scholarly journals On the Subspace Invariance of Population Responses

2018 ◽  
Author(s):  
Elaine Tring ◽  
Dario L. Ringach
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Power Distribution ◽  
Gain Control ◽  
Population Coding ◽  
Neural Population ◽  
Angular Deviation ◽  
Strong Negative Correlation ◽  
Population Responses ◽  
The Individual

The response of a neural population in cat primary visual cortex to the linear combination of two sinusoidal gratings (a plaid) can be well approximated by a weighted sum of the population responses to the individual gratings – a property we refer to as subspace invariance. We tested subspace invariance in mouse primary visual cortex by measuring the angle between the population response to a plaid and the plane spanned by the population responses to its individual components. We found robust violations of subspace invariance, represented by a median angular deviation of ~55 deg. The cause of this departure is a strong, negative correlation between the mean responses a neuron to the individual gratings and its response to the plaid. We suggest that an early nonlinearity may distort the power distribution of grating and plaid stimuli such that plaids have a prominent power component at ±45 deg off the fundamental orientations. We conclude that subspace invariance does not hold in mouse V1. This finding rules out a large class of possible models of population coding, including vector averaging and gain control.

Mapping of Stimulus Energy in Primary Visual Cortex

2005 ◽  
Vol 94 (1) ◽  
pp. 788-798 ◽  
Author(s):  
Valerio Mante ◽  
Matteo Carandini
Keyword(s):  
Visual Cortex ◽  
Optical Imaging ◽  
Primary Visual Cortex ◽  
Receptive Fields ◽  
Imaging Study ◽  
Energy Model ◽  
Related Phenomenon ◽  
Population Responses ◽  
Stimulus Energy ◽  
Length Direction

A recent optical imaging study of primary visual cortex (V1) by Basole, White, and Fitzpatrick demonstrated that maps of preferred orientation depend on the choice of stimuli used to measure them. These authors measured population responses expressed as a function of the optimal orientation of long drifting bars. They then varied bar length, direction, and speed and found that stimuli of a same orientation can elicit different population responses and stimuli with different orientation can elicit similar population responses. We asked whether these results can be explained from known properties of V1 receptive fields. We implemented an “energy model” where a receptive field integrates stimulus energy over a region of three-dimensional frequency space. The population of receptive fields defines a volume of visibility, which covers all orientations and a plausible range of spatial and temporal frequencies. This energy model correctly predicts the population response to bars of different length, direction, and speed and explains the observations made with optical imaging. The model also readily explains a related phenomenon, the appearance of motion streaks for fast-moving dots. We conclude that the energy model can be applied to activation maps of V1 and predicts phenomena that may otherwise appear to be surprising. These results indicate that maps obtained with optical imaging reflect the layout of neurons selective for stimulus energy, not for isolated stimulus features such as orientation, direction, and speed.

scholarly journals Locomotion enhances neural encoding of visual stimuli in mouse V1

2017 ◽  
Author(s):  
Maria C. Dadarlat ◽  
Michael P. Stryker
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Visual Stimuli ◽  
Major Effect ◽  
Neural Population ◽  
Neural Encoding ◽  
Firing Rates ◽  
Fold Reduction ◽  
Layer V ◽  
The Relationship

AbstractNeurons in mouse primary visual cortex (V1) are selective for particular properties of visual stimuli. Locomotion causes a change in cortical state that leaves their selectivity unchanged but strengthens their responses. Both locomotion and the change in cortical state are initiated by projections from the mesencephalic locomotor region (MLR), the latter through a disinhibitory circuit in V1. The function served by this change in cortical state is unknown. By recording simultaneously from a large number of single neurons in alert mice viewing moving gratings, we investigated the relationship between locomotion and the information contained within the neural population. We found that locomotion improved encoding of visual stimuli in V1 by two mechanisms. First, locomotion-induced increases in firing rates enhanced the mutual information between visual stimuli and single neuron responses over a fixed window of time. Second, stimulus discriminability was improved, even for fixed population firing rates, because of a decrease in noise correlations across the population during locomotion. These two mechanisms contributed differently to improvements in discriminability across cortical layers, with changes in firing rates most important in the upper layers and changes in noise correlations most important in layer V. Together, these changes resulted in a three- to five-fold reduction in the time needed to precisely encode grating direction and orientation. These results support the hypothesis that cortical state shifts during locomotion to accommodate an increased load on the visual system when mice are moving.Significance StatementThis paper contains three novel findings about the representation of information in neurons within the primary visual cortex of the mouse. First, we show that locomotion reduces by at least a factor of three the time needed for information to accumulate in the visual cortex that allows the distinction of different visual stimuli. Second, we show that the effect of locomotion is to increase information in cells of all layers of the visual cortex. Third we show that the means by which information is enhanced by locomotion differs between the upper layers, where the major effect is the increasing of firing rates, and in layer V, where the major effect is the reduction in noise correlations.

scholarly journals Orientation Tuning of Input Conductance, Excitation, and Inhibition in Cat Primary Visual Cortex

2000 ◽  
Vol 84 (2) ◽  
pp. 909-926 ◽  
Author(s):  
Jeffrey S. Anderson ◽  
Matteo Carandini ◽  
David Ferster
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Visual Stimulation ◽  
Gain Control ◽  
Orientation Tuning ◽  
Visual Responses ◽  
Stimulus Contrast ◽  
Simple Cells ◽  
Conductance Changes ◽  
Input Conductance

The input conductance of cells in the cat primary visual cortex (V1) has been shown recently to grow substantially during visual stimulation. Because increasing conductance can have a divisive effect on the synaptic input, theoretical proposals have ascribed to it specific functions. According to the veto model, conductance increases would serve to sharpen orientation tuning by increasing most at off-optimal orientations. According to the normalization model, conductance increases would control the cell's gain, by being independent of stimulus orientation and by growing with stimulus contrast. We set out to test these proposals and to determine the visual properties and possible synaptic origin of the conductance increases. We recorded the membrane potential of cat V1 cells while injecting steady currents and presenting drifting grating patterns of varying contrast and orientation. Input conductance grew with stimulus contrast by 20–300%, generally more in simple cells (40–300%) than in complex cells (20–120%), and in simple cells was strongly modulated in time. Conductance was invariably maximal for stimuli of the preferred orientation. Thus conductance changes contribute to a gain control mechanism, but the strength of this gain control does not depend uniquely on contrast. By assuming that the conductance changes are entirely synaptic, we further derived the excitatory and inhibitory synaptic conductances underlying the visual responses. In simple cells, these conductances were often arranged in push-pull: excitation increased when inhibition decreased and vice versa. Excitation and inhibition had similar preferred orientations and did not appear to differ in tuning width, suggesting that the intracortical synaptic inputs to simple cells of cat V1 originate from cells with similar orientation tuning. This finding is at odds with models where orientation tuning in simple cells is achieved by inhibition at off-optimal orientations or sharpened by inhibition that is more broadly tuned than excitation.

scholarly journals Shorter latencies for motion trajectories than for flashes in population responses of cat primary visual cortex

2004 ◽  
Vol 556 (3) ◽  
pp. 971-982 ◽  
Author(s):  
Dirk Jancke ◽  
Wolfram Erlhagen ◽  
Gregor Schöner ◽  
Hubert R. Dinse
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Population Responses ◽  
Motion Trajectories

scholarly journals Attending Multiple Items Decreases the Selectivity of Population Responses in Human Primary Visual Cortex

2013 ◽  
Vol 33 (22) ◽  
pp. 9273-9282 ◽  
Author(s):  
D. E. Anderson ◽  
E. F. Ester ◽  
J. T. Serences ◽  
E. Awh
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Population Responses

scholarly journals Gain control from beyond the classical receptive field in primate primary visual cortex

2003 ◽  
Vol 20 (3) ◽  
pp. 221-230 ◽  
Author(s):  
BEN S. WEBB ◽  
CHRIS J. TINSLEY ◽  
NICK E. BARRACLOUGH ◽  
AMANDA PARKER ◽  
ANDREW M. DERRINGTON
Keyword(s):  
Visual Cortex ◽  
Receptive Field ◽  
Primary Visual Cortex ◽  
Gain Control ◽  
Salient Feature ◽  
Retinal Eccentricity ◽  
V1 Neurons ◽  
Contrast Gain ◽  
Classical Receptive Field ◽  
Extrastriate Areas

Gain control is a salient feature of information processing throughout the visual system. Heeger (1991, 1992) described a mechanism that could underpin gain control in primary visual cortex (V1). According to this model, a neuron's response is normalized by dividing its output by the sum of a population of neurons, which are selective for orientations covering a broad range. Gain control in this scheme is manifested as a change in the semisaturation constant (contrast gain) of a V1 neuron. Here we examine how flanking and annular gratings of the same or orthogonal orientation to that preferred by a neuron presented beyond the receptive field modulate gain in V1 neurons in anesthetized marmosets (Callithrix jacchus). To characterize how gain was modulated by surround stimuli, the Michaelis–Menten equation was fitted to response versus contrast functions obtained under each stimulus condition. The modulation of gain by surround stimuli was modelled best as a divisive reduction in response gain. Response gain varied with the orientation of surround stimuli, but was reduced most when the orientation of a large annular grating beyond the classical receptive field matched the preferred orientation of neurons. The strength of surround suppression did not vary significantly with retinal eccentricity or laminar distribution. In the marmoset, as in macaques (Angelucci et al., 2002a, b), gain control over the sort of distances reported here (up to 10 deg) may be mediated by feedback from extrastriate areas.

scholarly journals Population Responses Represent Vocalization Identity, Intensity, and Signal-to-Noise Ratio in Primary Auditory Cortex

2019 ◽  
Author(s):  
Ruiye Ni ◽  
David A. Bender ◽  
Dennis L. Barbour
Keyword(s):  
Auditory Cortex ◽  
Single Unit ◽  
Temporal Dynamics ◽  
Population Analysis ◽  
Primary Auditory Cortex ◽  
Population Coding ◽  
Single Units ◽  
Neural Population ◽  
Population Responses ◽  
Noise Ratio

AbstractThe ability to process speech signals under challenging listening environments is critical for speech perception. Great efforts have been made to reveal the underlying single unit encoding mechanism. However, big variability is usually discovered in single-unit responses, and the population coding mechanism is yet to be revealed. In this study, we are aimed to study how a population of neurons encodes behaviorally relevant signals subjective to change in intensity and signal-noise-ratio (SNR). We recorded single-unit activity from the primary auditory cortex of awake common marmoset monkeys (Callithrix jacchus) while delivering conspecific vocalizations degraded by two different background noises: broadband white noise (WGN) and vocalization babble (Babble). By pooling all single units together, the pseudo-population analysis showed the population neural responses track intra- and inter-trajectory angle evolutions track vocalization identity and intensity/SNR, respectively. The ability of the trajectory to track the vocalizations attribute was degraded to a different degree by different noises. Discrimination of neural populations evaluated by neural response classifiers revealed that a finer optimal temporal resolution and longer time scale of temporal dynamics were needed for vocalizations in noise than vocalizations at multiple different intensities. The ability of population responses to discriminate between different vocalizations were mostly retained above the detection threshold.Significance StatementHow our brain excels in the challenge of precise acoustic signal encoding against noisy environment is of great interest for scientists. Relatively few studies have strived to tackle this mystery from the perspective of neural population responses. Population analysis reveals the underlying neural encoding mechanism of complex acoustic stimuli based upon a pool of single units via vector coding. We suggest the spatial population response vectors as one important way for neurons to integrate multiple attributes of natural acoustic signals, specifically, marmots’ vocalizations.

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