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Record W2123064567 · doi:10.1186/1471-2202-12-s1-p34

Burst dynamics enable contrast coding via synchrony

2011· article· en· W2123064567 on OpenAlexaff
Oscar Ávila Åkerberg, Maurice J. Chacron

Bibliographic record

VenueBMC Neuroscience · 2011
Typearticle
Languageen
FieldNeuroscience
TopicNeural dynamics and brain function
Canadian institutionsMcGill University
Fundersnot available
KeywordsStimulus (psychology)NeuroscienceInhibitory postsynaptic potentialNeural codingSensory systemPopulationENCODEElectrophysiologyPhysicsBiologyPsychologyCognitive psychology

Abstract

fetched live from OpenAlex

Neurons in various sensory systems respond to stimuli with a variety of action potential patterns including isolated action potentials and bursts (i.e. high frequency groups of action potentials). There is accumulating evidence that, instead of being just a collection of action potentials, bursts are instead a specific pattern that signals stimulus attributes that are distinct than those signaled by isolated action potentials [1]. Specifically, it has been proposed that synchronous bursts can signal the occurrence of certain stimuli [2] and encode higher order stimulus attributes such as contrast [3]. Here we test experimentally whether synchronous activity in a population of neurons can encode a time varying stimulus contrast. To do so, we performed intracellular recordings of the activity of electrosensory pyramidal cells in-vitro. These cells have been well characterized and previous studies have shown that they tonically fire isolated action potentials under control conditions but that application of the neuromodulator serotonin (5-HT) can cause them to transition into a burst firing mode [4]. As such, we tested the information transmission capabilities of these cells about stimulus contrast in both modes. To do so, we provided the cells with a time-varying stimulus and investigated how the number of synchronous spikes correlates with stimulus contrast. We found that synchrony had a larger dependence on stimulus contrast in pyramidal cells after 5-HT injection than under control conditions. These experimental results agree with the predictions of the model presented in [2]. Furthermore, we developed a mathematical theory that supports our experimental results and proposes that the change in coding properties between bursting and non-bursting neurons is solely attributed to the higher baseline response variability as quantified by the coefficient of variation (CV) present in bursting neurons. Our experimental results therefore show that bursting neurons are more apt at coding stimulus contrast through synchronous firing than tonic ones. Moreover, our theoretical results suggest that this occurs because burst dynamics introduce variability in the responses of single neurons. The latter is supported by the fact that bursting neurons with the highest CVs showed the greatest dependency on stimulus contrast in their synchronous activities. Our results thus provide the first experimental evidence that bursting neurons can code for stimulus contrast via their synchronous activity and provide a novel function for burst dynamics.

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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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.637
Threshold uncertainty score0.873

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.061
GPT teacher head0.245
Teacher spread0.184 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

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