scholarly journals Majority of choice-related variability in perceptual decisions is present in early sensory cortex

2017 ◽  
Author(s):  
Charles A. Michelson ◽  
Jonathan W. Pillow ◽  
Eyal Seidemann
Keyword(s):  
Visual Information ◽  
Visual Detection ◽  
Detection Task ◽  
Sensory Cortex ◽  
Neural Population ◽  
Processing Stage ◽  
Population Responses ◽  
Visible Target ◽  
Perceptual Variability ◽  
Neural Variability

ABSTRACTWhile performing challenging perceptual tasks such as detecting a barely visible target, our perceptual reports vary across presentations of identical stimuli. This perceptual variability is presumably caused by neural variability in our brains. How much of the neural variability that correlates with the perceptual variability is present in the primary visual cortex (V1), the first cortical processing stage of visual information? To address this question, we recorded neural population responses from V1 using voltage-sensitive dye imaging while monkeys performed a challenging reaction-time visual detection task. We found that V1 responses in the period leading to the decision correspond more closely to the monkey’s report than to the visual stimulus. These results, together with a simple computational model that allows one to quantify the captured choice-related variability, suggest that most this variability is present in V1, and that areas outside of V1 contain relatively little independent choice-related variability.

scholarly journals Optimal Temporal Decoding of Neural Population Responses in a Reaction-Time Visual Detection Task

2008 ◽  
Vol 99 (3) ◽  
pp. 1366-1379 ◽  
Author(s):  
Yuzhi Chen ◽  
Wilson S. Geisler ◽  
Eyal Seidemann
Keyword(s):  
Reaction Time ◽  
Initial Response ◽  
Detection Task ◽  
Ideal Observer ◽  
Neural Population ◽  
Population Responses ◽  
Temporal Correlations ◽  
Lower Amplitude ◽  
Temporal Decorrelation ◽  
Speed And Accuracy

Behavioral performance in detection and discrimination tasks is likely to be limited by the quality and nature of the signals carried by populations of neurons in early sensory cortical areas. Here we used voltage-sensitive dye imaging (VSDI) to directly measure neural population responses in the primary visual cortex (V1) of monkeys performing a reaction-time detection task. Focusing on the temporal properties of the population responses, we found that V1 responses are consistent with a stimulus-evoked response with amplitude and latency that depend on target contrast and a stimulus-independent additive noise with long-lasting temporal correlations. The noise had much lower amplitude than the ongoing activity reported previously in anesthetized animals. To understand the implications of these properties for subsequent processing stages that mediate behavior, we derived the Bayesian ideal observer that specifies how to optimally use neural responses in reaction time tasks. Using the ideal observer analysis, we show that 1) the observed temporal correlations limit the performance benefit that can be attained by accumulating V1 responses over time, 2) a simple temporal decorrelation operation with time-lagged excitation and inhibition minimizes the detrimental effect of these correlations, 3) the neural information relevant for target detection is concentrated in the initial response following stimulus onset, and 4) a decoder that optimally uses V1 responses far outperforms the monkey in both speed and accuracy. Finally, we demonstrate that for our particular detection task, temporal decorrelation followed by an appropriate running integrator can approach the speed and accuracy of the optimal decoder.

scholarly journals A flow-based latent state generative model of neural population responses to natural images

2021 ◽  
Author(s):  
Mohammad Bashiri ◽  
Edgar Y. Walker ◽  
Konstantin-Klemens Lurz ◽  
Akshay Kumar Jagadish ◽  
Taliah Muhammad ◽  
...  
Keyword(s):  
State Of The Art ◽  
Brain Area ◽  
Neural System ◽  
Generative Model ◽  
Natural Images ◽  
Neural Population ◽  
Population Responses ◽  
Previous State ◽  
State Models ◽  
Neural Variability

AbstractWe present a joint deep neural system identification model for two major sources of neural variability: stimulus-driven and stimulus-conditioned fluctuations. To this end, we combine (1) state-of-the-art deep networks for stimulus-driven activity and (2) a flexible, normalizing flow-based generative model to capture the stimulus-conditioned variability including noise correlations. This allows us to train the model end-to-end without the need for sophisticated probabilistic approximations associated with many latent state models for stimulus-conditioned fluctuations. We train the model on the responses of thousands of neurons from multiple areas of the mouse visual cortex to natural images. We show that our model outperforms previous state-of-the-art models in predicting the distribution of neural population responses to novel stimuli, including shared stimulus-conditioned variability. Furthermore, it successfully learns known latent factors of the population responses that are related to behavioral variables such as pupil dilation, and other factors that vary systematically with brain area or retinotopic location. Overall, our model accurately accounts for two critical sources of neural variability while avoiding several complexities associated with many existing latent state models. It thus provides a useful tool for uncovering the interplay between different factors that contribute to variability in neural activity.

scholarly journals Causal modulation of right hemisphere fronto-parietal phase synchrony with Transcranial Magnetic Stimulation during a conscious visual detection task

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chloé Stengel ◽  
Marine Vernet ◽  
Julià L. Amengual ◽  
Antoni Valero-Cabré
Keyword(s):  
Transcranial Magnetic Stimulation ◽  
Visual Perception ◽  
Frequency Band ◽  
Magnetic Stimulation ◽  
Visual Detection ◽  
Detection Task ◽  
Oscillatory Activity ◽  
Top Down ◽  
The Right ◽  
High Beta

AbstractCorrelational evidence in non-human primates has reported increases of fronto-parietal high-beta (22–30 Hz) synchrony during the top-down allocation of visuo-spatial attention. But may inter-regional synchronization at this specific frequency band provide a causal mechanism by which top-down attentional processes facilitate conscious visual perception? To address this question, we analyzed electroencephalographic (EEG) signals from a group of healthy participants who performed a conscious visual detection task while we delivered brief (4 pulses) rhythmic (30 Hz) or random bursts of Transcranial Magnetic Stimulation (TMS) to the right Frontal Eye Field (FEF) prior to the onset of a lateralized target. We report increases of inter-regional synchronization in the high-beta band (25–35 Hz) between the electrode closest to the stimulated region (the right FEF) and right parietal EEG leads, and increases of local inter-trial coherence within the same frequency band over bilateral parietal EEG contacts, both driven by rhythmic but not random TMS patterns. Such increases were accompained by improvements of conscious visual sensitivity for left visual targets in the rhythmic but not the random TMS condition. These outcomes suggest that high-beta inter-regional synchrony can be modulated non-invasively and that high-beta oscillatory activity across the right dorsal fronto-parietal network may contribute to the facilitation of conscious visual perception. Our work supports future applications of non-invasive brain stimulation to restore impaired visually-guided behaviors by operating on top-down attentional modulatory mechanisms.

scholarly journals Expectation and Surprise Determine Neural Population Responses in the Ventral Visual Stream

2010 ◽  
Vol 30 (49) ◽  
pp. 16601-16608 ◽  
Author(s):  
T. Egner ◽  
J. M. Monti ◽  
C. Summerfield
Keyword(s):  
Neural Population ◽  
Visual Stream ◽  
Population Responses ◽  
Ventral Visual Stream

Effectiveness of Accommodative Aids in Reducing Empty Field Myopia in Visual Search

1978 ◽  
Vol 20 (6) ◽  
pp. 733-740 ◽  
Author(s):  
Michael L. Matthews ◽  
Robert G. Angus ◽  
Douglas G. Pearce
Keyword(s):  
Visual Search ◽  
Visual Detection ◽  
Field Performance ◽  
Detection Task ◽  
Performance Loss ◽  
Aircraft Cabin ◽  
Search Area ◽  
A Performance

When a visual detection task is performed with distant targets in the absence of adequate accommodative cues, a performance loss is obtained which has been attributed to empty field myopia. It is shown that in a visual search situation an accommodative aid located at optical infinity improves detection by approximately 30% over empty field performance. It is further demonstrated that such an aid may overcome the conflicting accommodative cues provided by proximal contours defining the search area, i.e., a situation that is analogous to the detection of distant targets by observers searching through aircraft cabin windows.

Transient and linearly graded deactivation of the human default-mode network by a visual detection task

NeuroImage ◽  
2008 ◽  
Vol 41 (1) ◽  
pp. 100-112 ◽  
Author(s):  
K.D. Singh ◽  
I.P. Fawcett
Keyword(s):  
Default Mode Network ◽  
Visual Detection ◽  
Detection Task ◽  
Default Mode

Theoretical Note: Coordinate Systems in Visual Word Recognition

1985 ◽  
Vol 37 (4) ◽  
pp. 613-625 ◽  
Author(s):  
Andrew F. Monk
Keyword(s):  
Word Recognition ◽  
Visual Word Recognition ◽  
Visual Information ◽  
Visual Word ◽  
Visual Features ◽  
Intermediate Representation ◽  
Coordinate Systems ◽  
Processing Stage ◽  
Tentative Model ◽  
Spatial Coordinates

Marr and Nishihara (1978) have made certain recommendations about how representations postulated in a theory of visual information processing should be specified. Using this scheme the paper discusses representations which might be postulated in a model of visual word recognition. A representation is specified in terms of a set of primitives (e.g., word identities or visual features) in combination with a coordinate system. The coordinate systems considered are retinal, spatial (e.g., position on page) word-centred (position in word) and sentence-centred (position in sentence). Various combinations of primitives and coordinate systems are considered along with how to decide which combinations are actually generated in the process of fluent reading. A tentative model is put forward in which a single processing stage, which starts anew after each saccade, generates a representation with word identities as its primitives and sentence-centred coordinates. Evidence to support such a model which has no intermediate representation with spatial coordinates is briefly reviewed.

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