scholarly journals Neuronal adaptation reveals a suboptimal decoding of orientation tuned populations in the mouse visual cortex

2018 ◽  
Author(s):  
Miaomiao Jin ◽  
Jeffrey M. Beck ◽  
Lindsey L. Glickfeld
Keyword(s):  
Visual Cortex ◽  
Visual System ◽  
Cortical Neurons ◽  
Signal To Noise Ratio ◽  
Sensory Information ◽  
Orientation Discrimination ◽  
Signal To Noise ◽  
Neuronal Adaptation ◽  
Related Information ◽  
Mouse Visual Cortex

AbstractSensory information is encoded by populations of cortical neurons. Yet, it is unknown how this information is used for even simple perceptual choices such as discriminating orientation. To determine the computation underlying this perceptual choice, we took advantage of the robust adaptation in the mouse visual system. We find that adaptation increases animals’ thresholds for orientation discrimination. This was unexpected since optimal computations that take advantage of all available sensory information predict that the shift in tuning and increase in signal-to-noise ratio in the adapted condition should improve discrimination. Instead, we find that the effects of adaptation on behavior can be explained by the appropriate reliance of the perceptual choice circuits on target preferring neurons, but the failure to discount neurons that prefer the distractor. This suggests that to solve this task the circuit has adopted a suboptimal strategy that discards important task-related information to implement a feed-forward visual computation.

scholarly journals A Sparse Unreliable Distributed Code Underlies the Limits of Behavioral Discrimination

2018 ◽  
Author(s):  
Balaji Sriram ◽  
Alberto Cruz-Martin ◽  
Lillian Li ◽  
Pamela Reinagel ◽  
Anirvan Ghosh
Keyword(s):  
Visual Cortex ◽  
Visual System ◽  
Single Unit ◽  
Discrimination Task ◽  
Orientation Discrimination ◽  
Behavioral Performance ◽  
High Contrast ◽  
The World ◽  
Mouse Visual Cortex ◽  
Linear Decoding

ABSTRACTThe cortical code that underlies perception must enable subjects to perceive the world at timescales relevant for behavior. We find that mice can integrate visual stimuli very quickly (<100 ms) to reach plateau performance in an orientation discrimination task. To define features of cortical activity that underlie performance at these timescales, we measured single unit responses in the mouse visual cortex at timescales relevant to this task. In contrast to high contrast stimuli of longer duration, which elicit reliable activity in individual neurons, stimuli at the threshold of perception elicit extremely sparse and unreliable responses in V1 such that the activity of individual neurons do not reliably report orientation. Integrating information across neurons, however, quickly improves performance. Using a linear decoding model, we estimate that integrating information over 50-100 neurons is sufficient to account for behavioral performance. Thus, at the limits of perception the visual system is able to integrate information across a relatively small number of highly unreliable single units to generate reliable behavior.

scholarly journals Unsupervised Models of Mouse Visual Cortex

2021 ◽  
Author(s):  
Aran Nayebi ◽  
Nathan C. L. Kong ◽  
Chengxu Zhuang ◽  
Justin L. Gardner ◽  
Anthony M. Norcia ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Visual System ◽  
Network Architectures ◽  
Deep Convolutional Neural Networks ◽  
Visual Stream ◽  
Computational Theory ◽  
Visual Coding ◽  
Ventral Visual Stream ◽  
Mouse Visual Cortex ◽  
Image Transformations

Task-optimized deep convolutional neural networks are the most quantitatively accurate models of the primate ventral visual stream. However, such networks are implausible as a model of the mouse visual system because mouse visual cortex has a known shallower hierarchy and the supervised objectives these networks are typically trained with are likely neither ethologically relevant in content nor in quantity. Here we develop shallow network architectures that are more consistent with anatomical and physiological studies of mouse visual cortex than current models. We demonstrate that hierarchically shallow architectures trained using contrastive objective functions applied to visual-acuity-adapted images achieve neural prediction performance that exceed those of the same architectures trained in a supervised manner and result in the most quantitatively accurate models of the mouse visual system. Moreover, these models' neural predictivity significantly surpasses those of supervised, deep architectures that are known to correspond well to the primate ventral visual stream. Finally, we derive a novel measure of inter-animal consistency, and show that the best models closely match this quantity across visual areas. Taken together, our results suggest that contrastive objectives operating on shallow architectures with ethologically-motivated image transformations may be a biologically-plausible computational theory of visual coding in mice.

scholarly journals The influence of evidence volatility on choice, reaction time and confidence in a perceptual decision

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Ariel Zylberberg ◽  
Christopher R Fetsch ◽  
Michael N Shadlen
Keyword(s):  
Visual Cortex ◽  
Reaction Time ◽  
Choice Reaction Time ◽  
Signal To Noise Ratio ◽  
Stimulus Strength ◽  
Signal To Noise ◽  
Perceptual Decision ◽  
Evidence Accumulation ◽  
Decision Speed ◽  
Speed Accuracy

Many decisions are thought to arise via the accumulation of noisy evidence to a threshold or bound. In perception, the mechanism explains the effect of stimulus strength, characterized by signal-to-noise ratio, on decision speed, accuracy and confidence. It also makes intriguing predictions about the noise itself. An increase in noise should lead to faster decisions, reduced accuracy and, paradoxically, higher confidence. To test these predictions, we introduce a novel sensory manipulation that mimics the addition of unbiased noise to motion-selective regions of visual cortex, which we verified with neuronal recordings from macaque areas MT/MST. For both humans and monkeys, increasing the noise induced faster decisions and greater confidence over a range of stimuli for which accuracy was minimally impaired. The magnitude of the effects was in agreement with predictions of a bounded evidence accumulation model.

scholarly journals Orientation tuning depends on spatial frequency in mouse visual cortex

2016 ◽  
Author(s):  
Inbal Ayzenshtat ◽  
Jesse Jackson ◽  
Rafael Yuste
Keyword(s):  
Visual Cortex ◽  
Spatial Frequency ◽  
Visual System ◽  
Primary Visual Cortex ◽  
Receptive Fields ◽  
Orientation Selectivity ◽  
Natural Scenes ◽  
Response Properties ◽  
Layer 2 ◽  
Mouse Visual Cortex

AbstractThe response properties of neurons to sensory stimuli have been used to identify their receptive fields and functionally map sensory systems. In primary visual cortex, most neurons are selective to a particular orientation and spatial frequency of the visual stimulus. Using two-photon calcium imaging of neuronal populations from the primary visual cortex of mice, we have characterized the response properties of neurons to various orientations and spatial frequencies. Surprisingly, we found that the orientation selectivity of neurons actually depends on the spatial frequency of the stimulus. This dependence can be easily explained if one assumed spatially asymmetric Gabor-type receptive fields. We propose that receptive fields of neurons in layer 2/3 of visual cortex are indeed spatially asymmetric, and that this asymmetry could be used effectively by the visual system to encode natural scenes.Significance StatementIn this manuscript we demonstrate that the orientation selectivity of neurons in primary visual cortex of mouse is highly dependent on the stimulus SF. This dependence is realized quantitatively in a decrease in the selectivity strength of cells in non-optimum SF, and more importantly, it is also evident qualitatively in a shift in the preferred orientation of cells in non-optimum SF. We show that a receptive-field model of a 2D asymmetric Gabor, rather than a symmetric one, can explain this surprising observation. Therefore, we propose that the receptive fields of neurons in layer 2/3 of mouse visual cortex are spatially asymmetric and this asymmetry could be used effectively by the visual system to encode natural scenes.Highlights–Orientation selectivity is dependent on spatial frequency.–Asymmetric Gabor model can explain this dependence.

Mammalian Visual System Organization

2017 ◽  
Author(s):  
Farran Briggs
Keyword(s):  
Visual Cortex ◽  
Visual System ◽  
Visual Information ◽  
Contextual Information ◽  
Sensory Information ◽  
Visual Image ◽  
Brain Structures ◽  
Object Representations ◽  
System A ◽  
The Brain

Many mammals, including humans, rely primarily on vision to sense the environment. While a large proportion of the brain is devoted to vision in highly visual animals, there are not enough neurons in the visual system to support a neuron-per-object look-up table. Instead, visual animals evolved ways to rapidly and dynamically encode an enormous diversity of visual information using minimal numbers of neurons (merely hundreds of millions of neurons and billions of connections!). In the mammalian visual system, a visual image is essentially broken down into simple elements that are reconstructed through a series of processing stages, most of which occur beneath consciousness. Importantly, visual information processing is not simply a serial progression along the hierarchy of visual brain structures (e.g., retina to visual thalamus to primary visual cortex to secondary visual cortex, etc.). Instead, connections within and between visual brain structures exist in all possible directions: feedforward, feedback, and lateral. Additionally, many mammalian visual systems are organized into parallel channels, presumably to enable efficient processing of information about different and important features in the visual environment (e.g., color, motion). The overall operations of the mammalian visual system are to: (1) combine unique groups of feature detectors in order to generate object representations and (2) integrate visual sensory information with cognitive and contextual information from the rest of the brain. Together, these operations enable individuals to perceive, plan, and act within their environment.

Motion direction signals in the primary visual cortex of cat and monkey

2001 ◽  
Vol 18 (4) ◽  
pp. 501-516 ◽  
Author(s):  
WILSON S. GEISLER ◽  
DUANE G. ALBRECHT ◽  
ALISON M. CRANE ◽  
LAWRENCE STERN
Keyword(s):  
Visual Cortex ◽  
Receptive Field ◽  
Visual System ◽  
Primary Visual Cortex ◽  
Spatial Orientation ◽  
Cortical Neurons ◽  
Image Feature ◽  
Motion Direction ◽  
Parallel Motion ◽  
Tuning Function

When an image feature moves with sufficient speed it should become smeared across space, due to temporal integration in the visual system, effectively creating a spatial motion pattern that is oriented in the direction of the motion. Recent psychophysical evidence shows that such “motion streak signals” exist in the human visual system. In this study, we report neurophysiological evidence that these motion streak signals also exist in the primary visual cortex of cat and monkey. Single neuron responses were recorded for two kinds of moving stimuli: single spots presented at different velocities and drifting plaid patterns presented at different spatial and temporal frequencies. Measurements were made for motion perpendicular to the spatial orientation of the receptive field (“perpendicular motion”) and for motion parallel to the spatial orientation of the receptive field (“parallel motion”). For moving spot stimuli, as the speed increases, the ratio of the responses to parallel versus perpendicular motion increases, and above some critical speed, the response to parallel motion exceeds the response to perpendicular motion. For moving plaid patterns, the average temporal tuning function is approximately the same for both parallel motion and perpendicular motion; in contrast, the spatial tuning function is quite different for parallel motion and perpendicular motion (band pass for the former and low pass for the latter). In general, the responses to spots and plaids are consistent with the conventional model of cortical neurons with one rather surprising exception: Many cortical neurons appear to be direction selective for parallel motion. We propose a simple explanation for “parallel motion direction selectivity” and discuss its implications for the motion streak hypothesis. Taken as a whole, we find that the measured response properties of cortical neurons to moving spot and plaid patterns agree with the recent psychophysics and support the hypothesis that motion streak signals are present in V1.

Effects of vasoactive intestinal polypeptide on the response properties of cells in area 17 of the cat visual cortex

1993 ◽  
Vol 69 (5) ◽  
pp. 1465-1474 ◽  
Author(s):  
P. C. Murphy ◽  
K. L. Grieve ◽  
A. M. Sillito
Keyword(s):  
Visual Cortex ◽  
Spontaneous Activity ◽  
Vasoactive Intestinal Polypeptide ◽  
Signal To Noise Ratio ◽  
Response Magnitude ◽  
Visual Response ◽  
Area 17 ◽  
Signal To Noise ◽  
Cortical Cells ◽  
Cholinergic Agonist

1. Vasoactive intestinal polypeptide (VIP) was iontophoretically applied to a population of 90 single cells in the primary visual cortex (area 17) of the cat. Response magnitude, response selectivity, spontaneous activity, and the ratio between the visual response and spontaneous activity (signal-to-noise ratio) of the cells were assessed quantitatively before and during drug application. 2. VIP had little effect in the absence of visual stimulation, with only 29/90 (32%) of the cells showing a change of even 1 sp/s in their spontaneous activity. In contrast it had a clear effect on the visual responses of the majority (73/90, 81%) of the cells tested. 3. VIP produced a substantial change (i.e., > or = 40%) in optimal response magnitude for 57 of the affected cells. Of these 65% were facilitated, usually with no change or an improvement in signal-to-noise ratio and direction selectivity. The remaining cells were inhibited, with more variable effects on their visual response characteristics, and were found predominantly in the superficial laminae. 4. The effects of VIP bore a remarkable resemblance to those reported previously for the muscarinic action of acetylcholine (ACh). VIP and a muscarinic cholinergic agonist, either ACh or acetyl-beta-methacholine (MeCh), were therefore applied in turn to a group of 40 cells. In 23 cases VIP and the muscarinic agonist were also applied simultaneously. 5. The effects of VIP and the cholinergic agonist matched in 92% of the cases where both drugs were effective. That is to say, cells that were facilitated by VIP were facilitated also by ACh or MeCh, and vice versa. In many instances there was a clear similarity in the pattern as well as the direction of the effects produced by the two substances. The result of simultaneous application was generally additive. 6. These data suggest that VIP and ACh activate very similar postsynaptic mechanisms, and share a closely related function at the level of individual cortical cells. Thus VIP may facilitate the responses of both the excitatory and the inhibitory components of the cortical circuit, leading to an overall increase in responsiveness and selectivity. In contrast to the cholinergic input from the basal forebrain, however, the VIP-positive cortical cells are likely to exert a very localized influence, over a circumscribed region of the cortex, in response to the presence of an effective visual stimulus.

Cholinergic and noradrenergic afferents influence the functional properties of the postnatal visual cortex in rats

1999 ◽  
Vol 16 (6) ◽  
pp. 1015-1028 ◽  
Author(s):  
ROSITA SICILIANO ◽  
FRANCESCO FORNAI ◽  
IRENE BONACCORSI ◽  
LUCIANO DOMENICI ◽  
PAOLA BAGNOLI
Keyword(s):  
Visual Cortex ◽  
Functional Properties ◽  
Cortical Neurons ◽  
Developmental Plasticity ◽  
Signal To Noise Ratio ◽  
Ocular Dominance ◽  
Field Size ◽  
Cortical Cells ◽  
Visual Cortical ◽  
Na Depletion

Based on previous evidence that acetylcholine (ACh) and noradrenaline (NA) play a permissive role in developmental plasticity in the kitten visual cortex, we reinvestigated this topic in the postnatal visual cortex of rats with normal vision. In rats, the functional properties of visual cortical cells develop gradually between the second and the sixth postnatal week (Fagiolini et al., 1994). Cortical cholinergic depletion, by basal forebrain (BF) lesions at postnatal day (PD) 15 (eye opening), leads to a transient disturbance in the distribution of ocular dominance (Siciliano et al., 1997). In the present study, we investigated the development of visual cortical response properties following cytotoxic lesions of the locus coeruleus (LC) alone or in combination with lesions of cholinergic BF. The main result is that early NA depletion impairs the orientation selectivity of cortical neurons, causes a slight increase of their receptive-field size, and reduces the signal-to-noise ratio of cell responses. Similar effects are obtained following NA depletion in adult animals, although the effects of adult noradrenergic deafferentation are significantly more severe than those obtained after early NA depletion. Additional cholinergic depletion causes an additional transient change in ocular-dominance distribution similarly to that obtained after cholinergic deafferentation alone. Comparisons between depletion of NA on the one hand and depletion of both NA and ACh on the other suggest that the effects of combined deafferentation on the functional properties studied result from simple linear addition of the effects of depleting each afferent system alone.

Orientation Discrimination and Cortical Function in the Human Newborn

Perception ◽  
1988 ◽  
Vol 17 (5) ◽  
pp. 597-602 ◽  
Author(s):  
Alan Slater ◽  
Victoria Morison ◽  
Marcia Somers
Keyword(s):  
Visual Cortex ◽  
Visual System ◽  
Newborn Infants ◽  
Mirror Image ◽  
Orientation Discrimination ◽  
The Novel ◽  
Critical Test ◽  
Cortical Function ◽  
Human Newborn ◽  
Visual Cortical

There is some controversy concerning whether or not the visual abilities of the newborn are mediated entirely through subcortical pathways or whether the visual cortex is functioning at birth. A critical test of cortical functioning is discrimination of orientation: orientation-selective neurons are found in the visual cortex but not in subcortical parts of the visual system. An experiment is described in which newborn infants were habituated to a square-wave grating oriented 45° from vertical. After habituation, significant preferences for the novel, mirror-image, grating were found, a result which argues for some degree of visual cortical functioning at birth.

scholarly journals A Convolutional Network Architecture Driven by Mouse Neuroanatomical Data

2020 ◽  
Author(s):  
Jianghong Shi ◽  
Michael A. Buice ◽  
Eric Shea-Brown ◽  
Stefan Mihalas ◽  
Bryan Tripp
Keyword(s):  
Visual Cortex ◽  
Visual System ◽  
Network Architecture ◽  
Structural Parameters ◽  
Cortical Layer ◽  
Hierarchical Organization ◽  
Visually Guided ◽  
Convolutional Network ◽  
Mouse Visual Cortex ◽  
Neuroanatomical Data

Convolutional neural networks trained on object recognition derive some inspiration from the neuroscience of the visual system in primates, and have been used as models of the feedforward computation performed in the primate ventral stream. In contrast to the hierarchical organization of primates, the visual system of the mouse has flatter hierarchy. Since mice are capable of visually guided behavior, this raises questions about the role of architecture in neural computation. In this work, we introduce a framework for building a biologically constrained convolutional neural network model of lateral areas of the mouse visual cortex. The structural parameters of the network are derived from experimental measurements, specifically estimates of numbers of neurons in each area and cortical layer, the interareal connec-tome, and the statistics of connections between cortical layers. This network is constructed to support detailed task-optimized models of mouse visual cortex, with neural populations that can be compared to specific corresponding populations in the mouse brain. The code is freely available to support such research.

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