MétaCan
Menu
Back to cohort
Record W2608485585 · doi:10.5812/archneurosci.33683

Top-down Approach to the Investigation of the Neural Basis of Geometric-optical Illusions: Understanding the Brain as a Theoretical Entity

2017· article· en· W2608485585 on OpenAlexaff
Farshad Nemati

Bibliographic record

VenueArchives of Neuroscience · 2017
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsIllusionPerceptionOptical illusionContext (archaeology)PsychologyCognitive scienceCognitionCognitive psychologyUnificationCognitive neuroscienceNeuroscienceComputer science

Abstract

fetched live from OpenAlex

: Geometric-optical illusions have been the subjects of research interest in a number of disciplines in science. Moreover, investigation of the patients’ reactions to illusory configurations has been somewhat instrumental in the understanding of impaired neuro-cognitive processes underlying some of the neurological and/or psychiatric disorders. Recently, neuroscientists have made some progress in understanding the neural underpinning of the geometric-optical illusions. However, a closer collaboration between psychology and neuroscience may lead to a better understanding of not only the neural basis of the illusions but the function of the brain in general. The purpose of the present analysis is to outline a sound epistemological ground for such a relationship and to demonstrate how psychological theories may potentially play a guiding role in the context of scientific discoveries in the neuroscience of illusory phenomena. In order to do so, two concepts of the “many-one” relationship between the mental and the neural states and “context-sensitivity” will be described with regard to the possible relationships between perception and brain in the context of research on illusions. In addition, the implications of the top-down strategy for research in Psychiatry will be explained and the strategy will be discussed as a path towards the unification of scientific explanations.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.935
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
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 head0.089
GPT teacher head0.324
Teacher spread0.234 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueArchives of NeuroscienceSame topicAction Observation and SynchronizationFrench-language works237,207