PMID- 25497686
OWN - NLM
STAT- MEDLINE
DCOM- 20151229
LR  - 20220321
IS  - 1095-9572 (Electronic)
IS  - 1053-8119 (Print)
IS  - 1053-8119 (Linking)
VI  - 107
DP  - 2015 Feb 15
TI  - BOLD fractional contribution to resting-state functional connectivity above 0.1 
      Hz.
PG  - 207-218
LID - S1053-8119(14)01004-0 [pii]
LID - 10.1016/j.neuroimage.2014.12.012 [doi]
AB  - Blood oxygen level dependent (BOLD) spontaneous signals from resting-state (RS) 
      brains have typically been characterized by low-pass filtered timeseries at 
      frequencies </= 0.1 Hz, and studies of these low-frequency fluctuations have 
      contributed exceptional understanding of the baseline functions of our brain. 
      Very recently, emerging evidence has demonstrated that spontaneous activities may 
      persist in higher frequency bands (even up to 0.8 Hz), while presenting less 
      variable network patterns across the scan duration. However, as an indirect 
      measure of neuronal activity, BOLD signal results from an inherently slow 
      hemodynamic process, which in fact might be too slow to accommodate the observed 
      high-frequency functional connectivity (FC). To examine whether the observed 
      high-frequency spontaneous FC originates from BOLD contrast, we collected RS data 
      as a function of echo time (TE). Here we focus on two specific resting state 
      networks - the default-mode network (DMN) and executive control network (ECN), 
      and the major findings are fourfold: (1) we observed BOLD-like linear 
      TE-dependence in the spontaneous activity at frequency bands up to 0.5 Hz (the 
      maximum frequency that can be resolved with TR=1s), supporting neural relevance 
      of the RSFC at a higher frequency range; (2) conventional models of hemodynamic 
      response functions must be modified to support resting state BOLD contrast, 
      especially at higher frequencies; (3) there are increased fractions of 
      non-BOLD-like contributions to the RSFC above the conventional 0.1 Hz 
      (non-BOLD/BOLD contrast at 0.4-0.5 Hz is ~4 times that at <0.1 Hz); and (4) the 
      spatial patterns of RSFC are frequency-dependent. Possible mechanisms underlying 
      the present findings and technical concerns regarding RSFC above 0.1 Hz are 
      discussed.
CI  - Copyright (c) 2014 Elsevier Inc. All rights reserved.
FAU - Chen, Jingyuan E
AU  - Chen JE
AD  - Department of Radiology, Stanford University, Stanford, CA 94305, USA; Department 
      of Electrical Engineering, Stanford University, Stanford, CA 94305, USA. 
      Electronic address: cjy2010@stanford.edu.
FAU - Glover, Gary H
AU  - Glover GH
AD  - Department of Radiology, Stanford University, Stanford, CA 94305, USA.
LA  - eng
GR  - P41 EB015891/EB/NIBIB NIH HHS/United States
PT  - Journal Article
PT  - Research Support, N.I.H., Extramural
DEP - 20141212
PL  - United States
TA  - Neuroimage
JT  - NeuroImage
JID - 9215515
RN  - S88TT14065 (Oxygen)
SB  - IM
MH  - Adult
MH  - Algorithms
MH  - Cerebrovascular Circulation
MH  - Executive Function/physiology
MH  - Female
MH  - Humans
MH  - Image Processing, Computer-Assisted
MH  - Magnetic Resonance Imaging/*methods
MH  - Male
MH  - Middle Aged
MH  - Nerve Net/blood supply/physiology
MH  - Neural Pathways/blood supply/physiology
MH  - Neurons/physiology
MH  - Oxygen/*blood
MH  - Reproducibility of Results
MH  - Rest/physiology
MH  - Signal-To-Noise Ratio
MH  - Young Adult
PMC - PMC4318656
MID - NIHMS651245
OTO - NOTNLM
OT  - Above 0.1Hz
OT  - BOLD-like TE-dependence
OT  - High frequency
OT  - Resting state functional connectivity
EDAT- 2014/12/17 06:00
MHDA- 2015/12/30 06:00
PMCR- 2016/02/15
CRDT- 2014/12/16 06:00
PHST- 2014/08/17 00:00 [received]
PHST- 2014/11/27 00:00 [revised]
PHST- 2014/12/04 00:00 [accepted]
PHST- 2014/12/16 06:00 [entrez]
PHST- 2014/12/17 06:00 [pubmed]
PHST- 2015/12/30 06:00 [medline]
PHST- 2016/02/15 00:00 [pmc-release]
AID - S1053-8119(14)01004-0 [pii]
AID - 10.1016/j.neuroimage.2014.12.012 [doi]
PST - ppublish
SO  - Neuroimage. 2015 Feb 15;107:207-218. doi: 10.1016/j.neuroimage.2014.12.012. Epub 
      2014 Dec 12.