Changes In Brain Networks Research Articles

A SYSTEMATIC REVIEW OF RANDOMIZED CONTROLLED TRIALS OF COGNITIVE TRAINING INTERVENTIONS IN OLDER ADULTS

There has been a growing interest in cognitive training interventions for their potential effect of maintaining and promoting cognitive functioning in older adults. Rapid and significant changes in technology has had a significant impact on the design and assessment methods of cognitive training interventions. Investigating changes in brain networks and blood markers are relatively new approaches and sparsely examined in the literature. The purpose of this systematic literature review is to analyze the effect of cognitive training interventions on brain networks, blood markers and associated cognitive performance of healthy older adults. We conducted a comprehensive literature search on four databases, following PRISMA guidelines. Initially, 2426 citations were retrieved, and 251 full-text publications were evaluated in detail for eligibility. Fourteen randomized control trials were included in this review. Functional imaging analysis of brain networks showed significant activity changes primarily in the Default Mode Network. These changes were associated with improvement in memory, learning, attention, and affective performances. Also, there were activity changes in the Central Executive Network that were associated with improvement in reasoning, attentional control, innovative thinking, and processing speed. Training-induced changes have been observed in the brain-derived neurotrophic factor levels and the markers of antioxidative and anti-inflammatory regulatory mechanisms. Improvement in attention and memory performances were significantly related to these changes. Limitations of the studies included methodological inconsistencies, sampling issues, and the lack of long-term follow up assessment. Cognitive training appears to promote improvement and maintenance of cognitive functioning in healthy older adults.

Alterations in functional brain networks in depressed patients with a suicide attempt history.

Suicide is a major challenge in public health and is strongly associated with major depressive disorder (MDD). Despite recent neuroimaging developments, the neural correlates of suicide behavior in patients with MDD remain unclear. Independent component analysis (ICA) for neuroimaging data allows the identification of functional brain networks without prior regions of interest and may help to identify neurobiological markers of specific disorders. Using ICA, we investigated the differences in resting-state brain networks in patients with MDD who had or did not have a history of suicide attempts and in healthy controls (HCs). Suicidal depressed (SD) patients, non-suicidal depressed (NSD) patients, and HCs significantly differed from each other in the pattern of connectivity of multiple functional networks, network synchronization, and functional network connectivity (FNC). The patient groups had a decreased network synchronization in the insular, cerebellum, basal ganglia, thalamus, operculum, frontoparietal cortices, and sensory cortices relative to the HCs. The decreased FNC between these networks (insular-default mode network and insular-cerebellum) was found in the SD group compared to the NSD and HC groups. These differences were not related to illness duration and medication status differences between SD and NSD. Furthermore, the degree of FNC in these networks was associated with the suicide ideation and stress level. Our results demonstrated that widespread but discrete network changes in brain networks and their interconnectivity was associated with suicide attempts in patients with MDD. Our results suggest that the neural basis underlying the psychopathology of attempted suicide in patients with MDD involves multiple brain networks and their interaction.

Brain Network Changes Accompanying and Predicting Responses to Pharmacotherapy in OCD

Brain Network Changes Accompanying and Predicting Responses to Pharmacotherapy in OCD

Imaging of RBD: New MRI and spect data

Idiopathic rapid eye movement sleep behavior disorder (iRBD) is a prodromal stage of synucleinopathies such as Parkinson’s disease, dementia with Lewy bodies, and multiple system atrophy. Through recent advances in neuroimaging analysis, we made a progress in understanding the neurodegeneration signals in iRBD and early detection of individuals at prodromal stages of these synucleinopathies, thus identifying imaging biomarkers of prodromal synucleinopathies. In this session, I will present up-to-date researches on functional and structural brain changes in iRBD using high resolution MRI techniques visualizing substantia nigra and brainstem nuclei, and resting state brain network changes as well as molecular imaging studies using 18F-FDG and FP-CIT (dopamine transporter) positron emission tomography scans covering both cross-sectional and longitudinal studies. Further large scale cohort studies with integration of multimodal imaging data in conjunction with clinical signs of neurodegeneration can provide us useful markers to predict individuals with iRBD at high risk of conversion into synucleinopathies, and therefore guide us to select candidates for future neuroprotective clinical trials.

Alterations in the functional brain network in a rat model of epileptogenesis: A longitudinal resting state fMRI study

Epilepsy is a neurological disorder characterized by recurrent epileptic seizures. Electrophysiological and neuroimaging studies in patients with epilepsy suggest that abnormal functional brain networks play a role in the development of epilepsy, i.e. epileptogenesis, resulting in the generation of spontaneous seizures and cognitive impairment. In this longitudinal study, we investigated changes in functional brain networks during epileptogenesis in the intraperitoneal kainic acid (IPKA) rat model of temporal lobe epilepsy (TLE) using resting state functional magnetic resonance imaging (rsfMRI) and graph theory. Additionally, we investigated whether these changes are related to the frequency of occurrence of spontaneous epileptic seizures in the chronic phase of epilepsy. Using a 7T MRI system, rsfMRI images were acquired under medetomidine anaesthesia before and 1, 3, 6, 10 and 16 weeks after status epilepticus (SE) induction in 20 IPKA animals and 7 healthy control animals. To obtain a functional network, correlation between fMRI time series of 38 regions of interest (ROIs) was calculated. Then, several graph theoretical network measures were calculated to describe and quantify the network changes. At least 17 weeks post-SE, IPKA animals were implanted with electrodes in the left and right dorsal hippocampus, EEG was measured for 7 consecutive days and spontaneous seizures were counted. Our results show that correlation coefficients of fMRI time series shift to lower values during epileptogenesis, indicating weaker whole brain network connections. Segregation and integration in the functional brain network also decrease, indicating a lower local interconnectivity and a lower overall communication efficiency. Secondly, this study demonstrates that the largest decrease in functional connectivity is observed for the retrosplenial cortex. Finally, post-SE changes in functional connectivity, segregation and integration are correlated with seizure frequency in the IPKA rat model.

Alterations in Brain Structure and Amplitude of Low-frequency after 8 weeks of Mindfulness Meditation Training in Meditation-Na\xefve Subjects

Increasing neuroimaging evidence suggests that mindfulness meditation expertise is related to different functional and structural configurations of the default mode network (DMN), the salience network (SN) and the executive network at rest. However, longitudinal studies observing resting network plasticity effects in brains of novices who started to practice meditation are scarce and generally related to one dimension, such as structural or functional effects. The purpose of this study was to investigate structural and functional brain network changes (e.g. DMN) after 40 days of mindfulness meditation training in novices and set these in the context of potentially altered depression symptomatology and anxiety. We found overlapping structural and functional effects in precuneus, a posterior DMN region, where cortical thickness increased and low-frequency amplitudes (ALFF) decreased, while decreased ALFF in left precuneus/posterior cingulate cortex correlates with the reduction of (CES-D) depression scores. In conclusion, regional overlapping of structural and functional changes in precuneus may capture different components of the complex changes of mindfulness meditation training.

Topological Disruption of Structural Brain Networks in Patients With Cognitive Impairment Following Cerebellar Infarction.

Cerebellar lesions can lead to a series of cognitive and emotional disorders by influencing cerebral activity via cerebro-cerebellar loops. To explore changes in cognitive function and structural brain networks in patients with posterior cerebellar infarction, we conducted the current study using diffusion-weighted MRI (32 cerebellar infarction patients, 29 controls). Moreover, a series of neuropsychological tests were used to assess the subject's cognitive performance. We found cognitive impairment following cerebellar infarction involving multiple cognitive domains, including memory, executive functions, visuospatial abilities, processing speed and language functions, and brain topological abnormalities, including changes in clustering coefficients, shortest path lengths, global efficiency, local efficiencies, betweenness centrality and nodal efficiencies. Our results indicated that measures of local efficiency, mainly in the precuneus, cingulate gyrus and frontal-temporal cortex, were significantly reduced with posterior cerebellar infarction. At the same time, The correlation analysis suggested thatthe abnormal alterations in the right PCG, bilateral DCG, right PCUN may play a core role in the cognitive impairment following cerebellar infarctions. The differences in topological features of the structural brain networks within the cerebro-cerebellar circuits may provide a new approach to explore the pathophysiological mechanisms of cognitive impairment following cerebellar infarction.

Executive function training in chronic traumatic brain injury patients: study protocol

BackgroundSome individuals who sustain traumatic brain injuries (TBIs) continue to experience significant cognitive impairments chronically (months to years post injury). Many tests of executive function are insensitive to these executive function impairments, as such impairments may only appear during complex daily life conditions. Daily life often requires us to divide our attention and focus on abstract goals. In the current study, we compare the effects of two 1-month electronic cognitive rehabilitation programs for individuals with chronic TBI. The active program (Expedition: Strategic Advantage) focuses on improving goal-directed executive functions including working memory, planning, long-term memory, and inhibitory control by challenging participants to accomplish life-like cognitive simulations. The challenge level of the simulations increases in accordance with participant achievement. The control intervention (Expedition: Informational Advantage) is identical to the active program; however, the cognitive demand level is capped, preventing participants from advancing beyond a set level. We will evaluate these interventions with a military veteran TBI population.Methods/designOne hundred individuals will be enrolled in this double-blinded clinical trial (all participants and testers are blinded to condition). Each individual will be randomly assigned to one of two interventions. The primary anticipated outcomes are improvement of daily life cognitive function skills and daily life functions. These are measured by a daily life performance task, which tests cognitive skills, and a survey that evaluates daily life functions. Secondary outcomes are also predicted to include improvements in working memory, attention, planning, and inhibitory control as measured by a neuropsychological test battery. Lastly, neuroimaging measures will be used to evaluate changes in brain networks supporting cognition pre and post intervention.DiscussionWe will test whether electronically delivered cognitive rehabilitation aimed at improving daily life functional skills will provide cognitive and daily life functional improvements for individuals in the chronic phase of TBI recovery (greater than 3 months post injury). We aim to better understand the cognitive processes involved in recovery and the characteristics of individuals most likely to benefit. This study will also address the potential to observe generalizability or to transfer from a software-based cognitive training tool toward daily life improvement.Trial registrationClinicalTrials.gov, NCT03704116. Retrospectively registered on 12 Oct 2018.

Topological Modification of Brain Networks Organization in Children With High Intelligence Quotient: A Resting-State fMRI Study.

The idea that intelligence is embedded not only in a single brain network, but instead in a complex, well-optimized system of complementary networks, has led to the development of whole brain network analysis. Using graph theory to analyze resting-state functional MRI data, we investigated the brain graph networks (or brain networks) of high intelligence quotient (HIQ) children. To this end, we computed the “hub disruption index κ,” an index sensitive to graph network modifications. We found significant topological differences in the integration and segregation properties of brain networks in HIQ compared to standard IQ children, not only for the whole brain graph, but also for each hemispheric graph, and for the homotopic connectivity. Moreover, two profiles of HIQ children, homogenous and heterogeneous, based on the differences between the two main IQ subscales [verbal comprehension index (VCI) and perceptual reasoning index (PRI)], were compared. Brain network changes were more pronounced in the heterogeneous than in the homogeneous HIQ subgroups. Finally, we found significant correlations between the graph networks’ changes and the full-scale IQ (FSIQ), as well as the subscales VCI and PRI. Specifically, the higher the FSIQ the greater was the brain organization modification in the whole brain, the left hemisphere, and the homotopic connectivity. These results shed new light on the relation between functional connectivity topology and high intelligence, as well as on different intelligence profiles.

Quantifying Changes in Brain Function Following Injury via Network Measures.

Widefield optical imaging enables longitudinal capturing of the large-scale network activity of the cerebral cortex in awake behaving animals. Utilizing this technique, we investigate how the brain's functional network structure is altered following injury. Cortical activity in transgenic calcium reporter mice expressing GCaMP6s is recorded in two sessions, prior and after inducing the injury. As a quantitative network measure, "communicability" which is indicative of how easily the information flows between nodes in a network via both direct and indirect paths, is considered. Compared to control subjects, results confirm altered functional network structure after the injury. Links that significantly contribute to the altered connectivity after the injury are spatially localized. It is shown that spectral clustering applied to the communicability networks is capable of distinguishing trials associated with pre-and post-injury sessions, suggesting that this approach can be used as an effective way to track changes in brain networks following the injury, and potentially, towards recovery.

Latent resting-state network dynamics in boys and girls with attention-deficit/hyperactivity disorder.

Neuroimaging studies of subjects with ADHD typically show altered functional connectivity in prefrontal, striatal, and several temporal brain regions. While the majority of studies have focused on connectivity that is averaged over time, we investigated the temporal dynamics of brain network changes in resting-state fMRI. Using the ADHD-200 consortium, we characterized the time course of latent state changes using Hidden Markov Modeling, and compared state changes between boys and girls with ADHD along with typically developing controls. Sex differences were found in latent state switching, with boys dwelling longer in a given state than girls, and concurrently having fewer overall state transitions. These sex differences were found in children with ADHD and in typically developing controls. Children with ADHD were also found to be more variable in terms of state transitions than controls. These findings add to the growing literature on neural sex differences and may be related to the sex difference in focal versus diffuse attention.

Tasked-Based Functional Brain Connectivity in Multisensory Control of Wrist Movement After Stroke.

In this study we documented brain connectivity associated with multisensory integration during wrist control in healthy young adults, aged matched controls and stroke survivors. A novel functional MRI task paradigm involving wrist movement was developed to gain insight into the effects of multimodal sensory feedback on brain functional networks in stroke participants. This paradigm consisted of an intermittent position search task using the wrist during fMRI signal acquisition with visual and auditory feedback of proximity to a target position. We enrolled 12 young adults, 10 participants with chronic post-stroke hemiparesis, and nine age-matched controls. Activation maps were obtained, and functional connectivity networks were calculated using an independent component analysis (ICA) approach. Task-based networks were identified using activation maps, and nodes were obtained from the ICA components. These nodes were subsequently used for connectivity analyses. Stroke participants demonstrated significantly greater contralesional activation than controls during the visual feedback condition and less ipsilesional activity than controls during the auditory feedback condition. The sensorimotor component obtained from the ICA differed between rest and task for control and stroke participants: task-related lateralization to the contralateral cortex was observed in controls, but not in stroke participants. Connectivity analyses between the lesioned sensorimotor cortex and the contralesional cerebellum demonstrated decreased functional connectivity in stroke participants (p < 0.005), which was positively correlated the Box and Blocks arm function test (r2 = 0.59). These results suggest that task-based functional connectivity provides detail on changes in brain networks in stroke survivors. The data also highlight the importance of cerebellar connections for recovery of arm function after stroke.

Brain-State Extraction Algorithm Based on the State Transition (BEST): A Dynamic Functional Brain Network Analysis in fMRI Study.

Spatial pattern of the brain network changes dynamically. This change is closely linked to the brain-state transition, which vary depending on a dynamic stream of thoughts. To date, many dynamic methods have been developed for decoding brain-states. However, most of them only consider changes over time, not the brain-state transition itself. Here, we propose a novel dynamic functional connectivity analysis method, brain-state extraction algorithm based on state transition (BEST), which constructs connectivity matrices from the duration of brain-states and decodes the proper number of brain-states in a data-driven way. To set the duration of each brain-state, we detected brain-state transition time-points using spatial standard deviation of the brain activity pattern that changes over time. Furthermore, we also used Bayesian information criterion to the clustering method to estimate and extract the number of brain-states. Through validations, it was proved that BEST could find brain-state transition time-points and could estimate the proper number of brain-states without any a priori knowledge. It has also shown that BEST can be applied to resting state fMRI data and provide stable and consistent results.

P28-T Temporary changes of resting-state functional networks after fear learning

Introduction Resting-state functional connectivity (rsFC) may indicate abnormalities in the brain physiology as it was shown at the example of altered rsFC within fear-processing brain circuit in patients with posttraumatic stress disorder. However, little is known about whether resting state networks vary their functional connections after experimental fear learning (FL). Here, we studied brain network changes in the resting state immediately, in one day and a week after FL using graph theory metrics. Methods We collected resting state fMRI data from 19 healthy controls and 24 healthy participants of FL protocol. Control group underwent three fMRI sessions: the second and the third sessions took place in one day and a week after the first respectively. FL group underwent five sessions: before FL, with fear memory retrieval, after FL, one day after, and a week after the first. We calculated paired FC of 94 anatomical regions of interest and analyze graph theory metrics of reconstructed networks for each session. Results The network during fear memory retrieval showed greater global efficiency than other resting state networks. Bilateral middle frontal gyri and parietal lobes became and remained network hubs after FL as well as in one day and one week afterward. No significant network changes were observed in the control group. Discussion and conclusions Our findings highlight the temporary effect of FL at resting state networks, which implies the functional readjustment of neural connections even after mild aversive exposure. This study was funded by the Grant No. 16-15-00300 of the Russian Scientific Foundation .

Altered brain network integrity in patients with asthma: A structural connectomic diffusion tensor imaging study

Brain functional deficits had been reported in asthma patients. These deficits may be related to treatment resistance, inaccurate self-assessment and poor self-management. However, changes of the structural brain network in asthma patients remain largely unclear. Diffusion tensor imaging were acquired from 54 asthmatic patients and 44 controls. Then we calculated all the participants’ structural network metrics. All the participants underwent the test of Hamilton Rating Scale for Depression and Anxiety as well as a lung function. Multiple linear correlation analyses were conducted. At the global level, asthma patients had a higher path length and lower global efficiency than controls, implying a shift toward regular networks. At the local level, asthma patients exhibited abnormal nodal connectivity with other nodes involved the fronto-limbic regions. Our findings highlight more locally segregated but less efficiently integrated structural networks, particularly involving frontal-limbic networks, in asthmatic patients. These findings provide important evidence to support the role of brain networks in the pathophysiology of asthma.

A pilot study of combined endurance and resistance exercise rehabilitation for verbal memory and functional connectivity improvement in epilepsy

Memory impairment is common in persons with epilepsy (PWE), and exercise may be a strategy for its improvement. In this pilot study, we hypothesized that exercise rehabilitation would improve physical fitness and verbal memory and induce changes in brain networks involved in memory processes. We examined the effects of combined endurance and resistance exercise rehabilitation on memory and resting state functional connectivity (rsFC). Participants were randomized to exercise (PWE-E) or control (PWE-noE). The exercise intervention consisted of 18 supervised sessions on nonconsecutive days over 6 weeks. Before and after the intervention period, both groups completed self-report assessments (Short Form-36 (SF-36), Baecke Questionnaire (BQ) of habitual physical activity, and Profile of Mood States (POMS)), cognitive testing (California Verbal Learning Test-II (CVLT-II)), and magnetic resonance imaging (MRI); PWE-E also completed exercise performance tests. After completing the study, PWE-noE were offered cross-over to the exercise arm. There were no differences in baseline demographic, clinical, or assessment variables between 8 PWE-noE and 9 PWE-E. Persons with epilepsy that participated in exercise intervention increased maximum voluntary strength (all strength tests p < 0.05) and exhibited nonsignificant improvement in cardiorespiratory fitness (p = 0.15). Groups did not show significant changes in quality of life (QOL) or habitual physical activity between visits. However, there was an effect of visit on POMS total mood disturbance (TMD) measure showing improvement from baseline to visit 2 (p = 0.023). There were significant group by visit interactions on CVLT-II learning score (p = 0.044) and total recognition discriminability (d′) (p = 0.007). Persons with epilepsy that participated in exercise intervention had significant reductions in paracingulate rsFC with the anterior cingulate and increases in rsFC for the cerebellum, thalamus, posterior cingulate cortex (PCC), and left and right inferior parietal lobule (IPL) (corrected p < 0.05). Change in CVLT-II learning score was associated with rsFC changes for the paracingulate cortex (rS = −0.67; p = 0.0033), left IPL (rS = 0.70; p = 0.0019), and right IPL (rS = 0.71; p = 0.0015) while change in d′ was associated with change in cerebellum rsFC to angular/middle occipital gyrus (rS = 0.68; p = 0.0025). Our conclusion is that exercise rehabilitation may facilitate verbal memory improvement and brain network functional connectivity changes in PWE and that improved memory performance is associated with changes in rsFC. A larger randomized controlled trial of exercise rehabilitation for cognitive improvement in PWE is warranted.

Power Spectral Density and Functional Connectivity Changes due to a Sensorimotor Neurofeedback Training: A Preliminary Study.

Neurofeedback is a form of neuromodulation based on learning to modify some aspects of cortical activity. Sensorimotor rhythm (SMR) oscillation is one of the most used frequency bands in neurofeedback. Several studies have shown that subjects can learn to modulate SMR power to control output devices, but little is known about possible related changes in brain networks. The aim of this study was to investigate the enhanced performance and changes in EEG power spectral density at somatosensory cerebral areas due to a bidirectional modulation-based SMR neurofeedback training. Furthermore, we also analyzed the functional changes in somatosensory areas during resting state induced by the training as exploratory procedure. A six-session neurofeedback protocol based on learning to synchronize and desynchronize (modulate) the SMR was implemented. Moreover, half of the participants were enrolled in two functional magnetic resonance imaging resting-state sessions (before and after the training). At the end of the training, participants showed a successful performance enhancement, an increase in SMR power specific to somatosensory locations, and higher functional connectivity between areas associated with somatosensory activity in resting state. Our research increases the better understanding of the relation between EEG neuromodulation and functional changes and the use of SMR training in clinical practice.

Changes in functional brain networks and neurocognitive function in Chinese gynecological cancer patients after chemotherapy: a prospective longitudinal study

BackgroundPrevious neurocognitive assessments in non-central nervous system cancers highlight the high incidence of neurocognitive dysfunction in this study population. However, there have been few studies exploring neurocognitive dysfunction induced by chemotherapy in gynecological cancer patients. This prospective longitudinal study was conducted to assess neurocognitive functioning and functional brain networks in Chinese gynecological cancer patients pre- and post-chemotherapy, while additionally including age-matched healthy subjects as the control group.MethodsAll research participants were evaluated using a resting-state functional magnetic resonance imaging and neurocognition assessment. Behavioral data were conducted using SPSS for descriptive statistics, correlation and comparison analyses. Preprocessing of MRI (Magnetic Resonance Imaging) data and network analyses were performed using GRETNA (Graph Theoretical Network Analysis).ResultsA total of 40 subjects joined this study, with 20 subjects in each group. With the exception of the mean of psychomotor speed, there was no significant difference pre-chemotherapy between patients and healthy controls in neurocognitive test mean scores (Ps > 0.05). During the post-chemotherapy assessment, there were significant differences in the mean scores of neurocognitive tests (including Digit Span tests, verbal memory, immediate recall, delayed recall, and information processing speed tests) (all Ps < 0 .05). Longitudinal graph analysis revealed statistically significant differences in the patient group, with significant decreases in both local efficiency (P < 0.01) and global efficiency (P = 0.04). Lower raw TMT-A scores were significantly associated with lower local efficiency (r = 0.37, P = 0.03). Lower verbal memory scores were statistically significant and associated with lower global efficiency (r = 0.54, P = 0.02) in the patient group, but not in the healthy control group.ConclusionsThis study found that the risk of brain function and neurocognitive changes following chemotherapy could potentially guide patients in making appropriate treatment decisions, and this study may identify a cohort that could be suited for study of an intervention.

Cortical patterning of abnormal morphometric similarity in psychosis is associated with brain expression of schizophrenia-related genes

Schizophrenia has been conceived as a disorder of brain connectivity, but it is unclear how this network phenotype is related to the underlying genetics. We used morphometric similarity analysis of MRI data as a marker of interareal cortical connectivity in three prior case-control studies of psychosis: in total, n = 185 cases and n = 227 controls. Psychosis was associated with globally reduced morphometric similarity in all three studies. There was also a replicable pattern of case-control differences in regional morphometric similarity, which was significantly reduced in patients in frontal and temporal cortical areas but increased in parietal cortex. Using prior brain-wide gene expression data, we found that the cortical map of case-control differences in morphometric similarity was spatially correlated with cortical expression of a weighted combination of genes enriched for neurobiologically relevant ontology terms and pathways. In addition, genes that were normally overexpressed in cortical areas with reduced morphometric similarity were significantly up-regulated in three prior post mortem studies of schizophrenia. We propose that this combined analysis of neuroimaging and transcriptional data provides insight into how previously implicated genes and proteins as well as a number of unreported genes in their topological vicinity on the protein interaction network may drive structural brain network changes mediating the genetic risk of schizophrenia.

Multimodal Imaging of Repetitive Transcranial Magnetic Stimulation Effect on Brain Network: A Combined Electroencephalogram and Functional Magnetic Resonance Imaging Study.

Repetitive transcranial magnetic stimulation (rTMS) has been increasingly used to treat many neurological and neuropsychiatric disorders. However, the clinical response is heterogeneous mainly due to our inability to predict the effect of rTMS on the human brain. Our previous investigation based on functional magnetic resonance imaging (fMRI) suggested that neuroimaging-guided navigation for rTMS could be informed by understanding connectivity patterns that correlate with treatment response. In this study, 20 individuals with a balance disorder called Mal de Debarquement Syndrome completed high-density resting-state electroencephalogram (EEG) and fMRI recordings before and after 5 days of rTMS stimulation over both dorsolateral prefrontal cortices. Based on temporal independent component analysis of source-level EEG data, large-scale electrophysiological resting-state networks were reconstructed and connectivity values in each individual were quantified both before and after treatment. Our results show that high-density, resting-state EEG can reveal connectivity changes in brain networks after rTMS that correlate with symptom changes. The connectivity changes measured by EEG were primarily superficial cortical areas that correlate with previously shown default mode network changes revealed by fMRI. Further, higher baseline EEG connectivity values in the primary visual cortex were predictive of symptom reduction after rTMS. Our findings suggest that multimodal EEG and fMRI measures of brain networks can be biomarkers that correlate with the treatment effect of rTMS. Since EEG is compatible with rTMS, real-time navigation based on an EEG neuroimaging marker may augment rTMS optimization.