scholarly journals Binocular Integration Manifests as a Transient Spiking Increase Followed by Selective Suppression in Primary Visual Cortex

2018 ◽  
Author(s):  
Michele A. Cox ◽  
Kacie Dougherty ◽  
Jacob A. Westerberg ◽  
Michelle S. Schall ◽  
Alexander Maier
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Visual Information ◽  
Temporal Dynamics ◽  
Neuronal Population ◽  
Stimulus Onset ◽  
Monocular Stimulation ◽  
Binocular Stimulation ◽  
Behaving Monkeys ◽  
Open Question

AbstractResearch throughout the past decades revealed that neurons in primate primary visual cortex (V1) rapidly integrate the two eyes’ separate signals into a combined binocular response. The exact mechanisms giving underlying this binocular integration remain elusive. One open question is whether binocular integration occurs at a single stage of sensory processing or in a sequence of computational steps. To address this question, we examined the temporal dynamics of binocular integration across V1’s laminar microcircuit of awake behaving monkeys. We find that V1 processes binocular stimuli in a dynamic sequence that comprises at least two distinct phases: A transient phase, lasting 50-150ms from stimulus onset, in which neuronal population responses are significantly enhanced for binocular stimulation compared to monocular stimulation, followed by a sustained phase characterized by widespread suppression in which feature-specific computations emerge. In the sustained phase, incongruent binocular stimulation resulted in response reduction relative to monocular stimulation across the V1 population. By contrast, sustained responses for binocular congruent stimulation were either reduced or enhanced relative to monocular responses depending on the neurons’ selectivity for one or both eyes (i.e., ocularity). These results suggest that binocular integration in V1 occurs in at least two sequential steps, with an initial additive combination of the two eyes’ signals followed by the establishment of interocular concordance and discordance.Significance StatementOur two eyes provide two separate streams of visual information that are merged in the primary visual cortex (V1). Previous work showed that stimulating both eyes rather than one eye may either increase or decrease activity in V1, depending on the nature of the stimuli. Here we show that V1 binocular responses change over time, with an early phase of general excitation and followed by stimulus-dependent response suppression. These results provide important new insights into the neural machinery that supports the combination of the two eye’s perspectives into a single coherent view.

scholarly journals Visual motion computation in recurrent neural networks

2017 ◽  
Author(s):  
Marius Pachitariu ◽  
Maneesh Sahani
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Visual Information ◽  
Visual Motion ◽  
Hebbian Learning ◽  
Temporal Dynamics ◽  
Temporal Structure ◽  
Receptive Fields ◽  
Learning Rule ◽  
Connectivity Matrix

AbstractPopulations of neurons in primary visual cortex (V1) transform direct thalamic inputs into a cortical representation which acquires new spatio-temporal properties. One of these properties, motion selectivity, has not been strongly tied to putative neural mechanisms, and its origins remain poorly understood. Here we propose that motion selectivity is acquired through the recurrent mechanisms of a network of strongly connected neurons. We first show that a bank of V1 spatiotemporal receptive fields can be generated accurately by a network which receives only instantaneous inputs from the retina. The temporal structure of the receptive fields is generated by the long timescale dynamics associated with the high magnitude eigenvalues of the recurrent connectivity matrix. When these eigenvalues have complex parts, they generate receptive fields that are inseparable in time and space, such as those tuned to motion direction. We also show that the recurrent connectivity patterns can be learnt directly from the statistics of natural movies using a temporally-asymmetric Hebbian learning rule. Probed with drifting grating stimuli and moving bars, neurons in the model show patterns of responses analogous to those of direction-selective simple cells in primary visual cortex. These computations are enabled by a specific pattern of recurrent connections, that can be tested by combining connectome reconstructions with functional recordings.*Author summaryDynamic visual scenes provide our eyes with enormous quantities of visual information, particularly when the visual scene changes rapidly. Even at modest moving speeds, individual small objects quickly change their location causing single points in the scene to change their luminance equally fast. Furthermore, our own movements through the world add to the velocities of objects relative to our retinas, further increasing the speed at which visual inputs change. How can a biological system process efficiently such vast amounts of information, while keeping track of objects in the scene? Here we formulate and analyze a solution that is enabled by the temporal dynamics of networks of neurons.

Adult Cortical Dynamics

1998 ◽  
Vol 78 (2) ◽  
pp. 467-485 ◽  
Author(s):  
CHARLES D. GILBERT
Keyword(s):  
Visual Cortex ◽  
Functional Properties ◽  
Primary Visual Cortex ◽  
Visual Information ◽  
Visual Space ◽  
Visual Pathway ◽  
Local Features ◽  
Spatial Integration ◽  
Cortical Dynamics ◽  
Wide Range

Gilbert, Charles D. Adult Cortical Dynamics. Physiol. Rev. 78: 467–485, 1998. — There are many influences on our perception of local features. What we see is not strictly a reflection of the physical characteristics of a scene but instead is highly dependent on the processes by which our brain attempts to interpret the scene. As a result, our percepts are shaped by the context within which local features are presented, by our previous visual experiences, operating over a wide range of time scales, and by our expectation of what is before us. The substrate for these influences is likely to be found in the lateral interactions operating within individual areas of the cerebral cortex and in the feedback from higher to lower order cortical areas. Even at early stages in the visual pathway, cells are far more flexible in their functional properties than previously thought. It had long been assumed that cells in primary visual cortex had fixed properties, passing along the product of a stereotyped operation to the next stage in the visual pathway. Any plasticity dependent on visual experience was thought to be restricted to a period early in the life of the animal, the critical period. Furthermore, the assembly of contours and surfaces into unified percepts was assumed to take place at high levels in the visual pathway, whereas the receptive fields of cells in primary visual cortex represented very small windows on the visual scene. These concepts of spatial integration and plasticity have been radically modified in the past few years. The emerging view is that even at the earliest stages in the cortical processing of visual information, cells are highly mutable in their functional properties and are capable of integrating information over a much larger part of visual space than originally believed.

scholarly journals Thalamic inputs determine functionally distinct gamma bands in mouse primary visual cortex

2020 ◽  
Author(s):  
Nicolò Meneghetti ◽  
Chiara Cerri ◽  
Elena Tantillo ◽  
Eleonora Vannini ◽  
Matteo Caleo ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Visual Information ◽  
Narrow Band ◽  
Broad Band ◽  
Gamma Band ◽  
Neuron Network ◽  
Sensory Stimuli ◽  
Thalamic Input ◽  
Visual Contrast

AbstractGamma band is known to be involved in the encoding of visual features in the primary visual cortex (V1). Recent results in rodents V1 highlighted the presence, within a broad gamma band (BB) increasing with contrast, of a narrow gamma band (NB) peaking at ∼60 Hz suppressed by contrast and enhanced by luminance. However, the processing of visual information by the two channels still lacks a proper characterization. Here, by combining experimental analysis and modeling, we prove that the two bands are sensitive to specific thalamic inputs associated with complementary contrast ranges. We recorded local field potentials from V1 of awake mice during the presentation of gratings and observed that NB power progressively decreased from low to intermediate levels of contrast. Conversely, BB power was insensitive to low levels of contrast but it progressively increased going from intermediate to high levels of contrast. Moreover, BB response was stronger immediately after contrast reversal, while the opposite held for NB. All the aforementioned dynamics were accurately reproduced by a recurrent excitatory-inhibitory leaky integrate-and-fire network, mimicking layer IV of mouse V1, provided that the sustained and periodic component of the thalamic input were modulated over complementary contrast ranges. These results shed new light on the origin and function of the two V1 gamma bands. In addition, here we propose a simple and effective model of response to visual contrast that might help in reconstructing network dysfunction underlying pathological alterations of visual information processing.Significance StatementGamma band is a ubiquitous hallmark of cortical processing of sensory stimuli. Experimental evidence shows that in the mouse visual cortex two types of gamma activity are differentially modulated by contrast: a narrow band (NB), that seems to be rodent specific, and a standard broad band (BB), observed also in other animal models.We found that narrow band correlates and broad band anticorrelates with visual contrast in two complementary contrast ranges (low and high respectively). Moreover, BB displayed an earlier response than NB. A thalamocortical spiking neuron network model reproduced the aforementioned results, suggesting they might be due to the presence of two complementary but distinct components of the thalamic input into visual cortical circuitry.

A collicular visual cortex: Neocortical space for an ancient midbrain visual structure

Science ◽  
2019 ◽  
Vol 363 (6422) ◽  
pp. 64-69 ◽  
Author(s):  
Riccardo Beltramo ◽  
Massimo Scanziani
Keyword(s):  
Cerebral Cortex ◽  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Visual Information ◽  
Cortical Area ◽  
Moving Objects ◽  
Visual Responses ◽  
Visual Cortical Area ◽  
Postrhinal Cortex ◽  
Visual Cortical

Visual responses in the cerebral cortex are believed to rely on the geniculate input to the primary visual cortex (V1). Indeed, V1 lesions substantially reduce visual responses throughout the cortex. Visual information enters the cortex also through the superior colliculus (SC), but the function of this input on visual responses in the cortex is less clear. SC lesions affect cortical visual responses less than V1 lesions, and no visual cortical area appears to entirely rely on SC inputs. We show that visual responses in a mouse lateral visual cortical area called the postrhinal cortex are independent of V1 and are abolished upon silencing of the SC. This area outperforms V1 in discriminating moving objects. We thus identify a collicular primary visual cortex that is independent of the geniculo-cortical pathway and is capable of motion discrimination.

scholarly journals Temporal dynamics of binocular integration in primary visual cortex

2019 ◽  
Vol 19 (12) ◽  
pp. 13 ◽  
Author(s):  
Michele A. Cox ◽  
Kacie Dougherty ◽  
Jacob A. Westerberg ◽  
Michelle S. Schall ◽  
Alexander Maier
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Temporal Dynamics

scholarly journals Blindsight and Unconscious Vision: What They Teach Us about the Human Visual System

2016 ◽  
Vol 23 (5) ◽  
pp. 529-541 ◽  
Author(s):  
Sara Ajina ◽  
Holly Bridge
Keyword(s):  
Visual Cortex ◽  
Visual System ◽  
Primary Visual Cortex ◽  
Neural Activity ◽  
Human Visual System ◽  
Visual Information ◽  
Visual Loss ◽  
Physiological Conditions ◽  
The World ◽  
The Brain

Damage to the primary visual cortex removes the major input from the eyes to the brain, causing significant visual loss as patients are unable to perceive the side of the world contralateral to the damage. Some patients, however, retain the ability to detect visual information within this blind region; this is known as blindsight. By studying the visual pathways that underlie this residual vision in patients, we can uncover additional aspects of the human visual system that likely contribute to normal visual function but cannot be revealed under physiological conditions. In this review, we discuss the residual abilities and neural activity that have been described in blindsight and the implications of these findings for understanding the intact system.

The basis of orientation decoding in human primary visual cortex: fine- or coarse-scale biases?

2015 ◽  
Vol 113 (1) ◽  
pp. 1-3 ◽  
Author(s):  
Ryan T. Maloney
Keyword(s):  
Magnetic Resonance Imaging ◽  
Visual Cortex ◽  
Magnetic Resonance ◽  
Receptive Field ◽  
Primary Visual Cortex ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Coarse Scale ◽  
Multivariate Pattern ◽  
Open Question

Orientation signals in human primary visual cortex (V1) can be reliably decoded from the multivariate pattern of activity as measured with functional magnetic resonance imaging (fMRI). The precise underlying source of these decoded signals (whether by orientation biases at a fine or coarse scale in cortex) remains a matter of some controversy, however. Freeman and colleagues ( J Neurosci 33: 19695–19703, 2013) recently showed that the accuracy of decoding of spiral patterns in V1 can be predicted by a voxel's preferred spatial position (the population receptive field) and its coarse orientation preference, suggesting that coarse-scale biases are sufficient for orientation decoding. Whether they are also necessary for decoding remains an open question, and one with implications for the broader interpretation of multivariate decoding results in fMRI studies.

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