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Record W2160794767 · doi:10.1093/cercor/bhn184

Spectrotemporal Receptive Fields in Anesthetized Cat Primary Auditory Cortex Are Context Dependent

2008· article· en· W2160794767 on OpenAlexaff
Boris Gourévitch, Arnaud Noreña, Gregory Shaw, Jos J. Eggermont

Bibliographic record

VenueCerebral Cortex · 2008
Typearticle
Languageen
FieldNeuroscience
TopicNeural dynamics and brain function
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsReceptive fieldAuditory cortexNeuroscienceNatural soundsInhibitory postsynaptic potentialExcitatory postsynaptic potentialContext (archaeology)PsychologyComputer scienceSpeech recognitionBiology

Abstract

fetched live from OpenAlex

In order to investigate how the auditory scene is analyzed and perceived, auditory spectrotemporal receptive fields (STRFs) are generally used as a convenient way to describe how frequency and temporal sound information is encoded. However, using broadband sounds to estimate STRFs imperfectly reflects the way neurons process complex stimuli like conspecific vocalizations insofar as natural sounds often show limited bandwidth. Using recordings in the primary auditory cortex of anesthetized cats, we show that presentation of narrowband stimuli not including the best frequency of neurons provokes the appearance of residual peaks and increased firing rate at some specific spectral edges of stimuli compared with classical STRFs obtained from broadband stimuli. This result is the same for STRFs obtained from both spikes and local field potentials. Potential mechanisms likely involve release from inhibition. We thus emphasize some aspects of context dependency of STRFs, that is, how the balance of inhibitory and excitatory inputs is able to shape the neural response from the spectral content of stimuli.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.829
Threshold uncertainty score1.000

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 head0.027
GPT teacher head0.230
Teacher spread0.203 · 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.

Study designObservational
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

Citations62
Published2008
Admission routes1
Has abstractyes

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