A Study of the Role of the Maintained-Discharge Parameter in the Divisive Normalization Model of V1 Neurons

2016 ◽  
Author(s):  
Tadamasa Sawada ◽  
Alexander Petrov
Keyword(s):  
Discharge Parameter ◽  
V1 Neurons ◽  
Divisive Normalization ◽  
Maintained Discharge

scholarly journals Neuronal response variability as a product of divisive normalization; neurobiological implications at a macroscale level

2020 ◽  
Vol 3 ◽  
pp. 34
Author(s):  
Kathy L. Ruddy ◽  
David M. Cole ◽  
Colin Simon ◽  
Marc T. Bächinger
Keyword(s):  
Potential Role ◽  
Neuronal Response ◽  
Quantitative Model ◽  
Response Variability ◽  
Sensory Cortex ◽  
Neural Oscillations ◽  
Neural Encoding ◽  
Approach Response ◽  
Divisive Normalization

The occurrence of neuronal spikes recorded directly from sensory cortex is highly irregular within and between presentations of an invariant stimulus. The traditional solution has been to average responses across many trials. However, with this approach, response variability is downplayed as noise, so it is assumed that statistically controlling it will reveal the brain’s true response to a stimulus. A mounting body of evidence suggests that this approach is inadequate. For example, experiments show that response variability itself varies as a function of stimulus dimensions like contrast and state dimensions like attention. In other words, response variability has structure, is therefore potentially informative and should be incorporated into models which try to explain neural encoding. In this article we provide commentary on a recently published study by Coen-Cagli and Solomon that incorporates spike variability in a quantitative model, by explaining it as a function of divisive normalization. We consider the potential role of neural oscillations in this process as a potential bridge between the current microscale findings and response variability at the mesoscale/macroscale level.

scholarly journals Understanding the Cortical Specialization for Horizontal Disparity

2004 ◽  
Vol 16 (10) ◽  
pp. 1983-2020 ◽  
Author(s):  
Jenny C.A. Read ◽  
Bruce G. Cumming
Keyword(s):  
Orientation Tuning ◽  
Horizontal Disparity ◽  
Vertical Disparity ◽  
V1 Neurons ◽  
Relative Response ◽  
Response Range ◽  
Divisive Normalization ◽  
Identical Position ◽  
Recent Experimental Work ◽  
To Receive

Because the eyes are displaced horizontally, binocular vision is inherently anisotropic. Recent experimental work has uncovered evidence of this anisotropy in primary visual cortex (V1): neurons respond over a wider range of horizontal than vertical disparity, regardless of their orientation tuning. This probably reflects the horizontally elongated distribution of two-dimensional disparity experienced by the visual system, but it conflicts with all existing models of disparity selectivity, in which the relative response range to vertical and horizontal disparities is determined by the preferred orientation. Potentially, this discrepancy could require us to abandon the widely held view that processing in V1 neurons is initially linear. Here, we show that these new experimental data can be reconciled with an initial linear stage; we present two physiologically plausible ways of extending existing models to achieve this. First, we allow neurons to receive input from multiple binocular subunits with different position disparities (previous models have assumed all subunits have identical position and phase disparity). Then we incorporate a form of divisive normalization, which has successfully explained many response properties of V1 neurons but has not previously been incorporated into a model of disparity selectivity. We show that either of these mechanisms decouples disparity tuning from orientation tuning and discuss how the models could be tested experimentally. This represents the first explanation of how the cortical specialization for horizontal disparity may be achieved.

scholarly journals Critical-Period Visual Deprivation Disrupts Binocular Integration but Spares Spatial Acuity in the Geniculocortical Pathway

2018 ◽  
Author(s):  
Carey Y. L. Huh ◽  
Karim Abdelaal ◽  
Kirstie J. Salinas ◽  
Diyue Gu ◽  
Jack Zeitoun ◽  
...  
Keyword(s):  
Critical Period ◽  
Monocular Deprivation ◽  
Orientation Tuning ◽  
Visual Responses ◽  
V1 Neurons ◽  
Two Photon ◽  
Spatial Acuity ◽  
A Site

ABSTRACTMonocular deprivation (MD) during the juvenile critical period leads to long-lasting impairments in binocular function and visual acuity. The site of these changes has been widely considered to be cortical. However, recent evidence indicates that binocular integration may first occur in the dorsolateral geniculate nucleus of the thalamus (dLGN), raising the question of whether MD during the critical period may produce long-lasting deficits in dLGN binocular integration. Using in vivo two-photon Ca2+ imaging of dLGN afferents and excitatory neurons in superficial layers of primary visual cortex (V1), we demonstrate that critical-period MD leads to a persistent and selective loss of binocular dLGN inputs, while leaving spatial acuity in the thalamocortical pathway intact. Despite being few in number, binocular dLGN boutons display remarkably robust visual responses, on average twice stronger than monocular boutons, and their responses are exquisitely well-matched between the eyes. To our surprise, we found that MD leads to a profound binocular mismatch of response amplitude, spatial frequency and orientation tuning detected at the level of single thalamocortical synapses. In comparison, V1 neurons display deficits in both binocular integration and spatial acuity following MD. Our data provide the most compelling evidence to date demonstrating that following critical-period MD, binocular deficits observed at the level of V1 may at least in part originate from dLGN binocular dysfunction, while spatial acuity deficits arise from cortical circuits. These findings highlight a hitherto unknown role of the thalamus as a site for developmental refinement of binocular vision.

scholarly journals Beyond Fixation: detailed characterization of neural selectivity in free-viewing primates

2021 ◽  
Author(s):  
Jacob L Yates ◽  
Shanna H Coop ◽  
Gabriel H Sarch ◽  
Ruei-Jr Wu ◽  
Daniel A Butts ◽  
...  
Keyword(s):  
Eye Movements ◽  
Receptive Fields ◽  
Natural Behavior ◽  
Visual Neurons ◽  
Trained Subjects ◽  
V1 Neurons ◽  
Fixational Eye Movements ◽  
Neural Selectivity

Virtually all vision studies use a fixation point to stabilize gaze, rendering stimuli on video screens fixed to retinal coordinates. This approach 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 show this approach recovers receptive fields and tuning properties of visual neurons from multiple cortical areas of marmoset monkeys. Combined with high-precision eye-tracking, it achieves sufficient resolution to recover the receptive fields of foveal V1 neurons. These findings demonstrate the power of this approach for characterizing neural response while simultaneously studying the dynamics of natural behavior.

scholarly journals Divisive normalization unifies disparate response signatures throughout the human visual hierarchy

2021 ◽  
Vol 118 (46) ◽  
pp. e2108713118
Author(s):  
Marco Aqil ◽  
Tomas Knapen ◽  
Serge O. Dumoulin
Keyword(s):  
Information Integration ◽  
Model Parameters ◽  
Response Modulation ◽  
Information Encoding ◽  
Neuronal Populations ◽  
Visual Hierarchy ◽  
Divisive Normalization ◽  
Neural Computations ◽  
Visuospatial Information

Neural processing is hypothesized to apply the same mathematical operations in a variety of contexts, implementing so-called canonical neural computations. Divisive normalization (DN) is considered a prime candidate for a canonical computation. Here, we propose a population receptive field (pRF) model based on DN and evaluate it using ultra-high-field functional MRI (fMRI). The DN model parsimoniously captures seemingly disparate response signatures with a single computation, superseding existing pRF models in both performance and biological plausibility. We observe systematic variations in specific DN model parameters across the visual hierarchy and show how they relate to differences in response modulation and visuospatial information integration. The DN model delivers a unifying framework for visuospatial responses throughout the human visual hierarchy and provides insights into its underlying information-encoding computations. These findings extend the role of DN as a canonical computation to neuronal populations throughout the human visual hierarchy.

scholarly journals Coherent representations of subjective spatial position in primary visual cortex and hippocampus

2017 ◽  
Author(s):  
Aman B. Saleem ◽  
E. Mika Diamanti ◽  
Julien Fournier ◽  
Kenneth D. Harris ◽  
Matteo Carandini
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Spatial Location ◽  
Visual Responses ◽  
V1 Neurons ◽  
Neuronal Populations ◽  
Subjective Estimate ◽  
Ca1 Region ◽  
Navigational Systems

A major role of vision is to guide navigation, and navigation is strongly driven by vision1-4. Indeed, the brain’s visual and navigational systems are known to interact5, 6, and signals related to position in the environment have been suggested to appear as early as in visual cortex6, 7. To establish the nature of these signals we recorded in primary visual cortex (V1) and in the CA1 region of the hippocampus while mice traversed a corridor in virtual reality. The corridor contained identical visual landmarks in two positions, so that a purely visual neuron would respond similarly in those positions. Most V1 neurons, however, responded solely or more strongly to the landmarks in one position. This modulation of visual responses by spatial location was not explained by factors such as running speed. To assess whether the modulation is related to navigational signals and to the animal’s subjective estimate of position, we trained the mice to lick for a water reward upon reaching a reward zone in the corridor. Neuronal populations in both CA1 and V1 encoded the animal’s position along the corridor, and the errors in their representations were correlated. Moreover, both representations reflected the animal’s subjective estimate of position, inferred from the animal’s licks, better than its actual position. Indeed, when animals licked in a given location – whether correct or incorrect – neural populations in both V1 and CA1 placed the animal in the reward zone. We conclude that visual responses in V1 are tightly controlled by navigational signals, which are coherent with those encoded in hippocampus, and reflect the animal’s subjective position in the environment. The presence of such navigational signals as early as in a primary sensory area suggests that these signals permeate sensory processing in the cortex.

Input–output statistical independence in divisive normalization models of V1 neurons

2003 ◽  
Vol 14 (4) ◽  
pp. 733-745 ◽  
Author(s):  
Roberto Valerio ◽  
Rafael Navarro
Keyword(s):  
Statistical Independence ◽  
Input Output ◽  
V1 Neurons ◽  
Divisive Normalization

Optimal coding through divisive normalization models of V1 neurons

2003 ◽  
Vol 14 (3) ◽  
pp. 579-593 ◽  
Author(s):  
Roberto Valerio ◽  
Rafael Navarro
Keyword(s):  
V1 Neurons ◽  
Divisive Normalization ◽  
Optimal Coding

scholarly journals Cortically coordinated NREM thalamocortical oscillations play an essential, instructive role in visual system plasticity

2017 ◽  
Vol 114 (39) ◽  
pp. 10485-10490 ◽  
Author(s):  
Jaclyn Durkin ◽  
Aneesha K. Suresh ◽  
Julie Colbath ◽  
Christopher Broussard ◽  
Jiaxing Wu ◽  
...  
Keyword(s):  
Cortical Plasticity ◽  
Brain Plasticity ◽  
Stimulus Presentation ◽  
Nrem Sleep ◽  
Cortical Layers ◽  
V1 Neurons ◽  
Coherent Communication ◽  
Thalamocortical Oscillations ◽  
Field Coherence

Two long-standing questions in neuroscience are how sleep promotes brain plasticity and why some forms of plasticity occur preferentially during sleep vs. wake. Establishing causal relationships between specific features of sleep (e.g., network oscillations) and sleep-dependent plasticity has been difficult. Here we demonstrate that presentation of a novel visual stimulus (a single oriented grating) causes immediate, instructive changes in the firing of mouse lateral geniculate nucleus (LGN) neurons, leading to increased firing-rate responses to the presented stimulus orientation (relative to other orientations). However, stimulus presentation alone does not affect primary visual cortex (V1) neurons, which show response changes only after a period of subsequent sleep. During poststimulus nonrapid eye movement (NREM) sleep, LGN neuron overall spike-field coherence (SFC) with V1 delta (0.5–4 Hz) and spindle (7–15 Hz) oscillations increased, with neurons most responsive to the presented stimulus showing greater SFC. To test whether coherent communication between LGN and V1 was essential for cortical plasticity, we first tested the role of layer 6 corticothalamic (CT) V1 neurons in coherent firing within the LGN-V1 network. We found that rhythmic optogenetic activation of CT V1 neurons dramatically induced coherent firing in LGN neurons and, to a lesser extent, in V1 neurons in the other cortical layers. Optogenetic interference with CT feedback to LGN during poststimulus NREM sleep (but not REM or wake) disrupts coherence between LGN and V1 and also blocks sleep-dependent response changes in V1. We conclude that NREM oscillations relay information regarding prior sensory experience between the thalamus and cortex to promote cortical plasticity.

Cone Inputs in Macaque Primary Visual Cortex

2004 ◽  
Vol 91 (6) ◽  
pp. 2501-2514 ◽  
Author(s):  
Elizabeth N. Johnson ◽  
Michael J. Hawken ◽  
Robert Shapley
Keyword(s):  
Visual Cortex ◽  
Spatial Frequency ◽  
Primary Visual Cortex ◽  
Weight Ratio ◽  
Broad Distribution ◽  
V1 Neurons ◽  
A Value ◽  
Cone Type ◽  
Almost All

To understand the role of primary visual cortex (V1) in color vision, we measured directly the input from the 3 cone types in macaque V1 neurons. Cells were classified as luminance-preferring, color-luminance, or color-preferring from the ratio of the peak amplitudes of spatial frequency responses to red/green equiluminant and to black/white (luminance) grating patterns, respectively. In this study we used L-, M-, and S-cone–isolating gratings to measure spatial frequency response functions for each cone type separately. From peak responses to cone-isolating stimuli we estimated relative cone weights and whether cone inputs were the same or opposite sign. For most V1 cells the relative S-cone weight was <0.1. All color-preferring cells were cone opponent and their L/M cone weight ratio was clustered around a value of –1, which is roughly equal and opposite L and M cone signals. Almost all cells (88%) classified as luminance cells were cone nonopponent, with a broad distribution of cone weights. Most cells (73%) classified as color-luminance cells were cone opponent. This result supports our conclusion that V1 color-luminance cells are double-opponent. Such neurons are more sensitive to color boundaries than to areas of color and thereby could play an important role in color perception. The color-luminance population had a broad distribution of L/M cone weight ratios, implying a broad distribution of preferred colors for the double-opponent cells.

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