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Effect of the Temporal Pattern of Contralateral Inhibition on Sound Localization Cues

2005· article· en· W1486832246 on OpenAlexafffund
Gary Marsat, Gerald S. Pollack

Bibliographic record

VenueJournal of Neuroscience · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Vocal Communication and Behavior
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBinaural recordingCricketSound localizationHuman echolocationNeuronDichotic listeningNeuroscienceNeural codingInhibitory postsynaptic potentialBiologyAcousticsBiological systemCommunicationPsychologyPhysics

Abstract

fetched live from OpenAlex

We studied the temporal coding properties of identified interneurons in the auditory system of crickets, using information theory as an analytical tool. The ascending neuron 1 (AN1), which is tuned to the dominant carrier frequency (CF) of cricket songs, selectively codes the limited range of amplitude modulation (AM) frequencies that occur in these signals. AN2, which is most sensitive to the ultrasonic frequencies that occur in echolocation calls of insectivorous bats, codes a broader range of AM frequencies, as occur in bat calls. A third neuron, omega neuron 1 (ON1), which is dually tuned to both ranges of carrier frequency, was shown previously to have CF-specific coding properties, allowing it to represent accurately the differing temporal structures of both cricket songs and bat calls. ON1 is a source of contralateral inhibition to AN1 and AN2, enhancing binaural contrast and facilitating sound localization. We used dichotic stimulation to examine the importance of the temporal structure of contralateral inhibition for enhancing binaural contrast. Contralateral inhibition degrades the coding of temporal pattern by AN1 and AN2, but only if the temporal pattern of inhibitory input matches that of excitation. Firing rate is also decreased most strongly by temporally matched contralateral inhibition. This is apparent for AN1 in its mean firing rate; for AN2, high-frequency firing is selectively suppressed. Our results show that the CF-specific coding properties of ON1 allow this single neuron to enhance effectively localization cues for both cricket-like and bat-like acoustic signals.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.107

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 head0.018
GPT teacher head0.300
Teacher spread0.282 · 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

Citations43
Published2005
Admission routes2
Has abstractyes

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