Temporal Dynamics of Resting-state Functional Networks and Cognitive Functioning following Systemic Treatment for Breast Cancer

Many women with breast cancer suffer from a decline in memory and executive function, particularly after treatment with chemotherapy. Recent neuroimaging studies suggest that changes in network dynamics are fundamental in decline in these cognitive functions. This has, however, not yet been investigated in breast cancer patients. Using resting state functional magnetic resonance imaging, we prospectively investigated whether changes in dynamic functional connectivity were associated with changes in memory and executive function. We examined 34 breast cancer patients that received chemotherapy, 32 patients that did not receive chemotherapy, and 35 no-cancer controls. All participants were assessed prior to treatment and six months after completion of chemotherapy, or at similar intervals for the other groups. To assess memory and executive function, we used the Hopkins Verbal Learning Test – Immediate Recall and the Trail Making Test B, respectively. Using a sliding window approach, we then evaluated dynamic functional connectivity of resting state networks supporting memory and executive function, i.e. the default mode network and frontoparietal network, respectively. Next, we directly investigated the association between cognitive performance and dynamic functional connectivity. We found no group differences in cognitive performance or connectivity measures. The association between dynamic functional connectivity of the default mode network and memory differed significantly across groups. This was not the case for the frontoparietal network and executive function. This suggests that cancer and chemotherapy alter the role of dynamic functional connectivity in memory function. Further implications of these findings are discussed.

Pathologically reduced neural flexibility recovers during psychotherapy of OCD patients

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Psychiatric impairment is associated with decreased neural flexibility.

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Psychotherapy was able to increase the neural flexibility of the patients.

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Psychotherapy should increase adaptivity of cognitive-emotional-behavioral patterns.

Flexibility is a key feature of psychological health, allowing the individual to dynamically adapt to changing environmental demands, which is impaired in many psychiatric disorders like obsessive–compulsive disorder (OCD). Adequately responding to varying demands requires the brain to switch between different patterns of neural activity, which are represented by different brain network configurations (functional connectivity patterns). Here, we operationalize neural flexibility as the dissimilarity between consecutive connectivity matrices of brain regions (jump length). In total, 132 fMRI scans were obtained from 17 patients that were scanned four to five times during inpatient psychotherapy, and from 17 controls that were scanned at comparable time intervals. Significant negative correlations were found between the jump lengths and the symptom severity scores of OCD, depression, anxiety, and stress, suggesting that high symptom severity corresponds to inflexible brain functioning. Further analyses revealed that impaired reconfiguration (pattern stability) of the brain seems to be more related to general psychiatric impairment rather than to specific symptoms, e.g., of OCD or depression. Importantly, the group × time interaction of a repeated measures ANOVA was significant, as well as the post-hoc paired t-tests of the patients (first vs. last scan). The results suggest that psychotherapy is able to significantly increase the neural flexibility of patients. We conclude that psychiatric symptoms like anxiety, stress, depression, and OCD are associated with an impaired adaptivity of the brain. In general, our results add to the growing evidence that dynamic functional connectivity captures meaningful properties of brain functioning.

Dynamic functional brain networks underlying the temporal inertia of negative emotions

Affective inertia represents the lasting impact of transient emotions at one time point on affective state at a subsequent time point. Here we describe the neural underpinnings of inertia following negative emotions elicited by sad events in movies. Using a co-activation pattern analysis of dynamic functional connectivity, we examined the temporal expression and reciprocal interactions among brain-wide networks during movies and subsequent resting periods in twenty healthy subjects. Our findings revealed distinctive spatiotemporal expression of visual (VIS), default mode (DMN), central executive (CEN), and frontoparietal control (FPCN) networks both in negative movies and in rest periods following these movies. We also identified different reciprocal relationships among these networks, in transitions from movie to rest. While FPCN and DMN expression increased during and after negative movies, respectively, FPCN occurrences during the movie predicted lower DMN and higher CEN expression during subsequent rest after neutral movies, but this relationship was reversed after the elicitation of negative emotions. Changes in FPCN and DMN activity correlated with more negative subjective affect. These findings provide new insights into the transient interactions of intrinsic brain networks underpinning the inertia of negative emotions. More specifically, they describe a major role of FPCN in emotion elicitation processes, with prolonged impact on DMN activity in subsequent rest, presumably involved in emotion regulation and restoration of homeostatic balance after negative events.

Time-resolved effective connectivity in task fMRI: Psychophysiological interactions of Co-Activation patterns

Investigating context-dependent modulations of Functional Connectivity (FC) with functional magnetic resonance imaging is crucial to reveal the neurological underpinnings of cognitive processing. Most current analysis methods hypothesise sustained FC within the duration of a task, but this assumption has been shown too limiting by recent imaging studies. While several methods have been proposed to study functional dynamics during rest, task-based studies are yet to fully disentangle network modulations. Here, we propose a seed-based method to probe task-dependent modulations of brain activity by revealing Psychophysiological Interactions of Co-activation Patterns (PPI-CAPs). This point process-based approach temporally decomposes task-modulated connectivity into dynamic building blocks which cannot be captured by current methods, such as PPI or Dynamic Causal Modelling. Additionally, it identifies the occurrence of co-activation patterns at single frame resolution as opposed to window-based methods. In a naturalistic setting where participants watched a TV program, we retrieved several patterns of co-activation with a posterior cingulate cortex seed whose occurrence rates and polarity varied depending on the context; on the seed activity; or on an interaction between the two. Moreover, our method exposed the consistency in effective connectivity patterns across subjects and time, allowing us to uncover links between PPI-CAPs and specific stimuli contained in the video. Our study reveals that explicitly tracking connectivity pattern transients is paramount to advance our understanding of how different brain areas dynamically communicate when presented with a set of cues.

Dimensionality reduction impedes the extraction of dynamic functional connectivity states from fMRI recordings of resting wakefulness

BACKGROUND

Resting wakefulness is not a unitary state, with evidence accumulating that spontaneous reorganization of brain activity can be assayed through functional magnetic resonance imaging (fMRI). The dynamics of correlated fMRI signals among functionally-related brain regions, termed dynamic functional connectivity (dFC), may represent nonstationarity arising from underlying neural processes. However, given the dimensionality and noise inherent in such recordings, seeming fluctuations in dFC could be due to sampling variability or artifacts.

NEW METHOD

Here, we highlight key methodological considerations when evaluating dFC in resting-state fMRI data.

COMPARISON WITH EXISTING METHOD

In particular, we demonstrate how dimensionality reduction of fMRI data, a common practice often involving principal component analysis, may give rise to spurious dFC phenomenology due to its effect of decorrelating the underlying time-series.

CONCLUSION

We formalize a dFC assessment that avoids dimensionality reduction and use it to show the existence of at least two FC states in the resting-state.