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Record W4296713068 · doi:10.1152/jn.00114.2022

Adaptation-induced plasticity in the sensory cortex

2022· review· en· W4296713068 on OpenAlexafffund
Vishal Bharmauria, Afef Ouelhazi, Rudy Lussiez, Stéphane Molotchnikoff

Bibliographic record

VenueJournal of Neurophysiology · 2022
Typereview
Languageen
FieldNeuroscience
TopicNeural dynamics and brain function
Canadian institutionsUniversité de MontréalYork University
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsNeuroscienceVisual cortexNeuroplasticityStimulus (psychology)Sensory systemPlasticitySensory AdaptationAdaptation (eye)Receptive fieldNeurochemicalPsychologyCognitive psychology

Abstract

fetched live from OpenAlex

For medical and fundamental reasons, we need to understand adult brain plasticity at several levels: structural, physiological, and behavioral. Historically, brain plasticity has been mostly investigated by weakening or removing sensory inputs. The visual system has been extensively used because diminishing visual inputs, i.e., visual deprivation-induced plasticity, permits more tractable findings. The present review is centered on the reverse strategy, by imposing a novel stimulus, i.e., adaptation-induced plasticity. Adaptation refers to the constant (milliseconds to hours) presentation of a nonoptimal stimulus (adapter) within the receptive field (RF, spatial area that modulates neuronal firing) of the neuron under observation. We specifically focus on how adaptation impacts the tuning of visual neurons with other associated properties. After adaptation, visual cortical neurons respond robustly to the adapter (before adaptation it typically evokes feeble responses) by developing alternate tuning curves that outlast the adaptation time. Here, with dendritic structure as foundation, we synthesize a push-pull mechanism of development and acquisition of novel tuning curves following adaptation. We then explain how these changes apply at the global level across different brain regions and species with a short description of underlying neurochemical changes. Finally, we discuss physiopathological consequences and conclude with some gaps and questions that need to be addressed to further comprehend such neuroplasticity.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score0.671

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.150
GPT teacher head0.329
Teacher spread0.179 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations24
Published2022
Admission routes2
Has abstractyes

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