Predicting memory in preclinical AD from resting‐state functional connectivity

BackgroundPatients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) show functional and structural connectivity alterations in the default mode network (DMN) while cerebrovascular disease (CeVD) shows functional and structural connectivity changes in the executive control network (ECN). Such disruptions are associated with memory and executive function impairment, respectively. Concurrent AD and CeVD pathology is associated with a higher rate of cognitive decline and differential neurodegenerative patterns. Together, such findings are likely reflective of different underlying pathology in AD with and without CeVD. However, few studies have examined the effect of CeVD on network functional connectivity (task-free functional magnetic resonance imaging (fMRI)) and structural connectivity (diffusion MRI) of the DMN and ECN in aMCI and AD using a hypothesis-driven multiple seed-based approach.MethodsWe examined functional and structural connectivity network changes in 39 aMCI, 50 aMCI+CeVD, 47 AD, 47 AD+CeVD, and 65 healthy controls (HCs) and their associations with cognitive impairment in the executive/attention and memory domains.ResultsWe demonstrate divergent DMN and ECN functional connectivity changes in CeVD and non-CeVD subjects. Compared with controls, intra-DMN hippocampal functional connectivity reductions were observed in both AD and AD+CeVD, while intra-DMN parietal and medial prefrontal-parietal functional connectivity was higher in AD+CeVD and aMCI+CeVD, but lower in AD. Intra-ECN frontal functional connectivity increases and fronto-parietal functional connectivity decreases occurred in CeVD but not non-CeVD subjects. Such functional connectivity alterations were related with cognitive impairment in a dissociative manner: intra-DMN functional connectivity changes were associated with worse cognition primarily in non-CeVD groups, while intra-ECN functional connectivity changes were associated with worse cognition primarily in CeVD groups. Additionally, CeVD and non-CeVD groups showed overlapping and distinct alterations in inter-network DMN-ECN functional connectivity depending on disease severity. In contrast to functional connectivity, CeVD groups had greater network structural connectivity damage compared with non-CeVD groups in both aMCI and AD patients. Network structural connectivity damage was associated with worse cognition.ConclusionsWe demonstrate differential functional and structural network changes between aMCI and AD patients with and without CeVD through diverging and deleterious network-based degeneration underlying domain-specific cognitive impairment.

Deficits in the hippocampus are a consistent finding in schizophrenia and have also been demonstrated in early-stage psychosis. Moreover, alterations in hippocampal anatomy and connectivity have been implicated in aberrant functional interactions in subcortical and cortical networks. However, the nature and extent of these alterations and their association with frontal and subcortical regions remain unclear. To address these questions, we analysed resting state fMRI functional connectivity and graph properties in n = 93 individuals at clinical high-risk for psychosis (CHR-P), n = 26 patients with first-episode psychosis (FEP), n = 31 individuals with affective disorders and substance abuse as well as n = 58 healthy controls. We used novel denoising techniques and individually optimised functional connectivity matrices, which were compared across clinical groups. Finally, the centrality of the hippocampus as well as network segregation and integration were assessed using graph-based analysis. Both the FEP and CHR-P groups were characterised by reduced functional connectivity between the hippocampus and inferior frontal cortex albeit the differences in CHR-P individuals did not survive corrections for multiple comparisons. Compared to CHR-P, FEP show lower centrality of the hippocampus but increased network segregation. Our findings show lower connectivity between the hippocampus and frontal cortex in early-stage psychosis, with FEP patients showing stronger decreases in connectivity compared to CHR-Ps. Furthermore, network-based analyses highlight reduced centrality in FEPs compared to CHR-Ps, indicating reduced influence on the wider network. Thus, altered connectivity along the hippocampal-frontal axis could be a potential marker of illness stage in early-stage psychosis.

Altered brain functional connectivity and correlation with psychological status in patients with unilateral pulsatile tinnitus

Subregion-specific, modality-dependent and timescale-sensitive hippocampal connectivity alterations in patients with first-episode, drug-naïve major depression disorder

Developmental malformations (dysgenesis) of the corpus callosum lead to neurological conditions with a broad range of clinical presentations. Investigating the altered brain connectivity patterns is crucial to understanding both adaptive and maladaptive neuroplasticity in corpus callosum dysgenesis patients. Here, we acquired structural diffusion-weighted and resting-state functional MRI data from a cohort of 11 corpus callosum dysgenesis patients (five with agenesis and six with hypoplasia) and compared their structural and functional connectivity patterns to healthy subjects selected from the Human Connectome Project. We found that these patients have fewer structural inter- and intra-hemispheric brain connections relative to healthy controls. Interestingly, the patients with callosal agenesis have a scant number of inter-hemispheric connections but manage to maintain the full integrity of functional connectivity between the same cortical regions as the healthy subjects. On the other hand, the hypoplasic group presented abnormal structural and functional connectivity patterns relative to healthy controls while maintaining the same total amount of functional connections. These results demonstrate that acallosal patients can compensate for having fewer structural brain connections and present functional adaptation. However, hypoplasics present atypical structural connections to different brain regions, leading to entirely new and abnormal functional brain connectivity patterns.

White matter (WM) has traditionally been considered structurally important but functionally inert in fMRI research. However, growing evidence indicates that WM exhibits meaningful BOLD fluctuations and participates in functional connectivity. Here, we investigate alterations in WM functional network connectivity (FNC) across the Alzheimer's disease (AD) spectrum using resting-state fMRI data from the Alzheimer's Disease Neuroimaging Initiative (ADNI; 415 cognitively normal (CN), 283 mild cognitive impairment (MCI), 91 AD). We applied a guided independent component analysis (ICA) approach based on a combined multiscale template including 202 intrinsic connectivity networks [ICNs; 97 WM, 105 gray matter (GM)] to estimate subject-specific timecourses and compute FNC. Group differences in WM-WM, GM-GM, and WM-GM functional network connectivity (AD-CN, AD-MCI, MCI-CN) were evaluated using two-sample t-tests on residual FNC values for age, sex, and mean framewise displacement. Multiple comparisons across edges were controlled using false discovery rate correction (q < 0.05), and effect sizes were quantified using Hedges' g. Results showed robust alterations in WM-WM and WM-GM connectivity in AD, particularly involving WM subcortical, frontal, sensorimotor, and occipitotemporal networks. Several WM-GM interactions with cerebellar and hippocampal GM networks were also disrupted, including reduced GM-cerebellar: WM-frontal coupling and increased GM-hippocampal: WM-frontal connectivity. Notably, MCI already showed WM-GM dysconnectivity relative to CN, suggesting that functional disruption of WM circuits emerges prior to overt dementia. These findings provide converging evidence that WM functional connectivity is both measurable and selectively altered across the AD continuum. Our findings support WM FNC as a candidate biomarker to GM-based measures for staging and monitoring AD. Together, these results position WM-GM dysconnectivity as an important systems-level signature of the AD continuum and support WM functional network connectivity as a promising complement to established GM-based measures for understanding disease progression.

Low back pain (LBP) is a prevalent pain condition whose persistence can lead to changes in the brain regions responsible for sensory, cognitive, attentional, and emotional processing. Previous neuroimaging studies have identified various structural and functional abnormalities in patients with LBP; however, how the static and dynamic large-scale functional network connectivity (FNC) of the brain is affected in these patients remains unclear. Forty-one patients with chronic low back pain (cLBP) and 42 healthy controls underwent resting-state functional MRI scanning. The independent component analysis method was employed to extract the resting-state networks. Subsequently, we calculate and compare between groups for static intra- and inter-network functional connectivity. In addition, we investigated the differences between dynamic functional network connectivity and dynamic temporal metrics between cLBP patients and healthy controls. Finally, we tried to distinguish cLBP patients from healthy controls by support vector machine method. The results showed that significant reductions in functional connectivity within the network were found within the DMN,DAN, and ECN in cLBP patients. Significant between-group differences were also found in static FNC and in each state of dynamic FNC. In addition, in terms of dynamic temporal metrics, fraction time and mean dwell time were significantly altered in cLBP patients. In conclusion, our study suggests the existence of static and dynamic large-scale brain network alterations in patients with cLBP. The findings provide insights into the neural mechanisms underlying various brain function abnormalities and altered pain experiences in patients with cLBP.

Over the years, resting state functional magnetic resonance imaging (rsfMRI) has been a preferred design tool to analyze human brain functions and brain parcellations. Several different statistical methods have been proposed to study functional connectivity and generate various parcellation atlases based on corresponding connectivity maps. In this study, we employ a sliding window correlation method to generate accurate individual voxel-wise dynamic functional connectivity maps, based on which the brain can be parcellated into highly homogeneous functional parcels. Because there is no ground truth for functional brain parcellation, we accomplish parcellation via k-means clustering to compare with other available parcellations. With temporal characteristics of functional connectivity taken into consideration, high homogeneity can be observed in high resolution parcellation of human brain.

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.

Introduction:The human brain is a complex system consisting of connected nerve cells that adapt to and learn from the environment by changing its regional activities. The synchrony between these regional activities is called functional network changes during life and results in the learning of new skills. Time perception and interval discrimination are among the most necessary skills for the human being to perceive motions, coordinate motor functions, speak, and perform many cognitive functions. Despite its importance, the underlying mechanism of changes in brain functional connectivity patterns during learning time intervals still need to be well understood.Methods:This study aimed to show how electroencephalography (EEG) functional connectivity changes are associated with learning temporal intervals. In this regard, 12 healthy volunteers were trained with an auditory time-interval discrimination task over six days while their brain activities were recorded via EEG signals during the first and the last sessions. Then, changes in regional phase synchronization were calculated using the weighted/phase lag index (WPLI) approach, the most effective EEG functional connections at the temporal and prefrontal regions, and in the theta and beta bands frequency. In addition, the WPLI reported more accurate values.Results:The results showed that learning interval discrimination significantly changed functional connectivity in the prefrontal and temporal regions.Conclusion:These findings could shed light on a better understanding of the brain mechanism involved in time perception.HighlightsAccuracy of auditory interval discrimination improved by a six-day learning process.Most established connections were formed in the temporal, occipital and middle regions of brain.Creation of new significant connection was observed at the theta and gamma frequency bands.New neural networks are constructed between regions of the brain during interval learning.Plain Language SummaryThe time perception is a vital challenge that human beings face in various aspects of their lives. Researchers have always been challenged in how to calculate it and understand its mechanism for each individual. In the present study, which is based on the temporal perception, by comparing the timing of auditory stimuli, we seek to show the functional relationships of neural network formation related to learning temporal perception. Our aim was to understand how the hidden information of auditory stimuli (time intervals) is encoded in the content of the brain signals.

BackgroundThe extent to which pathological processes in aging and Alzheimer’s disease (AD) relate to functional disruption of the medial temporal lobe (MTL)‐dependent brain networks is poorly understood. To address this knowledge gap, we examined functional connectivity (FC) alterations between anterior and posterior regions of the MTL and in MTL‐associated functional communities – the Anterior‐Temporal (AT) and Posterior‐Medial (PM) networks – in normal agers, individuals with preclinical AD, and patients with Mild Cognitive Impairment or mild dementia due to AD.MethodIn this cross‐sectional study, we analyzed data from 179 individuals from the Aging Brain Cohort study of the Penn ADRC. Detailed information about participants is provided in Table 1. For intra‐MTL FC comparisons, the MTL subregions were segmented using the automated segmentation of hippocampal subfields‐T1 (ASHS‐T1) pipeline (Fig. 1a). When modeling the MTL’s interactions with the rest of the cortex, we employed four MTL ROIs (left/right × anterior/posterior) derived from an ex vivo atlas of tau accumulation in the MTL. Our functional datasets were preprocessed using a customized fMRIprep pipeline. Sparse network estimations and modularity‐based consensus clustering were used to reconstruct the AT and PM network systems (Fig. 1b). Age effect analyses and group comparisons along the AD continuum were performed using the General Linear Model within the network‐based statistical framework.ResultThe preclinical stage of AD was characterized by increased FC between the perirhinal cortex and other regions of the MTL, as well as between the anterior MTL and its direct neighbors in the AT network (Fig. 1c‐d). This effect was not present in symptomatic AD. Instead, symptomatic patients displayed reduced hippocampal and intra‐PM connectivity. For normal aging, our results led to three main conclusions (for visuals, see Fig. 2). First, intra‐network connectivity of both the AT and PM networks decreases with age. Second, FC between the anterior and posterior segments of the MTL declines with age. Finally, within the MTL, we observed greater vulnerability of the posterior MTL subregions, particularly the parahippocampal cortex, to age‐associated FC decline.ConclusionTogether, the current results provide evidence for aberrant connectivity in the preclinical stage of AD that may have implications for early AD pathophysiology.

BackgroundThe extent to which pathological processes in aging and Alzheimer’s disease (AD) relate to functional disruption of the medial temporal lobe (MTL)‐dependent brain networks is poorly understood. To address this knowledge gap, we examined functional connectivity (FC) alterations between anterior and posterior regions of the MTL and in MTL‐associated functional communities – the Anterior‐Temporal (AT) and Posterior‐Medial (PM) networks – in normal agers, individuals with preclinical AD, and patients with Mild Cognitive Impairment or mild dementia due to AD.MethodIn this cross‐sectional study, we analyzed data from 179 individuals from the Aging Brain Cohort study of the Penn ADRC. Detailed information about participants is provided in Table 1. For intra‐MTL FC comparisons, the MTL subregions were segmented using the automated segmentation of hippocampal subfields‐T1 (ASHS‐T1) pipeline (Fig. 1a). When modeling the MTL’s interactions with the rest of the cortex, we employed four MTL ROIs (left/right × anterior/posterior) derived from an ex vivo atlas of tau accumulation in the MTL. Our functional datasets were preprocessed using a customized fMRIprep pipeline. Sparse network estimations and modularity‐based consensus clustering were used to reconstruct the AT and PM network systems (Fig. 1b). Age effect analyses and group comparisons along the AD continuum were performed using the General Linear Model within the network‐based statistical framework.ResultsThe preclinical stage of AD was characterized by increased FC between the perirhinal cortex and other regions of the MTL, as well as between the anterior MTL and its direct neighbors in the AT network (Fig. 1c‐d). This effect was not present in symptomatic AD. Instead, symptomatic patients displayed reduced hippocampal and intra‐PM connectivity. For normal aging, our results led to three main conclusions (for visuals, see Fig. 2). First, intra‐network connectivity of both the AT and PM networks decreases with age. Second, FC between the anterior and posterior segments of the MTL declines with age. Finally, within the MTL, we observed greater vulnerability of the posterior MTL subregions, particularly the parahippocampal cortex, to age‐associated FC decline.ConclusionTogether, the current results provide evidence for aberrant connectivity in the preclinical stage of AD that may have implications for early AD pathophysiology.

To identify subgroups of people with internet gaming disorder (IGD) based on addiction-related resting-state functional connectivity and how these subgroups show different clinical correlates and responses to treatment. Secondary analysis of two functional magnetic resonance imaging (fMRI) data sets. Zhejiang province and Beijing, China. One hundred and sixty-nine IGD and 147 control subjects. k-Means algorithmic and support-vector machine-learning approaches were used to identify subgroups of IGD subjects. These groups were examined with respect to assessments of craving, behavioral activation and inhibition, emotional regulation, cue-reactivity and guessing-related measures. Two groups of subjects with IGD were identified and defined by distinct patterns of connectivity in brain networks previously implicated in addictions: subgroup 1 ('craving-related subgroup') and subgroup 2 ('mixed psychological subgroup'). Clustering IGD on this basis enabled the development of diagnostic classifiers with high sensitivity and specificity for IGD subgroups in 10-fold validation (n = 218) and out-of-sample replication (n = 98) data sets. Subgroup 1 is characterized by high craving scores, cue-reactivity during fMRI and responsiveness to a craving behavioral intervention therapy. Subgroup 2 is characterized by high craving, behavioral inhibition and activations scores, non-adaptive emotion-regulation strategies and guessing-task fMRI measures. Subgroups 1 and 2 showed largely opposite functional-connectivity patterns in overlapping networks. There appear to be two subgroups of people with internet gaming disorder, each associated with differing patterns of brain functional connectivity and distinct clinical symptom profiles and gender compositions.

Functional and structural brain networks in posterior cortical atrophy: A two-centre multiparametric MRI study.

Estimation of dynamic functional connectivity using Multiplication of Temporal Derivatives