Dynamics of Receptive Field Size in Primary Visual Cortex

Backward masking reveals coarse-to-fine dynamics in human V1

Natural images exhibit luminance variations aligned across a broad spectrum of spatial frequencies (SFs). It has been proposed that, at early stages of processing, the coarse signals carried by the low SF (LSF) of the visual input are sent rapidly from primary visual cortex (V1) to ventral, dorsal and frontal regions to form a coarse representation of the input, which is later sent back to V1 to guide the processing of fine-grained high SFs (i.e., HSF). We used functional resonance imaging (fMRI) to investigate the role of human V1 in the coarse-to-fine integration of visual input. We disrupted the processing of the coarse and fine content of full-spectrum human face stimuli via backward masking of selective SF ranges (LSFs: <1.75cpd and HSFs: >1.75cpd) at specific times (50, 83, 100 or 150ms). In line with coarse-to-fine proposals, we found that (1) the selective masking of stimulus LSF disrupted V1 activity in the earliest time window, and progressively decreased in influence, while (2) an opposite trend was observed for the masking of stimulus' HSF. This pattern of activity was found in V1, as well as in ventral (i.e. the Fusiform Face area, FFA), dorsal and orbitofrontal regions. We additionally presented subjects with contrast negated stimuli. While contrast negation significantly reduced response amplitudes in the FFA, as well as coupling between FFA and V1, coarse-to-fine dynamics were not affected by this manipulation. The fact that V1 response dynamics to strictly identical stimulus sets differed depending on the masked scale adds to growing evidence that V1 role goes beyond the early and quasi-passive transmission of visual information to the rest of the brain. It instead indicates that V1 may yield a 'spatially registered common forum' or 'blackboard' that integrates top-down inferences with incoming visual signals through its recurrent interaction with high-level regions located in the inferotemporal, dorsal and frontal regions.

Modulation of Spike Count Correlations Between Macaque Primary Visual Cortex Neurons by Difficulty of Attentional Task

Studies have shown that spatial attention remarkably affects the trial-to-trial response variability shared between neurons. Difficulty in the attentional task adjusts how much concentration we maintain on what is currently important and what is filtered as irrelevant sensory information. However, how task difficulty mediates the interactions between neurons with separated receptive fields (RFs) that are attended to or attended away is still not clear. We examined spike count correlations between single-unit activities recorded simultaneously in the primary visual cortex (V1) while monkeys performed a spatial attention task with two levels of difficulty. Moreover, the RFs of the two neurons recorded were non-overlapping to allow us to study fluctuations in the correlated responses between competing visual inputs when the focus of attention was allocated to the RF of one neuron. While increasing difficulty in the spatial attention task, spike count correlations were either decreased to become negative between neuronal pairs, implying competition among them, with one neuron (or none) exhibiting attentional enhancement of firing rate, or increased to become positive, suggesting inter-neuronal cooperation, with one of the pair showing attentional suppression of spiking responses. Besides, the modulation of spike count correlations by task difficulty was independent of the attended locations. These findings provide evidence that task difficulty affects the functional interactions between different neuronal pools in V1 when selective attention resolves the spatial competition.

Spatiotemporal Content of Saccade Transients

Humans use rapid gaze shifts, known as saccades, to explore visual scenes. These movements yield abrupt luminance changes on the retina, which elicit robust neural discharges at fixation onsets. Yet little is known about the spatial content of saccade transients. Here, we show that saccades redistribute spatial information within the temporal range of retinal sensitivity following two distinct regimes: saccade modulations counterbalance (whiten) the spectral density of natural scenes at low spatial frequencies and follow the external power distribution at higher frequencies. This redistribution is a consequence of saccade dynamics, particularly the speed/amplitude/duration relation known as the main sequence. It resembles the redistribution resulting from inter-saccadic eye drifts, revealing a continuum in the modulations given by different eye movements, with oculomotor transitions primarily acting by regulating the bandwidth of whitening. Our findings suggest important computational roles for saccade transients in the establishment of spatial representations and lead to testable predictions about their consequences for visual functions and encoding mechanisms.

Layer 3 Dynamically Coordinates Columnar Activity According to Spatial Context

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

Relationship between the Dynamics of Orientation Tuning and Spatiotemporal Receptive Field Structures of Cat LGN Neurons

Simple cells in the cat primary visual cortex usually have elongated receptive fields (RFs), and their orientation selectivity can be largely predicted by their RFs. As to the relay cells in cats' lateral geniculate nucleus (LGN), they also have weak but significant orientation bias (OB). It is thus of interest to investigate the fine spatiotemporal receptive field (STRF) properties in LGN, compare them with the dynamics of orientation tuning, and examine the dynamic relationship between STRF and orientation sensitivity in LGN. We mapped the STRFs of the LGN neurons in cats with white noise and characterized the dynamics of the orientation tuning by flashing gratings. We found that most of the LGN neurons showed elongated RFs and that the elongation axes were consistent with the preferred orientations. STRFs and the dynamics of orientation tuning were closely correlated temporally: the elongation of RFs and OB emerged, peaked and decayed at the same pace, with unchanged elongation axis of RF and preferred orientation but consistently changing aspect ratio of RF and OB strength across time. Importantly, the above consistency between RF and orientation tuning was not influenced by the ablation of the primary visual cortex. Furthermore, biased orientation tuning emerged 20-30 ms earlier than those in the primary visual cortex. These data demonstrated that similar to the primary visual cortex, the orientation sensitivity was closely reflected by the RF properties in LGN. However, the elongated RF and OB in LGN did not originate from the primary visual cortex feedback.

Cluster-based analysis improves predictive validity of spike-triggered receptive field estimates

Spectrotemporal receptive field (STRF) characterization is a central goal of auditory physiology. STRFs are often approximated by the spike-triggered average (STA), which reflects the average stimulus preceding a spike. In many cases, the raw STA is subjected to a threshold defined by gain values expected by chance. However, such correction methods have not been universally adopted, and the consequences of specific gain-thresholding approaches have not been investigated systematically. Here, we evaluate two classes of statistical correction techniques, using the resulting STRF estimates to predict responses to a novel validation stimulus. The first, more traditional technique eliminated STRF pixels (time-frequency bins) with gain values expected by chance. This correction method yielded significant increases in prediction accuracy, including when the threshold setting was optimized for each unit. The second technique was a two-step thresholding procedure wherein clusters of contiguous pixels surviving an initial gain threshold were then subjected to a cluster mass threshold based on summed pixel values. This approach significantly improved upon even the best gain-thresholding techniques. Additional analyses suggested that allowing threshold settings to vary independently for excitatory and inhibitory subfields of the STRF resulted in only marginal additional gains, at best. In summary, augmenting reverse correlation techniques with principled statistical correction choices increased prediction accuracy by over 80% for multi-unit STRFs and by over 40% for single-unit STRFs, furthering the interpretational relevance of the recovered spectrotemporal filters for auditory systems analysis.

Altered visual cortical processing in a mouse model of MECP2 duplication syndrome

As an epigenetic modulator of gene expression, Methyl-CpG binding protein 2 (MeCP2) is essential for normal neurological function. Dysfunction of MeCP2 is associated with a variety of neurological disorders. MECP2 gene duplication in human causes neuropsychiatric symptoms such as mental retardation and autism. MeCP2 overexpression in mice results in neurobehavioural disorders, dendritic abnormalities, and synaptic defects. However, how gain of MeCP2 function influences cortical processing of sensory information remains unclear. In this study, we examined visual processing in a mouse model of MECP2 duplication syndrome (MECP2 Tg1 mouse) at 8 and 14 weeks, which were before and after the onset of behavioural symptoms, respectively. In vivo extracellular recordings from primary visual cortex (V1) showed that neurons in Tg1 mice at both adult ages preferred higher spatial frequencies (SFs) than those in wild-type (WT) littermate controls, and the semi-saturation contrasts of neurons were lower in Tg1 mice at 8 weeks but not at 14 weeks. Behavioural experiments showed that the performance for visual detection at high SFs and low contrasts was higher in MECP2 Tg1 mice. Thus, MeCP2 gain-of-function in mice leads to higher visual acuity and contrast sensitivity, both at the levels of cortical response and behavioural performance.

Consequences of the Oculomotor Cycle for the Dynamics of Perception

Much evidence indicates that humans and other species process large-scale visual information before fine spatial detail. Neurophysiological data obtained with paralyzed eyes suggest that this coarse-to-fine sequence results from spatiotemporal filtering by neurons in the early visual pathway. However, the eyes are normally never stationary: rapid gaze shifts (saccades) incessantly alternate with slow fixational movements. To investigate the consequences of this oculomotor cycle on the dynamics of perception, we combined spectral analysis of visual input signals, neural modeling, and gaze-contingent control of retinal stimulation in humans. We show that the saccade/fixation cycle reformats the flow impinging on the retina in a way that initiates coarse-to-fine processing at each fixation. This finding reveals that the visual system uses oculomotor-induced temporal modulations to sequentially encode different spatial components and suggests that, rather than initiating coarse-to-fine processing, spatiotemporal coupling in the early visual pathway builds on the information dynamics of the oculomotor cycle.

Categorically distinct types of receptive fields in early visual cortex

In the visual cortex, distinct types of neurons have been identified based on cellular morphology, response to injected current, or expression of specific markers, but neurophysiological studies have revealed visual receptive field (RF) properties that appear to be on a continuum, with only two generally recognized classes: simple and complex. Most previous studies have characterized visual responses of neurons using stereotyped stimuli such as bars, gratings, or white noise and simple system identification approaches (e.g., reverse correlation). Here we estimate visual RF models of cortical neurons using visually rich natural image stimuli and regularized regression system identification methods and characterize their spatial tuning, temporal dynamics, spatiotemporal behavior, and spiking properties. We quantitatively demonstrate the existence of three functionally distinct categories of simple cells, distinguished by their degree of orientation selectivity (isotropic or oriented) and the nature of their output nonlinearity (expansive or compressive). In addition, these three types have differing average values of several other properties. Cells with nonoriented RFs tend to have smaller RFs, shorter response durations, no direction selectivity, and high reliability. Orientation-selective neurons with an expansive output nonlinearity have Gabor-like RFs, lower spontaneous activity and responsivity, and spiking responses with higher sparseness. Oriented RFs with a compressive nonlinearity are spatially nondescript and tend to show longer response latency. Our findings indicate multiple physiologically defined types of RFs beyond the simple/complex dichotomy, suggesting that cortical neurons may have more specialized functional roles rather than lying on a multidimensional continuum.

Spatio-temporal properties of letter crowding

Crowding between adjacent letters has been investigated primarily as a spatial effect. The purpose of this study was to investigate the spatio-temporal properties of letter crowding. Specifically, we examined the systematic changes in the degradation effects in letter identification performance when adjacent letters were presented with a temporal asynchrony, as a function of letter separation and between the fovea and the periphery. We measured proportion-correct performance for identifying the middle target letter in strings of three lowercase letters at the fovea and 10° in the inferior visual field, for a range of center-to-center letter separations and a range of stimulus onset asynchronies (SOA) between the target and flanking letters (positive SOAs: target preceded flankers). As expected, the accuracy for identifying the target letters reduces with decreases in letter separation. This crowding effect shows a strong dependency on SOAs, such that crowding is maximal between 0 and ∼100 ms (depending on conditions) and diminishes for larger SOAs (positive or negative). Maximal crowding does not require the target and flanking letters to physically coexist for the entire presentation duration. Most importantly, crowding can be minimized even for closely spaced letters if there is a large temporal asynchrony between the target and flankers. The reliance of letter identification performance on SOAs and how it changes with letter separations imply that the crowding effect can be traded between space and time. Our findings are consistent with the notion that crowding should be considered as a spatio-temporal, and not simply a spatial, effect.

V1 neurons respond to luminance changes faster than contrast changes

Luminance and contrast are two major attributes of objects in the visual scene. Luminance and contrast information received by visual neurons are often updated simultaneously. We examined the temporal response properties of neurons in the primary visual cortex (V1) to stimuli whose luminance and contrast were simultaneously changed by 50 Hz. We found that response tuning to luminance changes precedes tuning to contrast changes in V1. For most V1 neurons, the onset time of response tuning to luminance changes was shorter than that to contrast changes. Most neurons carried luminance information in the early response stage, while all neurons carried both contrast and luminance information in the late response stage. The early luminance response suggests that cortical processing for luminance is not as slow as previously thought.

Spatial Frequency Components of Images Modulate Neuronal Activity in Monkey Amygdala

Processing the spatial frequency components of an image is a crucial feature for visual perception, especially in recognition of faces. Here, we study the correlation between spatial frequency components of images of faces and neuronal activity in monkey amygdala while performing a visual recognition task. The frequency components of the images were analyzed using a fast Fourier transform for 40 spatial frequency ranges. We recorded 65 neurons showing statistically significant responses to at least one of the images used as a stimulus. A total of 37 of these neurons (n = 37) showed significant responses to at least three images, and in eight of them (8/37, 22%), we found a statistically significant correlation between neuron response and the modulus amplitude of at least one frequency range present in the images. Our results indicate that high spatial frequency and low spatial frequency components of images influence the activity of amygdala neurons.

Neural mechanisms of coarse-to-fine discrimination in the visual cortex

Vision is a dynamic process that refines the spatial scale of analysis over time, as evidenced by a progressive improvement in the ability to detect and discriminate finer details. To understand coarse-to-fine discrimination, we studied the dynamics of spatial frequency (SF) response using reverse correlation in the primary visual cortex (V1) of the primate. In a majority of V1 cells studied, preferred SF either increased monotonically with time (group 1) or changed nonmonotonically, with an initial increase followed by a decrease (group 2). Monotonic shift in preferred SF occurred with or without an early suppression at low SFs. Late suppression at high SFs always accompanied nonmonotonic SF dynamics. Bayesian analysis showed that SF discrimination performance and best discriminable SF frequencies changed with time in different ways in the two groups of neurons. In group 1 neurons, SF discrimination performance peaked on both left and right flanks of the SF tuning curve at about the same time. In group 2 neurons, peak discrimination occurred on the right flank (high SFs) later than on the left flank (low SFs). Group 2 neurons were also better discriminators of high SFs. We examined the relationship between the time at which SF discrimination performance peaked on either flank of the SF tuning curve and the corresponding best discriminable SFs in both neuronal groups. This analysis showed that the population best discriminable SF increased with time in V1. These results suggest neural mechanisms for coarse-to-fine discrimination behavior and that this process originates in V1 or earlier.

Selective stimulation of neurons in visual cortex enables segregation of slow and fast connections

Organization of the central visual pathway is generally studied from a perspective of feedforward processes. However, there are horizontal connections and also strong feedback from extra striate to visual cortex. Here, we use visual stimuli designed to maximize relative differential involvements of these three main types of connections. The approach relies on differences between stimulation within the classical receptive field (CRF) and that of the surround region. Although previous studies have used similar approaches, they were limited primarily to spatial segregation of neural connections. Our experimental design provides clear segregation of fast and slow components of surround modulation. We assume these are mediated by feedback and horizontal connections, respectively, but other factors may be involved. Our results imply that both horizontal and feedback connections contribute to integration of visual information outside the CRF and provide suppressive or facilitative modulation. For a given cell, modulation may change in strength and sign from suppression to facilitation or the reverse depending on surround parameters. Sub-threshold input from the CRF surround increases local field potential (LFP) power in distinct frequency ranges which differ for suppression and facilitation. Horizontal connections have delayed CRF-surround modulation and are sensitive to position changes in the surround. Therefore, surround information beyond the CRF is initially processed by fast connections which we consider to be feedback, whereas spatially tuned mechanisms are relatively slow and presumably mediated by horizontal connections. Overall, results suggest that convergent fast (feedforward) inputs determine size and structure of the CRFs of recipient cells in visual cortex. And fast connections from extra striate regions (feedback) plus slow-tuned connections (horizontal) within visual cortex contribute to spatial influences of CRF surround activation.

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.

Orientation enhancement in early visual processing can explain time course of brightness contrast and White's illusion

Dynamics of orientation tuning in V1 indicates that computational model of V1 should not only comprise of bank of static spatially oriented filters but also include the contribution for dynamical response facilitation or suppression along orientation. Time evolution of orientation response in V1 can emerge due to time- dependent excitation and lateral inhibition in the orientation domain. Lateral inhibition in the orientation domain suggests that Ernst Mach's proposition can be applied for the enhancement of initial orientation distribution that is generated due to interaction of visual stimulus with spatially oriented filters and subcortical temporal filter. Oriented spatial filtering that appears much early (<70 ms) in the sequence of visual information processing can account for many of the brightness illusions observed at steady state. It is therefore expected that time evolution of orientation response might be reflecting in the brightness percept over time. Our numerical study suggests that only spatio-temporal filtering at early phase can explain experimentally observed temporal dynamics of brightness contrast illusion. But, enhancement of orientation response at early phase of visual processing is the key mechanism that can guide visual system to predict the brightness by "Max-rule" or "Winner Takes All" (WTA) estimation and thus producing White's illusions at any exposure.

Stimulus-entrained oscillatory activity propagates as waves from area 18 to 17 in cat visual cortex

Previous studies in cat visual cortex reported that area 18 can actively drive neurons in area 17 through cortico-cortical projections. However, the dynamics of such cortico-cortical interaction remains unclear. Here we used multielectrode arrays to examine the spatiotemporal pattern of neuronal activity in cat visual cortex across the 17/18 border. We found that full-field contrast reversal gratings evoked oscillatory wave activity propagating from area 18 to 17. The wave direction was independent of the grating orientation, and could not be accounted for by the spatial distribution of receptive field latencies, suggesting that the waves are largely mediated by intrinsic connections in the cortex. Different from the evoked waves, spontaneous waves propagated along both directions across the 17/18 border. Together, our results suggest that visual stimulation may enhance the flow of information from area 18 to 17.

Perceptual inference predicts contextual modulations of sensory responses

Sensory receptive fields (RFs) vary as a function of stimulus properties and measurement methods. Previous stimuli or surrounding stimuli facilitate, suppress, or change the selectivity of sensory neurons' responses. Here, we propose that these spatiotemporal contextual dependencies are signatures of efficient perceptual inference and can be explained by a single neural mechanism, input targeted divisive inhibition. To respond both selectively and reliably, sensory neurons should behave as active predictors rather than passive filters. In particular, they should remove input they can predict ("explain away") from the synaptic inputs to all other neurons. This implies that RFs are constantly and dynamically reshaped by the spatial and temporal context, while the true selectivity of sensory neurons resides in their "predictive field." This approach motivates a reinvestigation of sensory representations and particularly the role and specificity of surround suppression and adaptation in sensory areas.

Generation of black-dominant responses in V1 cortex

Consistent with human perceptual data, we found many more black-dominant than white-dominant responses in layer 2/3 neurons of the macaque primary visual cortex (V1). Seeking the mechanism of this black dominance of layer 2/3 neurons, we measured the laminar pattern of population responses (multiunit activity and local field potential) and found that a small preference for black is observable in early responses in layer 4Cβ, the parvocellular-input layer, but not in the magnocellular-input layer 4Cα. Surprisingly, further analysis of the dynamics of black-white responses in layers 4Cβ and 2/3 suggested that black-dominant responses in layer 2/3 were not generated simply because of the weak black-dominant inputs from 4Cβ. Instead, our results indicated the neural circuitry in V1 is wired with a preference to strengthen black responses. We hypothesize that this selective wiring could be due to (1) feedforward connectivity from black-dominant neurons in layer 4C to cells in layer 2/3 or (2) recurrent interactions between black-dominant neurons in layer 2/3, or a combination of both.

Spatial and temporal features of synaptic to discharge receptive field transformation in cat area 17

The aim of the present study was to characterize the spatial and temporal features of synaptic and discharge receptive fields (RFs), and to quantify their relationships, in cat area 17. For this purpose, neurons were recorded intracellularly while high-frequency flashing bars were used to generate RFs maps for synaptic and spiking responses. Comparison of the maps shows that some features of the discharge RFs depended strongly on those of the synaptic RFs, whereas others were less dependent. Spiking RF duration depended poorly and spiking RF amplitude depended moderately on those of the underlying synaptic RFs. At the other extreme, the optimal spatial frequency and phase of the discharge RFs in simple cells were almost entirely inherited from those of the synaptic RFs. Subfield width, in both simple and complex cells, was less for spiking responses compared with synaptic responses, but synaptic to discharge width ratio was relatively variable from cell to cell. When considering the whole RF of simple cells, additional variability in width ratio resulted from the presence of additional synaptic subfields that remained subthreshold. Due to these additional, subthreshold subfields, spatial frequency tuning predicted from synaptic RFs appears sharper than that predicted from spiking RFs. Excitatory subfield overlap in spiking RFs was well predicted by subfield overlap at the synaptic level. When examined in different regions of the RF, latencies appeared to be quite variable, but this variability showed negligible dependence on distance from the RF center. Nevertheless, spiking response latency faithfully reflected synaptic response latency.

"Black" responses dominate macaque primary visual cortex v1

Achromatic visual information is transferred from the retina to the brain through two parallel channels: ON-center cells carry "white" information and OFF-center cells "black" information (Nelson et al., 1978; Schiller, 1982; Schiller et al., 1986). Responses of ON and OFF retinal and thalamic neurons are approximately equal in magnitude (Krüger and Fischer, 1975; Kremers et al., 1993), but psychophysical studies have shown that humans detect light decrements (black) better and faster than increments (white) (Blackwell, 1946; Short, 1966; Krauskopf, 1980; Whittle, 1986; Bowen et al., 1989; Chan and Tyler, 1992; Kontsevich and Tyler, 1999; Chubb and Nam, 2000; Dannemiller and Stephens, 2001). From recordings of single-cell activity in the macaque monkey's primary visual cortex (V1), we found that black-dominant neurons substantially outnumbered white-dominant neurons in the corticocortical output layers 2/3, but the numbers of black- and white-dominant neurons were nearly equal in the thalamocortical input layer 4c. These results strongly suggest that the black-over-white preference is generated or greatly amplified in V1. The predominance of OFF neurons in layers 2/3 of V1, which provide visual input to higher cortical areas, may explain why human subjects detect black more easily than white. Furthermore, our results agree with human EEG and fMRI findings that V1 responses to decrements are stronger than to increments, though the OFF/ON imbalance we found in layers 2/3 of macaque V1 is much larger than in the whole V1 population in the human V1 experiments (Zemon et al., 1988, 1995; Olman et al., 2008).

Spatial spread of the local field potential and its laminar variation in visual cortex

We developed a new method to estimate the spatial extent of summation, the cortical spread, of the local field potential (LFP) throughout all layers of macaque primary visual cortex V1 by taking advantage of the V1 retinotopic map. We mapped multi-unit activity and LFP visual responses with sparse-noise at several cortical sites simultaneously. The cortical magnification factor near the recording sites was precisely estimated by track reconstruction. The new method combined experimental measurements together with a model of signal summation to obtain the cortical spread of the LFP. This new method could be extended to cortical areas that have topographic maps such as S1 or A1, and to cortical areas without functional columnar maps, such as rodent visual cortex. In macaque V1, the LFP was the sum of signals from a very local region, the radius of which was on average 250 microm. The LFP's cortical spread varied across cortical layers, reaching a minimum value of 120 microm in layer 4B. An important functional consequence of the small cortical spread of the LFP is that the visual field maps of LFP and MUA recorded at a single electrode site were very similar. The similar spatial scale of the visual responses, the restricted cortical spread, and their laminar variation led to new insights about the sources and possible applications of the LFP.

Stimulus ensemble and cortical layer determine V1 spatial receptive fields

The concept of receptive field is a linear, feed-forward view of visual signal processing. Frequently used models of V1 neurons, like the dynamic Linear filter--static nonlinearity--Poisson [corrected] spike encoder model, predict that receptive fields measured with different stimulus ensembles should be similar. Here, we tested this concept by comparing spatiotemporal maps of V1 neurons derived from two very different, but commonly used, stimulus ensembles: sparse noise and Hartley subspace stimuli. We found maps from the two methods agreed for neurons in input layer 4C but were very different for neurons in superficial layers of V1. Many layer 2/3 cells have receptive fields with multiple elongated subregions when mapped with Hartley stimuli, but their spatial maps collapse to only a single, less-elongated subregion when mapped with sparse noise. Moreover, for upper layer V1 neurons, the preferred orientation for Hartley maps is much closer to the preferred orientation measured with drifting gratings than is the orientation preference of sparse-noise maps. These results challenge the concept of a stimulus-invariant receptive field and imply that intracortical interactions shape fundamental properties of layer 2/3 neurons.

Spatial and temporal jitter distort estimated functional properties of visual sensory neurons

The functional properties of neural sensory cells or small neural ensembles are often characterized by analyzing response-conditioned stimulus ensembles. Many widely used analytical methods, like receptive fields (RF), Wiener kernels or spatio-temporal receptive fields (STRF), rely on simple statistics of those ensembles. They also tend to rely on simple noise models for the residuals of the conditional ensembles. However, in many cases the response-conditioned stimulus set has more complex structure. If not taken explicitly into account, it can bias the estimates of many simple statistics, and lead to erroneous conclusions about the functionality of a neural sensory system. In this article, we consider sensory noise in the visual system generated by small stimulus shifts in two dimensions (2 spatial or 1-space 1-time jitter). We model this noise as the action of a set of translations onto the stimulus that leave the response invariant. The analysis demonstrates that the spike-triggered average is a biased estimator of the model mean, and provides a de-biasing method. We apply this approach to observations from the stimulus/response characteristics of cells in the cat visual cortex and provide improved estimates of the structure of visual receptive fields. In several cases the new estimates differ substantially from the classic receptive fields, to a degree that may require re-evaluation of the functional description of the associated cells.

Postsynaptic receptive field size and spike threshold determine encoding of high-frequency information via sensitivity to synchronous presynaptic activity

Parallel sensory streams carrying distinct information about various stimulus properties have been observed in several sensory systems, including the visual system. What remains unclear is why some of these streams differ in the size of their receptive fields (RFs). In the electrosensory system, neurons with large RFs have short-latency responses and are tuned to high-frequency inputs. Conversely, neurons with small RFs are low-frequency tuned and exhibit longer-latency responses. What principle underlies this organization? We show experimentally that synchronous electroreceptor afferent (P-unit) spike trains selectively encode high-frequency stimulus information from broadband signals. This finding relies on a comparison of stimulus-spike output coherence using output trains obtained by either summing pairs of recorded afferent spike trains or selecting synchronous spike trains based on coincidence within a small time window. We propose a physiologically realistic decoding mechanism, based on postsynaptic RF size and postsynaptic output rate normalization that tunes target pyramidal cells in different electrosensory maps to low- or high-frequency signal components. By driving realistic neuron models with experimentally obtained P-unit spike trains, we show that a small RF is matched with a postsynaptic integration regime leading to responses over a broad range of frequencies, and a large RF with a fluctuation-driven regime that requires synchronous presynaptic input and therefore selectively encodes higher frequencies, confirming recent experimental data. Thus our work reveals that the frequency content of a broadband stimulus extracted by pyramidal cells, from P-unit afferents, depends on the amount of feedforward convergence they receive.

A quantitative explanation of responses to disparity-defined edges in macaque V2

Previous experiments have shown that V2 neurons respond to complex stimuli such as cyclopean edges (edges defined purely by binocular disparity), angles, and motion borders. It is currently unknown whether these responses are a simple consequence of converging inputs from a prior stage of processing (V1). Alternatively, they may identify edges in a way that is invariant across a range of visual cues defining the edge, in which case they could provide a neuronal substrate for scene segmentation. Here, we examine the ability of a simple feedforward model that combines two V1-like inputs to describe the responses of V2 neurons to cyclopean edges. A linear feedforward model was able to qualitatively reproduce the major patterns of response enhancement for cyclopean edges seen in V2. However, quantitative fitting revealed that this model usually predicts response suppression by some edge configurations and such suppression was rarely seen in the data. This problem was resolved by introducing a squaring nonlinearity at the output of the individual inputs prior to combination. The extended model produced extremely good fits to most of our data. We conclude that the responses of V2 neurons to complex stimuli such as cyclopean edges can be adequately explained by a simple convergence model and do not necessarily represent the development of sophisticated mechanisms that signal scene segmentation, although they probably constitute a step toward this goal.

Level invariant representation of sounds by populations of neurons in primary auditory cortex

A fundamental feature of auditory perception is the constancy of sound recognition over a large range of intensities. Although this invariance has been described in behavioral studies, the underlying neural mechanism is essentially unknown. Here we show a putative level-invariant representation of sounds by populations of neurons in primary auditory cortex (A1) that may provide a neural basis for the behavioral observations. Previous studies reported that pure-tone frequency tuning of most A1 neurons widens with increasing sound level. In sharp contrast, we found that a large proportion of neurons in A1 of awake marmosets were narrowly and separably tuned to both frequency and sound level. Tuning characteristics and firing rates of the neural population were preserved across all tested sound levels. These response properties lead to a level-invariant representation of sounds over the population of A1 neurons. Such a representation is an important step for robust feature recognition in natural environments.

Spatiotemporal structure of complex cell receptive fields and influence of GABAergic inhibition

Spatiotemporal receptive field (RF) profiles were mapped with reverse correlation technique for complex cells in the striate cortex of cat. The RFs were constituted with ON and OFF subfields that overlapped much extensively in space and also largely in time. The subfields had spatial width of 1.0-4.3 degrees and temporal duration of 33-139 ms, whereas late responses were absent in most cases. When microiontophoresis of gamma-aminobutyric acid type A (GABAA) antagonist bicuculline was performed on the cells, little change occurred in width and onset time of the subfields, but the duration was prolonged in a subset of cells. These results suggest that intracortical inhibition may contribute to improve the accuracy of visual signals encoded in neuronal activities, but is unlikely critical for determining the primary structure of complex cell RF.