Fields In V1 Research Articles

Detailed characterization of neural selectivity in free viewing primates

Fixation constraints in visual tasks are ubiquitous in visual and cognitive neuroscience. Despite its widespread use, fixation requires trained subjects, is limited by the accuracy of fixational eye movements, and ignores the role of eye movements in shaping visual input. To overcome these limitations, we developed a suite of hardware and software tools to study vision during natural behavior in untrained subjects. We measured visual receptive fields and tuning properties from multiple cortical areas of marmoset monkeys who freely viewed full-field noise stimuli. The resulting receptive fields and tuning curves from primary visual cortex (V1) and area MT match reported selectivity from the literature which was measured using conventional approaches. We then combined free viewing with high-resolution eye tracking to make the first detailed 2D spatiotemporal measurements of foveal receptive fields in V1. These findings demonstrate the power of free viewing to characterize neural responses in untrained animals while simultaneously studying the dynamics of natural behavior.

Efficient processing of natural scenes in visual cortex.

Neural circuits in the periphery of the visual, auditory, and olfactory systems are believed to use limited resources efficiently to represent sensory information by adapting to the statistical structure of the natural environment. This "efficient coding" principle has been used to explain many aspects of early visual circuits including the distribution of photoreceptors, the mosaic geometry and center-surround structure of retinal receptive fields, the excess OFF pathways relative to ON pathways, saccade statistics, and the structure of simple cell receptive fields in V1. We know less about the extent to which such adaptations may occur in deeper areas of cortex beyond V1. We thus review recent developments showing that the perception of visual textures, which depends on processing in V2 and beyond in mammals, is adapted in rats and humans to the multi-point statistics of luminance in natural scenes. These results suggest that central circuits in the visual brain are adapted for seeing key aspects of natural scenes. We conclude by discussing how adaptation to natural temporal statistics may aid in learning and representing visual objects, and propose two challenges for the future: (1) explaining the distribution of shape sensitivity in the ventral visual stream from the statistics of object shape in natural images, and (2) explaining cell types of the vertebrate retina in terms of feature detectors that are adapted to the spatio-temporal structures of natural stimuli. We also discuss how new methods based on machine learning may complement the normative, principles-based approach to theoretical neuroscience.

Different attentional focus sizes modulate the size-eccentricity effect.

The size-eccentricity effect is a perceptual distortion phenomenon in which a peripherally located object is perceived to be smaller than a centrally located object. Although the increase in apparent object size caused by attention has been documented, little is known about the effect of different sizes of attentional focus on object appearance. The present study investigated how different sizes of attentional focus affect the size-eccentricity effect using a spatial pre-cueing paradigm. Additionally, we examined the influence of different task types on size perception. A peripheral object following a small attentional focus appeared larger, without observation of the size-eccentricity effect. In contrast, a peripheral object appeared smaller following a large attentional focus in both larger and smaller judgement tasks. These results suggest that the relative size of the attentional focus has opposite effects on the perception of object size, independent of task type. Furthermore, in addition to the structural properties of the retina and the locus of attention, the size of attentional focus determines the extent to which an object appears smaller in the periphery. The present study complements the attentional attraction field model of the size and density of population receptive fields in V1 and further explains how the effect of attention is restricted by retinal structure.

Sparse deep predictive coding captures contour integration capabilities of the early visual system.

Both neurophysiological and psychophysical experiments have pointed out the crucial role of recurrent and feedback connections to process context-dependent information in the early visual cortex. While numerous models have accounted for feedback effects at either neural or representational level, none of them were able to bind those two levels of analysis. Is it possible to describe feedback effects at both levels using the same model? We answer this question by combining Predictive Coding (PC) and Sparse Coding (SC) into a hierarchical and convolutional framework applied to realistic problems. In the Sparse Deep Predictive Coding (SDPC) model, the SC component models the internal recurrent processing within each layer, and the PC component describes the interactions between layers using feedforward and feedback connections. Here, we train a 2-layered SDPC on two different databases of images, and we interpret it as a model of the early visual system (V1 & V2). We first demonstrate that once the training has converged, SDPC exhibits oriented and localized receptive fields in V1 and more complex features in V2. Second, we analyze the effects of feedback on the neural organization beyond the classical receptive field of V1 neurons using interaction maps. These maps are similar to association fields and reflect the Gestalt principle of good continuation. We demonstrate that feedback signals reorganize interaction maps and modulate neural activity to promote contour integration. Third, we demonstrate at the representational level that the SDPC feedback connections are able to overcome noise in input images. Therefore, the SDPC captures the association field principle at the neural level which results in a better reconstruction of blurred images at the representational level.

Population receptive fields in V1 enlarge as luminance is reduced from photopic to scotopic levels

Population receptive fields in V1 enlarge as luminance is reduced from photopic to scotopic levels

Cortical feedback signals generalise across different spatial frequencies of feedforward inputs

Visual processing in cortex relies on feedback projections contextualising feedforward information flow. Primary visual cortex (V1) has small receptive fields and processes feedforward information at a fine-grained spatial scale, whereas higher visual areas have larger, spatially invariant receptive fields. Therefore, feedback could provide coarse information about the global scene structure or alternatively recover fine-grained structure by targeting small receptive fields in V1. We tested if feedback signals generalise across different spatial frequencies of feedforward inputs, or if they are tuned to the spatial scale of the visual scene. Using a partial occlusion paradigm, functional magnetic resonance imaging (fMRI) and multivoxel pattern analysis (MVPA) we investigated whether feedback to V1 contains coarse or fine-grained information by manipulating the spatial frequency of the scene surround outside an occluded image portion. We show that feedback transmits both coarse and fine-grained information as it carries information about both low (LSF) and high spatial frequencies (HSF). Further, feedback signals containing LSF information are similar to feedback signals containing HSF information, even without a large overlap in spatial frequency bands of the HSF and LSF scenes. Lastly, we found that feedback carries similar information about the spatial frequency band across different scenes. We conclude that cortical feedback signals contain information which generalises across different spatial frequencies of feedforward inputs.

Edge-Related Activity Is Not Necessary to Explain Orientation Decoding in Human Visual Cortex.

A significant theoretical limitation of multivariate pattern analysis in neuroscience is the ambiguity in interpreting the source of decodable information used by classifiers. For example, orientation can be decoded from BOLD activation patterns in human V1, even though orientation columns are at a finer spatial scale than 3T fMRI. Consequently, the source of decodable information remains controversial. Here we test the proposal that information related to the stimulus edges underlies orientation decoding. We map voxel population receptive fields in V1 and evaluate orientation decoding performance as a function of stimulus location in retinotopic cortex. We find orientation is decodable from voxels whose receptive fields do not overlap with the stimulus edges, suggesting edge-related activity does not substantially drive orientation decoding.

The broad orientation dependence of the motion streak aftereffect reveals interactions between form and motion neurons.

The extended integration time of visual neurons can lead to the production of the neural equivalent of an orientation cue along the axis of motion in response to fast-moving objects. The dominant model argues that these motion streaks resolve the inherent directional uncertainty arising from the small size of receptive fields in V1, by combining spatial orientation with motion signals in V1. This model was tested in humans using visual aftereffects, in which adapting to a static grating causes the perceived direction of a subsequently presented motion stimulus to be tilted away from the adapting orientation. We found that a much broader range of orientations produced aftereffects than predicted by the current model, suggesting that these orientation cues influence motion perception at a later stage than V1. We also found that varying the spatial frequency of the adaptor changed the aftereffect from repulsive to attractive for motion-test but not form-test stimuli. Finally, manipulations of V1 excitability, using transcranial stimulation, reduced the aftereffect, suggesting that the orientation cue is dependent on V1. These results can be accounted for if the orientation information from the motion streak, gathered in V1, enters the motion system at a later stage of motion processing, most likely V5. A computational model of motion direction is presented incorporating gain modifications of broadly tuned motion-selective neurons by narrowly tuned orientation-selective cells in V1, which successfully accounts for the extant data. These results reinforce the suggestion that orientation places strong constraints on motion processing but in a previously undescribed manner.

The orientation dependence of the motion streak aftereffect reveals interactions between form and motion neurons

The extended integration time of visual neurons leads to fast-moving objects producing the neural equivalent of an orientation cue along the axis of motion. The dominant model [Geisler, W.S. (1999). Motion streaks provide a spatial code for motion direction. Nature, 400(6739), 65–69] proposes that these ‘motion streaks’ resolve the inherent directional uncertainty arising from the small size of receptive fields in V1, by combining spatial orientation with motion signals in V1. This model was tested using visual aftereffects, where adapting to a static grating causes the perceived direction of a subsequently-presented fast motion stimulus to be repelled away from the adapting orientation. Using a similar adaptation method, we measured the angular dependence of this effect and found in each human observer that a much broader range of adapting orientations (mean of 38.82º instead of 21.72°) produced aftereffects than predicted by the current model of motion streaks. This suggests that motion streaks influence motion perception at a later stage than V1. We also found that varying the spatial frequency of the adaptor by approximately two octaves changed the aftereffect from repulsive to attractive for motion, but not form stimuli. Finally, manipulations of V1 excitability, using transcranial direct current stimulation, reduced the aftereffect, suggesting that the orientation cue is dependent upon V1. These results can be accounted for if the orientation information from the motion streak, gathered in V1, enters the motion system at a later stage of motion processing, most likely V5. A new computational model of motion direction is presented incorporating gain modifications of broadly-tuned motion-selective neurons, most likely in V5, by narrowly-tuned orientation-selective cells in V1, which successfully accounts for the data in the current study. These results stress that orientation places strong constraints on motion processing in a different way than the current models predict. Meeting abstract presented at VSS 2015

A computational theory of visual receptive fields.

A receptive field constitutes a region in the visual field where a visual cell or a visual operator responds to visual stimuli. This paper presents a theory for what types of receptive field profiles can be regarded as natural for an idealized vision system, given a set of structural requirements on the first stages of visual processing that reflect symmetry properties of the surrounding world. These symmetry properties include (i) covariance properties under scale changes, affine image deformations, and Galilean transformations of space–time as occur for real-world image data as well as specific requirements of (ii) temporal causality implying that the future cannot be accessed and (iii) a time-recursive updating mechanism of a limited temporal buffer of the past as is necessary for a genuine real-time system. Fundamental structural requirements are also imposed to ensure (iv) mutual consistency and a proper handling of internal representations at different spatial and temporal scales. It is shown how a set of families of idealized receptive field profiles can be derived by necessity regarding spatial, spatio-chromatic, and spatio-temporal receptive fields in terms of Gaussian kernels, Gaussian derivatives, or closely related operators. Such image filters have been successfully used as a basis for expressing a large number of visual operations in computer vision, regarding feature detection, feature classification, motion estimation, object recognition, spatio-temporal recognition, and shape estimation. Hence, the associated so-called scale-space theory constitutes a both theoretically well-founded and general framework for expressing visual operations. There are very close similarities between receptive field profiles predicted from this scale-space theory and receptive field profiles found by cell recordings in biological vision. Among the family of receptive field profiles derived by necessity from the assumptions, idealized models with very good qualitative agreement are obtained for (i) spatial on-center/off-surround and off-center/on-surround receptive fields in the fovea and the LGN, (ii) simple cells with spatial directional preference in V1, (iii) spatio-chromatic double-opponent neurons in V1, (iv) space–time separable spatio-temporal receptive fields in the LGN and V1, and (v) non-separable space–time tilted receptive fields in V1, all within the same unified theory. In addition, the paper presents a more general framework for relating and interpreting these receptive fields conceptually and possibly predicting new receptive field profiles as well as for pre-wiring covariance under scaling, affine, and Galilean transformations into the representations of visual stimuli. This paper describes the basic structure of the necessity results concerning receptive field profiles regarding the mathematical foundation of the theory and outlines how the proposed theory could be used in further studies and modelling of biological vision. It is also shown how receptive field responses can be interpreted physically, as the superposition of relative variations of surface structure and illumination variations, given a logarithmic brightness scale, and how receptive field measurements will be invariant under multiplicative illumination variations and exposure control mechanisms.

Plasticity and Stability of the Visual System in Human Achiasma

The absence of the optic chiasm is an extraordinary and extreme abnormality in the nervous system. The abnormality produces highly atypical functional responses in the cortex, including overlapping hemifield representations and bilateral population receptive fields in both striate and extrastriate visual cortex. Even in the presence of these large functional abnormalities, the effect on visual perception and daily life is not easily detected. Here, we demonstrate that in two achiasmic humans the gross topography of the geniculostriate and occipital callosal connections remains largely unaltered. We conclude that visual function is preserved by reorganization of intracortical connections instead of large-scale reorganizations of the visual cortex. Thus, developmental mechanisms of local wiring within cortical maps compensate for the improper gross wiring to preserve function in human achiasma.

Now you see it, now you don?t: surround suppression of bold is predictive of perceptual pop-out

Event Abstract Back to Event Now you see it, now you don’t: surround suppression of bold is predictive of perceptual pop-out Branka Milivojevic1*, Mathijs Raemaekers2, Johan M. Jansma2, Nick Ramsey2, Margarita Calabrese3 and Chantal Kemner1 1 Utrecht University, Netherlands 2 UMC Utrecht, Netherlands 3 University of Amsterdam, Netherlands When an object differs markedly from its background environment it is more likely to capture attention. This perceptual pop-out effect has been attributed to surround suppression in V1. In human fMRI studies, surround suppression has been shown to result in lower BOLD signal, but the link with visual search performance has not been made so far. The aim of the current study is to establish this link. We compared BOLD amplitudes in response to circular textures consisting of either homogeneously (HT) or inhomogeneously (IhT) oriented gabor patches. We expected that HTs will elicit more suppression than IhTs. The results indicated that this is indeed the case with lower BOLD amplitudes in response to HTs than IhTs. Furthermore, the results indicate that surround suppression originates in V1, and the effects of surround suppression gets carried forward to higher-level visual areas. Outside the scanner, the participants also had to perform a target-detection task with similar stimuli. In this task, the targets had either SIMILAR, DIFFERENT, RANDOM or NO surround. Reaction times and accuracy to targets embedded in homogeneous, but DIFFERENT, surround and to targets presented in isolation (NONE) did not differ. In contrast, highly SIMILAR surround interfered with target detection to a similar degree as RANDOM surround. Behavioural results suggest that target pop-out facilitates visual search considerably more when the ratio between inhibition levels at target location and in the surround is large. Based on the idea that surround suppression arises in the V1, we designed stimuli that mimic the properties of population receptive fields in V1 and, as a control, V3. Both behavioural and fMRI effects were more pronounced for stimuli optimized for V1 response properties. Funding: Supported by NWO (Dutch scientific organisation) Vici grant to Prof. Chantal Kemner. Keywords: BOLD, Perception Conference: XI International Conference on Cognitive Neuroscience (ICON XI), Palma, Mallorca, Spain, 25 Sep - 29 Sep, 2011. Presentation Type: Poster Presentation Topic: Poster Sessions: Neurophysiology of Sensation and Perception Citation: Milivojevic B, Raemaekers M, Jansma JM, Ramsey N, Calabrese M and Kemner C (2011). Now you see it, now you don’t: surround suppression of bold is predictive of perceptual pop-out. Conference Abstract: XI International Conference on Cognitive Neuroscience (ICON XI). doi: 10.3389/conf.fnhum.2011.207.00341 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 23 Nov 2011; Published Online: 28 Nov 2011. * Correspondence: Dr. Branka Milivojevic, Utrecht University, Utrecht, Netherlands, b.milivojevic@donders.ru.nl Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Branka Milivojevic Mathijs Raemaekers Johan M Jansma Nick Ramsey Margarita Calabrese Chantal Kemner Google Branka Milivojevic Mathijs Raemaekers Johan M Jansma Nick Ramsey Margarita Calabrese Chantal Kemner Google Scholar Branka Milivojevic Mathijs Raemaekers Johan M Jansma Nick Ramsey Margarita Calabrese Chantal Kemner PubMed Branka Milivojevic Mathijs Raemaekers Johan M Jansma Nick Ramsey Margarita Calabrese Chantal Kemner Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Normative Visual Development: efficient coding principles for adult V1 predict properties of LGN waves prior to eye opening

We present a novel approach to understanding spontaneous activity in the LGN and V1 prior to natural visual experience. Patterned, spontaneous neural activity has been measured in these areas but is poorly understood in comparison to work on retinal waves [1]. Our predictions about LGN/V1 spontaneous activity not only have implications for future experiments, but provide an additional computational-level interpretation. In the same way that V1 can be understood through neural network receptive field models (Marr's algorithmic level) as well as an efficient coding of natural images (Marr's computational level), we propose that early visual spontaneous activity can be understood not only through neural network models of receptive field and map formation, as in many previous approaches [2,3], but also by how this activity relates to the high-level coding objectives of V1. The key insight in this work is that the form of spontaneous activity in the early visual system can be constrained by these normative principles to resemble measured spontaneous activity patterns. The neural code in fully-developed adult primary visual cortex (V1) is presumed to be an efficient code; by encoding images of our natural visual environment, techniques such as sparse coding [4] and independent components analysis [5] have produced linear filters which resemble experimentally measured receptive fields in V1. Our simulations show how patterns which qualitatively resemble such activity are capable of producing these V1-like visual codes by using the same learning algorithms. The spontaneous activity model is similar to a previous abstracted version of retinal wave generation [6] with the addition of multiple eye-layers and correlated interaction between the layers as has been measured experimentally [7]. All model parameters have a direct physiological interpretation and also relate to theoretical models used in the physics of critical phenomena (e.g. percolation networks). This normative approach demonstrates that binocular disparity-selective cells can be refined by spontaneous activity in a way that promotes early stereopsis. This unique, normative approach to visual development provides a way of applying the tools of efficient coding used in the adult visual system to better understand how the how V1 refines prior to visual experience.

Functions confined in space and spatial frequency include Gabor-like functions as well as intrinsically two-dimensional functions resembling "non-Cartesian" gratings

Established theoretical reasons recommend functions that are limited in space and spatial frequency as models for receptive fields of visual neurons. On the basis of an interpretation of spread as variance and via analogy to quantum mechanics, the Gabor functions are often stated to be maximally limited in space and spatial frequency (Daugman, 1985). Some Gabor functions indeed resemble receptive fields in V1, but this view provides little insight into why V1 receptive fields have only a small number of lobes, nor into receptive field shape beyond V1. Here we consider an alternative interpretation of “limited in space and spatial frequency.” We consider a function to be “confined” in space (or spatial frequency) if it is unchanged by windowing in space (or spatial frequency). While no function can be simultaneously confined in both space and spatial frequency, there is a rigorous sense in which the 2-dimensional Hermite functions achieve simultaneous confinement as nearly as possible. The 2-dimensional Hermite functions are a complete basis set and form a natural hierarchy. The first levels of this hierarchy contain functions that resemble Gabor functions with a small number of lobes, and thus resemble V1 receptive fields. Further down the hierarchy are intrinsically 2-dimensional functions, some of which resemble the non-Cartesian gratings, to which some V4 neurons respond preferentially (Gallant, 1996). In addition to their many interesting mathematical properties, the two-dimensional Hermite functions allow for efficient (“sparse”) local synthesis of images, including natural scenes, faces, and letters. While we make no claim that this view suffices to account for receptive field structure, we suggest that it provides a framework for a principled study of receptive fields, and that it is useful to think of receptive fields (along the V1-to-V2-to-V4 pathway) as not only expanding, but also increasing in their combined space-bandwidth aperture.

A Shout Out to Immature Synapses. Focus on “Different Roles for AMPA and NMDA Receptors in Transmission at the Immature Retinogeniculate Synapse”

A major topic of investigation in the field of developmental neuroscience is to understand how newly formed excitatory synapses receive and transmit information. It is now widely accepted that neural activity plays an important role in a number of developmental processes, including the refinement and establishment of orderly connections (Grubb and Thompson 2004). However, it remains unclear how many immature excitatory synapses (i.e., ones that utilize glutamate as a neurotransmitter) participate in the relay of activity. Contributing to this problem is the finding that immature glutamatergic synapses are comprised largely of N-methyl-D-aspartate (NMDA) receptors and lack AMPA receptors that mediate fast excitatory transmission. Such synapses are said to be “silent,” incapable of causing postsynaptic action potentials from resting levels because in addition to glutamate, the NMDA receptor requires membrane depolarization to relieve a voltage-dependent Mg 2 block. How then do silent synapses “speak” loudly enough to cause postsynaptic firing and thereby successfully relay information? In a recent article, Liu and Chen (2008) provide some answers to this question. They examine the synaptic responses and intrinsic properties of developing neurons by making use of an in vitro thalamic slice preparation that maintains the excitatory synaptic connections between retinal ganglion cells and relay cells of the dorsal lateral geniculate nucleus (LGN). In an elegant series of whole cell recording experiments, they show how a constellation of properties, including ligand-gated channel kinetics, receptor subunit composition, extended presence of neurotransmitter

Direction selectivity in V1 of alert monkeys: evidence for parallel pathways for motion processing

In primary visual cortex (V1) of macaque monkeys, motion selective cells form three parallel pathways. Two sets of direction selective cells, one in layer 4B, and the other in layer 6, send parallel direct outputs to area MT in the dorsal cortical stream. We show that these two outputs carry different types of spatial information. Direction selective cells in layer 4B have smaller receptive fields than those in layer 6, and layer 4B cells are more selective for orientation. We present evidence for a third direction selective pathway that flows through V1 layers 4Cm (the middle tier of layer 4C) to layer 3. Cells in layer 3 are very selective for orientation, have the smallest receptive fields in V1, and send direct outputs to area V2. Layer 3 neurons are well suited to contribute to detection and recognition of small objects by the ventral cortical stream, as well as to sense subtle motions within objects, such as changes in facial expressions.

Brightness processing in the visual cortex

Single cell recordings have shown that some cells in the primary visual cortex (V1) signal surface brightness. However, fMRI experiments have found brightness related activation only in the higher cortical areas. In a psychophysical setup, we were able to dissociate the reduction of brightness caused by Gabor flankers, similar to the receptive fields in V1, from the edge induced brightness change. The former resemble the single cell recording results and the latter the fMRI results.

Spontaneous Retinal Activity Mediates Development of Ocular Dominance Columns and Binocular Receptive Fields in V1

The mechanisms that give rise to ocular dominance columns (ODCs) during development are controversial. Early experiments indicated a key role for retinal activity in ODC formation. However, later studies showed that in those early experiments, the retinal activity perturbation was initiated after ODCs had already formed. Moreover, recent studies concluded that early eye removals do not impact ODC segregation. Here we blocked spontaneous retinal activity during the very early stages of ODC development. This permanently disrupted the anatomical organization of ODCs and led to a dramatic increase in receptive field size for binocular cells in primary visual cortex. Our data suggest that early spontaneous retinal activity conveys crucial information about whether thalamocortical axons represent one or the other eye and that this activity mediates binocular competition important for shaping receptive fields in primary visual cortex.

A self-organizing neural network model of the development of motion direction selectivity, orientation, and ocular dominance maps and receptive fields in V1 and MT

A self-organizing neural network model of the development of motion direction selectivity, orientation, and ocular dominance maps and receptive fields in V1 and MT