike generation and somatic adaptation in the recorded direction-selective cells. Such mechanisms are too broadly tuned, or occur too far downstream, to explain the channel-specific and multiplexed temporal integration that we observe in single neurons. Instead, we are compelled to conclude that parallel processing pathways are involved, and we demonstrate one such circuit using a computer model. This solution allows processing in different direction/orientation channels to be separately optimized and is sensible given that, under typical motion conditions (e.g., translation or looming), speed on the retina is a function of the orientation of image components.

SIGNIFICANCE STATEMENT

Many neurons in visual cortex are understood in terms of their spatial and temporal receptive fields. It is now known that the spatiotemporal integration underlying visual responses is not fixed but depends on the visual input. For example, neurons that respond selectively to motion direction integrate signals over a shorter time window when visual motion is fast and a longer window when motion is slow. We investigated the mechanisms underlying this useful adaptation by recording from neurons as they responded to stimuli moving in two different directions at different speeds. Computer simulations of our results enabled us to rule out several candidate theories in favor of a model that integrates across multiple parallel channels that operate at different time scales.

Primary visual cortex represents the difference between past and present

The visual system is confronted with rapidly changing stimuli in everyday life. It is not well understood how information in such a stream of input is updated within the brain. We performed voltage-sensitive dye imaging across the primary visual cortex (V1) to capture responses to sequences of natural scene contours. We presented vertically and horizontally filtered natural images, and their superpositions, at 10 or 33 Hz. At low frequency, the encoding was found to represent not the currently presented images, but differences in orientation between consecutive images. This was in sharp contrast to more rapid sequences for which we found an ongoing representation of current input, consistent with earlier studies. Our finding that for slower image sequences, V1 does no longer report actual features but represents their relative difference in time counteracts the view that the first cortical processing stage must always transfer complete information. Instead, we show its capacities for change detection with a new emphasis on the role of automatic computation evolving in the 100-ms range, inevitably affecting information transmission further downstream.

Auditory properties in the parabelt regions of the superior temporal gyrus in the awake macaque monkey: an initial survey

The superior temporal gyrus (STG) is on the inferior-lateral brain surface near the external ear. In macaques, 2/3 of the STG is occupied by an auditory cortical region, the "parabelt," which is part of a network of inferior temporal areas subserving communication and social cognition as well as object recognition and other functions. However, due to its location beneath the squamous temporal bone and temporalis muscle, the STG, like other inferior temporal regions, has been a challenging target for physiological studies in awake-behaving macaques. We designed a new procedure for implanting recording chambers to provide direct access to the STG, allowing us to evaluate neuronal properties and their topography across the full extent of the STG in awake-behaving macaques. Initial surveys of the STG have yielded several new findings. Unexpectedly, STG sites in monkeys that were listening passively responded to tones with magnitudes comparable to those of responses to 1/3 octave band-pass noise. Mapping results showed longer response latencies in more rostral sites and possible tonotopic patterns parallel to core and belt areas, suggesting the reversal of gradients between caudal and rostral parabelt areas. These results will help further exploration of parabelt areas.

Multidimensional gain control in image representation and processing in vision

A generic model of automatic gain control (AGC) is proposed as a general framework for multidimensional automatic contrast sensitivity adjustment in vision, as well as in other sensory modalities. We show that a generic feedback AGC mechanism, incorporating a nonlinear synaptic interaction into the feedback loop of a neural network, can enhance and emphasize important image attributes, such as curvature, size, depth, convexity/concavity and more, similar to its role in the adjustment of photoreceptors and retinal network sensitivity over the extremely high dynamic range of environmental light intensities, while enhancing the contrast. We further propose that visual illusions, well established by psychophysical experiments, are a by-product of the multidimensional AGC. This hypothesis is supported by simulations implementing AGC, which reproduce psychophysical data regarding size contrast effects known as the Ebbinghaus illusion, and depth contrast effects. Processing of curvature by an AGC network illustrates that it is an important mechanism of image structure pre-emphasis, which thereby enhances saliency. It is argued that the generic neural network of AGC constitutes a universal, parsimonious, unified mechanism of neurobiological automatic contrast sensitivity control. This mechanism/model can account for a wide range of physiological and psychophysical phenomena, such as visual illusions and contour completion, in cases of occlusion, by a basic neural network. Likewise, and as important, biologically motivated AGC provides attractive new means for the development of intelligent computer vision systems.

Imaging the awake visual cortex with a genetically encoded voltage indicator

Genetically encoded voltage indicators (GEVIs) promise to reveal the membrane potential of genetically targeted neuronal populations through noninvasive, chronic imaging of large portions of cortical space. Here we test a promising GEVI in mouse cortex during wakefulness, a challenging condition due to large hemodynamic activity, and we introduce a straightforward projection method to separate a signal dominated by membrane voltage from a signal dominated by hemodynamic activity. We expressed VSFP-Butterfly 1.2 plasmid in layer 2/3 pyramidal cells of visual cortex through electroporation in utero. We then used wide-field imaging with two cameras to measure both fluorophores of the indicator in response to visual stimuli. By taking weighted sums and differences of the two measurements, we obtained clear separation of hemodynamic and voltage signals. The hemodynamic signal showed strong heartbeat oscillations, superimposed on slow dynamics similar to blood oxygen level-dependent (BOLD) or "intrinsic" signals. The voltage signal had fast dynamics similar to neural responses measured electrically, and showed an orderly retinotopic mapping. We compared this voltage signal with calcium signals imaged in transgenic mice that express a calcium indicator (GCaMP3) throughout cortex. The voltage signal from VSFP had similar signal-to-noise ratios as the calcium signal, it was more immune to vascular artifacts, and it integrated over larger regions of visual space, which was consistent with its reporting mostly subthreshold activity rather than the spiking activity revealed by calcium signals. These results demonstrate that GEVIs provide a powerful tool to study the dynamics of neural populations at mesoscopic spatial scales in the awake cortex.

A sensorimotor role for traveling waves in primate visual cortex

Traveling waves of neural activity are frequently observed to occur in concert with the presentation of a sensory stimulus or the execution of a movement. Although such waves have been studied for decades, little is known about their function. Here we show that traveling waves in the primate extrastriate visual cortex provide a means of integrating sensory and motor signals. Specifically, we describe a traveling wave of local field potential (LFP) activity in cortical area V4 of macaque monkeys that is triggered by the execution of saccadic eye movements. These waves sweep across the V4 retinotopic map, following a consistent path from the foveal to the peripheral representations of space; their amplitudes correlate with the direction and size of each saccade. Moreover, these waves are associated with a reorganization of the postsaccadic neuronal firing patterns, which follow a similar retinotopic progression, potentially prioritizing the processing of behaviorally relevant stimuli.

Long-range traveling waves of activity triggered by local dichoptic stimulation in V1 of behaving monkeys

Traveling waves of cortical activity, in which local stimulation triggers lateral spread of activity to distal locations, have been hypothesized to play an important role in cortical function. However, there is conflicting physiological evidence for the existence of spreading traveling waves of neural activity triggered locally. Dichoptic stimulation, in which the two eyes view dissimilar monocular patterns, can lead to dynamic wave-like fluctuations in visual perception and therefore, provides a promising means for identifying and studying cortical traveling waves. Here, we used voltage-sensitive dye imaging to test for the existence of traveling waves of activity in the primary visual cortex of awake, fixating monkeys viewing dichoptic stimuli. We find clear traveling waves that are initiated by brief, localized contrast increments in one of the monocular patterns and then, propagate at speeds of ∼ 30 mm/s. These results demonstrate that under an appropriate visual context, circuitry in visual cortex in alert animals is capable of supporting long-range traveling waves triggered by local stimulation.

Voltage-sensitive dye imaging of transcranial magnetic stimulation-induced intracortical dynamics

Transcranial magnetic stimulation (TMS) is widely used in clinical interventions and basic neuroscience. Additionally, it has become a powerful tool to drive plastic changes in neuronal networks. However, highly resolved recordings of the immediate TMS effects have remained scarce, because existing recording techniques are limited in spatial or temporal resolution or are interfered with by the strong TMS-induced electric field. To circumvent these constraints, we performed optical imaging with voltage-sensitive dye (VSD) in an animal experimental setting using anaesthetized cats. The dye signals reflect gradual changes in the cells' membrane potential across several square millimeters of cortical tissue, thus enabling direct visualization of TMS-induced neuronal population dynamics. After application of a single TMS pulse across visual cortex, brief focal activation was immediately followed by synchronous suppression of a large pool of neurons. With consecutive magnetic pulses (10 Hz), widespread activity within this "basin of suppression" increased stepwise to suprathreshold levels and spontaneous activity was enhanced. Visual stimulation after repetitive TMS revealed long-term potentiation of evoked activity. Furthermore, loss of the "deceleration-acceleration" notch during the rising phase of the response, as a signature of fast intracortical inhibition detectable with VSD imaging, indicated weakened inhibition as an important driving force of increasing cortical excitability. In summary, our data show that high-frequency TMS changes the balance between excitation and inhibition in favor of an excitatory cortical state. VSD imaging may thus be a promising technique to trace TMS-induced changes in excitability and resulting plastic processes across cortical maps with high spatial and temporal resolutions.

Broadband noise masks suppress neural responses to narrowband stimuli

White pixel noise is widely used to estimate the level of internal noise in a system by injecting external variance into the detecting mechanism. Recent work (Baker and Meese, 2012) has provided psychophysical evidence that such noise masks might also cause suppression that could invalidate estimates of internal noise. Here we measure neural population responses directly, using steady-state visual evoked potentials, elicited by target stimuli embedded in different mask types. Sinusoidal target gratings of 1 c/deg flickered at 5 Hz, and were shown in isolation, or with superimposed orthogonal grating masks or 2D white noise masks, flickering at 7 Hz. Compared with responses to a blank screen, the Fourier amplitude at the target frequency increased monotonically as a function of target contrast when no mask was present. Both orthogonal and white noise masks caused rightward shifts of the contrast response function, providing evidence of contrast gain control suppression. We also calculated within-observer amplitude variance across trials. This increased in proportion to the target response, implying signal-dependent (i.e., multiplicative) noise at the system level, the implications of which we discuss for behavioral tasks. This measure of variance was reduced by both mask types, consistent with the changes in mean target response. An alternative variety of noise, which we term zero-dimensional noise, involves trial-by-trial jittering of the target contrast. This type of noise produced no gain control suppression, and increased the amplitude variance across trials.

The stimulus-evoked population response in visual cortex of awake monkey is a propagating wave

Propagating waves occur in many excitable media and were recently found in neural systems from retina to neocortex. While propagating waves are clearly present under anaesthesia, whether they also appear during awake and conscious states remains unclear. One possibility is that these waves are systematically missed in trial-averaged data, due to variability. Here we present a method for detecting propagating waves in noisy multichannel recordings. Applying this method to single-trial voltage-sensitive dye imaging data, we show that the stimulus-evoked population response in primary visual cortex of the awake monkey propagates as a travelling wave, with consistent dynamics across trials. A network model suggests that this reliability is the hallmark of the horizontal fibre network of superficial cortical layers. Propagating waves with similar properties occur independently in secondary visual cortex, but maintain precise phase relations with the waves in primary visual cortex. These results show that, in response to a visual stimulus, propagating waves are systematically evoked in several visual areas, generating a consistent spatiotemporal frame for further neuronal interactions.

Propagating waves of cortical neuronal activity are implicated in various cognitive processes and have been observed in anaesthetised animals. Here, the authors demonstrate the existence of propagating waves in awake monkeys during visual stimulation, and show that they are mediated by horizontal fibres in the cortex.

Abnormal visual gain control in a Parkinson's disease model

Our understanding of Parkinson's disease (PD) has been revolutionized by the discovery of disease-causing genetic mutations. The most common of these is the G2019S mutation in the LRRK2 kinase gene, which leads to increased kinase activity. However, the link between increased kinase activity and PD is unclear. Previously, we showed that dopaminergic expression of the human LRRK2-G2019S transgene in flies led to an activity-dependent loss of vision in older animals and we hypothesized that this may have been preceded by a failure to regulate neuronal activity correctly in younger animals. To test this hypothesis, we used a sensitive measure of visual function based on frequency-tagged steady-state visually evoked potentials. Spectral analysis allowed us to identify signals from multiple levels of the fly visual system and wild-type visual response curves were qualitatively similar to those from human cortex. Dopaminergic expression of hLRRK2-G2019S increased contrast sensitivity throughout the retinal network. To test whether this was due to increased kinase activity, we fed Drosophila with kinase inhibitors targeted at LRRK2. Contrast sensitivity in both day 1 and day 14 flies was normalized by a novel LRRK2 kinase inhibitor ‘BMPPB-32’. Biochemical and cellular assays suggested that BMPPB-32 would be a more specific kinase inhibitor than LRRK2-IN-1. We confirmed this in vivo, finding that dLRRK⁻ null flies show large off-target effects with LRRK2-IN-1 but not BMPPB-32. Our data link the increased Kinase activity of the G2019S-LRRK2 mutation to neuronal dysfunction and demonstrate the power of the Drosophila visual system in assaying the neurological effects of genetic diseases and therapies.

Cumulative latency advance underlies fast visual processing in desynchronized brain state

Fast sensory processing is vital for the animal to efficiently respond to the changing environment. This is usually achieved when the animal is vigilant, as reflected by cortical desynchronization. However, the neural substrate for such fast processing remains unclear. Here, we report that neurons in rat primary visual cortex (V1) exhibited shorter response latency in the desynchronized state than in the synchronized state. In vivo whole-cell recording from the same V1 neurons undergoing the two states showed that both the resting and visually evoked conductances were higher in the desynchronized state. Such conductance increases of single V1 neurons shorten the response latency by elevating the membrane potential closer to the firing threshold and reducing the membrane time constant, but the effects only account for a small fraction of the observed latency advance. Simultaneous recordings in lateral geniculate nucleus (LGN) and V1 revealed that LGN neurons also exhibited latency advance, with a degree smaller than that of V1 neurons. Furthermore, latency advance in V1 increased across successive cortical layers. Thus, latency advance accumulates along various stages of the visual pathway, likely due to a global increase of membrane conductance in the desynchronized state. This cumulative effect may lead to a dramatic shortening of response latency for neurons in higher visual cortex and play a critical role in fast processing for vigilant animals.

Spatiotemporal dynamics of neuronal population response in the primary visual cortex

One of the fundamental questions in system neuroscience is how the brain encodes external stimuli in the early sensory cortex. It has been found in experiments that even some simple sensory stimuli can activate large populations of neurons. It is believed that information can be encoded in the spatiotemporal profile of these collective neuronal responses. Here, we use a large-scale computational model of the primary visual cortex (V1) to study the population responses in V1 as observed in experiments in which monkeys performed visual detection tasks. We show that our model can capture very well spatiotemporal activities measured by voltage-sensitive-dye-based optical imaging in V1 of the awake state. In our model, the properties of horizontal long-range connections with NMDA conductance play an important role in the correlated population responses and have strong implications for spatiotemporal coding of neuronal populations. Our computational modeling approach allows us to reveal intrinsic cortical dynamics, separating them from those statistical effects arising from averaging procedures in experiment. For example, in experiments, it was shown that there was a spatially antagonistic center-surround structure in optimal weights in signal detection theory, which was believed to underlie the efficiency of population coding. However, our study shows that this feature is an artifact of data processing.

Temporally-structured acquisition of multidimensional optical imaging data facilitates visualization of elusive cortical representations in the behaving monkey

Fundamental understanding of higher cognitive functions can greatly benefit from imaging of cortical activity with high spatiotemporal resolution in the behaving non-human primate. To achieve rapid imaging of high-resolution dynamics of cortical representations of spontaneous and evoked activity, we designed a novel data acquisition protocol for sensory stimulation by rapidly interleaving multiple stimuli in continuous sessions of optical imaging with voltage-sensitive dyes. We also tested a new algorithm for the "temporally structured component analysis" (TSCA) of a multidimensional time series that was developed for our new data acquisition protocol, but was tested only on simulated data (Blumenfeld, 2010). In addition to the raw data, the algorithm incorporates prior knowledge about the temporal structure of the data as well as input from other information. Here we showed that TSCA can successfully separate functional signal components from other signals referred to as noise. Imaging of responses to multiple visual stimuli, utilizing voltage-sensitive dyes, was performed on the visual cortex of awake monkeys. Multiple cortical representations, including orientation and ocular dominance maps as well as the hitherto elusive retinotopic representation of orientation stimuli, were extracted in only 10s of imaging, approximately two orders of magnitude faster than accomplished by conventional methods. Since the approach is rather general, other imaging techniques may also benefit from the same stimulation protocol. This methodology can thus facilitate rapid optical imaging explorations in monkeys, rodents and other species with a versatility and speed that were not feasible before.

Cortical long-range interactions embed statistical knowledge of natural sensory input: a voltage-sensitive dye imaging study

How is contextual processing as demonstrated with simplified stimuli, cortically enacted in response to ecologically relevant complex and dynamic stimuli? Using voltage-sensitive dye imaging, we captured mesoscopic population dynamics across several square millimeters of cat primary visual cortex. By presenting natural movies locally through either one or two adjacent apertures, we show that simultaneous presentation leads to mutual facilitation of activity. These synergistic effects were most effective when both movie patches originated from the same natural movie, thus forming a coherent stimulus in which the inherent spatio-temporal structure of natural movies were preserved in accord with Gestalt principles of perceptual organization. These results suggest that natural sensory input triggers cooperative mechanisms that are imprinted into the cortical functional architecture as early as in primary visual cortex.

Population response to natural images in the primary visual cortex encodes local stimulus attributes and perceptual processing

The primary visual cortex (V1) is extensively studied with a large repertoire of stimuli, yet little is known about its encoding of natural images. Using voltage-sensitive dye imaging in behaving monkeys, we measured neural population response evoked in V1 by natural images presented during a face/scramble discrimination task. The population response showed two distinct phases of activity: an early phase that was spread over most of the imaged area, and a late phase that was spatially confined. To study the detailed relation between the stimulus and the population response, we used a simple encoding model to compute a continuous map of the expected neural response based on local attributes of the stimulus (luminance and contrast), followed by an analytical retinotopic transformation. Then, we computed the spatial correlation between the maps of the expected and observed response. We found that the early response was highly correlated with the local luminance of the stimulus and was sufficient to effectively discriminate between stimuli at the single trial level. The late response, on the other hand, showed a much lower correlation to the local luminance, was confined to central parts of the face images, and was highly correlated with the animal's perceptual report. Our study reveals a continuous spatial encoding of low- and high-level features of natural images in V1. The low level is directly linked to the stimulus basic local attributes and the high level is correlated with the perceptual outcome of the stimulus processing.

Dynamics of local input normalization result from balanced short- and long-range intracortical interactions in area V1

To efficiently drive many behaviors, sensory systems have to integrate the activity of large neuronal populations within a limited time window. These populations need to rapidly achieve a robust representation of the input image, probably through canonical computations such as divisive normalization. However, little is known about the dynamics of the corticocortical interactions implementing these rapid and robust computations. Here, we measured the real-time activity of a large neuronal population in V1 using voltage-sensitive dye imaging in behaving monkeys. We found that contrast gain of the population increases over time with a time constant of ~30 ms and propagates laterally over the cortical surface. This dynamic is well accounted for by a divisive normalization achieved through a recurrent network that transiently increases in size after response onset with a slow swelling speed of 0.007-0.014 m/s, suggesting a polysynaptic intracortical origin. In the presence of a surround, this normalization pool is gradually balanced by lateral inputs propagating from distant cortical locations. This results in a centripetal propagation of surround suppression at a speed of 0.1-0.3 m/s, congruent with horizontal intracortical axons speed. We propose that a simple generalized normalization scheme can account for both the dynamical contrast response function through recurrent polysynaptic intracortical loops and for the surround suppression through long-range monosynaptic horizontal spread. Our results demonstrate that V1 achieves a rapid and robust context-dependent input normalization through a timely push-pull between local and lateral networks. We suggest that divisive normalization, a fundamental canonical computation, should be considered as a dynamic process.

Long-range parallel processing and local recurrent activity in the visual cortex of the mouse

The transfer of visual information from the primary visual cortex (V1) to higher order visual cortices is an essential step in visual processing. However, the dynamics of activation of visual cortices is poorly understood. In mice, several extrastriate areas surrounding V1 have been described. Using voltage-sensitive dye imaging in vivo, we determined the spatiotemporal dynamics of the activity evoked in the visual cortex by simple stimuli. Independently of precise areal boundaries, we found that V1 activation is rapidly followed by the depolarization of three functional groups of higher order visual areas organized retinotopically. After this sequential activation, all four regions were simultaneously active for most of the response. Concomitantly with the parallel processing of the visual input, the activity initiated retinotopically and propagated quickly and isotropically within each region. The size of this activation by local recurrent activity, which extended beyond the initial retinotopic response, was dependent on the intensity of the stimulus. Moreover the difference in the spatiotemporal dynamic of the response to dark and bright stimuli suggested the dominance in the mouse of the ON pathway. Our results suggest that the cortex integrates visual information simultaneously through across-area parallel and within-area serial processing.

Traveling waves in visual cortex

Electrode recordings and imaging studies have revealed that localized visual stimuli elicit waves of activity that travel across primary visual cortex. Traveling waves are present also during spontaneous activity, but they can be greatly reduced by widespread and intensive visual stimulation. In this Review, we summarize the evidence in favor of these traveling waves. We suggest that their substrate may lie in long-range horizontal connections and that their functional role may involve the integration of information over large regions of space.

Feedforward origins of response variability underlying contrast invariant orientation tuning in cat visual cortex

Contrast invariant orientation tuning in simple cells of the visual cortex depends critically on contrast dependent trial-to-trial variability in their membrane potential responses. This observation raises the question of whether this variability originates from within the cortical circuit or the feedforward inputs from the lateral geniculate nucleus (LGN). To distinguish between these two sources of variability, we first measured membrane potential responses while inactivating the surrounding cortex, and found that response variability was nearly unaffected. We then studied variability in the LGN, including contrast dependence, and the trial-to-trial correlation in responses between nearby neurons. Variability decreased significantly with contrast, whereas correlation changed little. When these experimentally measured parameters of variability were applied to a feedforward model of simple cells that included realistic mechanisms of synaptic integration, contrast-dependent, orientation independent variability emerged in the membrane potential responses. Analogous mechanisms might contribute to the stimulus dependence and propagation of variability throughout the neocortex.

Robustness of traveling waves in ongoing activity of visual cortex

Numerous studies have revealed traveling waves of activity in sensory cortex, both following sensory stimulation and during ongoing activity. We contributed to this body of work by measuring the spike-triggered average of the local field potential (stLFP) at multiple concurrent locations (Nauhaus et al., 2009) in the visual cortex of anesthetized cats and macaques. We found the stLFP to be progressively delayed at increasing distances from the site of the triggering spikes, and interpreted this as a traveling wave of depolarization originating from that site. Our results were criticized, however, on two grounds. First, a study using the same recording techniques in the visual cortex of awake macaques reported an apparent lack of traveling waves, and proposed that traveling waves could arise artifactually from excessive filtering of the field potentials (Ray and Maunsell, 2011). Second, the interpretability of the stLFP was questioned (Kenneth Miller, personal communication), as the stLFP must reflect not only interactions between spike trains and field potentials, but also correlations within and across the spike trains. Here, we show that our data and interpretation are not imperiled by these criticisms. We reanalyzed our field potentials to remove any possible artifact due to filtering and to discount the effects of correlations within and across the triggering spike trains. In both cases, we found that the traveling waves were still present. In fact, closer inspection of Ray and Maunsell's (2011) data from awake cortex shows that they do agree with ours, as they contain clear evidence for traveling waves.

Dynamics of normalization underlying masking in human visual cortex

Stimulus visibility can be reduced by other stimuli that overlap the same region of visual space, a process known as masking. Here we studied the neural mechanisms of masking in humans using source-imaged steady state visual evoked potentials and frequency-domain analysis over a wide range of relative stimulus strengths of test and mask stimuli. Test and mask stimuli were tagged with distinct temporal frequencies and we quantified spectral response components associated with the individual stimuli (self terms) and responses due to interaction between stimuli (intermodulation terms). In early visual cortex, masking alters the self terms in a manner consistent with a reduction of input contrast. We also identify a novel signature of masking: a robust intermodulation term that peaks when the test and mask stimuli have equal contrast and disappears when they are widely different. We fit all of our data simultaneously with family of a divisive gain control models that differed only in their dynamics. Models with either very short or very long temporal integration constants for the gain pool performed worse than a model with an integration time of ∼30 ms. Finally, the absolute magnitudes of the response were controlled by the ratio of the stimulus contrasts, not their absolute values. This contrast-contrast invariance suggests that many neurons in early visual cortex code relative rather than absolute contrast. Together, these results provide a more complete description of masking within the normalization framework of contrast gain control and suggest that contrast normalization accomplishes multiple functional goals.