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Record W2085323454 · doi:10.1371/journal.pone.0064294

Adaptation Shifts Preferred Orientation of Tuning Curve in the Mouse Visual Cortex

2013· article· en· W2085323454 on OpenAlexaff
Jeyadarshan Jeyabalaratnam, Vishal Bharmauria, Lyes Bachatene, Sarah Cattan, Annie Angers, Stéphane Molotchnikoff

Bibliographic record

VenuePLoS ONE · 2013
Typearticle
Languageen
FieldNeuroscience
TopicNeural dynamics and brain function
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsVisual cortexStimulus (psychology)NeuroscienceAdaptation (eye)BiophysicsBiologyPhysicsPsychologyCognitive psychology

Abstract

fetched live from OpenAlex

In frontalized mammals it has been demonstrated that adaptation produces shift of the peak of the orientation tuning curve of neuron following frequent or lengthier presentation of a non-preferred stimulus. Depending on the duration of adaptation the shift is attractive (toward the adapter) or repulsive (away from the adapter). Mouse exhibits a salt-and-pepper cortical organization of orientation maps, hence this species may respond differently to adaptation. To examine this question, we determined the effect of twelve minutes of adaptation to one particular orientation on neuronal orientation tuning curves in V1 of anesthetized mice. Multi-unit activity of neurons in V1 was recorded in a conventional fashion. Cells were stimulated with sine-wave drifting gratings whose orientation tilted in steps. Results revealed that similarly to cats and monkeys, majority of cells shifted their optimal orientation in the direction of the adapter while a small proportion exhibited a repulsive shift. Moreover, initially untuned cells showing poor tuning curves reacted to adaptation by displaying sharp orientation selectivity. It seems that modification of the cellular property following adaptation is a general phenomenon observed in all mammals in spite of the different organization pattern of the visual cortex. This study is of pertinence to comprehend the mechanistic pathways of brain plasticity.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.635
Threshold uncertainty score0.178

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.084
GPT teacher head0.265
Teacher spread0.181 · 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

Citations44
Published2013
Admission routes1
Has abstractyes

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