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Decoding motor imagery and action planning in the early visual cortex: Overlapping but distinct neural mechanisms

2020· article· en· W3027047923 on OpenAlexaff
Simona Monaco, Giulia Malfatti, Jody C. Culham, Luigi Cattaneo, Luca Turella

Bibliographic record

VenueNeuroImage · 2020
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsWestern University
FundersH2020 Marie Skłodowska-Curie ActionsH2020 European Research CouncilEuropean Research CouncilHorizon 2020 Framework ProgrammeEuropean Commission
KeywordsPremotor cortexFunctional magnetic resonance imagingMotor imageryPosterior parietal cortexPsychologyVisual cortexNeuroscienceBrain activity and meditationPrimary motor cortexNeuroimagingMotor cortexCognitive psychologyElectroencephalographyDorsumBrain–computer interfaceBiology

Abstract

fetched live from OpenAlex

Recent evidence points to a role of the primary visual cortex that goes beyond visual processing into high-level cognitive and motor-related functions, including action planning, even in absence of feedforward visual information. It has been proposed that, at the neural level, motor imagery is a simulation based on motor representations, and neuroimaging studies have shown overlapping and shared activity patterns for motor imagery and action execution in frontal and parietal cortices. Yet, the role of the early visual cortex in motor imagery remains unclear. Here we used multivoxel pattern analyses on functional magnetic resonance imaging (fMRI) data to examine whether the content of motor imagery and action intention can be reliably decoded from the activity patterns in the retinotopic location of the target object in the early visual cortex. Further, we investigated whether the discrimination between specific actions generalizes across imagined and intended movements. Eighteen right-handed human participants (11 females) imagined or performed delayed hand actions towards a centrally located object composed of a small shape attached on a large shape. Actions consisted of grasping the large or small shape, and reaching to the center of the object. We found that despite comparable fMRI signal amplitude for different planned and imagined movements, activity patterns in the early visual cortex, as well as dorsal premotor and anterior intraparietal cortex, accurately represented action plans and action imagery. However, movement content is similar irrespective of whether actions are actively planned or covertly imagined in parietal but not early visual or premotor cortex, suggesting a generalized motor representation only in regions that are highly specialized in object directed grasping actions and movement goals. In sum, action planning and imagery have overlapping but non identical neural mechanisms in the cortical action network.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.085
GPT teacher head0.341
Teacher spread0.257 · 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 source (direct Gemma or distilled Codex), 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

Citations74
Published2020
Admission routes1
Has abstractyes

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