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Record W2037905235 · doi:10.1186/1471-2202-15-s1-p145

Dynamics of dichoptic masking in the primary visual cortex

2014· article· en· W2037905235 on OpenAlexafffund
Eva Chadnova, Alexandre Reynaud, Simon Clavagnier, Daniel H. Baker, Sylvain Baillet, Robert F. Hess

Bibliographic record

VenueBMC Neuroscience · 2014
Typearticle
Languageen
FieldNeuroscience
TopicNeural dynamics and brain function
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsMagnetoencephalographyVisual cortexContrast (vision)NeuroscienceMasking (illustration)Saccadic maskingGazeComputer scienceVisual perceptionArtificial intelligenceEye movementPsychologyPerceptionElectroencephalography

Abstract

fetched live from OpenAlex

The inputs from the two eyes interact in a nonlinear fashion. This interaction can be either excitatory or inhibitory: Excitatory interaction (combination) occurs first in the primary visual cortex but little is known about the site of the inhibitory interaction (suppression). To investigate the latter, experimental paradigms typically present distinct inputs to the eyes (dichoptic presentation, one target and one mask are respectively presented to different eyes at the same time). Here we used magnetoencephalography (MEG) source imaging to establish the site of the cortical neural signature of interocular suppression in visual cortex. We presented different noise stimuli to each eye: The target-noise was presented for contrasts ranging between 0 and 32 %. The mask-contrast was presented to the other eye at fixed contrast (32%). We flickered the two noise stimuli (4 and 6 Hz) to elicit a frequency-tagged steady-state visual evoked response (SSVER) that was readily detectable in MEG traces [1]. Four participants passively observed the visual presentation while keeping their gaze fixed on the center of the screen. The Brainstorm application was used to analyze the MEG data [3]. MEG source time series were extracted from cortical regions of interest (ROIs) defined from the visual retinotopic maps of each participant obtained from previous fMRI acquisitions. Using the power of the cortical responses to the frequency-tagged stimuli, we constructed contrast response functions for all the ROIs (Figure 1 A). To investigate dynamics of propagation of the response along visual cortical areas, the instantaneous phase of the signal was identified in each ROI. As expected [2], when the target was presented alone, the power of the responses was found to increase monotonically with contrast (Figure 1 B, solid line). When a mask was added to the other eye, the contrast response was attenuated (Figure 1 B, dotted line). Interestingly, the mask presented at a fixed contrast was also found to be gradually suppressed with increasing target contrast (Figure 1 C). These effects were revealed for responses as early as the primary visual cortex. In the time-domain, we detected a progressive phase shift between the cortical responses along the ventral and dorsal streams. Figure 1 A. Localization of V1 on the activity map B. Normalized power of SSVER response as a function of contrast for target only (solid line), target and mask (dotted line); C. Normalized power in a 32% contrast mask as the contrast in the target is increasing. ...

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.950
Threshold uncertainty score0.362

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.264
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2014
Admission routes2
Has abstractyes

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