Receptive Field Location Research Articles

A competition framework for fixation-preference in strabismus.

Strabismic subjects often develop the ability to fixate on a target with either eye. Previous studies have shown that fixation-preference behavior varies systematically depending on spatial location of the target. We hypothesized that, when an eccentric target is presented, oculomotor fixation-preference in strabismus may be accounted for in a competitive decision framework wherein the brain must choose between two possible retinal errors to prepare a conjugate saccade that results in one of the eyes acquiring the eccentric target. We tested this framework by recording from visuo-motor neurons in the superior colliculus (SC) of two strabismic rhesus macaque monkeys as they performed a delayed saccade task under binocular viewing conditions. In one experiment, visual targets were presented at one of two locations corresponding to the neuronal receptive field location with respect to either the viewing or the deviated eye. Robust visual sensory responses were observed when targets were presented at either location indicating the presence of competing sensory signals for eye-choice. In a second experiment, a single visual target was placed at the neuronal receptive field location where the animal switched fixation on some trials and did not on other trials. At such target locations where either eye could acquire the target, both visual and build-up activity was greater in trials when the saccade encoded by the neuron "won." These findings provide evidence for the influence of visual suppression within SC sensory activity and support the possible utilization of a competition framework, one that has been previously described for when a binocularly aligned animal chooses from among multiple targets, to drive fixation-preference behavior in strabismus.

Intrinsic timescales in the visual cortex change with selective attention and reflect spatial connectivity

Intrinsic timescales characterize dynamics of endogenous fluctuations in neural activity. Variation of intrinsic timescales across the neocortex reflects functional specialization of cortical areas, but less is known about how intrinsic timescales change during cognitive tasks. We measured intrinsic timescales of local spiking activity within columns of area V4 in male monkeys performing spatial attention tasks. The ongoing spiking activity unfolded across at least two distinct timescales, fast and slow. The slow timescale increased when monkeys attended to the receptive fields location and correlated with reaction times. By evaluating predictions of several network models, we found that spatiotemporal correlations in V4 activity were best explained by the model in which multiple timescales arise from recurrent interactions shaped by spatially arranged connectivity, and attentional modulation of timescales results from an increase in the efficacy of recurrent interactions. Our results suggest that multiple timescales may arise from the spatial connectivity in the visual cortex and flexibly change with the cognitive state due to dynamic effective interactions between neurons.

Brain2Pix: Fully convolutional naturalistic video frame reconstruction from brain activity.

Reconstructing complex and dynamic visual perception from brain activity remains a major challenge in machine learning applications to neuroscience. Here, we present a new method for reconstructing naturalistic images and videos from very large single-participant functional magnetic resonance imaging data that leverages the recent success of image-to-image transformation networks. This is achieved by exploiting spatial information obtained from retinotopic mappings across the visual system. More specifically, we first determine what position each voxel in a particular region of interest would represent in the visual field based on its corresponding receptive field location. Then, the 2D image representation of the brain activity on the visual field is passed to a fully convolutional image-to-image network trained to recover the original stimuli using VGG feature loss with an adversarial regularizer. In our experiments, we show that our method offers a significant improvement over existing video reconstruction techniques.

Unraveling neural coding of dynamic natural visual scenes via convolutional recurrent neural networks

SummaryTraditional models of retinal system identification analyze the neural response to artificial stimuli using models consisting of predefined components. The model design is limited to prior knowledge, and the artificial stimuli are too simple to be compared with stimuli processed by the retina. To fill in this gap with an explainable model that reveals how a population of neurons work together to encode the larger field of natural scenes, here we used a deep-learning model for identifying the computational elements of the retinal circuit that contribute to learning the dynamics of natural scenes. Experimental results verify that the recurrent connection plays a key role in encoding complex dynamic visual scenes while learning biological computational underpinnings of the retinal circuit. In addition, the proposed models reveal both the shapes and the locations of the spatiotemporal receptive fields of ganglion cells.

Unravelling Neural Coding of Dynamic Natural Visual Scenes via Convolutional Recurrent Neural Networks

Retina, providing and preprocessing almost all the visual information for brain, is a much sophisticated neural system than we think. In neural coding, the central goal is to finding the relationship between a cause (e.g. a visual stimulus) and the effect (i.e., the neural response). Neural system identification aims to reveal the computational black boxes by learning the stimulus-response relationship. Traditional models of retinal system identification analysis the neural respond to artificial stimulus by models consisted of predefined components. The design of the model is limited by prior knowledge, and the artificial stimulus is too simple to be compared with the stimulus actually processed by the retina. As the most successful prediction models, deep neural networks, have demonstrated powerful computational ability in neural coding. In this study, to fill in the gap of explainable model that reveals how population of neurons work together to encode the larger field of dynamic natural scenes, we used a deep learning model to identify the computational elements of the retinal neural system that contribute to learning of the dynamics of natural visual scenes. Specifically, the proposed model can separate intricate spatiotemporal patterns by leveraging building blocks of the neural network model. By using physiological data with sequential natural scene inputs, we verify that the recurrent connection plays a key role in encoding complex dynamic visual scenes while learning biological computational underpinnings of the retina circuit. Our model subsequently learns both the shapes and location of the spatiotemporal receptive fields of ganglion cells. Moreover, we propose a method for evaluating the importance of the kernels learned by the network model in encoding dynamic visual scenes, which allows us to disentangle the dynamic computational structure of the retina. These results provide new insights into understanding the encoding mechanisms of retinal neurons and promote model design in machine learning for computational vision involving complex dynamic visual scenes.

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.

Automatic Identification of Axon Bundle Activation for Epiretinal Prosthesis.

Objective:Retinal prostheses must be able to activate cells in a selective way in order to restore high-fidelity vision. However, inadvertent activation of far-away retinal ganglion cells (RGCs) through electrical stimulation of axon bundles can produce irregular and poorly controlled percepts, limiting artificial vision. In this work, we aim to provide an algorithmic solution to the problem of detecting axon bundle activation with a bi-directional epiretinal prostheses.Methods:The algorithm utilizes electrical recordings to determine the stimulation current amplitudes above which axon bundle activation occurs. Bundle activation is defined as the axonal stimulation of RGCs with unknown soma and receptive field locations, typically beyond the electrode array. The method exploits spatiotemporal characteristics of electrically-evoked spikes to overcome the challenge of detecting small axonal spikes.Results:The algorithm was validated using large-scale, single-electrode and short pulse, ex vivo stimulation and recording experiments in macaque retina, by comparing algorithmically and manually identified bundle activation thresholds. For 88% of the electrodes analyzed, the threshold identified by the algorithm was within ±10% of the manually identified threshold, with a correlation coefficient of 0.95.Conclusion:This works presents a simple, accurate and efficient algorithm to detect axon bundle activation in epiretinal prostheses.Significance:The algorithm could be used in a closed-loop manner by a future epiretinal prosthesis to reduce poorly controlled visual percepts associated with bundle activation. Activation of distant cells via axonal stimulation will likely occur in other types of retinal implants and cortical implants, and the method may therefore be broadly applicable.

Lack of Evidence for Stereotypical Direction Columns in the Mouse Superior Colliculus.

Neurons in the visual system can be spatially organized according to their response properties such as receptive field location and feature selectivity. For example, the visual cortex of many mammalian species contains orientation and direction columns where neurons with similar preferences are clustered. Here, we examine whether such a columnar structure exists in the mouse superior colliculus (SC), a prominent visual center for motion processing. By performing large-scale physiological recording and two-photon calcium imaging in adult male and female mice, we show that direction-selective neurons in the mouse SC are not organized into stereotypical columns as a function of their preferred directions, although clusters of similarly tuned neurons are seen in a minority of mice. Nearby neurons can prefer similar or opposite directions in a largely position-independent manner. This finding holds true regardless of animal state (anesthetized vs awake, running vs stationary), SC depth (most superficial lamina vs deeper in the SC), research technique (calcium imaging vs electrophysiology), and stimulus type (drifting gratings vs moving dots, full field vs small patch). Together, these results challenge recent reports of region-specific organizations in the mouse SC and reveal how motion direction is represented in this important visual center.

Long-term performance of Utah slanted electrode arrays and intramuscular electromyographic leads implanted chronically in human arm nerves and muscles

Objective. We explore the long-term performance and stability of seven percutaneous Utah Slanted Electrode Arrays (USEAs) and intramuscular recording leads (iEMGs) implanted chronically in the residual arm nerves and muscles of three human participants as a means to permanently restore sensorimotor function after transradial amputations. Approach. We quantify the number of functional recording and functional stimulating electrodes over time. We also calculate the signal-to-noise ratio (SNR) of USEA and iEMG recordings and quantify the stimulation current necessary to evoke detectable sensory percepts. Furthermore, we quantify the consistency of the sensory modality, receptive field location, and receptive field size of USEA-evoked percepts. Main results. In the most recent subject, involving USEAs with technical improvements, neural recordings persisted for 502 d (entire implant duration) and the number of functional recording electrodes for one USEA increased over time. However, for six out of seven USEAs across the three participants, the number of functional recording electrodes decreased within the first 2 months after implantation. The SNR of neural recordings and electromyographic recordings stayed relatively consistent over time. Sensory percepts were consistently evoked over the span of 14 months, were not significantly different in size, and highlighted the nerves’ fascicular organization. The percentage of percepts with consistent modality or consistent receptive field location between sessions (∼1 month apart) varied between 0%–86.2% and 9.1%–100%, respectively. Stimulation thresholds and electrode impedances increased initially but then remained relatively stable over time. Significance. This work demonstrates improved performance of USEAs, and provides a basis for comparing the longevity and stability of USEAs to that of other neural interfaces. USEAs provide a rich repertoire of neural recordings and sensory percepts. Although their performance still generally declines over time, functionality can persist long-term. Future work should leverage the results presented here to further improve USEA design or to develop adaptive algorithms that can maintain a high level of performance.

Effect of electrical stimulation of receptive fields in people with lower limb amputation on variables of gait

People with amputation may perceive phantom limb sensations or pain in the amputated body part when ipsilateral body-regions are stimulated. These body-regions are called receptive fields. This study assessed whether receptive fields change in size and position over the course of one month in people with trans-tibial amputation and whether electrical stimulation of these fields in synchrony with walking affects phantom sensations and variables of gait. Thirty-one subjects participated in this study. Receptive fields were mapped seven times over a one month period. Thereafter, the effect of electrical stimulation in synchrony with walking was compared to placebo stimulation in an acute setting with a randomized, single-blind gait analysis in 18 participants. Results showed that receptive field size and position presented an adequate degree of consistency (difference in point of first response position of 4.9±4.8cm and overlap of total receptive field area of 54.3±35.0 %) for future use of electrical stimulation. Gait parameters for everyday activities (speed, gait width, % stance and swing phase) as well as perception of phantom pain were not altered to a clinically relevant degree by electrical stimulation and no negative effects were reported. In conclusion: Location and size of receptive fields are consistent enough for daily electrical stimulation without laborious daily assessment. If applied acutely, no significant effect on gait or pain could be detected. However, results are promising enough to test chronic application of electrical stimulation during gait in a long-term setting.

Spatial Neuronal Integration Supports a Global Representation of Visual Numerosity in Primate Association Cortices.

Our sense of number rests on the activity of neurons that are tuned to the number of items and show great invariance across display formats and modalities. Whether numerosity coding becomes abstracted from local spatial representations characteristic of visual input is not known. We mapped the visual receptive fields (RFs) of numerosity-selective neurons in the pFC and ventral intraparietal area in rhesus monkeys. We found numerosity selectivity in pFC and ventral intraparietal neurons irrespective of whether they exhibited an RF and independent of the location of their RFs. RFs were not predictive of the preference of numerosity-selective neurons. Furthermore, the presence and location of RFs had no impact on tuning width and quality of the numerosity-selective neurons. These findings show that neurons in frontal and parietal cortices integrate abstract visuospatial stimuli to give rise to global and spatially released number representations as required for number perception.

Generative Feedback Explains Distinct Brain Activity Codes for Seen and Mental Images

The relationship between mental imagery and vision is a long-standing problem in neuroscience. Currently, it is not known whether differences between the activity evoked during vision and reinstated during imagery reflect different codes for seen and mental images. To address this problem, we modeled mental imagery in the human brain as feedback in a hierarchical generative network. Such networks synthesize images by feeding abstract representations from higher to lower levels of the network hierarchy. When higher processing levels are less sensitive to stimulus variation than lower processing levels, as in the human brain, activity in low-level visual areas should encode variation in mental images with less precision than seen images. To test this prediction, we conducted an fMRI experiment in which subjects imagined and then viewed hundreds of spatially varying naturalistic stimuli. To analyze these data, we developed imagery-encoding models. These models accurately predicted brain responses to imagined stimuli and enabled accurate decoding of their position and content. They also allowed us to compare, for every voxel, tuning to seen and imagined spatial frequencies, as well as the location and size of receptive fields in visual and imagined space. We confirmed our prediction, showing that, in low-level visual areas, imagined spatial frequencies in individual voxels are reduced relative to seen spatial frequencies and that receptive fields in imagined space are larger than in visual space. These findings reveal distinct codes for seen and mental images and link mental imagery to the computational abilities of generative networks.

Binocular Encoding in the Damselfly Pre-motor Target Tracking System.

Akin to all damselflies, Calopteryx (family Calopterygidae), commonly known as jewel wings or demoiselles, possess dichoptic (separated) eyes with overlapping visual fields of view. In contrast, many dragonfly species possess holoptic (dorsally fused) eyes with limited binocular overlap. We have here compared the neuronal correlates of target tracking between damselfly and dragonfly sister lineages and linked these changes in visual overlap to pre-motor neural adaptations. Although dragonflies attack prey dorsally, we show that demoiselles attack prey frontally. We identify demoiselle target-selective descending neurons (TSDNs) with matching frontal visual receptive fields, anatomically and functionally homologous to the dorsally positioned dragonfly TSDNs. By manipulating visual input using eyepatches and prisms, we show that moving target information at the pre-motor level depends on binocular summation in demoiselles. Consequently, demoiselles encode directional information in a binocularly fused frame of reference such that information of a target moving toward the midline in the left eye is fused with information of the target moving away from the midline in the right eye. This contrasts with dragonfly TSDNs, where receptive fields possess a sharp midline boundary, confining responses to a single visual hemifield in a sagittal frame of reference (i.e., relative to the midline). Our results indicate that, although TSDNs are conserved across Odonata, their neural inputs, and thus the upstream organization of the target tracking system, differ significantly and match divergence in eye design and predatory strategies. VIDEO ABSTRACT.

A model for the origin and development of visual orientation selectivity.

Orientation selectivity is a key property of primary visual cortex that contributes, downstream, to object recognition. The origin of orientation selectivity, however, has been debated for decades. It is known that on- and off-centre subcortical pathways converge onto single neurons in primary visual cortex, and that the spatial offset between these pathways gives rise to orientation selectivity. On- and off-centre pathways are intermingled, however, so it is unclear how their inputs to cortex come to be spatially segregated. We here describe a model in which the segregation occurs through Hebbian strengthening and weakening of geniculocortical synapses during the development of the visual system. Our findings include the following. 1. Neighbouring on- and off-inputs to cortex largely cancelled each other at the start of development. At each receptive field location, the Hebbian process increased the strength of one input sign at the expense of the other sign, producing a spatial segregation of on- and off-inputs. 2. The resulting orientation selectivity was precise in that the bandwidths of the orientation tuning functions fell within empirical estimates. 3. The model produced maps of preferred orientation–complete with iso-orientation domains and pinwheels–similar to those found in real cortex. 4. These maps did not originate in cortical processes, but from clustering of off-centre subcortical pathways and the relative location of neighbouring on-centre clusters. We conclude that a model with intermingled on- and off-pathways shaped by Hebbian synaptic plasticity can explain both the origin and development of orientation selectivity.

Superior Colliculus: A Vision for Orienting

The superior colliculus contains neurons sensitive to motion direction. New research shows that these neurons are anatomically clustered: those representing the region of visual space 'seen' by both eyes preferentially respond to nasal motion directions and others to opposite directions.

Engineering Artificial Somatosensation Through Cortical Stimulation in Humans.

Sensory feedback is a critical aspect of motor control rehabilitation following paralysis or amputation. Current human studies have demonstrated the ability to deliver some of this sensory information via brain-machine interfaces, although further testing is needed to understand the stimulation parameters effect on sensation. Here, we report a systematic evaluation of somatosensory restoration in humans, using cortical stimulation with subdural mini-electrocorticography (mini-ECoG) grids. Nine epilepsy patients undergoing implantation of cortical electrodes for seizure localization were also implanted with a subdural 64-channel mini-ECoG grid over the hand area of the primary somatosensory cortex (S1). We mapped the somatotopic location and size of receptive fields evoked by stimulation of individual channels of the mini-ECoG grid. We determined the effects on perception by varying stimulus parameters of pulse width, current amplitude, and frequency. Finally, a target localization task was used to demonstrate the use of artificial sensation in a behavioral task. We found a replicable somatotopic representation of the hand on the mini-ECoG grid across most subjects during electrical stimulation. The stimulus-evoked sensations were usually of artificial quality, but in some cases were more natural and of a cutaneous or proprioceptive nature. Increases in pulse width, current strength and frequency generally produced similar quality sensations at the same somatotopic location, but with a perception of increased intensity. The subjects produced near perfect performance when using the evoked sensory information in target acquisition tasks. These findings indicate that electrical stimulation of somatosensory cortex through mini-ECoG grids has considerable potential for restoring useful sensation to patients with paralysis and amputation.

Spatial elongation of population receptive field profiles revealed by model-free fMRI back-projection.

Estimates of visual field topographies in human visual cortex obtained through fMRI traveling wave techniques usually provide the parameters of population receptive field (pRF) location (polar angle, eccentricity) and receptive field size. These parameters are obtained by fitting the recorded data to a standard model population receptive field. In this work, pRF profiles are measured directly by back-projecting preprocessed fMRI time-series to sweeps of a bar across the visual field in different angles. The current data suggest that the model-free pRF profiles contain information not only about receptive field location and size but also about the pRF shape characteristics. The elongation (ellipticity) of pRFs decreases along the early visual hierarchy to a different degree for the ventral and the dorsal stream. Furthermore, ellipticity changes as a function of eccentricity. pRF orientation shows a high degree of collinearity with its angular position within the visual field. Using model-free pRF measurements, the traveling wave technique provides additional characteristics of pRF topographies that are not restricted to size and provide robust measures within the single subject.

Beyond the labeled line: variation in visual reference frames from intraparietal cortex to frontal eye fields and the superior colliculus.

We accurately perceive the visual scene despite moving our eyes ~3 times per second, an ability that requires incorporation of eye position and retinal information. In this study, we assessed how this neural computation unfolds across three interconnected structures: frontal eye fields (FEF), intraparietal cortex (LIP/MIP), and the superior colliculus (SC). Single-unit activity was assessed in head-restrained monkeys performing visually guided saccades from different initial fixations. As previously shown, the receptive fields of most LIP/MIP neurons shifted to novel positions on the retina for each eye position, and these locations were not clearly related to each other in either eye- or head-centered coordinates (defined as hybrid coordinates). In contrast, the receptive fields of most SC neurons were stable in eye-centered coordinates. In FEF, visual signals were intermediate between those patterns: around 60% were eye-centered, whereas the remainder showed changes in receptive field location, boundaries, or responsiveness that rendered the response patterns hybrid or occasionally head-centered. These results suggest that FEF may act as a transitional step in an evolution of coordinates between LIP/MIP and SC. The persistence across cortical areas of mixed representations that do not provide unequivocal location labels in a consistent reference frame has implications for how these representations must be read out. NEW & NOTEWORTHY How we perceive the world as stable using mobile retinas is poorly understood. We compared the stability of visual receptive fields across different fixation positions in three visuomotor regions. Irregular changes in receptive field position were ubiquitous in intraparietal cortex, evident but less common in the frontal eye fields, and negligible in the superior colliculus (SC), where receptive fields shifted reliably across fixations. Only the SC provides a stable labeled-line code for stimuli across saccades.

A predictive coding model of gaze shifts and the underlying neurophysiology

ABSTRACTA comprehensive model of gaze control must account for a number of empirical observations at both the behavioural and neurophysiological levels. The computational model presented in this article can simulate the coordinated movements of the eye, head, and body required to perform horizontal gaze shifts. In doing so it reproduces the predictable relationships between the movements performed by these different degrees of freedom (DOFs) in the primate. The model also accounts for the saccadic undershoot that accompanies large gaze shifts in the biological visual system. It can also account for our perception of a stable external world despite frequent gaze shifts and the ability to perform accurate memory-guided and double-step saccades. The proposed model also simulates peri-saccadic compression: the mis-localization of a briefly presented visual stimulus towards the location that is the target for a saccade. At the neurophysiological level, the proposed model is consistent with the existence of cortical neurons tuned to the retinal, head-centred, body-centred, and world-centred locations of visual stimuli and cortical neurons that have gain-modulated responses to visual stimuli. Finally, the model also successfully accounts for peri-saccadic receptive field (RF) remapping which results in reduced responses to stimuli in the current RF location and an increased sensitivity to stimuli appearing at the location that will be occupied by the RF after the saccade. The proposed model thus offers a unified explanation for this seemingly diverse range of phenomena. Furthermore, as the proposed model is an implementation of the predictive coding theory, it offers a single computational explanation for these phenomena and relates gaze shifts to a wider framework for understanding cortical function.

Spatially tuned normalization explains attention modulation variance within neurons.

Spatial attention improves perception of attended parts of a scene, a behavioral enhancement accompanied by modulations of neuronal firing rates. These modulations vary in size across neurons in the same brain area. Models of normalization explain much of this variance in attention modulation with differences in tuned normalization across neurons (Lee J, Maunsell JHR. PLoS One 4: e4651, 2009; Ni AM, Ray S, Maunsell JHR. Neuron 73: 803-813, 2012). However, recent studies suggest that normalization tuning varies with spatial location both across and within neurons (Ruff DA, Alberts JJ, Cohen MR. J Neurophysiol 116: 1375-1386, 2016; Verhoef BE, Maunsell JHR. eLife 5: e17256, 2016). Here we show directly that attention modulation and normalization tuning do in fact covary within individual neurons, in addition to across neurons as previously demonstrated. We recorded the activity of isolated neurons in the middle temporal area of two rhesus monkeys as they performed a change-detection task that controlled the focus of spatial attention. Using the same two drifting Gabor stimuli and the same two receptive field locations for each neuron, we found that switching which stimulus was presented at which location affected both attention modulation and normalization in a correlated way within neurons. We present an equal-maximum-suppression spatially tuned normalization model that explains this covariance both across and within neurons: each stimulus generates equally strong suppression of its own excitatory drive, but its suppression of distant stimuli is typically less. This new model specifies how the tuned normalization associated with each stimulus location varies across space both within and across neurons, changing our understanding of the normalization mechanism and how attention modulations depend on this mechanism.NEW & NOTEWORTHY Tuned normalization studies have demonstrated that the variance in attention modulation size seen across neurons from the same cortical area can be largely explained by between-neuron differences in normalization strength. Here we demonstrate that attention modulation size varies within neurons as well and that this variance is largely explained by within-neuron differences in normalization strength. We provide a new spatially tuned normalization model that explains this broad range of observed normalization and attention effects.