Changes In Network Connectivity Research Articles

Neuronal functional connectivity is impaired in a layer dependent manner near chronically implanted intracortical microelectrodes in C57BL6 wildtype mice.

This study aims to reveal longitudinal changes in functional network connectivity within and across different brain structures near chronically implanted microelectrodes. While it is well established that the foreign-body response (FBR) contributes to the gradual decline of the signals recorded from brain implants over time, how the FBR affects the functional stability of neural circuits near implanted Brain-Computer Interfaces (BCIs) remains unknown. This research aims to illuminate how the chronic FBR can alter local neural circuit function and the implications for BCI decoders. This study utilized single-shank, 16-channel,100 µm site-spacing Michigan-style microelectrodes (3mm length, 703 µm2 site area) that span all cortical layers and the hippocampal CA1 region. Sex balanced C57BL6 wildtype mice (11-13 weeks old) received perpendicularly implanted microelectrode in left primary visual cortex. Electrophysiological recordings were performed during both spontaneous activity and visual sensory stimulation. Alterations in neuronal activity near the microelectrode were tested assessing cross-frequency synchronization of LFP and spike entrainment to LFP oscillatory activity throughout 16 weeks after microelectrode implantation. The study found that cortical layer 4, the input-receiving layer, maintained activity over the implantation time. However, layers 2/3 rapidly experienced severe impairment, leading to a loss of proper intralaminar connectivity in the downstream output layers 5/6. Furthermore, the impairment of interlaminar connectivity near the microelectrode was unidirectional, showing decreased connectivity from Layers 2/3 to Layers 5/6 but not the reverse direction. In the hippocampus, CA1 neurons gradually became unable to properly entrain to the surrounding LFP oscillations. This study provides a detailed characterization of network connectivity dysfunction over long-term microelectrode implantation periods. This new knowledge could contribute to the development of targeted therapeutic strategies aimed at improving the health of the tissue surrounding brain implants and potentially inform engineering of adaptive decoders as the FBR progresses. Our study's understanding of the dynamic changes in the functional network over time opens the door to developing interventions for improving the long-term stability and performance of intracortical microelectrodes.

Analysis of functional connectivity changes in attention networks and default mode networks in patients with depression and insomnia.

Major Depressive Disorder (MDD) and Insomnia Disorder (ID) are prevalent psychiatric conditions often occurring concurrently, leading to substantial impairment in daily functioning. Understanding the neurobiological underpinnings of these disorders and their comorbidity is crucial for developing effective interventions. This study aims to analyze changes in functional connectivity within attention networks and default mode networks in patients with depression and insomnia. The functional connectivity alterations in individuals with MDD, ID, comorbid MDD and insomnia (iMDD), and healthy controls (HC) were assessed from a cohort of 174 participants. They underwent rs-fMRI scans, demographic assessments, and scale evaluations for depression and sleep quality. Functional connectivity analysis was conducted using region-of-interest (ROI) and whole-brain methods. The MDD and iMDD groups exhibited higher Hamilton Depression Scale (HAMD) scores compared to HC and ID groups (P < 0.001). Both ID and MDD groups displayed enhanced connectivity between the left and right orbital frontal cortex compared to HC (P < 0.05), while the iMDD group showed reduced connectivity compared to HC and ID groups (P < 0.05). In the left insula, reduced connectivity with the right medial superior frontal gyrus was observed across patient groups compared to HC (P < 0.05), with the iMDD group showing increased connectivity compared to MDD (P < 0.05). Moreover, alterations in functional connectivity between the left thalamus and left temporal pole were found in iMDD compared to HC and MDD (P < 0.05). Correlation analyses revealed associations between abnormal connectivity and symptom severity in MDD and ID groups. Our findings demonstrate distinct patterns of altered functional connectivity in individuals with MDD, ID, and iMDD compared to healthy controls. These findings contribute to a better understanding of the pathophysiology of depression and insomnia, which could be used as a reference for the diagnosis and treatments of these patients.

Graph Analysis of the Visual Cortical Network during Naturalistic Movie Viewing Reveals Increased Integration and Decreased Segregation Following Mild TBI.

Traditional neuroimaging methods have identified alterations in brain activity patterns following mild traumatic brain injury (mTBI), particularly during rest, complex tasks, and normal vision. However, studies using graph theory to examine brain network changes in mTBI have produced varied results, influenced by the specific networks and task demands analyzed. In our study, we employed functional MRI to observe 17 mTBI patients and 54 healthy individuals as they viewed a simple, non-narrative underwater film, simulating everyday visual tasks. This approach revealed significant mTBI-related changes in network connectivity, efficiency, and organization. Specifically, the mTBI group exhibited higher overall connectivity and local network specialization, suggesting enhanced information integration without overwhelming the brain's processing capabilities. Conversely, these patients showed reduced network segregation, indicating a less compartmentalized brain function compared to healthy controls. These patterns were consistent across various visual cortex subnetworks, except in primary visual areas. Our findings highlight the potential of using naturalistic stimuli in graph-based neuroimaging to understand brain network alterations in mTBI and possibly other conditions affecting brain integration.

Abnormal dynamic functional connectivity in young nondisabling intracerebral hemorrhage patients.

Previous resting-state functional magnetic resonance imaging studies on intracerebral hemorrhage patients have focused more on the static characteristics of brain activity, while the time-varying effects during scanning have received less attention. Therefore, the current study aimed to explore the dynamic functional network connectivity changes of intracerebral hemorrhage patients. Using independent component analysis, the sliding window approach, and the k-means clustering analysis method, different dynamic functional network connectivity states were detected from resting-state functional magnetic resonance imaging data of 37 intracerebral hemorrhage patients and 44 healthy controls. The inter-group differences in dynamic functional network connectivity patterns and temporal properties were investigated, followed by correlation analyses between clinical scales and abnormal functional indexes. Ten resting-state networks were identified, and the dynamic functional network connectivity matrices were clustered into four different states. The transition numbers were decreased in the intracerebral hemorrhage patients compared with healthy controls, which was associated with trail making test scores in patients. The cerebellar network and executive control network connectivity in State 1 was reduced in patients, and this abnormal dynamic functional connectivity was positively correlated with the animal fluency test scores of patients. The current study demonstrated the characteristics of dynamic functional network connectivity in intracerebral hemorrhage patients and revealed that abnormal temporal properties and functional connectivity may be related to the performance of different cognitive domains after ictus. These results may provide new insights into exploring the neurocognitive mechanisms of intracerebral hemorrhage.

Non-trivial relationship between behavioral avalanches and internal neuronal dynamics in a recurrent neural network.

Neuronal activity gives rise to behavior, and behavior influences neuronal dynamics, in a closed-loop control system. Is it possible then, to find a relationship between the statistical properties of behavior and neuronal dynamics? Measurements of neuronal activity and behavior have suggested a direct relationship between scale-free neuronal and behavioral dynamics. Yet, these studies captured only local dynamics in brain sub-networks. Here, we investigate the relationship between internal dynamics and output statistics in a mathematical model system where we have access to the dynamics of all network units. We train a recurrent neural network (RNN), initialized in a high-dimensional chaotic state, to sustain behavioral states for durations following a power-law distribution as observed experimentally. Changes in network connectivity due to training affect the internal dynamics of neuronal firings, leading to neuronal avalanche size distributions approximating power-laws over some ranges. Yet, randomizing the changes in network connectivity can leave these power-law features largely unaltered. Specifically, whereas neuronal avalanche duration distributions show some variations between RNNs with trained and randomized decoders, neuronal avalanche size distributions are invariant, in the total population and in output-correlated sub-populations. This is true independent of whether the randomized decoders preserve power-law distributed behavioral dynamics. This demonstrates that a one-to-one correspondence between the considered statistical features of behavior and neuronal dynamics cannot be established and their relationship is non-trivial. Our findings also indicate that statistical properties of the intrinsic dynamics may be preserved, even as the internal state responsible for generating the desired output dynamics is perturbed.

Gamma oscillations induced by 40-Hz visual-auditory stimulation for the treatment of acute-phase limb motor rehabilitation after stroke: study protocol for a prospective randomized controlled trial

BackgroundThe incidence of hemiparetic limb dysfunction reaches 85% in stroke patients, emerging as a critical factor influencing their daily lives. However, the effectiveness of current rehabilitation treatments is considerably limited, particularly in patients with upper extremity impairment. This study aims to conduct a prospective clinical trial to validate the safety and effectiveness of gamma oscillations induced by 40-Hz visual-auditory stimulation in treating post-stroke upper limb dysfunction and to explore the relevant mechanisms.MethodsThis trial is a prospective, randomized controlled, double-blind study. All enrolled patients were randomly assigned to two groups. The experimental group received intervention through 40-Hz visual-auditory stimulation, while the control group underwent intervention with randomly matched visual-auditory stimulation frequencies. The primary efficacy endpoint is the change in motor function. Secondary efficacy endpoints include motor-evoked potentials, cerebral hemodynamic changes, neural network connectivity, and alterations in synaptic-related genes. Safety evaluation included major adverse events, all-cause mortality, and photosensitive epilepsy. Assessments will be conducted at baseline, after a 14-day treatment period, and during subsequent follow-up visits (at 3 and 6 months) post-treatment. The differences between the two groups will be compared.DiscussionThis study will evaluate the safety and efficacy of gamma oscillations induced by 40-Hz visual-auditory stimulation in treating patients with upper extremity dysfunction after an acute cerebral stroke. Concurrently, we will explore potential mechanisms, including changes in synaptic-related genes and neural network connectivity. This trial is expected to provide evidence for the effectiveness of this new technique in treating upper extremity dysfunction after a stroke and improving patients’ quality of life.Trial registrationThe study protocol has been registered with the Chinese Clinical Trial Registry (ChiCTR) under registration number ChiCTR2300076579 on October 12, 2023.

Changes in the land-use landscape pattern and ecological network of Xuzhou planning area

Ongoing rapid urbanization has triggered significant changes in land use, rendering landscape patterns adversely impacted and certain habitat patches degraded. Ecological networks have consequently contracted overall. As such, an investigation into how land-use landscape patterns and ecological networks change over time and space is of major significance for ecological restoration and regional sustainability. Taking Xuzhou Planning Area as a case study, we examined spatiotemporal changes and features of the landscape pattern by employing the land-use change degree, the land-use transition matrix, and quantified landscape pattern indices. An ecological network analysis, which studies the changes in network connectivity and robustness, as well as their causes and contributors, was undertaken to probe into the features and trends of spatiotemporal changes in the land-use landscape pattern and ecological network amid expeditious urbanization. Analysis results unveiled the following: (1) From 1985 to 2020, there was a decline in the area of farmland, forest, and grassland, accompanied by an increase in land for construction, water bodies, and unused land. The southwestern research area witnessed farmland substantially give way to land for construction for this period, and the most dramatic change in land use occurred between 2000 and 2010. (2) The area of dominant patches in the research area shrank, along with more fragmented, complex landscapes. The land for construction was emerging as the dominant landscape by area, whereas patches of farmland, forest, grassland, and water bodies became less connected. (3) The ecological network was densely linked in the northeast, with sparser connections in the southwest. Spatial shrinkage was observed in the research area’s southwestern and central ecological corridors. Overall, the number of ecological sources and corridors rose and subsequently dropped before a rebound. (4) The ecological network grew more connected and robust from 1985 through 1990, as portions of farmland were converted into water bodies, which led to an increase in ecological sources. Given a reduction in ecological sources and corridors in the southwestern and central regions between 1990 and 2010, network connectivity and robustness declined, which was reversed from 2010 onward with the addition of two ecological sources—Pan’an Lake and Dugong Lake. With an optimal ecological network in 1990, however, it deteriorated significantly by 2010. The research area saw the minimum value of its network connectivity indices of network stability index (α), evenness index (β), and connectivity index (γ), in 2010, when its ecological network was highly fragmented and vulnerable, attributing to a strong contrast between the maximal connected subgraph’s relative size and connectivity robustness. The research findings can lay scientific groundwork for addressing ecological issues, restoring landscape patterns, and developing ecological networks amid urbanization.

Frequency modulation increases the specificity of time-resolved connectivity: A resting-state fMRI study

Abstract Representing data using time-resolved networks is valuable for analyzing functional data of the human brain. One commonly used method for constructing time-resolved networks from data is sliding window Pearson correlation (SWPC). One major limitation of SWPC is that it applies a high-pass filter to the activity time series. Therefore, if we select a short window (desirable to estimate rapid changes in connectivity), we will remove important low-frequency information. Here, we propose an approach based on single sideband modulation (SSB) in communication theory. This allows us to select shorter windows to capture rapid changes in the time-resolved functional network connectivity (trFNC). We use simulation and real resting-state functional magnetic resonance imaging (fMRI) data to demonstrate the superior performance of SSB+SWPC compared to SWPC. We also compare the recurring trFNC patterns between individuals with the first episode of psychosis (FEP) and typical controls (TC) and show that FEPs stay more in states that show weaker connectivity across the whole brain. A result exclusive to SSB+SWPC is that TCs stay more in a state with negative connectivity between sub-cortical and cortical regions. Based on all the results, we argue that SSB+SWPC is more sensitive for capturing temporal variation in trFNC.

Neural Oscillations and Functional Significances for Prioritizing Dual-Task Walking in Parkinson's Disease.

Task prioritization involves allocating brain resources in a dual-task scenario, but the mechanistic details of how prioritization strategies affect dual-task walking performance for Parkinson's disease (PD) are little understood. We investigated the performance benefits and corresponding neural signatures for people with PD during dual-task walking, using gait-prioritization (GP) and manual-prioritization (MP) strategies. Participants (N = 34) were asked to hold two inter-locking rings while walking and to prioritize either taking big steps (GP strategy) or separating the two rings (MP strategy). Gait parameters and ring-touch time were measured, and scalp electroencephalograph was performed. Compared with the MP strategy, the GP strategy yielded faster walking speed and longer step length, whereas ring-touch time did not significantly differ between the two strategies. The MP strategy led to higher alpha (8-12 Hz) power in the posterior cortex and beta (13-35 Hz) power in the left frontal-temporal area, but the GP strategy was associated with stronger network connectivity in the beta band. Changes in walking speed and step length because of prioritization negatively correlated with changes in alpha power. Prioritization-related changes in ring-touch time correlated negatively with changes in beta power but positively with changes in beta network connectivity. A GP strategy in dual-task walking for PD can enhance walking speed and step length without compromising performance in a secondary manual task. This strategy augments attentional focus and facilitates compensatory reinforcement of inter-regional information exchange.

Increased functional connectivity between default mode network and visual network potentially correlates with duration of residual dizziness in patients with benign paroxysmal positional vertigo.

To assess changes in static and dynamic functional network connectivity (sFNC and dFNC) and explore their correlations with clinical features in benign paroxysmal positional vertigo (BPPV) patients with residual dizziness (RD) after successful canalith repositioning maneuvers (CRM) using resting-state fMRI. We studied resting-state fMRI data from 39 BPPV patients with RD compared to 38 BPPV patients without RD after successful CRM. Independent component analysis and methods of sliding window and k-means clustering were adopted to investigate the changes in dFNC and sFNC between the two groups. Additionally, temporal features and meta-states were compared between the two groups. Furthermore, the associations between fMRI results and clinical characteristics were analyzed using Pearson's partial correlation analysis. Compared with BPPV patients without RD, patients with RD had longer duration of BPPV and higher scores of dizziness handicap inventory (DHI) before successful CRM. BPPV patients with RD displayed no obvious abnormal sFNC compared to patients without RD. In the dFNC analysis, patients with RD showed increased FNC between default mode network (DMN) and visual network (VN) in state 4, the FNC between DMN and VN was positively correlated with the duration of RD. Furthermore, we found increased mean dwell time (MDT) and fractional windows (FW) in state 1 but decreased MDT and FW in state 3 in BPPV patients with RD. The FW of state 1 was positively correlated with DHI score before CRM, the MDT and FW of state 3 were negatively correlated with the duration of BPPV before CRM in patients with RD. Additionally, compared with patients without RD, patients with RD showed decreased number of states and state span. The occurrence of RD might be associated with increased FNC between DMN and VN, and the increased FNC between DMN and VN might potentially correlate with the duration of RD symptoms. In addition, we found BPPV patients with RD showed altered global meta-states and temporal features. These findings are helpful for us to better understand the underlying neural mechanisms of RD and potentially contribute to intervention development for BPPV patients with RD.

Traumatic brain injury disrupts state-dependent functional cortical connectivity in a mouse model.

Traumatic brain injury (TBI) is the leading cause of death in young people and can cause cognitive and motor dysfunction and disruptions in functional connectivity between brain regions. In human TBI patients and rodent models of TBI, functional connectivity is decreased after injury. Recovery of connectivity after TBI is associated with improved cognition and memory, suggesting an important link between connectivity and functional outcome. We examined widespread alterations in functional connectivity following TBI using simultaneous widefield mesoscale GCaMP7c calcium imaging and electrocorticography (ECoG) in mice injured using the controlled cortical impact (CCI) model of TBI. Combining CCI with widefield cortical imaging provides us with unprecedented access to characterize network connectivity changes throughout the entire injured cortex over time. Our data demonstrate that CCI profoundly disrupts functional connectivity immediately after injury, followed by partial recovery over 3weeks. Examining discrete periods of locomotion and stillness reveals that CCI alters functional connectivity and reduces theta power only during periods of behavioral stillness. Together, these findings demonstrate that TBI causes dynamic, behavioral state-dependent changes in functional connectivity and ECoG activity across the cortex.

Modeling effects of variable preBotzinger Complex network topology and cellular properties on opioid-induced respiratory depression and recovery.

The pre-Botzinger complex (preBotC), located in the medulla, is the essential rhythm-generating neural network for breathing. The actions of opioids on this network impair its ability to generate robust, rhythmic output, contributing to life-threatening opioid-induced respiratory depression (OIRD).The occurrence of OIRD varies across individuals and internal and external states, increasing the risk of opioid use, yet the mechanisms of this variability are largely unknown. In this study, we utilize a computational model of the preBotC to perform several in silico experiments exploring how differences in network topology and the intrinsic properties of preBotC neurons influence the sensitivity of the network rhythm to opioids. We find that rhythms produced by preBotC networks in silico exhibit variable responses to simulated opioids, similar to the preBotC network in vitro. This variability is primarily due to random differences in network topology and can be manipulated by imposed changes in network connectivity and intrinsic neuronal properties. Our results identify features of the preBootC network that may regulate its susceptibility to opioids.Significance Statement The neural network in the brainstem that generates the breathing rhythm is disrupted by opioid drugs. However, this response can be surprisingly unpredictable. By constructing computational models of this rhythm-generating network, we illustrate how random differences in the distribution of biophysical properties and connectivity patterns within individual networks can predict their response to opioids, and we show how modulation of these network features can make breathing more susceptible or resistant to the effects of opioids.

CHANGES IN FUNCTIONAL CONNECTIVITY FOLLOWING INTENSIVE ATTENTION TRAINING IN PATIENTS WITH TRAUMATIC BRAIN INJURY. A PILOT STUDY.

To explore functional connectivity after intensive attention training in the chronic phase after traumatic brain injury as clinical evidence indicates that intensive attention training improves attention dysfunction in persons with traumatic brain injury. A case series study. Two young adults, 13- and 18-months post traumatic brain injury, with traumatic brain injury induced attention deficits were assigned to 20 h of intensive attention training and neuroimaging. Functional magnetic resonance imaging during a psychomotor vigilance test was conducted pre- and post-intervention. The neuroimaging indicated both increased and decreased connectivity density in frontal, posterior and subcortical brain regions, for some regions with separate change patterns for left and right hemisphere respectively, and an overall reduction in variability in functional connectivity. The changed and decreased variability of functional connectivity in various brain regions, captured by fMRI during a psychomotor vigilance test after direct attention training in a small sample of persons with traumatic brain injury, suggests further studies of functional connectivity changes in neural networks.

Resting state functional connectivity differences following working memory training with massed exposure in individuals with public speaking anxiety

Exposure-based cognitive behavioral therapy (CBT) is a gold standard treatment for Social Anxiety Disorder (SAD), but many patients do not gain complete symptom relief. Since fear extinction is central to the effectiveness of exposure within CBT, adjunctive treatments that target neurocognitive systems underlying fear extinction could increase the effectiveness of CBT. Successful fear extinction and cognitive tasks like working memory share neurocognitive substrates. The present study evaluates the neural impact of working memory training (WMT) as an adjunctive CBT treatment by exploring changes in intrinsic network connectivity associated with combining WMT with exposure exercises. The sample included twenty-four adults (Mean Age = 27.42(9.75), 62.5% female) with elevated social anxiety symptoms. Participants completed either a WMT or sham training (ST) condition, followed by a speech-based massed exposure session (WMT+Exp versus ST+Exp). Compared to ST+Exp, WMT+Exp participants exhibited lower connectivity between the default and visual networks and visual and dorsal networks. Lower connectivity between these networks was associated with lower subjective distress at the end of the massed exposure across the whole sample. WMT+Exp completers exhibited unique functional connectivity between the frontoparietal and dorsal attention networks. WM+Exp was associated with a neural connectivity profile involving networks critical to working memory, fear learning, and emotion regulation, as well as emotional and sensory processing functions. Data provisionally point to combined working memory training and exposure facilitating improvement in neural connections useful for benefitting from CBT for SAD.

Connecting the dots: Motor and default mode network crossroads in post-stroke motor learning deficits

BackgroundStrokes frequently result in long-term motor deficits, imposing significant personal and economic burdens. However, our understanding of the underlying neural mechanisms governing motor learning in stroke survivors remains limited - a fact that poses significant challenges to the development and optimisation of therapeutic strategies. ObjectiveThis study investigates the diversity in motor learning aptitude and its associated neurological mechanisms. We hypothesised that stroke patients exhibit compromised overall motor learning capacity, which is associated with altered activity and connectivity patterns in the motor- and default-mode-network in the brain. MethodsWe assessed a cohort of 40 chronic-stage, mildly impaired stroke survivors and 39 age-matched healthy controls using functional Magnetic Resonance Imaging (fMRI) and connectivity analyses. We focused on neural activity and connectivity patterns during an unilateral motor sequence learning task performed with the unimpaired or non-dominant hand. Primary outcome measures included task-induced changes in neural activity and network connectivity. ResultsCompared to controls, stroke patients showed significantly reduced motor learning capacity, associated with diminished cerebral lateralization. Task induced activity modulation was reduced in the motor network but increased in the default mode network. The modulated activation strength was associated with an opposing trend in task-induced functional connectivity, with increased connectivity in the motor network and decreased connectivity in the DMN. ConclusionsStroke patients demonstrate altered neural activity and connectivity patterns during motor learning with their unaffected hand, potentially contributing to globally impaired motor learning skills. The reduced ability to lateralize cerebral activation, along with the enhanced connectivity between the right and left motor cortices in these patients, may signify maladaptive neural processes that impede motor adaptation, possibly affecting long-term rehabilitation post-stroke. The contrasting pattern of activity modulation and connectivity alteration in the default mode network suggests a nuanced role of this network in post-stroke motor learning. These insights could have significant implications for the development of customised rehabilitation strategies for stroke patients.

Creativity Stimulation by Idea Generation: A Resting-state fMRI Study on Effective Connectivity

Studies on creativity have bloomed in the past decade. However, little is known about the effective connectivity (EC) between default-mode network (DMN) regions after creativity stimulation. This study aimed to measure the brain connectivity induced by creativity stimulation and to relate it with creativity score. A total of 50 participants were recruited and assigned to control and experimental groups. The experimental participants underwent a two-day creativity stimulation session. Resting state functional magnetic resonance imaging (rs-fMRI) scans were performed on all participants after the session. The rs-fMRI data were analysed using statistical parametric mapping and spectral dynamic causal modelling. A fully connected model comprising angular gyrus (AG), medial pre-frontal cortex (mPFC) and pre-cuneus (PCU) as regions-of-interest (ROIs) was fitted for every participant’s data. The model underwent Bayesian parameter averaging to determine the average strength of connection between ROIs. There was a significant increase in creativity score for the experimental group in the aspect of fluency (p=0.018) and flexibility (p=0.048) except in originality (p&gt;0.05). No difference in brain activation was observed between groups. All the EC between ROIs in the left and right hemisphere for both groups were significant (P&gt;0.9). Symmetrical EC networks for the experimental group were observed with left hemisphere PCU→PCU, PCU→mPFC and AG→PCU connections which were more significant in the experimental group. These findings suggested that creativity stimulation as short as two days was able to evoke changes in creativity score and network connectivity but insufficient to cause convincing differences in the brain activation.

Longitudinal resting-state network connectivity changes in electroconvulsive therapy patients compared to healthy controls

ObjectiveElectroconvulsive therapy (ECT) is effective for major depressive episodes. Understanding of underlying mechanisms has been increased by examining changes of brain connectivity but studies often do not correct for test-retest variability in healthy controls (HC). In this study, we investigated changes in resting-state networks after ECT in a multicenter study. MethodsFunctional resting-state magnetic resonance imaging data, acquired before start and within one week after ECT, from 90 depressed patients were analyzed, as well as longitudinal data of 24 HC. Group-information guided independent component analysis (GIG-ICA) was used to spatially restrict decomposition to twelve canonical resting-state networks. Selected networks of interest were the default mode network (DMN), salience network (SN), and left and right frontoparietal network (LFPN, and RFPN). Whole-brain voxel-wise analyses were used to assess group differences at baseline, group by time interactions, and correlations with treatment effectiveness. In addition, between-network connectivity and within-network strengths were computed. ResultsWithin-network strength of the DMN was lower at baseline in ECT patients which increased after ECT compared to HC, after which no differences were detected. At baseline, ECT patients showed lower whole-brain voxel-wise DMN connectivity in the precuneus. Increase of within-network strength of the LFPN was correlated with treatment effectiveness. We did not find whole-brain voxel-wise or between-network changes. ConclusionDMN within-network connectivity normalized after ECT. Within-network increase of the LFPN in ECT patients was correlated with higher treatment effectiveness. In contrast to earlier studies, we found no whole-brain voxel-wise changes, which highlights the necessity to account for test-retest effects.

Resting‐state network connectivity changes in prodromal stage of Alzheimer’s disease

AbstractBackgroundAlzheimer Disease (AD), the most common type of dementia, is accompanied by a generalized loss of neurons and cause severe changes in brain’s structure and function. Mild Cognitive Impairment is associated with a higher risk of developing dementia. This clinical classification is particularly relevant because each subtype is linked to a presumed etiology, with the amnestic subtypes (aMCI) considered as a prodromal form of AD (Petersen et al., 2009, 2014). Resting state fMRI functional connectivity (FCrs‐fMRI) analysis is broadly used to detect brain network differences in neurodegenerative diseases such as AD.MethodForty‐five participants were evaluated: patients with aMCI (n = 17), patients with dementia due to AD (n = 14) and healthy controls (HC) (n = 14). All participants received an extensive neuropsychological battery and brain MRI scanning. Resting state functional scans consisted of 240 T2*‐weighted echo planar imaging volumes (repetition time 3000 ms; echo time 60 ms; ip angle 90°; 32 axial slices; matrix 64×64; voxel size 3.3×3.4×4 mm). Additionally, a high‐resolution T1‐weighted magnetization prepared rapid acquisition gradient echo image was acquired. Data analyses were performed using the Functional Connectivity Toolbox (CONN) for Matlab (https://www.nitrc.org/frs/) to identify large‐scale patterns of temporal signal‐intensity coherence, interpreted as functional connectivity (Beckmann et al., 2005). Regions of interests (ROIs) analysis was performed for each participants and among group. Spatial maps of the group independent component analysis were used in a linear model t against each individual fMRI data set.ResultThe Default Mode Network (DMN) showed two regions of lower functional connectivity (FC) in AD when comparing with HC within the precuneus (p&lt;0.001 uncorrected). No regions of FC changes were found in the DMN when comparing aMCI with HC or AD.ConclusionThe changes in FC rsfMRI in adults with AD are specifically related to regions of the DMN.

Interventional clinical trial findings from targeted multiday repetitive transcranial magnetic stimulation to treat memory loss in amnestic mild cognitive impairment

AbstractBackgroundMemory loss is the hallmark cognitive symptom of Alzheimer’s disease (AD), and it affects independence, autonomy, and identity. AD‐related memory deficits are associated with pathological changes in brain structure and function, and current treatments offer limited relief. Targeted repetitive transcranial magnetic stimulation (rTMS) of AD‐vulnerable intrinsic brain networks can enhance memory abilities in healthy adults (Wang et al., 2014). To test rTMS approaches as a potential treatment for clinical memory loss, we administered a local clinical trial (ClinicalTrials.gov #alz078533) that enrolled patients with amnestic mild cognitive impairment (aMCI), a frequent precursor to AD (target enrollment of 16). Here, we report cognitive and brain findings from our trial.MethodsPatients with aMCI completed two weeklong interventions consisting of pre‐stimulation brain and cognitive measurement, rTMS for five consecutive days, and post‐stimulation brain and cognitive measurement. Brain measures included structural and resting‐state functional MRI data; cognitive assessments included measures of memory function. Interventions were identically formatted except for rTMS intensity (treatment/sham). Stimulation used β‐frequency pulse sequences which alternated 2‐sec. 20 Hz stimulation with 28‐sec. rest for 20 min (1600 pulses); stimulation location was a left lateral parietal cortex location coactive with a hippocampus‐centered functional network. Stimulation intensity varied with each participant’s resting motor threshold (treatment, 100%; sham, 10%). Condition order was counterbalanced.ResultsWe identified hippocampus‐centered networks in each participant, then localized parietal rTMS targets. Critically, we observed changes in brain and cognitive (memory) measures in the treatment‐intensity condition that were not observed in the sham‐intensity condition. Furthermore, we observed changes in intrinsic network connectivity within the stimulated hippocampus‐centered network.ConclusionsOur trial of patients with aMCI measured changes in brain and cognitive variables after rTMS of a brain network supporting memory processes. We found evidence consistent with neural plasticity, and we frequently observed memory improvement in patients with aMCI after treatment‐intensity rTMS. Our findings suggest that rTMS can improve memory in clinical populations. This is important because, counterintuitively, new disease modifying therapies for AD may increase need for symptomatic treatment of memory loss due to prolongation of prodromal/mild stages of AD. Thus, adjuvant therapies such as rTMS for memory loss could improve AD treatment outcomes.

Interventional clinical trial findings from targeted multiday repetitive transcranial magnetic stimulation to treat memory loss in amnestic mild cognitive impairment

AbstractBackgroundMemory loss is the hallmark cognitive symptom of Alzheimer’s disease (AD), and it affects independence, autonomy, and identity. AD‐related memory deficits are associated with pathological changes in brain structure and function, and current treatments offer limited relief. Targeted repetitive transcranial magnetic stimulation (rTMS) of AD‐vulnerable intrinsic brain networks can enhance memory abilities in healthy adults (Wang et al., 2014). To test rTMS approaches as a potential treatment for clinical memory loss, we administered a local clinical trial (ClinicalTrials.gov #alz081816) that enrolled patients with amnestic mild cognitive impairment (aMCI), a frequent precursor to AD (target enrollment of 16). Here, we report cognitive and brain findings from our trial.MethodPatients with aMCI completed two weeklong interventions consisting of pre‐stimulation brain and cognitive measurement, rTMS for five consecutive days, and post‐stimulation brain and cognitive measurement. Brain measures included structural and resting‐state functional MRI data; cognitive assessments included measures of memory function. Interventions were identically formatted except for rTMS intensity (treatment/sham). Stimulation used ß‐frequency pulse sequences which alternated 2‐sec. 20 Hz stimulation with 28‐sec. rest for 20 min (1600 pulses); stimulation location was a left lateral parietal cortex location coactive with a hippocampus‐centered functional network. Stimulation intensity varied with each participant’s resting motor threshold (treatment, 100%; sham, 10%). Condition order was counterbalanced.ResultWe identified hippocampus‐centered networks in each participant, then localized parietal rTMS targets. Critically, we observed changes in brain and cognitive (memory) measures in the treatment‐intensity condition that were not observed in the sham‐intensity condition. Furthermore, we observed changes in intrinsic network connectivity within the stimulated hippocampus‐centered network.ConclusionOur trial of patients with aMCI measured changes in brain and cognitive variables after rTMS of a brain network supporting memory processes. We found evidence consistent with neural plasticity, and we frequently observed memory improvement in patients with aMCI after treatment‐intensity rTMS. Our findings suggest that rTMS can improve memory in clinical populations. This is important because, counterintuitively, new disease modifying therapies for AD may increase need for symptomatic treatment of memory loss due to prolongation of prodromal/mild stages of AD. Thus, adjuvant therapies such as rTMS for memory loss could improve AD treatment outcomes.