PMID- 29672091
OWN - NLM
STAT- MEDLINE
DCOM- 20190109
LR  - 20191008
IS  - 1939-1846 (Electronic)
IS  - 0021-843X (Print)
IS  - 0021-843X (Linking)
VI  - 127
IP  - 3
DP  - 2018 Apr
TI  - Resting state connectivity dynamics in individuals at risk for psychosis.
PG  - 314-325
LID - 10.1037/abn0000330 [doi]
AB  - Clarifying dynamic fluctuations in resting-state connectivity in individuals at 
      risk for psychosis (termed clinical high risk [CHR]) may inform understanding of 
      psychotic disorders, such as schizophrenia, which have been associated with 
      dysconnectivity and aberrant salience processing. Dynamic functional connectivity 
      (DFC) investigations provide insight into how neural networks exchange 
      information over time. Currently, there are no published DFC studies involving 
      CHR individuals. This is notable, because understanding how networks may come 
      together and disassociate over time could lend insight into the neural 
      communication that underlies psychosis development and symptomatology. A 
      sliding-window analysis was utilized to examine DFC (defined as the standard 
      deviation over a series of sliding windows) in resting-state scans in a total of 
      31 CHR individuals and 28 controls. Clinical assessments at baseline and 12 
      months later were conducted. CHR participants exhibited less DFC (lower standard 
      deviation) in connectivity involving areas of both the salience network (SN) and 
      default mode network (DMN) with regions involved in sensory, motor, attention, 
      and internal cognitive functions relative to controls. Within CHR participants, 
      this pattern was associated with greater positive symptoms 12 months later, 
      possibly reflecting a mechanism behind aberrant salience processing. Higher 
      SN-DMN internetwork DFC related to elevated baseline negative symptoms, anxiety, 
      and depression in CHR participants, which may indicate neurological processes 
      underlying worry and rumination. Overall, through highlighting unique DFC 
      properties within CHR individuals and detecting informative links with clinically 
      relevant symptomatology, results support dysconnectivity and aberrant salience 
      processing models of psychosis. (PsycINFO Database Record
CI  - (c) 2018 APA, all rights reserved).
FAU - Pelletier-Baldelli, Andrea
AU  - Pelletier-Baldelli A
AD  - Department of Psychology and Neuroscience, University of Colorado Boulder.
FAU - Andrews-Hanna, Jessica R
AU  - Andrews-Hanna JR
AD  - Department of Psychology, University of Arizona.
FAU - Mittal, Vijay A
AU  - Mittal VA
AD  - Department of Psychology, Northwestern University.
LA  - eng
GR  - F31 MH100821/MH/NIMH NIH HHS/United States
GR  - R01 MH094650/MH/NIMH NIH HHS/United States
PT  - Journal Article
PL  - United States
TA  - J Abnorm Psychol
JT  - Journal of abnormal psychology
JID - 0034461
SB  - IM
MH  - Adolescent
MH  - Adult
MH  - Brain/*physiopathology
MH  - Brain Mapping/methods
MH  - Female
MH  - Humans
MH  - Magnetic Resonance Imaging
MH  - Male
MH  - Neural Pathways/physiopathology
MH  - Psychotic Disorders/*physiopathology
MH  - Risk Factors
MH  - Young Adult
PMC - PMC5912697
MID - NIHMS935438
COIS- Authors Pelletier-Baldelli and Dr. Andrews-Hanna report no biomedical financial 
      interests or potential conflicts of interest.
EDAT- 2018/04/20 06:00
MHDA- 2019/01/10 06:00
PMCR- 2019/04/01
CRDT- 2018/04/20 06:00
PHST- 2018/04/20 06:00 [entrez]
PHST- 2018/04/20 06:00 [pubmed]
PHST- 2019/01/10 06:00 [medline]
PHST- 2019/04/01 00:00 [pmc-release]
AID - 2018-15774-003 [pii]
AID - 10.1037/abn0000330 [doi]
PST - ppublish
SO  - J Abnorm Psychol. 2018 Apr;127(3):314-325. doi: 10.1037/abn0000330.