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Record W4406200864 · doi:10.1002/alz.087419

Investigating covert awareness in individuals with Alzheimer’s Disease using functional near‐infrared spectroscopy (fNIRS)

2024· article· en· W4406200864 on OpenAlexaff
Garima Gupta, Matthew Kolisnyk, Karnig Kazazian, Rafeh Shahid, Diana M Urian, Sergio L. Novi, Koula Pantazopoulos, Androu Abdalmalak, Jonathan Huntley, Derek Debicki, Stephen Pasternak, Adrian M. Owen

Bibliographic record

VenueAlzheimer s & Dementia · 2024
Typearticle
Languageen
FieldMedicine
TopicCholinesterase and Neurodegenerative Diseases
Canadian institutionsParkwood InstituteWestern University
Fundersnot available
KeywordsFunctional near-infrared spectroscopyCovertPsychologyFunctional connectivityCognitive psychologyNeuroscienceCognitionPhilosophy

Abstract

fetched live from OpenAlex

Abstract Background Alzheimer’s disease (AD) is a form of dementia that impairs memory, language, and daily functioning. With disease progression, AD patients reportedly experience disturbances in their awareness of self, others, and their environment. These disturbances are associated with unfavourable clinical outcomes, which prompts critical questions about how AD patients experience the world around them. The present study utilizes a validated neuroimaging paradigm to ‘map’ conscious experiences through changes in brain activity. The premise is that similarity (i.e., synchrony) in conscious experiences of different people can be detected by investigating activity in fronto‐parietal areas linked with higher‐order processing essential for plot‐following. This paradigm was previously used to assess conscious states of behaviorally non‐responsive brain‐injured patients, showing that the internal mental experience of some patients was similar to that of healthy controls. Methods In this study, patients with mild‐moderate AD (n = 9) and age‐matched healthy controls (n = 29) underwent a 40‐minute functional near‐infrared spectroscopy (fNIRS) scan. During the scan, participants watched two short movies, each with an intact‐ and scrambled‐plot version. Scrambled versions were included to demonstrate that synchrony was associated with higher‐order processing rather than the mere presentation of audio‐visual stimuli. Inter‐subject correlations (i.e., Pearson correlation coefficients between the hemodynamic activity of one or more AD patients and the remaining participants, including healthy controls) were used as the metric for synchrony. Results Compared to the scrambled plot conditions, healthy controls showed robust synchronization in the frontal and parietal regions in the intact‐plot conditions. AD patients, in contrast, did not demonstrate a consistent pattern of synchronization in these regions during the intact‐plot conditions. Single‐subject analyses (i.e., comparing individual patients to the control group) further revealed that only one AD patient exhibited some degree of synchronization with the healthy controls during the audio‐visual stimuli. Conclusion These preliminary findings indicate that AD patients may be experiencing the world differently from healthy individuals. The variability noted in synchronization across AD patients may be reflective of the heterogeneity in disease‐related impairments. Understanding deficits and patient needs from the lens of impaired conscious processing could support disease prognosis and promote improvements in person‐centered care.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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

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 head0.067
GPT teacher head0.327
Teacher spread0.260 · 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 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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