State and trait characteristics of anterior insula time-varying functional connectivity.

The human anterior insula (aINS) is a topographically organized brain region, in which ventral portions contribute to socio-emotional function through limbic and autonomic connections, whereas the dorsal aINS contributes to cognitive processes through frontal and parietal connections. Open questions remain, however, regarding how aINS connectivity varies over time. We implemented a novel approach combining seed-to-whole-brain sliding-window functional connectivity MRI and k-means clustering to assess time-varying functional connectivity of aINS subregions. We studied three independent large samples of healthy participants and longitudinal datasets to assess inter- and intra-subject stability, and related aINS time-varying functional connectivity profiles to dispositional empathy. We identified four robust aINS time-varying functional connectivity modes that displayed both "state" and "trait" characteristics: while modes featuring connectivity to sensory regions were modulated by eye closure, modes featuring connectivity to higher cognitive and emotional processing regions were stable over time and related to empathy measures

Fluctuations between high- and low-modularity topology in time-resolved functional connectivity

Modularity is an important topological attribute for functional brain networks. Recent studies have reported that modularity of functional networks varies not only across individuals being related to demographics and cognitive performance, but also within individuals co-occurring with fluctuations in network properties of functional connectivity, estimated over short time intervals. However, characteristics of these time-resolved functional networks during periods of high and low modularity have remained largely unexplored. In this study we investigate spatiotemporal properties of time-resolved networks in the high and low modularity periods during rest, with a particular focus on their spatial connectivity patterns, temporal homogeneity and test-retest reliability. We show that spatial connectivity patterns of time-resolved networks in the high and low modularity periods are represented by increased and decreased dissociation of the default mode network module from task-positive network modules, respectively. We also find that the instances of time-resolved functional connectivity sampled from within the high (low) modularity period are relatively homogeneous (heterogeneous) over time, indicating that during the low modularity period the default mode network interacts with other networks in a variable manner. We confirmed that the occurrence of the high and low modularity periods varies across individuals with moderate inter-session test-retest reliability and that it is correlated with previously-reported individual differences in the modularity of functional connectivity estimated over longer timescales. Our findings illustrate how time-resolved functional networks are spatiotemporally organized during periods of high and low modularity, allowing one to trace individual differences in long-timescale modularity to the variable occurrence of network configurations at shorter timescales.Comment: Reorganized the paper; to appear in NeuroImage; arXiv abstract shortened to fit within character limit

Inspection of Short-Time Resting-State Electroencephalogram Functional Networks in Alzheimer's Disease

Functional connectivity has proven useful to characterise electroencephalogram (EEG) activity in Alzheimer’s disease (AD). However, most current functional connectivity analyses have been static, disregarding any potential variability of the connectivity with time. In this pilot study, we compute short-time resting state EEG functional connectivity based on the imaginary part of coherency for 12 AD patients and 11 controls. We derive binary unweighted graphs using the cluster-span threshold, an objective binary threshold. For each short-time binary graph, we calculate its local clustering coefficient (Cloc), degree (K), and efficiency (E). The distribution of these graph metrics for each participant is then characterised with four statistical moments: mean, variance, skewness, and kurtosis. The results show significant differences between groups in the mean of K and E, and the kurtosis of Cloc and K. Although not significant when considered alone, the skewness of Cloc is the most frequently selected feature for the discrimination of subject groups. These results suggest that the variability of EEG functional connectivity may convey useful information about AD

Neural correlates of attention-executive dysfunction in lewy body dementia and Alzheimer's disease.

Attentional and executive dysfunction contribute to cognitive impairment in both Lewy body dementia and Alzheimer's disease. Using functional MRI, we examined the neural correlates of three components of attention (alerting, orienting, and executive/conflict function) in 23 patients with Alzheimer's disease, 32 patients with Lewy body dementia (19 with dementia with Lewy bodies and 13 with Parkinson's disease with dementia), and 23 healthy controls using a modified Attention Network Test. Although the functional MRI demonstrated a similar fronto-parieto-occipital network activation in all groups, Alzheimer's disease and Lewy body dementia patients had greater activation of this network for incongruent and more difficult trials, which were also accompanied by slower reaction times. There was no recruitment of additional brain regions or, conversely, regional deficits in brain activation. The default mode network, however, displayed diverging activity patterns in the dementia groups. The Alzheimer's disease group had limited task related deactivations of the default mode network, whereas patients with Lewy body dementia showed heightened deactivation to all trials, which might be an attempt to allocate neural resources to impaired attentional networks. We posit that, despite a common endpoint of attention-executive disturbances in both dementias, the pathophysiological basis of these is very different between these diseases.This work was supported by an Intermediate Clinical Fellowship . Grant Number: (WT088441MA) to John‐Paul Taylor the National Institute for Health Research (NIHR), and Newcastle Biomedical Research Unit (BRU) based at Newcastle upon Tyne Hospitals NHS Trust, Newcastle University

Verbal Creativity Is Correlated With the Dynamic Reconfiguration of Brain Networks in the Resting State

Creativity is the foundation of human culture. All inventions and innovations in history rely upon us to break with the traditional thinking and create something novel. A number of neuroimaging studies have explored the neural mechanism of creativity. However, a majority of researches have focused only on the stationary functional connectivity in resting-state fMRI and task-related fMRI, neglecting the dynamic variation of brain networks. Here, we used dynamic network analysis to investigate the relation between the dynamic reorganization of brain networks and verbal creativity in 370 healthy subjects. We found that the integration of the left lingual gyrus and left middle temporal gyrus (MTG) in default mode network (DMN) and the integration of the DMN and cerebellum, frontoparietal task control network (FPTC) and auditory network (Aud) showed positive correlation with verbal creativity performance. In addition, the recruitment of the bilateral postcentral gyrus from the sensory/somatomotor network (SMN) and the recruitment of the SMN in general displayed a significant correlation with verbal creativity scores. Taken together, these results suggested that the dynamic reorganization among the brain networks involved multiple cognitive processes, such as memory retrieval, imaginative process, cognitive control – these are all important for verbal creativity. These findings provided direct evidence that verbal creativity was related to the dynamic variation of brain mechanism during resting-state, extending past research on the neural mechanism of creativity. Meanwhile, these results bought about new perspectives for verbal creative training and rehabilitation training of depression

The dynamic functional connectome: State-of-the-art and perspectives

Resting-state functional magnetic resonance imaging (fMRI) has highlighted the rich structure of brain activity in absence of a task or stimulus. A great effort has been dedicated in the last two decades to investigate functional connectivity (FC), i.e. the functional interplay between different regions of the brain, which was for a long time assumed to have stationary nature. Only recently was the dynamic behaviour of FC revealed, showing that on top of correlational patterns of spontaneous fMRI signal fluctuations, connectivity between different brain regions exhibits meaningful variations within a typical resting-state fMRI experiment. As a consequence, a considerable amount of work has been directed to assessing and characterising dynamic FC (dFC), and several different approaches were explored to identify relevant FC fluctuations. At the same time, several questions were raised about the nature of dFC, which would be of interest only if brought back to a neural origin. In support of this, correlations with electroencephalography (EEG) recordings, demographic and behavioural data were established, and various clinical applications were explored, where the potential of dFC could be preliminarily demonstrated. In this review, we aim to provide a comprehensive description of the dFC approaches proposed so far, and point at the directions that we see as most promising for the future developments of the field. Advantages and pitfalls of dFC analyses are addressed, helping the readers to orient themselves through the complex web of available methodologies and tools

Neurobiological, attentional and memory changes in posttraumatic stress disorder

This dissertation aimed at investigating the role of fear learning and encoding mechanisms in the development and maintenance of anxiety and trauma-related disorders in two studies. In study 1, we combined functional resting state connectivity with skin conductance data of cued and contextual fear conditioning in 119 healthy individuals. In study 2, we applied simultaneous high-density electroencephalography (EEG) with eye-tracking during free picture viewing (including traumatic cues in neutral contexts) and memory tests of the same materials in 20 patients with post-traumatic stress disorder (PTSD) and 20 trauma controls who did not develop PTSD (NPTSD). In study 1, we hypothesized that increased functional connectivity of the default mode network (DMN) (1) with the amygdala and frontal control regions would be associated with a decrease in the magnitude of cue aversive learning, and (2) that another DMN connectivity pattern including the hippocampal formation, would negatively correlate with the strength of contextual conditioning indices. The main result of this study is that two different DMN patterns were identified in which stronger connectivity linked to lower differential SCRs during fear and anxiety was learning. One was related to cue conditioning and involved the amygdala and the medial prefrontal cortex, and one was associated with context conditioning and included the hippocampal formation and sensorimotor areas. In the second study, we expected an early perceptual bias on trauma-related cues at the expense of the context in PTSD compared to NPTSD as visible in the modulation of polarity/amplitudes of the visual C1 and in eye tracking early fixation measures. Referring to the memory performance we expected the PTSD group to better retrieve pictures requiring a more elemental/unitary strategy (aka where the association between cues and contexts was kept constant) and consequently in being especially worse than NPTSD in retrieving cue-context modified associations. We finally expected encoding strategies to account for the memory performance. In the simultaneous EEG-eye-tracking task we found that the PTSD but not the NPTSD group oriented more towards traumatic but not neutral cues at the expense of the context. These outcomes were present at the first stages of information processing as indicated by the changes in polarity of the C1 component of the EEG and predicted the following associative memory performance. Different resting-state connectivity patterns within the DMN could emerge in association with individual predispositions of learning fear and anxiety. Because of the recognized clinical implications of these learning mechanisms in trauma and anxiety disorders, our findings highlight the relevance of brain connectivity differences as possible biomarkers already at rest and in healthy individuals, for example in healthy populations with high exposure to traumatic events (such as medical personal, rescue workers, police officer, soldiers) in order to reduce vulnerability and/or promote resilience to develop PTSD. An hippocampal processing impairment is probably responsible for the memory deficits in PTSD but possibly promoted from the strongly biased encoding strategy of the cues versus contexts, which also it is helpful in explaining intrusions and hyperarousal symptoms in a more complex perspective. Moreover, increasing awareness encoding used strategies could help existing therapies (e.g. cognitive behavioral and exposure therapy) in modifying faster the appraisal and memory of the trauma through trained restructuring of events and contextual representations

Neural Mechanisms Underlying Attention Deficits in Posttraumatic Stress Disorder

OBJECTIVE: Post-traumatic stress disorder (PTSD) is associated with altered attentional performance and functional connectivity in intrinsic connectivity networks (ICNs) related to attention. There is conflicting research regarding the specific type of attention impairments present in PTSD as the commonly used tests of attention do not isolate the mechanisms behind attention abnormalities. Additionally, because ICNs are typically measured at rest, it is unclear how altered connectivity may contribute to task performance.  Understanding which aspects of attention are affected in PTSD could improve our understanding of the mechanisms by which these deficits influence symptoms, in turn, improving treatment by targeting these processes. AIM 1: We sought to characterize the type of behavioral attentional impairment present in PTSD according to Posner and Peterson’s tripartite model of attention using the Attention Network Task (ANT). We then examined the association between attention performance and resting-state functional connectivity (rsFC). Male veterans with PTSD were impaired at disengaging spatial attention relative to male community controls and exhibited greater cross-network rsFC of the salience network. Moreover, attention performance was related to rsFC in the control, but not in the PTSD group. However, it remained unclear whether patterns of rsFC are also related to changes in neural function during attention performance as the ANT was completed outside of scanner. We investigated this question in aim 2. AIM 2: We examined whether patterns of rsFC were predictive of attention task performance, activity and connectivity across a sample of non-trauma exposed controls, trauma-exposed controls and individuals with PTSD. Across all subjects, we found that ICNs present at rest were predictive of attention task neural activation, connectivity and behavioral performance. However, the relationships we found were very different depending on the task condition, network node and task measure (i.e. activation vs connectivity). This suggests that resting-state could be an alternative to active tasks to study brain function in psychiatric populations in the future, such that alterations in ICNs at rest in PTSD may be reflective of impairments on an attention task. However, the mechanisms by which ICNs contribute to attention abnormalities in PTSD remained unclear. Additionally, it remained unclear whether alterations of ICNs are specific to PTSD or are partially related to trauma-exposure. We investigated these questions in aim 3. AIM 3: We investigated the neural mechanisms underlying attention impairments in PTSD by using the same measures as aim 2. We found that the PTSD group showed deficits in the utilization of spatial information. During cue processing, the PTSD group exhibited salience network intrusions, but during target processing, they showed both a failure to suppress the default-mode network and a greater engagement of attentional control regions. Lastly, trauma-exposed controls showed some behavioral and neural alterations in attention measures. CONCLUSION: In this dissertation, we demonstrated that 1) resting-state ICNs are predictive of attention-task measures and 2) spatial attention is disrupted in PTSD. Our results suggest a possible mechanism of attention disruptions in PTSD, by which the salience network interferes with goal-directed attention, resulting in a reduced ability to encode contextual information. This in turn may influence one’s propensity for attentional lapses, thus requiring greater engagement of attentional control regions to execute correct responses. Treatments which target these neural networks or cognitive deficits could be a new avenue for PTSD research.PHDPsychologyUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/146062/1/srblo_1.pd