Changes In Brain Network Connectivity Research Articles

Investigating altered brain functional hubs and causal connectivity in coronary artery disease with cognitive impairment.

Coronary artery disease (CAD) and cognitive impairment (CI) have become significant global disease and medical burdens. There have been several reports documenting the alterations in regional brain function and their correlation with CI in CAD patients. However, there is limited research on the changes in brain network connectivity in CAD patients. To investigate the resting-state connectivity and further understand the effective connectivity strength and directionality in patients with CAD, we utilized degree centrality (DC) and spectral dynamic causal modeling (spDCM) to detect functional hubs in the whole brain network, followed by an analysis of directional connections. Using the aforementioned approaches, it is possible to investigate the hub regions and aberrant connections underlying the altered brain function in CAD patients, providing neuroimaging evidence for the cognitive decline in patients with coronary artery disease. This study was prospectively conducted involving 24 patients diagnosed with CAD and 24 healthy controls (HC) who were matched in terms of age, gender, and education. Functional MRI (fMRI) scans were utilized to investigate brain activity in these individuals. Neuropsychological examinations were performed on all participants. DC analysis and spDCM were employed to investigate abnormal brain networks in patients with CAD. Additionally, the association between effective connectivity strength and cognitive function in patients with CAD was examined based on the aforementioned results. By assessing cognitive functions, we discovered that patients with CAD exhibited notably lower cognitive function compared to the HC group. By utilizing DC analysis and spDCM, we observed significant reductions in DC values within the left parahippocampal cortex (PHC) and the left medial temporal gyrus (MTG) in CAD patients when compared to the control group. In terms of effective connectivity, we observed the absence of positive connectivity between the right superior frontal gyrus (SFG) and PHC in CAD patients. Moreover, there was an increase in negative connectivity from PHC and MTG to SFG, along with a decrease in the strength of positive connectivity between PHC and MTG. Furthermore, we identified a noteworthy positive correlation (r = 0.491, p = 0.015) between the strength of connectivity between the PHC and the MTG and cognitive function in CAD patients. These research findings suggest that alterations in the connectivity of the brain networks involving SFG, PHC, and MTG in CAD patients may mediate changes in cognitive function.

Abstract 11433: Elevated Vascular Endothelial Growth Factor A is Associated With Disruption of Default Network Connectivity

Introduction: Vascular Endothelial Growth Factor A (VEGF-A) is an angiogenic signaling protein involved in the maintenance of the cerebral vasculature. VEGF-A may play a role in the pathogenesis of Alzheimer’s disease and vascular dementia; however, whether elevated VEGF-A levels indicate a pathophysiolocal response or protective mechanism remains unclear. No prior study has explored whether VEGF-A levels may be associated with changes in functional connectivity among brain regions prior to the development of cognitive decline. Hypothesis: Disruption of the default network often precedes the development of cognitive changes. In a sample of older adults, we hypothesized that VEGF-A levels may be associated with default network connectivity, indicating early involvement of VEGF-A in disease processes. Methods: Forty-six independently living older adults (mean age = 72.0 years; SD = 6.4; 34.8% male) free of dementia or clinical stroke underwent venipuncture and brain MRI. Plasma was assayed for VEGF-A. Using resting state functional MRI, blood-oxygen level dependent (BOLD) time series from all voxels in each region of interest (ROI) was averaged to determine mean ROI activity. Medial prefrontal cortex, lateral parietal cortex and precuneus cortex ROIs comprised the default network. Results: Accounting for age and sex, multiple linear regression analysis revealed a significant negative association between VEGF-A levels and default mode network connectivity (B =-.0007, 95% CI (-.0012, -.0002), p = .0096). This association persisted after adjusting for APOE4 carrier status and Framingham score. A significant association was present in both APOE4 carriers (p = .019) and non-carriers (p = .029). Conclusions: Prior studies evaluating the association between VEGF-A levels and cognition have been conflicted. This study is the first to examine whether VEGF-A may be linked to early changes in brain network connectivity which precede cognitive decline. These findings suggest that VEGF-A may be elevated early in the progression of neurocognitive disorders. Whether higher levels of VEGF-A contribute to the pathogenesis of neurocognitive disorders or play a protective role in persevering cognitive function warrants further investigation.

Six month lower-leg mechanical tactile sensory stimulation alters functional network connectivity associated with improved gait in older adults with peripheral neuropathy - A pilot study.

Foot sole somatosensory impairment associated with peripheral neuropathy (PN) is prevalent and a strong independent risk factor for gait disturbance and falls in older adults. Walkasins, a lower-limb sensory prosthesis, has been shown to improve gait and mobility in people with PN by providing afferent input related to foot sole pressure distributions via lower-leg mechanical tactile stimulation. Given that gait and mobility are regulated by sensorimotor and cognitive brain networks, it is plausible improvements in gait and mobility from wearing the Walkasins may be associated with elicited neuroplastic changes in the brain. As such, this study aimed to examine changes in brain network connectivity after 26 weeks of daily use of the prosthesis among individuals with diagnosed PN and balance problems. In this exploratory investigation, assessments of participant characteristics, Functional Gait Assessment (FGA), and resting-state functional magnetic resonance imaging were completed at study baseline and 26 weeks follow-up. We found that among those who have completed the study (N = 8; mean age 73.7 years) we observed a five-point improvement in FGA performance as well as significant changes in network connectivity over the 26 weeks that were correlated with improved FGA performance. Specifically, greater improvement in FGA score over 26 weeks was associated with increased connectivity within the Default Mode Network (DMN; p < 0.01), the Somatosensory Network (SMN; p < 0.01), and the Frontoparietal Network (FPN; p < 0.01). FGA improvement was also correlated with increased connectivity between the DMN and the FPN (p < 0.01), and decreased connectivity between the SMN and both the FPN (p < 0.01) and cerebellum (p < 0.01). These findings suggest that 26 weeks of daily use of the Walkasins device may provide beneficial neural modulatory changes in brain network connectivity via the sensory replacement stimulation that are relevant to gait improvements among older adults with PN.

Dynamic connectivity patterns of resting-state brain functional networks in healthy individuals after acute alcohol intake.

AimsCurrently, there are only a few studies concerning brain functional alterations after acute alcohol exposure, and the majority of existing studies attach more importance to the spatial properties of brain function without considering the temporal properties. The current study adopted sliding window to investigate the resting-state brain networks in healthy volunteers after acute alcohol intake and to explore the dynamic changes in network connectivity.Materials and methodsTwenty healthy volunteers were enrolled in this study. Blood-oxygen-level-dependent (BOLD) data prior to drinking were obtained as control, while that 0.5 and 1 h after drinking were obtained as the experimental group. Reoccurring functional connectivity patterns (states) were determined following group independent component analysis (ICA), sliding window analysis and k-means clustering. Between-group comparisons were performed with respect to the functional connectivity states fractional windows, mean dwell time, and the number of transitions.ResultsThree optimal functional connectivity states were identified. The fractional windows and mean dwell time of 0.5 h group and 1 h group increased in state 3, while the fraction window and mean dwell time of 1 h group decreased in state 1. State 1 is characterized by strong inter-network connections between basal ganglia network (BGN) and sensorimotor network (SMN), BGN and cognitive executive network (CEN), and default mode network (DMN) and visual network (VN). However, state 3 is distinguished by relatively weak intra-network connections in SMN, VN, CEN, and DMN. State 3 was thought to be a characteristic connectivity pattern of the drunk brain. State 1 was believed to represent the brain’s main connection pattern when awake. Such dynamic changes in brain network connectivity were consistent with participants’ subjective feelings after drinking.ConclusionThe current study reveals the dynamic change in resting-state brain functional network connectivity before and after acute alcohol intake. It was discovered that there might be relatively independent characteristic functional network connection patterns under intoxication, and the corresponding patterns characterize the clinical manifestations of volunteers. As a valuable imaging biomarker, dynamic functional network connectivity (dFNC) offers a new approach and basis for further explorations on brain network alterations after alcohol consumption and the alcohol-related mechanisms for neurological damage.

Network analysis of preictal iEEG reveals changes in network structure preceding seizure onset

Seizures likely result from aberrant network activity and synchronization. Changes in brain network connectivity may underlie seizure onset. We used a novel method of rapid network model estimation from intracranial electroencephalography (iEEG) data to characterize pre-ictal changes in network structure prior to seizure onset. We analyzed iEEG data from 20 patients from the iEEG.org database. Using 10 s epochs sliding by 1 s intervals, a multiple input, single output (MISO) state space model was estimated for each output channel and time point with all other channels as inputs, generating sequential directed network graphs of channel connectivity. These networks were assessed using degree and betweenness centrality. Both degree and betweenness increased at seizure onset zone (SOZ) channels 37.0 ± 2.8 s before seizure onset. Degree rose in all channels 8.2 ± 2.2 s prior to seizure onset, with increasing connections between the SOZ and surrounding channels. Interictal networks showed low and stable connectivity. A novel MISO model-based network estimation method identified changes in brain network structure just prior to seizure onset. Increased connectivity was initially isolated within the SOZ and spread to non-SOZ channels before electrographic seizure onset. Such models could help confirm localization of SOZ regions.

Unraveling the Mysteries of Mental Illness With Psilocybin.

Current medications have not been effective in reducing the prevalence of mental illness worldwide. The prevalence of illnesses such as treatment-resistant depression has increased despite the widespread use of a broad set of psychopharmaceuticals. Transcranial magnetic stimulation and ketamine therapy are making great strides in improving treatment-resistant depression outcomes but they have limitations. New psychotherapeutics are required that specifically target the underlying cellular pathologies leading to neuronal atrophy. This neuronal atrophy model is supplanting the long-held neurotransmitter deficit hypothesis to explain mental illness. Interest in psychedelics as therapeutic molecules to treat mental illness is experiencing a 21st-century reawakening that is on the cusp of a transformation. Psilocybin is a pro-drug, found in various naturally occurring mushrooms, that is dephosphorylated to produce psilocin, a classic tryptamine psychedelic functional as a 5-hydroxytryptamine 2A receptor agonist. We have focused this review to include studies in the last two years that suggest psilocybin promotes neuronal plasticity, which may lead to changes in brain network connectivity. Recent advancements in clinical trials using pure psilocybin in therapy suggest that it may effectively relieve the symptoms of depression in patients diagnosed with major depressive disorder and treatment-resistant depression. Sophisticated cellular and molecular experiments at the systems level have produced evidence that demonstrates psilocybin promotes neuritogenesis in the mouse brain - a mechanism that may address the root cause of depression at the cellular level. Finally, studies with psilocybin therapy for major depressive disorder suggest that this ancient molecule can promote functionally connected intrinsic networks in the human brain, resulting in durable improvements in the severity of depressive symptoms. Although further research is necessary, the prospect of using psilocybin for the treatment of mental illness is an enticing possibility.

Propofol-induced Unresponsiveness Is Associated with a Brain Network Phase Transition.

Background:The wakeful brain can easily access and coordinate a large repertoire of different states—dynamics suggestive of “criticality.” Anesthesia causes loss of criticality at the level of electroencephalogram waveforms, but the criticality of brain network connectivity is less well studied. The authors hypothesized that propofol anesthesia is associated with abrupt and divergent changes in brain network connectivity for different frequencies and time scales—characteristic of a phase transition, a signature of loss of criticality.Methods:As part of a previously reported study, 16 volunteers were given propofol in slowly increasing brain concentrations, and their behavioral responsiveness was assessed. The network dynamics from 31-channel electroencephalogram data were calculated from 1 to 20 Hz using four phase and envelope amplitude–based functional connectivity metrics that covered a wide range of time scales from milliseconds to minutes. The authors calculated network global efficiency, clustering coefficient, and statistical complexity (using the Jensen–Shannon divergence) for each functional connectivity metric and compared their findings with those from an in silico Kuramoto network model.Results:The transition to anesthesia was associated with critical slowing and then abrupt profound decreases in global network efficiency of 2 Hz power envelope metrics (from mean ± SD of 0.64 ± 0.15 to 0.29 ± 0.28 absolute value, P < 0.001, for medium; and from 0.47 ± 0.13 to 0.24 ± 0.21, P < 0.001, for long time scales) but with an increase in global network efficiency for 10 Hz weighted phase lag index (from 0.30 ± 0.20 to 0.72 ± 0.06, P < 0.001). Network complexity decreased for both the 10 Hz hypersynchronous (0.44 ± 0.13 to 0.23 ± 0.08, P < 0.001), and the 2 Hz asynchronous (0.73 ± 0.08 to 0.40 ± 0.13, P < 0.001) network states. These patterns of network coupling were consistent with those of the Kuramoto model of an order–disorder phase transition.Conclusions:Around loss of behavioral responsiveness, a small increase in propofol concentrations caused a collapse of long time scale power envelope connectivity and an increase in 10 Hz phase-based connectivity—suggestive of a brain network phase transition.

This Month in Anesthesiology

This Month in Anesthesiology

Abnormal static and dynamic functional connectivity of networks related to cognition in patients with subcortical ischemic vascular disease.

To investigate the specific features of static functional connectivity (SFC) and dynamic functional connectivity (DFC) of networks related to cognition in patients with subcortical ischemic vascular disease (SIVD). In this retrospective study, resting-state functional MRI data and a series of cognitive scores were obtained from 38 patients with SIVD and 23 normal controls. Independent component analysis, sliding window method, k-means clustering analysis and graph theory method were used to examine FC between the default mode network (DMN), dorsal attention network (DAN), frontoparietal network (FPN), salience network (SN) and executive control network (ECN) in patients with SIVD. Then, correlations between abnormal FC features and cognition were assessed. Compared with normal controls, SFC within the DMN significantly increased and SFC between the DMN and DAN significantly decreased in patients with SIVD. The decreased DFC mainly occurred in weakly connected states, especially the DFC of the SN; but the increased DFC, global network efficiency and local network efficiency and the decreased mean dwell time (MDT) and frequency mainly occurred in strongly connected states in SIVD patients. Moreover, aberrant SFC, DFC and MDT were significantly correlated with patients' cognitive scores. The overall results are suggestive of abnormal functional segregation and integration of SFC and DFC among networks related to cognition, especially in the SN. This may advance our comprehensive understanding of the abnormal changes in brain network connectivity in patients with SIVD. Our findings also highlight DFC may be an effective neuroimaging marker for the clinical diagnosis of SIVD.

Abnormal dynamic brain activity and functional connectivity of primary motor cortex in blepharospasm.

Accumulating evidence indicates that dynamic amplitude of low-frequency fluctuations (dALFF) or dynamic functional connectivity (dFC) can provide complementary information, distinct from static amplitude of low-frequency fluctuations (sALFF) or static functional connectivity (sFC), in detecting brain functional abnormalities in brain diseases. We aimed to examine whether dALFF and dFC can offer valuable information for the detection of functional brain abnormalities in patients with blepharospasm. We collected resting-state functional magnetic resonance imaging data from 46 patients each of blepharospasm, hemifacial spasm (HFS), and healthy controls (HCs). We examined intergroup differences in sALFF and dALFF to investigate abnormal regional brain activity in patients with blepharospasm. Based on the dALFF results, we conducted seed-based sFC and dFC analyses to identify static and dynamic connectivity changes in brain networks centered on areas showing abnormal temporal variability of local brain activity in patients with blepharospasm. Compared with HCs, patients with blepharospasm displayed different brain functional change patterns characterized by increased sALFF in the left primary motor cortex (PMC) but increased dALFF variance in the right PMC. However, differences were not found between patients with HFS and HCs. Additionally, patients with blepharospasm exhibited decreased dFC strength, but no change in sFC, between right PMC and ipsilateral cerebellum compared with HCs; these findings were replicated when patients with blepharospasm were compared to those with HFS. Our findings highlight that dALFF and dFC are complementary to sALFF and sFC and can provide valuable information for detecting brain functional abnormalities in blepharospasm. Blepharospasm may be a network disorder involving the cortico-ponto-cerebello-thalamo-cortical circuit.

Six-Month Lower-Leg Sensory Stimulation Augments Neural Network Connectivity Associated With Improved Gait

Foot sole somatosensory impairment associated with peripheral neuropathy (PN) is prevalent and a strong independent risk factor for gait disturbance and falls in older adults. A lower-limb sensory prosthesis providing afferent input related to foot sole pressure distributions via lower-leg vibrotactile stimulation has been demonstrated to improve gait in people with PN. The effects of this device on brain function related to motor control, however, remains equivocal. This study aimed to explore changes in brain network connectivity after six months of daily use of the prosthesis among individuals with diagnosed PN and balance problems. Functional Gait Assessment (FGA) and resting-state functional magnetic resonance imaging were completed before and after the intervention. Preliminary analysis on participants who have completed the study to date (N=5; mean age 76 years) indicated altered connectivity of the sensorimotor network (SMN), frontoparietal network (FPN), and the default mode network (DMN) post-intervention (Z>3.11, unadjusted p<0.05). Participants displayed an average improvement of 5.5 point in the FGA (Minimal Clinically Important Differences>4 for community-dwelling older adults) that was correlated with connectivity changes (unadjusted p<0.05). Specifically, improved FGA was associated with: 1) increased connectivity between the SMN, cerebellum, and occipital cortex; 2) increased connectivity between the FPN, cerebellum, calcarine and intracalcarine; and 3) decreased connectivity between DMN and intracalcarine. These early findings suggest that long-term use of a lower-limb sensory prosthesis may induce neuroplastic changes in brain network connectivity reflecting enhanced bottom-up sensory-attentional processing and suppression of the DMN that are relevant to gait improvements among older adults with PN.

Propofol sedation-induced alterations in brain connectivity reflect parvalbumin interneurone distribution in human cerebral cortex

BackgroundPropofol, a commonly used intravenous anaesthetic, binds to type A gamma aminobutyric acid (GABA) receptors in mammalian brain. Previous work on its anaesthetic action has characterised either the biochemistry underlying propofol binding or the associated changes in brain network dynamics during sedation. Despite these advances, no study has focused on understanding how propofol action at the cellular level results in changes in brain network connectivity. MethodsWe used human whole-brain microarray data to generate distribution maps for genes that mark the primary GABAergic cortical interneurone subtypes (somatostatin, parvalbumin [PV], and 5-hydroxytryptamine 3A. Next, 25 healthy participants underwent propofol-induced sedation during resting state functional MRI scanning. We used partial least squares analysis to identify the brain regions in which connectivity patterns were most impacted by propofol sedation. We then correlated these multimodal cortical patterns to determine if a specific interneurone subtype was disproportionately expressed in brain regions in which connectivity patterns were altered during sedation. ResultsBrain networks that were significantly altered by propofol sedation had a high density of PV-expressing GABAergic interneurones. Brain networks that anticorrelated during normal wakefulness, namely the default mode network and attentional and frontoparietal control networks, increased in correlation during sedation. ConclusionsPV-expressing interneurones are highly expressed in brain regions with altered connectivity profiles during propofol-induced sedation. This study also demonstrates the utility of leveraging multiple datasets to address multiscale neurobiological problems.

Neural Connectivity Changes Facilitated by Familiar Auditory Sensory Training in Disordered Consciousness: A TBI Pilot Study.

For people with disordered consciousness (DoC) after traumatic brain injury (TBI), relationships between treatment-induced changes in neural connectivity and neurobehavioral recovery have not been explored. To begin building a body of evidence regarding the unique contributions of treatments to changes in neural network connectivity relative to neurobehavioral recovery, we conducted a pilot study to identify relationships meriting additional examination in future research. To address this objective, we examined previously unpublished neural connectivity data derived from a randomized clinical trial (RCT). We leveraged these data because treatment efficacy, in the RCT, was based on a comparison of a placebo control with a specific intervention, the familiar auditory sensory training (FAST) intervention, consisting of autobiographical auditory-linguistic stimuli. We selected a subgroup of RCT participants with high-quality imaging data (FAST n = 4 and placebo n = 4) to examine treatment-related changes in brain network connectivity and how and if these changes relate to neurobehavioral recovery. To discover promising relationships among the FAST intervention, changes in neural connectivity, and neurobehavioral recovery, we examined 26 brain regions and 19 white matter tracts associated with default mode, salience, attention, and language networks, as well as three neurobehavioral measures. Of the relationships discovered, the systematic filtering process yielded evidence supporting further investigation of the relationship among the FAST intervention, connectivity of the left inferior longitudinal fasciculus, and auditory-language skills. Evidence also suggests that future mechanistic research should focus on examining the possibility that the FAST supports connectivity changes by facilitating redistribution of brain resources. For a patient population with limited treatment options, the reported findings suggest that a simple, yet targeted, passive sensory stimulation treatment may have altered functional and structural connectivity. If replicated in future research, then these findings provide the foundation for characterizing the unique contributions of the FAST intervention and could inform development of new treatment strategies. For persons with severely damaged brain networks, this report represents a first step toward advancing understanding of the unique contributions of treatments to changing brain network connectivity and how these changes relate to neurobehavioral recovery for persons with DoC after TBI.Clinical Trial Registry: NCT00557076, The Efficacy of Familiar Voice Stimulation During Coma Recovery (http://www.clinicaltrials.gov).

Tracking Changes in Brain Network Connectivity under Transcranial Current Stimulation.

Noninvasive transcranial brain stimulation has been widely used in experimental and clinical applications to perturb the brain activity, aiming at promoting synaptic plasticity or enhancing functional connectivity within targeted brain regions. However, there are different types of neurostimulations and various choices of stimulation parameters; how these choices influence the intermediate neurophysiological effects and brain connectivity remain incompletely understood. We propose several quantitative methods to investigate the brain connectivity of an epileptic patient before and after transcranial alternating/direct current stimulation (tACS/tDCS). The neuro-feedback derived from our analyses may provide useful cues for the effectiveness of neurostimulation.

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.

Cognitive behavioral training reverses the effect of pain exposure on brain network activity.

Repeated sensory exposures shape the brain's function and its responses to environmental stimuli. An important clinical and scientific question is how exposure to pain affects brain network activity and whether that activity is modifiable with training. We sought to determine whether repeated pain exposure would impact brain network activity and whether these effects can be reversed by cognitive behavioral therapy (CBT)-based training. Healthy subjects underwent 8 experimental sessions on separate days on which they received painful thermal stimuli. They were randomly assigned to groups receiving either CBT-based training (regulate group, n = 17) or a non-pain-focused treatment (control group, n = 13). Before and after these sessions, participants underwent functional magnetic resonance imaging (fMRI) during painful stimulation and at rest. The effect of repeated pain over time in the control group was a decrease in the neurotypical pain-evoked default mode network (DMN) deactivation. The regulate group did not show these DMN effects but rather had decreased deactivation of the right ventrolateral prefrontal cortex (R vlPFC) of the executive control network. In the regulate group, reduced pain-evoked DMN deactivation was associated with greater individual reduction in pain intensity and unpleasantness over time. Finally, the regulate group showed enhanced resting functional connectivity between areas of the DMN and executive control network over time, compared with the control group. Our study demonstrates that trainable cognitive states can alter the effect of repeated sensory exposure on the brain. The findings point to the potential utility of cognitive training to prevent changes in brain network connectivity that occur with repeated experience of pain.

Violence-related content in video game may lead to functional connectivity changes in brain networks as revealed by fMRI-ICA in young men

In violent video games, players engage in virtual aggressive behaviors. Exposure to virtual aggressive behavior induces short-term changes in players’ behavior. In a previous study, a violence-related version of the racing game “Carmageddon TDR2000” increased aggressive affects, cognitions, and behaviors compared to its non-violence-related version. This study investigates the differences in neural network activity during the playing of both versions of the video game.Functional magnetic resonance imaging (fMRI) recorded ongoing brain activity of 18 young men playing the violence-related and the non-violence-related version of the video game Carmageddon. Image time series were decomposed into functional connectivity (FC) patterns using independent component analysis (ICA) and template-matching yielded a mapping to established functional brain networks.The FC patterns revealed a decrease in connectivity within 6 brain networks during the violence-related compared to the non-violence-related condition: three sensory-motor networks, the reward network, the default mode network (DMN), and the right-lateralized frontoparietal network.Playing violent racing games may change functional brain connectivity, in particular and even after controlling for event frequency, in the reward network and the DMN. These changes may underlie the short-term increase of aggressive affects, cognitions, and behaviors as observed after playing violent video games.