Responses Of V1 Neurons Research Articles

A neural mechanism of dynamic gating of task-relevant information by top-down influence in primary visual cortex

Visual recognition involves bidirectional information flow, which consists of bottom-up information coding from retina and top-down information coding from higher visual areas. Recent studies have demonstrated the involvement of early visual areas such as primary visual area (V1) in recognition and memory formation. V1 neurons are not passive transformers of sensory inputs but work as adaptive processor, changing their function according to behavioral context. Top-down signals affect tuning property of V1 neurons and contribute to the gating of sensory information relevant to behavior. However, little is known about the neuronal mechanism underlying the gating of task-relevant information in V1. To address this issue, we focus on task-dependent tuning modulations of V1 neurons in two tasks of perceptual learning. We develop a model of the V1, which receives feedforward input from lateral geniculate nucleus and top-down input from a higher visual area. We show here that the change in a balance between excitation and inhibition in V1 connectivity is necessary for gating task-relevant information in V1. The balance change well accounts for the modulations of tuning characteristic and temporal properties of V1 neuronal responses. We also show that the balance change of V1 connectivity is shaped by top-down signals with temporal correlations reflecting the perceptual strategies of the two tasks. We propose a learning mechanism by which synaptic balance is modulated. To conclude, top-down signal changes the synaptic balance between excitation and inhibition in V1 connectivity, enabling early visual area such as V1 to gate context-dependent information under multiple task performances.

Neurons in primary visual cortex represent distribution of luminance.

To efficiently detect a wide range of light‐intensity changes, visual neurons must adapt to ambient luminance. However, how neurons in the primary visual cortex (V1) code the distribution of luminance remains unknown. We designed stimuli that represent rapid changes in luminance under different luminance distributions and investigated V1 neuron responses to these novel stimuli. We demonstrate that V1 neurons represent luminance changes by dynamically adjusting their responses when the luminance distribution changes. Many cells (35%) detected luminance changes by responding to dark stimuli when the distribution was dominated by bright stimuli, bright stimuli when dominated by dark stimuli, and both dark and bright stimuli when dominated by intermediate luminance stimuli; 13% of cells signaled the mean luminance that was varied with different distributions; the remaining 52% of cells gradually shifted the responses that were most sensitive to luminance changes when the luminance distribution varied. The remarkable response changes of the former two cell groups suggest their crucial roles in detecting luminance changes. These response characteristics demonstrate that V1 neurons are not only sensitive to luminance change, but also luminance distribution change. They encode luminance changes according to the luminance distribution. Mean cells represent the prevailing luminance and reversal cells represent the salient stimuli in the environment.

Calcium imaging with genetically encoded indicators in behaving primates.

Understanding the neural basis of behaviour requires studying brain activity in behaving subjects using complementary techniques that measure neural responses at multiple spatial scales, and developing computational tools for understanding the mapping between these measurements. Here we report the first results of widefield imaging of genetically encoded calcium indicator (GCaMP6f) signals from V1 of behaving macaques. This technique provides a robust readout of visual population responses at the columnar scale over multiple mm(2) and over several months. To determine the quantitative relation between the widefield GCaMP signals and the locally pooled spiking activity, we developed a computational model that sums the responses of V1 neurons characterized by prior single unit measurements. The measured tuning properties of the GCaMP signals to stimulus contrast, orientation and spatial position closely match the predictions of the model, suggesting that widefield GCaMP signals are linearly related to the summed local spiking activity.

Bilocal visual noise as a probe of wide field motion computation

Using an apparent visual motion stimulus with motion energies limited to specific separations in space and time, we study the computational structure of wide-field motion sensitive neurons in the fly visual brain. There is ample experimental evidence for correlation-based motion computation in many biological systems, but one of its central properties, namely that the response is proportional to the product of two bilocal signal amplitudes, remains to be tested. The design of the apparent motion stimuli used here allows us to manipulate the amplitudes of the bilocal input signals that serve as inputs to the computation. We demonstrate that the wide-field motion response of H1 and V1 neurons indeed shows bilinear behavior, even under contrast sign reversal, as predicted. But the response also varies inversely with contrast variance, an effect not described by the correlator operation. We also quantify the correlator contributions for different spatial and temporal separations. With suitable modification, the apparent motion stimuli used here can be applied to a broad range of neurophysiological as well as human psychophysical studies on motion perception.

Selectivity and tolerance for visual texture in macaque V2

As information propagates along the ventral visual hierarchy, neuronal responses become both more specific for particular image features and more tolerant of image transformations that preserve those features. Here, we present evidence that neurons in area V2 are selective for local statistics that occur in natural visual textures, and tolerant of manipulations that preserve these statistics. Texture stimuli were generated by sampling from a statistical model, with parameters chosen to match the parameters of a set of visually distinct natural texture images. Stimuli generated with the same statistics are perceptually similar to each other despite differences, arising from the sampling process, in the precise spatial location of features. We assessed the accuracy with which these textures could be classified based on the responses of V1 and V2 neurons recorded individually in anesthetized macaque monkeys. We also assessed the accuracy with which particular samples could be identified, relative to other statistically matched samples. For populations of up to 100 cells, V1 neurons supported better performance in the sample identification task, whereas V2 neurons exhibited better performance in texture classification. Relative to V1, the responses of V2 show greater selectivity and tolerance for the representation of texture statistics.

Evidence of Stereoscopic Surface Disambiguation in the Responses of V1 Neurons.

For the important task of binocular depth perception from complex natural-image stimuli, the neurophysiological basis for disambiguating multiple matches between the eyes across similar features has remained a long-standing problem. Recurrent interactions among binocular disparity-tuned neurons in the primary visual cortex (V1) could play a role in stereoscopic computations by altering responses to favor the most likely depth interpretation for a given image pair. Psychophysical research has shown that binocular disparity stimuli displayed in 1 region of the visual field can be extrapolated into neighboring regions that contain ambiguous depth information. We tested whether neurons in macaque V1 interact in a similar manner and found that unambiguous binocular disparity stimuli displayed in the surrounding visual fields of disparity-selective V1 neurons indeed modified their responses when either bistable stereoscopic or uniform featureless stimuli were presented within their receptive field centers. The delayed timing of the response behavior compared with the timing of classical surround suppression and multiple control experiments suggests that these modulations are carried out by slower disparity-specific recurrent connections among V1 neurons. These results provide explicit evidence that the spatial interactions that are predicted by cooperative algorithms play an important role in solving the stereo correspondence problem.

Dietary Restriction Affects Neuronal Response Property and GABA Synthesis in the Primary Visual Cortex.

Previous studies have reported inconsistent effects of dietary restriction (DR) on cortical inhibition. To clarify this issue, we examined the response properties of neurons in the primary visual cortex (V1) of DR and control groups of cats using in vivo extracellular single-unit recording techniques, and assessed the synthesis of inhibitory neurotransmitter GABA in the V1 of cats from both groups using immunohistochemical and Western blot techniques. Our results showed that the response of V1 neurons to visual stimuli was significantly modified by DR, as indicated by an enhanced selectivity for stimulus orientations and motion directions, decreased visually-evoked response, lowered spontaneous activity and increased signal-to-noise ratio in DR cats relative to control cats. Further, it was shown that, accompanied with these changes of neuronal responsiveness, GABA immunoreactivity and the expression of a key GABA-synthesizing enzyme GAD67 in the V1 were significantly increased by DR. These results demonstrate that DR may retard brain aging by increasing the intracortical inhibition effect and improve the function of visual cortical neurons in visual information processing. This DR-induced elevation of cortical inhibition may favor the brain in modulating energy expenditure based on food availability.

The interaction between integration and segmentation neurons for motion perception

The main challenge for understanding motion processing in the visual system is that local motion signals do not accurately represent the direction of the whole object. This is known as the The small receptive fields of individual neurons can only measure motion components orthogonal to their preferred direction. Neuro-physiological studies show that neurons in brain area MT (V5) have a major role in dealing with this problem [1]. We develop a model to overcome the aperture problem through excitatory and inhibitory interconnections between MT neurons. The model contains two levels of rate-based neuron. The first level is a model of V1 with two sets of neurons: complex neurons and hyper-complex end-stopped neurons. End-stopped neurons respond to the end-points of the stimulus , thereby representing an unambiguous estimation of the direction of motion [2]. The response of V1 neurons is transmitted to the second level, the model of MT neurons. MT neurons are categorized as integration and segmentation neurons. The role of integration neurons is to integrate local motion signals to solve the aperture problem; the role of segmentation neurons is to detect discontinuities in the input stimulus to inhibit integration neurons [3]. Excitatory recurrent connections between integration neurons propagate end-stopped information from the object terminators. As each spatial location contains neurons selective to different directions, inhibitory connections are added between the neurons such that there will be only one neuron active at each spatial location. Long-range inhibitory connections are also added between more distant MT neurons selective to other directions. Segmentation neurons send inhibitory connections to integration neurons to prevent the propagation of motion signals outside the border of the input stimulus. Inhibitory connections between segmentation neurons are defined based on center-surround interactions; this suppresses activity when the motion signals in the center and surround are in the same directions; ensuring that their activity will not prevent the propagation of motion signals when there is no discontinuity. The results of simulations show that the activity of V1 neurons along the edges is much stronger than the activity of the neurons at the end-points. Activation of end-stopped neurons in V1 suppresses ambiguous motion signals along the edges of the stimulus. Therefore, unambiguous information at the end-points wins the competition over the neurons with ambiguous motion signals. The final output of the model shows that MT neurons achieve an accurate estimation of motion using the information provided by the end-stopped neurons. We developed a model of MT neurons for motion perception based on the available neuro-physiological data. These neurons receive their input from neurons in V1. The results show the successful function of these neurons in the perception of motion of a single moving bar. In this model, we also investigated the role of end-stopped neurons in overcoming the aperture problem. The results suggest that MT neurons are not able to solve the aperture problem without the vital role played by end-stopped cells.

Spatial summation revealed in the earliest visual evoked component C1 and the effect of attention on its linearity.

In natural scenes, multiple objects are usually presented simultaneously. How do specific areas of the brain respond to multiple objects based on their responses to each individual object? Previous functional magnetic resonance imaging (fMRI) studies have shown that the activity induced by a multiobject stimulus in the primary visual cortex (V1) can be predicted by the linear or nonlinear sum of the activities induced by its component objects. However, there has been little evidence from electroencephelogram (EEG) studies so far. Here we explored how V1 responded to multiple objects by comparing the EEG signals evoked by a three-grating stimulus with those evoked by its two components (the central grating and 2 flanking gratings). We focused on the earliest visual component C1 (onset latency of ∼50 ms) because it has been shown to reflect the feedforward responses of neurons in V1. We found that when the stimulus was unattended, the amplitude of the C1 evoked by the three-grating stimulus roughly equaled the sum of the amplitudes of the C1s evoked by its two components, regardless of the distances between these gratings. When the stimulus was attended, this linear spatial summation existed only when the three gratings were far apart from each other. When the three gratings were close to each other, the spatial summation became compressed. These results suggest that the earliest visual responses in V1 follow a linear summation rule when attention is not involved and that attention can affect the earliest interactions between multiple objects.

Responses of macaque V1 neurons to color images of natural scenes

Responses of macaque V1 neurons to color images of natural scenes

The responses of V1 cortical neurons to flashed presentations of orthogonal single lines and edges.

How cortical neurons process multiple inputs is a fundamental issue in modern neuroscience. Neurons in visual cortical area V1 have been shown to exhibit cross-orientation suppression, where the response to an optimally oriented visual stimulus is reduced by the simultaneous presence of an orthogonally oriented stimulus. This is consistent with the view that cortical neurons respond to multiple inputs with a weighted average (or normalization) of the responses to the inputs presented separately. However, most of these studies have used drifting or counterphase-modulated grating stimuli, potentially confounding orientation effects with non-orientation-specific gain control mechanisms. Additionally, primate vision depends to a great extent on transient stimulus presentations during fixations between saccades. Therefore this study examined the responses of primate V1 neurons to orthogonal flashed-onset single edges and lines, and to their combinations. Single edges or lines do not typically cause strong suppression of the responses to an orthogonal stimulus, even though a grating does. This appears to hold true regardless of the relative contrasts of the orthogonal single lines or edges. This is consistent with response suppression from an orthogonal grating being due to non-orientation-specific contrast gain control (Koeling M, Shapley R, Shelley M. J Comp Neurosci 25: 390-400, 2008; Priebe NJ, Ferster D. Nat Neurosci 9: 552-561, 2006; Walker GA, Ohzawa I, Freeman RD. J.Neurophysiol 79: 227-239, 1998). While normalization mechanisms are clearly important for the cerebral cortex, under many conditions the responses of V1 cortical neurons to an optimally oriented stimulus can be unaffected by the presence of orthogonal stimuli, which may be important to avoid confounding the interpretation of a neural response.

Effects of surround suppression on response adaptation of V1 neurons to visual stimuli.

The influence of intracortical inhibition on the response adaptation of visual cortical neurons remains in debate. To clarify this issue, in the present study the influence of surround suppression evoked through the local inhibitory interneurons on the adaptation effects of neurons in the primary visual cortex (V1) were observed. Moreover, the adaptations of V1 neurons to both the high-contrast visual stimuli presented in the classical receptive field (CRF) and to the costimulation presented in the CRF and the surrounding nonclassical receptive field (nCRF) were compared. The intensities of surround suppression were modulated with different sized grating stimuli. The results showed that the response adaptation of V1 neurons decreased significantly with the increase of surround suppression and this adaptation decrease was due to the reduction of the initial response of V1 neurons to visual stimuli. However, the plateau response during adaptation showed no significant changes. These findings indicate that the adaptation effects of V1 neurons may not be directly affected by surround suppression, but may be dynamically regulated by a negative feedback network and be finely adjusted by its initial spiking response to stimulus. This adaptive regulation is not only energy efficient for the central nervous system, but also beneficially acts to maintain the homeostasis of neuronal response to long-presenting visual signals.

Neural processes in symmetry perception: a parallel spatio-temporal model

Symmetry is usually computationally expensive to detect reliably, while it is relatively easy to perceive. In spite of many attempts to understand the neurofunctional properties of symmetry processing, no symmetry-specific activation was found in earlier cortical areas. Psychophysical evidence relating to the processing mechanisms suggests that the basic processes of symmetry perception would not perform a serial, point-by-point comparison of structural features but rather operate in parallel. Here, modeling of neural processes in psychophysical detection of bilateral texture symmetry is considered. A simple fine-grained algorithm that is capable of performing symmetry estimation without explicit comparison of remote elements is introduced. A computational model of symmetry perception is then described to characterize the underlying mechanisms as one-dimensional spatio-temporal neural processes, each of which is mediated by intracellular horizontal connections in primary visual cortex and adopts the proposed algorithm for the neural computation. Simulated experiments have been performed to show the efficiency and the dynamics of the model. Model and human performances are comparable for symmetry perception of intensity images. Interestingly, the responses of V1 neurons to propagation activities reflecting higher-order perceptual computations have been reported in neurophysiologic experiments.

Network model of top-down influences on local gain and contextual interactions in visual cortex

The visual system uses continuity as a cue for grouping oriented line segments that define object boundaries in complex visual scenes. Many studies support the idea that long-range intrinsic horizontal connections in early visual cortex contribute to this grouping. Top-down influences in primary visual cortex (V1) play an important role in the processes of contour integration and perceptual saliency, with contour-related responses being task dependent. This suggests an interaction between recurrent inputs to V1 and intrinsic connections within V1 that enables V1 neurons to respond differently under different conditions. We created a network model that simulates parametrically the control of local gain by hypothetical top-down modification of local recurrence. These local gain changes, as a consequence of network dynamics in our model, enable modulation of contextual interactions in a task-dependent manner. Our model displays contour-related facilitation of neuronal responses and differential foreground vs. background responses over the neuronal ensemble, accounting for the perceptual pop-out of salient contours. It quantitatively reproduces the results of single-unit recording experiments in V1, highlighting salient contours and replicating the time course of contextual influences. We show by means of phase-plane analysis that the model operates stably even in the presence of large inputs. Our model shows how a simple form of top-down modulation of the effective connectivity of intrinsic cortical connections among biophysically realistic neurons can account for some of the response changes seen in perceptual learning and task switching.

GABA increases stimulus selectivity of neurons in primary visual cortices of cats chronically treated with morphine

Chronic exposure to opiates leads to maladaptive changes in various functions of the mammalian brain, including properties of neuronal response in the visual pathway. In the present study, we used multibarreled microelectrodes to study the effects of electrophoretic application of GABA or the GABAA receptor antagonist bicuculline on the properties of individual V1 neurons in cats which were chronically treated with morphine (MTCs) or saline (STCs). The results showed that the application of either GABA or bicuculline significantly altered spontaneous activity as well as orientation selectivity and signal-to-noise ratios of visually evoked responses in both MTCs and STCs. While administration of bicuculline exerted a much stronger effect on neuronal responses of V1 neurons of the STCs, administration of GABA resulted in improved visual function mainly in MTCs. Most importantly, GABA-treated cells in area V1 of the MTCs displayed similar responses to those in STCs. These results are consistent with the idea that: (1) there is a decrease in GABA-mediated inhibition in area V1 of cats exposed chronically to morphine, and (2) this decrease contributes strongly to the apparent degradation of neuronal function observed in animals exposed chronically to morphine.

Neural correlates of stimulus spatial frequency-dependent contrast detection

Psychophysical studies on human and non-human vertebrate species have shown that visual contrast sensitivity function (CSF) peaks at a certain stimulus spatial frequency and declines in both lower and higher spatial frequencies. The underlying neural substrate and mechanisms remain in debate. Here, we investigated the role of primary visual cortex (V1: area 17) in spatial frequency-dependent contrast detection in cats. Perceptual CSFs of three cats were measured using a two-alternative forced-choice task. The responses of V1 neurons to their optimal visual stimuli in a range of luminance contrast levels (from 0 to 1.0) were recorded subsequently using in vivo extracellular single-unit recording techniques. The contrast sensitivity of each neuron was determined. The neuronal CSF for each cat was constructed from the mean contrast sensitivity of neurons with different preferred stimulus spatial frequencies. (1) The perceptual and neuronal CSFs of each of the three cats exhibited a similar shape with peak amplitude near 0.4 cpd. (2) The neuronal CSF of each cat was highly correlated with its perceptual CSF. (3) V1 neurons with different preferred stimulus spatial frequencies had different contrast gains. (1) Contrast detection of visual stimuli with different spatial frequencies may likely involve population coding of V1 neurons with different preferred stimulus spatial frequencies. (2) Difference in contrast gain may underlie the observed contrast sensitivity variation of V1 neurons with different preferred stimulus spatial frequencies, possibly from either evolution or postnatal visual experiences.

Modulation of V1 Spike Response by Temporal Interval of Spatiotemporal Stimulus Sequence

The spike activity of single neurons of the primary visual cortex (V1) becomes more selective and reliable in response to wide-field natural scenes compared to smaller stimuli confined to the classical receptive field (RF). However, it is largely unknown what aspects of natural scenes increase the selectivity of V1 neurons. One hypothesis is that modulation by surround interaction is highly sensitive to small changes in spatiotemporal aspects of RF surround. Such a fine-tuned modulation would enable single neurons to hold information about spatiotemporal sequences of oriented stimuli, which extends the role of V1 neurons as a simple spatiotemporal filter confined to the RF. In the current study, we examined the hypothesis in the V1 of awake behaving monkeys, by testing whether the spike response of single V1 neurons is modulated by temporal interval of spatiotemporal stimulus sequence encompassing inside and outside the RF. We used two identical Gabor stimuli that were sequentially presented with a variable stimulus onset asynchrony (SOA): the preceding one (S1) outside the RF and the following one (S2) in the RF. This stimulus configuration enabled us to examine the spatiotemporal selectivity of response modulation from a focal surround region. Although S1 alone did not evoke spike responses, visual response to S2 was modulated for SOA in the range of tens of milliseconds. These results suggest that V1 neurons participate in processing spatiotemporal sequences of oriented stimuli extending outside the RF.

P1-4: Neural Correlates of Fading Illusion Revealed in Responses of V1 Neurons

Visual stimuli without sharp edges fade gradually under visual fixation. This phenomenon is known as Troxler fading or fading illusion. Traditionally, this fading is explained by a hypothesis that physical stimulus is cancelled by a negative image generated in the visual pathway, because the negative image is perceived momentarily when the physical stimulus is removed suddenly. One prediction that may be tested neurophysiologically is that, in the faded or adapted state, visual neurons actually respond to a blank screen, as if they actually ‘see’ the negative image. To examine this prediction in cat V1, we measured the contrast response function of single neurons by presenting flashed grating stimuli of various contrasts (7 contrasts in straddle, ±25%, range and pedestal, within 0–50%, range; negative values for phase reversal) in a rapid succession. Data were analyzed using reverse correlation. The orientation and spatial frequency of gratings were fixed at the optimal value of each cell. We found that V...

A Retinal Source of Spatial Contrast Gain Control

Sensory cortex is able to encode a broad range of stimulus features despite a great variation in signal strength. In cat primary visual cortex (V1), for example, neurons are able to extract stimulus features like orientation or spatial configuration over a wide range of stimulus contrasts. The contrast-invariant spatial tuning found in V1 neuron responses has been modeled as a gain control mechanism, but at which stage of the visual pathway it emerges has remained unclear. Here we describe our findings that contrast-invariant spatial tuning occurs not only in the responses of lateral geniculate nucleus (LGN) relay cells but also in their afferent retinal input. Our evidence suggests that a similar contrast-invariant mechanism is found throughout the stages of the early visual pathway, and that the contrast-invariant spatial selectivity is evident in both retinal ganglion cell and LGN cell responses.

Context Matters: The Illusive Simplicity of Macaque V1 Receptive Fields

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