Automatic mapping of visual cortex receptive fields: a fast and precise algorithm

On the Functional Role of Gamma Synchronization in the Retinogeniculate System of the Cat

Fast gamma oscillations, generated within the retina, and transmitted to the cortex via the lateral geniculate nucleus (LGN), are thought to carry information about stimulus size and continuity. This hypothesis relies mainly on studies conducted under anesthesia and the extent to which it holds under more naturalistic conditions remains unclear. Using multielectrode recordings of spiking activity in the retina and the LGN of both male and female cats, we show that visually driven gamma oscillations are absent for awake states and are highly dependent on halothane (or isoflurane). Under ketamine, responses were nonoscillatory, as in the awake condition. Response entrainment to the monitor refresh was commonly observed up to 120 Hz and was superseded by the gamma oscillatory responses induced by halothane. Given that retinal gamma oscillations are contingent on halothane anesthesia and absent in the awake cat, such oscillations should be considered artifactual, thus playing no functional role in vision.SIGNIFICANCE STATEMENT Gamma rhythms have been proposed to be a robust encoding mechanism critical for visual processing. In the retinogeniculate system of the cat, many studies have shown gamma oscillations associated with responses to static stimuli. Here, we extend these observations to dynamic stimuli. An unexpected finding was that retinal gamma responses strongly depend on halothane concentration levels and are absent in the awake cat. These results weaken the notion that gamma in the retina is relevant for vision. Notably, retinal gamma shares many of the properties of cortical gamma. In this respect, oscillations induced by halothane in the retina may serve as a valuable preparation, although artificial, for studying oscillatory dynamics.

Cortical maps as a fundamental neural substrate for visual representation

Visual perception is the product of serial hierarchical processing, parallel processing, and remapping on a dynamic network involving several topographically organized cortical visual areas. Here, we will focus on the topographical organization of cortical areas and the different kinds of visual maps found in the primate brain. We will interpret our findings in light of a broader representational framework for perception. Based on neurophysiological data, our results do not support the notion that vision can be explained by a strict representational model, where the objective visual world is faithfully represented in our brain. On the contrary, we find strong evidence that vision is an active and constructive process from the very initial stages taking place in the eye and from the very initial stages of our development. A constructive interplay between perceptual and motor systems (e.g., during saccadic eye movements) is actively learnt from early infancy and ultimately provides our fluid stable visual perception of the world.

Visual Field Coordinate Systems in Visual Neurophysiology

In this work, algorithms have been developed to: 1. Compare visual field coordinate data, presented in different representation systems; 2. Determine the distance in degrees between any two points in the visual field; 3. Predict new coordinates of a given point in the visual field after the rotation of the head, around axes that pass through the nodal point of the eye. Formulas are proposed for the transformation of Polar coordinates into Zenithal Equatorial coordinates and vice versa; of Polar coordinates into Gnomic Equatorial of double meridians and vice versa; and projections of double meridians system into Zenithal Equatorial and vice versa. Using the transformation of polar coordinates into Cartesian coordinates, we can also propose algorithms for rotating the head or the visual field representation system around the dorsoventral, lateral-lateral and anterior-posterior axes, in the mediolateral, dorsoventral and clockwise directions, respectively. In addition, using the concept of the scalar product in linear algebra, we propose new algorithms for calculating the distance between two points and to determine the area of receptive fields in the visual field.

Microstimulation of visual area V4 improves visual stimulus detection

Neuronal activity in visual area V4 is well known to be modulated by selective attention, and there are reports on V4 lesions leading to attentional deficits. However, it remains unclear whether V4 microstimulation can elicit attentional benefits. To test this hypothesis, we performed local microstimulation in area V4 and explored its spatial and time dynamics in two macaque monkeys performing a visual detection task. Microstimulation was delivered via chronically implanted multi-electrode arrays. We found that microstimulation increases average performance by 35% and reduces luminance detection thresholds by −30%. This benefit critically depends on the onset of microstimulation relative to the stimulus, consistent with known dynamics of endogenous attention. These results show that local microstimulation of V4 can improve behavior and highlight the critical role of V4 for attention.

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Microstimulation of visual area V4 improves visual stimulus detection

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Effects of V4 microstimulation extend to the other hemifield

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Microstimulation effects are time dependent and consistent with attention dynamics

Populations of local direction-selective cells encode global motion patterns generated by self-motion

Self-motion generates visual patterns on the eye that are important for navigation. These optic flow patterns are encoded by the population of local direction–selective cells in the mouse retina, whereas in flies, local direction–selective T4/T5 cells are thought to be uniformly tuned. How complex global motion patterns can be computed downstream is unclear. We show that the population of T4/T5 cells in Drosophila encodes global motion patterns. Whereas the mouse retina encodes four types of optic flow, the fly visual system encodes six. This matches the larger number of degrees of freedom and the increased complexity of translational and rotational motion patterns during flight. The four uniformly tuned T4/T5 subtypes described previously represent a local subset of the population. Thus, a population code for global motion patterns appears to be a general coding principle of visual systems that matches local motion responses to modes of the animal’s movement.

The role of feedback projections in feature tuning and neuronal excitability in the early primate visual system

A general assumption in visual neuroscience is that basic receptive field properties such as orientation and direction selectivity are constructed within intrinsic neuronal circuits and feedforward projections. In addition, it is assumed that general neuronal excitability and responsiveness in early visual areas is to a great extent independent of feedback input originating in areas higher in the stream. Here, we review the contribution of feedback projections from MT, V4 and pulvinar to the receptive field properties of V2 neurons in the anesthetized and paralyzed monkey. Importantly, our results contradict both of these assumptions. We separately inactivated each of these three brain regions using GABA pressure injections, while simultaneously recording V2 single unit activity before and hours after inactivation. Recordings and GABA injections were carried out in topographically corresponding regions of the visual field. We outline the changes in V2 activity, responsiveness and receptive field properties for early, mid and late post-injection phases. Immediately after injection, V2 activity is globally suppressed. Subsequently, there is an increase in stimulus-driven relative to spontaneous neuronal activity, which improves the signal-to-noise coding for the oriented moving bars. Notably, V2 tuning properties change substantially relative to its pre-injection selectivity profile. The resulting increase or decrease in selectivity could not be readily predicted based on the selectivity profile of the inactivated site. Finally, V2 activity rebounds before returning to it pre-injection profile Our results show that feedback projections profoundly impact neuronal circuits in early visual areas, and may have been heretofore largely underestimated in their physiological role.

Visual Neuroscience Methods for Marmosets: Efficient Receptive Field Mapping and Head-Free Eye Tracking

The marmoset has emerged as a promising primate model system, in particular for visual neuroscience. Many common experimental paradigms rely on head fixation and an extended period of eye fixation during the presentation of salient visual stimuli. Both of these behavioral requirements can be challenging for marmosets. Here, we present two methodological developments, each addressing one of these difficulties. First, we show that it is possible to use a standard eye-tracking system without head fixation to assess visual behavior in the marmoset. Eye-tracking quality from head-free animals is sufficient to obtain precise psychometric functions from a visual acuity task. Second, we introduce a novel method for efficient receptive field (RF) mapping that does not rely on moving stimuli but uses fast flashing annuli and wedges. We present data recorded during head-fixation in areas V1 and V6 and show that RF locations are readily obtained within a short period of recording time. Thus, the methodological advancements presented in this work will contribute to establish the marmoset as a valuable model in neuroscience.

Reward-Related Suppression of Neural Activity in Macaque Visual Area V4

In order for organisms to survive, they need to detect rewarding stimuli, for example, food or a mate, in a complex environment with many competing stimuli. These rewarding stimuli should be detected even if they are nonsalient or irrelevant to the current goal. The value-driven theory of attentional selection proposes that this detection takes place through reward-associated stimuli automatically engaging attentional mechanisms. But how this is achieved in the brain is not very well understood. Here, we investigate the effect of differential reward on the multiunit activity in visual area V4 of monkeys performing a perceptual judgment task. Surprisingly, instead of finding reward-related increases in neural responses to the perceptual target, we observed a large suppression at the onset of the reward indicating cues. Therefore, while previous research showed that reward increases neural activity, here we report a decrease. More suppression was caused by cues associated with higher reward than with lower reward, although neither cue was informative about the perceptually correct choice. This finding of reward-associated neural suppression further highlights normalization as a general cortical mechanism and is consistent with predictions of the value-driven attention theory.

High-density electrophysiological recordings in macaque using a chronically implanted 128-channel passive silicon probe

OBJECTIVE

The analysis of interactions among local populations of neurons in the cerebral cortex (e.g. within cortical microcolumns) requires high resolution and high channel count recordings from chronically implanted laminar microelectrode arrays. The request for high-density recordings of a large number of recording sites can presently only be accomplished by probes realized using complementary metal-oxide-semiconductor (CMOS) technology. In preparation for their use in non-human primates, we aimed for neural probe validation in a head-fixed approach analyzing the long-term recording capability.

APPROACH

We examined chronically implanted silicon-based laminar probes, realized using a CMOS technology in combination with micromachining, to record from the primary visual cortex (V1) of a monkey. We used a passive CMOS probe that had 128 electrodes arranged at a pitch of 22.5 µm in four columns and 32 rows on a slender shank. In order to validate the performance of a dedicated microdrive, the overall dimensions of probe and interface boards were chosen to be compatible with the final active CMOS probe comprising integrated circuitry.

MAIN RESULTS

Using the passive probe, we recorded simultaneously local field potentials (LFP) and spiking multiunit activity (MUA) in V1 of an awake behaving macaque monkey. We found that an insertion through the dura and subsequent readjustments of the chronically implanted neural probe was possible and allowed us to record stable LFPs for more than five months. The quality of MUA degraded within the first month but remained sufficiently high to permit mapping of receptive fields during the full recording period.

SIGNIFICANCE

We conclude that the passive silicon probe enables semi-chronic recordings of high quality of LFP and MUA for a time span exceeding five months. The new microdrive compatible with a commercial recording chamber successfully demonstrated the readjustment of the probe position while the implemented plug structure effectively reduced brain tissue movement relative to the probe.

Visual epidural field potentials possess high functional specificity in single trials

Recordings of epidural field potentials (EFPs) allow neuronal activity to be acquired over a large region of cortical tissue with minimal invasiveness. Because electrodes are placed on top of the dura and do not enter the neuronal tissue, EFPs offer intriguing options for both clinical and basic science research. On the other hand, EFPs represent the integrated activity of larger neuronal populations and possess a higher trial-by-trial variability and a reduced signal-to-noise ratio due the additional barrier of the dura. It is thus unclear whether and to what extent EFPs have sufficient spatial selectivity to allow for conclusions about the underlying functional cortical architecture, and whether single EFP trials provide enough information on the short timescales relevant for many clinical and basic neuroscience purposes. We used the high spatial resolution of primary visual cortex to address these issues and investigated the extent to which very short EFP traces allow reliable decoding of spatial information. We briefly presented different visual objects at one of nine closely adjacent locations and recorded neuronal activity with a high-density epidural multielectrode array in three macaque monkeys. With the use of receiver operating characteristics (ROC) to identify the most informative data, machine-learning algorithms provided close-to-perfect classification rates for all 27 stimulus conditions. A binary classifier applying a simple max function on ROC-selected data further showed that single trials might be classified with 100% performance even without advanced offline classifiers. Thus, although highly variable, EFPs constitute an extremely valuable source of information and offer new perspectives for minimally invasive recording of large-scale networks.NEW & NOTEWORTHY Epidural field potential (EFP) recordings provide a minimally invasive approach to investigate large-scale neural networks, but little is known about whether they possess the required specificity for basic and clinical neuroscience. By making use of the spatial selectivity of primary visual cortex, we show that single-trial information can be decoded with close-to-perfect performance, even without using advanced classifiers and based on very few data. This labels EFPs as a highly attractive and widely usable signal.

High throughput, rapid receptive field estimation for global motion sensitive neurons using a contiguous motion noise stimulus

BACKGROUND

The systematic characterization of receptive fields (RF) is essential for understanding visual motion processing. The performance of RF estimation depends on the employed stimuli, the complexity of the encoded features, and the quality of the activity readout. Calcium imaging is an attractive readout method for high-throughput neuronal activity recordings. However, calcium recordings are oftentimes noisy and of low temporal resolution. The RF estimation of neurons sensitive to global motion is particularly challenging due to their potentially complex combination of preferred directions across visual field positions.

NEW METHOD

Here, we present a novel noise stimulus, which is enriched with spatiotemporally contiguous motion and thus triggers robust calcium responses. We combined this contiguous motion noise (CMN) stimulus with reverse correlation followed by a two-step nonparametric cluster-based bootstrapping test for efficient and reliable RF estimation.

RESULTS

The in silico evaluation of our approach showed that RF centre positions and preferred directions are reliably detected in most of the simulated neurons. Suppressive RF components were detected in 40% of the simulated neurons. We successfully applied our approach to estimate the RFs of 163 motion-sensitive neurons in vivo within 40 min in the pretectum of zebrafish. Many in vivo neurons were sensitive to elaborate directional flow fields in their RFs.

COMPARISON WITH EXISTING METHODS

Our approach outperforms white noise methods and others due to the optimized motion stimulus statistics and ascertainable fine RF structures.

CONCLUSIONS

The CMN method enables efficient, non-biased RF estimation and will benefit systematic high-throughput investigations of RFs using calcium imaging.

Optimizing the Yield of Multi-Unit Activity by Including the Entire Spiking Activity

Neurophysiological data acquisition using multi-electrode arrays and/or (semi-) chronic recordings frequently has to deal with low signal-to-noise ratio (SNR) of neuronal responses and potential failure of detecting evoked responses within random background fluctuations. Conventional methods to extract action potentials (spikes) from background noise often apply thresholds to the recorded signal, usually allowing reliable detection of spikes when data exhibit a good SNR, but often failing when SNR is poor. We here investigate a threshold-independent, fast, and automated procedure for analysis of low SNR data, based on fullwave-rectification and low-pass filtering the signal as a measure of the entire spiking activity (ESA). We investigate the sensitivity and reliability of the ESA-signal for detecting evoked responses by applying an automated receptive field (RF) mapping procedure to semi-chronically recorded data from primary visual cortex (V1) of five macaque monkeys. For recording sites with low SNR, the usage of ESA improved the detection rate of RFs by a factor of 2.5 in comparison to MUA-based detection. For recording sites with medium and high SNR, ESA delivered 30% more RFs than MUA. This significantly higher yield of ESA-based RF-detection still hold true when using an iterative procedure for determining the optimal spike threshold for each MUA individually. Moreover, selectivity measures for ESA-based RFs were quite compatible with MUA-based RFs. Regarding RF size, ESA delivered larger RFs than thresholded MUA, but size difference was consistent over all SNR fractions. Regarding orientation selectivity, ESA delivered more sites with significant orientation-dependent responses but with somewhat lower orientation indexes than MUA. However, preferred orientations were similar for both signal types. The results suggest that ESA is a powerful signal for applications requiring automated, fast, and reliable response detection, as e.g., brain-computer interfaces and neuroprosthetics, due to its high sensitivity and its independence from user-dependent intervention. Because the full information of the spiking activity is preserved, ESA also constitutes a valuable alternative for offline analysis of data with limited SNR.

Stimulus complexity shapes response correlations in primary visual cortex

Spike count correlations (SCCs) are ubiquitous in sensory cortices, are characterized by rich structure, and arise from structured internal dynamics. However, most theories of visual perception treat contributions of neurons to the representation of stimuli independently and focus on mean responses. Here, we argue that, in a functional model of visual perception, featuring probabilistic inference over a hierarchy of features, inferences about high-level features modulate inferences about low-level features ultimately introducing structured internal dynamics and patterns in SCCs. Specifically, high-level inferences for complex stimuli establish the local context in which neurons in the primary visual cortex (V1) interpret stimuli. Since the local context differentially affects multiple neurons, this conjecture predicts specific modulations in the fine structure of SCCs as stimulus identity and, more importantly, stimulus complexity varies. We designed experiments with natural and synthetic stimuli to measure the fine structure of SCCs in V1 of awake behaving macaques and assessed their dependence on stimulus identity and stimulus statistics. We show that the fine structure of SCCs is specific to the identity of natural stimuli and changes in SCCs are independent of changes in response mean. Critically, we demonstrate that stimulus specificity of SCCs in V1 can be directly manipulated by altering the amount of high-order structure in synthetic stimuli. Finally, we show that simple phenomenological models of V1 activity cannot account for the observed SCC patterns and conclude that the stimulus dependence of SCCs is a natural consequence of structured internal dynamics in a hierarchical probabilistic model of natural images.

A 3D Convolutional Neural Network to Model Retinal Ganglion Cell's Responses to Light Patterns in Mice

Deep Learning offers flexible powerful tools that have advanced our understanding of the neural coding of neurosensory systems. In this work, a 3D Convolutional Neural Network (3D CNN) is used to mimic the behavior of a population of mice retinal ganglion cells in response to different light patterns. For this purpose, we projected homogeneous RGB flashes and checkerboards stimuli with variable luminances and wavelength spectrum to mimic a more naturalistic stimuli environment onto the mouse retina. We also used white moving bars in order to localize the spatial position of the recorded cells. Then recorded spikes were smoothed with a Gaussian kernel and used as the output target when training a 3D CNN in a supervised way. To find a suitable model, two hyperparameter search stages were performed. In the first stage, a trial and error process allowed us to obtain a system that is able to fit the neurons firing rates. In the second stage, a systematic procedure was used to compare several gradient-based optimizers, loss functions and the model's convolutional layers number. We found that a three layered 3D CNN was able to predict the ganglion cells firing rates with high correlations and low prediction error, as measured with Mean Squared Error and Dynamic Time Warping in test sets. These models were either competitive or outperformed other models used already in neuroscience, as Feed Forward Neural Networks and Linear-Nonlinear models. This methodology allowed us to capture the temporal dynamic response patterns in a robust way, even for neurons with high trial-to-trial variable spontaneous firing rates, when providing the peristimulus time histogram as an output to our model.

Neuronal response properties across cytochrome oxidase stripes in primate V2

Cytochrome oxidase histochemistry reveals large-scale cortical modules in area V2 of primates known as thick, thin, and interstripes. Anatomical, electrophysiological, and tracing studies suggest that V2 cytochrome oxidase stripes participate in functionally distinct streams of visual information processing. However, there is controversy whether the different V2 compartments indeed correlate with specialized neuronal response properties. We used multiple-electrode arrays (16 × 2, 8 × 4 and 4 × 4 matrices) to simultaneously record the spiking activity (N = 190 single units) across distinct V2 stripes in anesthetized and paralyzed capuchin monkeys (N = 3 animals, 6 hemispheres). Visual stimulation consisted of moving bars and full-field gratings with different contrasts, orientations, directions of motion, spatial frequencies, velocities, and color contrasts. Interstripe neurons exhibited the strongest orientation and direction selectivities compared to the thick and thin stripes, with relatively stronger coding for orientation. Additionally, they responded best to higher spatial frequencies and to lower stimulus velocities. Thin stripes showed the highest proportion (80%) of neurons selective to color contrast (compared to 47% and 21% for thick and interstripes, respectively). The great majority of the color selective cells (86%) were also orientation selective. Additionally, thin stripe neurons continued to increase their firing rate for stimulus contrasts above 50%, while thick and interstripe neurons already exhibited some degree of response saturation at this point. Thick stripes best coded for lower spatial frequencies and higher stimulus velocities. In conclusion, V2 CytOx stripes exhibit a mixed degree of segregation and integration of information processing, shedding light into the early mechanisms of vision.

Callosal Influence on Visual Receptive Fields Has an Ocular, an Orientation-and Direction Bias

One leading hypothesis on the nature of visual callosal connections (CC) is that they replicate features of intrahemispheric lateral connections. However, CC act also in the central part of the binocular visual field. In agreement, early experiments in cats indicated that they provide the ipsilateral eye part of binocular receptive fields (RFs) at the vertical midline (Berlucchi and Rizzolatti, 1968), and play a key role in stereoscopic function. But until today callosal inputs to receptive fields activated by one or both eyes were never compared simultaneously, because callosal function has been often studied by cutting or lesioning either corpus callosum or optic chiasm not allowing such a comparison. To investigate the functional contribution of CC in the intact cat visual system we recorded both monocular and binocular neuronal spiking responses and receptive fields in the 17/18 transition zone during reversible deactivation of the contralateral hemisphere. Unexpectedly from many of the previous reports, we observe no change in ocular dominance during CC deactivation. Throughout the transition zone, a majority of RFs shrink, but several also increase in size. RFs are significantly more affected for ipsi- as opposed to contralateral stimulation, but changes are also observed with binocular stimulation. Noteworthy, RF shrinkages are tiny and not correlated to the profound decreases of monocular and binocular firing rates. They depend more on orientation and direction preference than on eccentricity or ocular dominance of the receiving neuron's RF. Our findings confirm that in binocularly viewing mammals, binocular RFs near the midline are constructed via the direct geniculo-cortical pathway. They also support the idea that input from the two eyes complement each other through CC: Rather than linking parts of RFs separated by the vertical meridian, CC convey a modulatory influence, reflecting the feature selectivity of lateral circuits, with a strong cardinal bias.

Motion contrast in primary visual cortex: a direct comparison of single neuron and population encoding

Features from outside the classical receptive field (CRF) can modulate the stimulus-driven activity of single cells in the primary visual cortex. This modulation, mediated by horizontal and feedback networks, has been extensively described as a variation of firing rate and is considered the basis of processing features as, for example, motion contrast. However, surround influences have also been identified in pairwise spiking or local field coherence. Yet, evidence about co-existence and integration of different neural signatures remains elusive. To compare multiple signatures, we recorded spiking and LFP activity evoked by stimuli exhibiting a motion contrast in the CRFs surround in anesthetized cat primary visual cortex. We chose natural-like scenes over gratings to avoid predominance of simple visual features, which could be easily represented by a rate code. We analyzed firing rates and phase-locking to low-gamma frequency in single cells and neuronal assemblies. Motion contrast was reflected in all measures but in semi-independent populations. Whereas activation of assemblies accompanied single neuron rates, their phase relations were modulated differently. Interestingly, only assembly phase relations mirrored the direction of movement of the surround and were selectively affected by thermal deactivation of visual interhemispheric connections. We argue that motion contrast can be reflected in complementary and superimposed neuronal signatures that can represent different surround features in independent neuronal populations.

Connecting the Brain to Itself through an Emulation

Pilot clinical trials of human patients implanted with devices that can chronically record and stimulate ensembles of hundreds to thousands of individual neurons offer the possibility of expanding the substrate of cognition. Parallel trains of firing rate activity can be delivered in real-time to an array of intermediate external modules that in turn can trigger parallel trains of stimulation back into the brain. These modules may be built in software, VLSI firmware, or biological tissue as in vitro culture preparations or in vivo ectopic construct organoids. Arrays of modules can be constructed as early stage whole brain emulators, following canonical intra- and inter-regional circuits. By using machine learning algorithms and classic tasks known to activate quasi-orthogonal functional connectivity patterns, bedside testing can rapidly identify ensemble tuning properties and in turn cycle through a sequence of external module architectures to explore which can causatively alter perception and behavior. Whole brain emulation both (1) serves to augment human neural function, compensating for disease and injury as an auxiliary parallel system, and (2) has its independent operation bootstrapped by a human-in-the-loop to identify optimal micro- and macro-architectures, update synaptic weights, and entrain behaviors. In this manner, closed-loop brain-computer interface pilot clinical trials can advance strong artificial intelligence development and forge new therapies to restore independence in children and adults with neurological conditions.

Modular Representation of Luminance Polarity in the Superficial Layers of Primary Visual Cortex

The spatial arrangement of luminance increments (ON) and decrements (OFF) falling on the retina provides a wealth of information used by central visual pathways to construct coherent representations of visual scenes. But how the polarity of luminance change is represented in the activity of cortical circuits remains unclear. Using wide-field epifluorescence and two-photon imaging we demonstrate a robust modular representation of luminance polarity (ON or OFF) in the superficial layers of ferret primary visual cortex. Polarity-specific domains are found with both uniform changes in luminance and single light/dark edges, and include neurons selective for orientation and direction of motion. The integration of orientation and polarity preference is evident in the selectivity and discrimination capabilities of most layer 2/3 neurons. We conclude that polarity selectivity is an integral feature of layer 2/3 neurons, ensuring that the distinction between light and dark stimuli is available for further processing in downstream extrastriate areas.

Input and output gain modulation by the lateral interhemispheric network in early visual cortex

Neurons in the cerebral cortex are constantly integrating different types of inputs. Dependent on their origin, these inputs can be modulatory in many ways and, for example, change the neuron's responsiveness, sensitivity, or selectivity. To investigate the modulatory role of lateral input from the same level of cortical hierarchy, we recorded in the primary visual cortex of cats while controlling synaptic input from the corresponding contralateral hemisphere by reversible deactivation. Most neurons showed a pronounced decrease in their response to a visual stimulus of different contrasts and orientations. This indicates that the lateral network acts via an unspecific gain-setting mechanism, scaling the output of a neuron. However, the interhemispheric input also changed the contrast sensitivity of many neurons, thereby acting on the input. Such a contrast gain mechanism has important implications because it extends the role of the lateral network from pure response amplification to the modulation of a specific feature. Interestingly, for many neurons, we found a mixture of input and output gain modulation. Based on these findings and the known physiology of callosal connections in the visual system, we developed a simple model of lateral interhemispheric interactions. We conclude that the lateral network can act directly on its target, leading to a sensitivity change of a specific feature, while at the same time it also can act indirectly, leading to an unspecific gain setting. The relative contribution of these direct and indirect network effects determines the outcome for a particular neuron.

Precise visuotopic organization of the blind spot representation in primate V1

The optic disk is a region of the retina consisting mainly of ganglion cell axons and blood vessels, which generates a visual scotoma known as the blind spot (BS). Information present in the surroundings of the BS can be used to complete the missing information. However, the neuronal mechanisms underlying these perceptual phenomena are poorly understood. We investigate the topography of the BS representation (BSR) in cortical area V1 of the capuchin monkey, using single and multiple electrodes. Receptive fields (RFs) of neurons inside the BSR were investigated using two distinct automatic bias-free mapping methods. The first method (local mapping) consisted of randomly flashing small white squares. For the second mapping method (global mapping), we used a single long bar that moved in one of eight directions. The latter stimulus was capable of eliciting neuronal activity inside the BSR, possibly attributable to long-range surround activity taking place outside the borders of the BSR. Importantly, we found that the neuronal activity inside the BSR is organized topographically in a manner similar to that found in other portions of V1. On average, the RFs inside the BS were larger than those outside. However, no differences in orientation or direction tuning were found between the two regions. We propose that area V1 exhibits a continuous functional topographic map, which is not interrupted in the BSR, as expected by the distribution of photoreceptors in the retina. Thus V1 topography is better described as “visuotopic” rather than as a discontinuous “retinotopic” map.