Generalization of conditioned-fear, a core feature of post-traumatic stress disorder (PTSD), has been the focus of several recent neuroimaging studies. A striking outcome of these studies is the frequency with which neural correlates of generalization fall within hubs of well-established functional networks including salience (SN), central executive (CEN), and default networks (DN). Neural substrates of generalization found to date may thus reflect traces of large-scale brain networks that form more expansive neural representations of generalization. The present study includes the first network-based analysis of generalization and PTSD-related abnormalities therein.

fMRI responses in established intrinsic connectivity networks (ICNs) representing SN, CEN, and DN were assessed during a generalized conditioned-fear task in male combat veterans (N = 58) with wide-ranging PTSD symptom severity. The task included five rings of graded size. Extreme sizes served as conditioned danger-cues (CS+: paired with shock) and safety-cues (CS−), and the three intermediate sizes served as generalization stimuli (GSs) forming a continuum-of-size between CS+ and CS–. Generalization-gradients were assessed as behavioral and ICN response slopes from CS+, through GSs, to CS–. Increasing PTSD symptomatology was predicted to relate to less-steep slopes indicative of stronger generalization.

SN, CEN, and DN responses fell along generalization-gradients with levels of generalization within and between SN and CEN scaling with PTSD symptom severity.

Neural substrates of generalized conditioned-fear include large-scale networks that adhere to the functional organization of the brain. Current findings implicate levels of generalization in SN and CEN as promising neural markers of PTSD.

Previous studies have analyzed brain functional connectivity to reveal the neural physiopathology of bipolar disorder (BD) and major depressive disorder (MDD) based on the triple-network model [involving the salience network, default mode network (DMN), and central executive network (CEN)]. However, most studies assumed that the brain intrinsic fluctuations throughout the entire scan are static. Thus, we aimed to reveal the dynamic functional network connectivity (dFNC) in the triple networks of BD and MDD.

We collected resting state fMRI data from 51 unmedicated depressed BD II patients, 51 unmedicated depressed MDD patients, and 52 healthy controls. We analyzed the dFNC by using an independent component analysis, sliding window correlation and k-means clustering, and used the parameters of dFNC state properties and dFNC variability for group comparisons.

The dFNC within the triple networks could be clustered into four configuration states, three of them showing dense connections (States 1, 2, and 4) and the other one showing sparse connections (State 3). Both BD and MDD patients spent more time in State 3 and showed decreased dFNC variability between posterior DMN and right CEN (rCEN) compared with controls. The MDD patients showed specific decreased dFNC variability between anterior DMN and rCEN compared with controls.

This study revealed more common but less specific dFNC alterations within the triple networks in unmedicated depressed BD II and MDD patients, which indicated their decreased information processing and communication ability and may help us to understand their abnormal affective and cognitive functions clinically.