The Dynamics of Functional Brain Networks Associated With Depressive Symptoms in a Nonclinical Sample

Abstract

Brain function depends on the flexible and dynamic coordination of functional subsystems within distributed neural networks operating on multiple scales. Recent progress has been made in the characterization of functional connectivity (FC) at the whole-brain scale from a dynamic, rather than static, perspective, but its validity for cognitive sciences remains under debate. Here, we analyzed brain activity recorded with functional Magnetic Resonance Imaging from 71 healthy participants evaluated for depressive symptoms after a relationship breakup based on the conventional Major Depression Inventory (MDI). We compared both static and dynamic FC patterns between participants reporting high and low depressive symptoms. Between-group differences in static FC were estimated using a standard pipeline for networkbased statistic (NBS). Additionally, FC was analyzed from a dynamic perspective by characterizing the occupancy, lifetime, and transition profiles of recurrent FC patterns. Recurrent FC patterns were defined by clustering the BOLD phase-locking patterns obtained using leading eigenvector dynamics analysis (LEiDA). NBS analysis revealed a brain subsystem exhibiting significantly lower within-subsystem correlation values in more depressed participants (high MDI). This subsystem predominantly comprised connections between regions of the default mode network (i.e., precuneus) and regions outside this network. On the other hand, LEiDA results showed that high MDI participants engaged more in a state connecting regions of the default mode, memory retrieval, and frontoparietal network (p-FDR = 0.012); and less in a state connecting mostly the visual and dorsal attention systems (p-FDR = 0.004). Although both our analyses on static and dynamic FC implicate the role of the precuneus in depressive symptoms, only including the temporal evolution of BOLD FC helped to disentangle over time the distinct configurations in which this region plays a role. This finding further indicates that a holistic understanding of brain function can only be gleaned if the temporal dynamics of FC is included.

Pathologically reduced neural flexibility recovers during psychotherapy of OCD patients

“…While this window is very short with respect to conventional FC analyses, it also allows to observe a larger number of jumps between FCs estimated from non-overlapping windows, a factor which is here more important than precision on the estimation of instantaneous FC networks themselves (see Materials and Methods). Recent evidence of meaningful and converging results stress the validity of using a higher temporal resolution in dFC analyses ( Alonso Martínez et al, 2020 , Tagliazucchi et al, 2012 ) and is confirmed by the robustness of our results over different window sizes (see Supplement E and F).…”

Working Memory Alterations After a Romantic Relationship Breakup

“…Results from a questionnaire study in our laboratory, administered to the same study population as presented in the present paper, display elevated depression scores, albeit subclinical, in individuals who have experienced a romantic relationship dissolution compared to a reference group consisting of individuals in a romantic relationship (Verhallen et al, 2019). In addition, high depression scores after breakup were associated with altered resting-state functional connectivity patterns in our laboratory (Alonso Martínez et al, 2020). The finding of elevated depression scores following relationship breakup is complemented by previous results from other laboratories displaying an association between suffering from a romantic relationship breakup and symptoms of depression (Monroe et al, 1999;Field et al, 2009;Stoessel et al, 2011).…”

LSD and psilocybin flatten the brain’s energy landscape: insights from receptor-informed network control theory

“…It is well-known that even at rest the brain is not static, but rather it dynamically alternates between a number of recurrent states [9][10][11][12][13][14][15][16] . Such recurrent brain-states may be relevant for cognition [17][18][19][20] and even consciousness [21][22][23][24][25][26][27] , and have been shown to undergo prominent reorganization during the psychedelic state induced by LSD 5,6 and psilocybin 7,28 . Crucially, network control theory approaches enable mapping of the brain's energy landscape by quantifying the energy required to transition between these recurrent states (Figure 1a,b).…”