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Record W2274933657 · doi:10.1016/j.jalz.2015.06.1785

P4‐080: Differences in saliency network between Alzheimer's and parkinson's disease

2015· article· en· W2274933657 on OpenAlexaff
Namita Multani, Cassandra Jessica Anor, David F. Tang‐Wai, Ron Keren, Anthony E. Lang, Susan H. Fox, Connie Marras, Maria Carmela Tartaglia

Bibliographic record

VenueAlzheimer s & Dementia · 2015
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsParkinson's diseaseNeuroscienceDiseasePsychologyMedicinePathology

Abstract

fetched live from OpenAlex

Neurodegenerative diseases, in addition to cognitive and motoric impairments also include changes in social behavior and personality. The phenotypes associated with the different neurodegenerative diseases display varying amounts of social cognitive deficits. A number of brain regions working as dynamic networks are now known to subserve socio-emotional processing and are involved in multiple, distinct social functions. Alzheimer's disease (AD) and Parkinson's disease (PD) have predilections for different brain structures and so it ensues that they are associated with different social cognitive and personality changes. Resting-state networks (RSN) represent functional connectivity between anatomically separate brain regions during task-free conditions. Regions within each network are interconnected through the white matter tracts and demonstrate synchronized activity. Recent RSN studies suggest that neurodegeneration may alter these connections, leading to network deterioration. The Salience Network (SN) is hypothesized to play a role in selective attention towards emotionally salient events and regulating behavior. The aim of this study is to compare the SN in AD and PD and determine its relationship to personality traits. Fifteen patients diagnosed with probable AD (N=9) and PD (N=6) underwent rs-fMRI scans. ROI-to-ROI analysis of the anterior salience network was performed to examine connectivity differences between PD and AD. Personality was measured using the Big Five Inventory scale, a well-validated questionnaire that measures individual differences in personality traits (conscientiousness, openness, extroverted, agreeableness, and neuroticism). The PD group exhibited greater connectivity of the right and left dorsolateral prefrontal cortex (DLPFC) (t(12) = 3.94, p<.05) compared with AD. In the PD group, there was also increased connectivity between the right DLPFC and the left cerebellum (t(12) = 2.95, p<.05). There was no group difference in the personality traits between PD and AD. Moreover, no association between the saliency network and the personality traits measured with the Five-factors of BFI was evident. We found altered “increased” connectivity between bilateral DLPFC and DLPFC and cerebellum in PD compared with AD. There was no significant difference in personality traits between AD and PD across the BFI. These results suggest a compensatory mechanism in the saliency network in PD as compared to AD.

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)0.001
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.318
Teacher spread0.251 · 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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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