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Record W4283166607 · doi:10.3389/fnhum.2022.883337

Effects of Online Single Pulse Transcranial Magnetic Stimulation on Prefrontal and Parietal Cortices in Deceptive Processing: A Preliminary Study

2022· article· en· W4283166607 on OpenAlexaff
Bruce Luber, Lysianne Beynel, Timothy Spellman, Hannah Gura, Markus Ploesser, Kate Termini, Sarah H. Lisanby

Bibliographic record

VenueFrontiers in Human Neuroscience · 2022
Typearticle
Languageen
FieldPsychology
TopicDeception detection and forensic psychology
Canadian institutionsUniversity of British Columbia
FundersAdvanced Research Projects AgencyDefense Advanced Research Projects Agency
KeywordsTranscranial magnetic stimulationPsychologyNeuroscienceStimulus (psychology)Posterior parietal cortexDorsolateral prefrontal cortexPrefrontal cortexStimulationCognitive psychologyCognition

Abstract

fetched live from OpenAlex

Transcranial magnetic stimulation (TMS) was used to test the functional role of parietal and prefrontal cortical regions activated during a playing card Guilty Knowledge Task (GKT). Single-pulse TMS was applied to 15 healthy volunteers at each of three target sites: left and right dorsolateral prefrontal cortex and midline parietal cortex. TMS pulses were applied at each of five latencies (from 0 to 480 ms) after the onset of a card stimulus. TMS applied to the parietal cortex exerted a latency-specific increase in inverse efficiency score and in reaction time when subjects were instructed to lie relative to when asked to respond with the truth, and this effect was specific to when TMS was applied at 240 ms after stimulus onset. No effects of TMS were detected at left or right DLPFC sites. This manipulation with TMS of performance in a deception task appears to support a critical role for the parietal cortex in intentional false responding, particularly in stimulus selection processes needed to execute a deceptive response in the context of a GKT. However, this interpretation is only preliminary, as further experiments are needed to compare performance within and outside of a deceptive context to clarify the effects of deceptive intent.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.425
Threshold uncertainty score0.622

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.022
GPT teacher head0.306
Teacher spread0.284 · 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 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

Citations4
Published2022
Admission routes1
Has abstractyes

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