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Connectome-based models can predict processing speed in older adults
Mengxia GAO
,
Ho Yin Clive WONG
, Huiyuan HUANG
, Robin SHAO
, Ruiwang HUANG
,
Che Hin Chetwyn CHAN
, Tatia M. C. LEE
Office of the Vice President (Research and Development) (VP(RD))
Department of Psychology (PS)
Research output
:
Contribution to journal
›
Articles
›
peer-review
47
Citations (Scopus)
Overview
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Keyphrases
Age Groups
10%
Aging Process
10%
Aging Research
10%
Between-network Connectivity
10%
Cerebellum
10%
Clinical Benefit
10%
Clinical Diagnosis
10%
Clinical Management
10%
Clinical Population
10%
Clinical Prognosis
20%
Clinical Research
10%
Cognitive Function
10%
Connectivity Pattern
10%
Connectome
100%
Connectome-based Predictive Modeling
20%
Copyright
10%
Diagnosis Management
10%
Fast Processing
20%
Frontoparietal Network
10%
Middle-aged Adults
20%
Motor Network
10%
Neurocognitive Assessment
10%
Neurocognitive Function
20%
Older Adults
100%
Patient Management
10%
Predictive Models
20%
Processing Speed
100%
Resting-state Functional Connectivity (rs-FC)
10%
Translational Implications
10%
Visual Network
10%
Visual-motor
10%
Whole Brain
10%
Within-network Connectivity
10%
Neuroscience
Cerebellum
100%
Cognitive Function
100%
Resting-State Functional Connectivity
100%