Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging

Abstract

The majority of functional neuroscience studies have focused on the brain's response to a task or stimulus. However, the brain is very active even in the absence of explicit input or output. In this Article we review recent studies examining spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal of functional magnetic resonance imaging as a potentially important and revealing manifestation of spontaneous neuronal activity. Although several challenges remain, these studies have provided insight into the intrinsic functional architecture of the brain, variability in behaviour and potential physiological correlates of neurological and psychiatric disease.

Dissociable relations between amygdala subregional networks and psychopathy trait dimensions in conduct‐disordered juvenile offenders

“…Preprocessing consisted of nonbrain‐tissue removal, motion correction, grand mean‐based intensity normalization of the entire 4‐D data set by a single scaling factor, slice timing correction, spatial smoothing with a 6 mm full width at half maximum Gaussian kernel, and temporal bandpass filtering at 0.009 <  f  < 0.15 Hz, which improves BOLD signal estimation and produces connectivity patterns that relate most closely to task‐based activations [Aghajani et al, 2016; Fox and Raichle, 2007; Fransson, 2006; Roy et al, 2009; Toro et al, 2008]. Finally, the RS data were registered to T1‐weighted anatomical images, and subsequently to the 2‐mm Montreal Neurological Institute (MNI) standard space image [Aghajani et al, 2016; Aghajani et al, 2016; Roy et al, 2013].…”

“…Seed‐based whole‐brain iFC analysis implemented within FSL FEAT [Jenkinson et al, 2012], was then employed to reveal BLA and CMA connectivity patterns [Fox and Raichle, 2007]. Specifically, for each participant, and in each hemisphere, a general linear model (GLM) was created that included individual participant's mean time series of BLA and CMA complexes as predictors [Aghajani et al, 2016; Brown et al, 2014; Roy et al, 2013].…”

“…One particularly powerful method for examining BLA and CMA functional connectivity is intrinsic functional connectivity (iFC) analysis, which delineates the functional architecture of intrinsically (i.e., spontaneously) coupled brain networks [Fox and Raichle, 2007]. These intrinsic brain networks are relatively stable across participants and time [Smith et al, 2009], correspond spatially with well‐known functional networks [Smith et al, 2009], and can signal abnormal brain function and psychopathology [Greicius, 2008].…”

Resting state and personality component (BIS/BAS) predict the brain activity (EEG and fNIRS measure) in response to emotional cues

“…Moreover, NIRS and EEG measurement in a resting condition demonstrated that an increase of oxy‐hemoglobin (O2Hb) was associated with an increase in neuronal responsiveness, whereas a decrease in O2Hb was associated with a decrease in neuronal responsiveness (Butti et al., 2006; Hoshi, Kosaka, Xie, Kohri, & Tamura, 1998). Indeed, it was observed that spontaneous hemodynamic brain activity is not just random noise, but is specifically organized in the resting brain (for a review, see Fox & Raichle, 2007). …”

Time related effects on functional brain connectivity after serotonergic and cholinergic neuromodulation

“…Consequently, studies of cholinergic or serotonergic drug effects also need to consider their extensive modulatory effects [Bargmann, 2012]. This is possible with resting state functional magnetic resonance imaging (RS‐fMRI) in the context of pharmacological stimulation [Fox and Raichle, 2007; Khalili‐Mahani et al, 2014]. …”