MétaCan
Menu
Back to cohort

Recruitment of Foveal Retinotopic Cortex During Haptic Exploration of Shapes and Actions in the Dark

2017· article· en· W2766291058 on OpenAlexafffund
Simona Monaco, Jason P. Gallivan, Teresa D. Figley, Anthony Singhal, Jody C. Culham

Bibliographic record

VenueJournal of Neuroscience · 2017
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsWestern UniversityUniversity of AlbertaUniversity of ManitobaHealth Sciences CentreManitoba HealthQueen's University
FundersCanadian Institutes of Health Research
KeywordsFovealCuneusIntraparietal sulcusHaptic technologyVisual cortexPsychologyVisual fieldFixation (population genetics)Stimulus (psychology)NeuroscienceComputer visionCognitive psychologyFunctional magnetic resonance imagingComputer scienceArtificial intelligencePrecuneusMedicineOphthalmology

Abstract

fetched live from OpenAlex

The role of the early visual cortex and higher-order occipitotemporal cortex has been studied extensively for visual recognition and to a lesser degree for haptic recognition and visually guided actions. Using a slow event-related fMRI experiment, we investigated whether tactile and visual exploration of objects recruit the same “visual” areas (and in the case of visual cortex, the same retinotopic zones) and if these areas show reactivation during delayed actions in the dark toward haptically explored objects (and if so, whether this reactivation might be due to imagery). We examined activation during visual or haptic exploration of objects and action execution (grasping or reaching) separated by an 18 s delay. Twenty-nine human volunteers (13 females) participated in this study. Participants had their eyes open and fixated on a point in the dark. The objects were placed below the fixation point and accordingly visual exploration activated the cuneus, which processes retinotopic locations in the lower visual field. Strikingly, the occipital pole (OP), representing foveal locations, showed higher activation for tactile than visual exploration, although the stimulus was unseen and location in the visual field was peripheral. Moreover, the lateral occipital tactile–visual area (LOtv) showed comparable activation for tactile and visual exploration. Psychophysiological interaction analysis indicated that the OP showed stronger functional connectivity with anterior intraparietal sulcus and LOtv during the haptic than visual exploration of shapes in the dark. After the delay, the cuneus, OP, and LOtv showed reactivation that was independent of the sensory modality used to explore the object. These results show that haptic actions not only activate “visual” areas during object touch, but also that this information appears to be used in guiding grasping actions toward targets after a delay. SIGNIFICANCE STATEMENT Visual presentation of an object activates shape-processing areas and retinotopic locations in early visual areas. Moreover, if the object is grasped in the dark after a delay, these areas show “reactivation.” Here, we show that these areas are also activated and reactivated for haptic object exploration and haptically guided grasping. Touch-related activity occurs not only in the retinotopic location of the visual stimulus, but also at the occipital pole (OP), corresponding to the foveal representation, even though the stimulus was unseen and located peripherally. That is, the same “visual” regions are implicated in both visual and haptic exploration; however, touch also recruits high-acuity central representation within early visual areas during both haptic exploration of objects and subsequent actions toward them. Functional connectivity analysis shows that the OP is more strongly connected with ventral and dorsal stream areas when participants explore an object in the dark than when they view it.

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)0.001
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 score0.675
Threshold uncertainty score0.216

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.327
GPT teacher head0.412
Teacher spread0.085 · 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

Citations52
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueJournal of NeuroscienceSame topicVisual perception and processing mechanismsFrench-language works237,207