Local Functional Connectivity Research Articles

Aberrant functional connectivity associated with drug response in patients with newly diagnosed epilepsy.

To analyze the local functional activity and connectivity features of the brain associated with drug response inpatients newly diagnosed with epilepsy (NDE) who are naïve to anti-seizure medication (ASM). Recruited patients, underwent functional magnetic resonance imaging at baseline, and were assigned to the well-controlled (WC, n = 28) or uncontrolled (UC, n = 11) groups based on their response to ASM. Healthy participants were included in the control group (HC, n = 29). The amplitudes of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) were used to measure local functional activity, and voxel-wise degree centrality (DC) and seed-based functional connectivity (FC) were used to evaluate the connecting intensity of the brain areas. Compared to the HC and WC groups, the UC group had higher ALFF values in the left posterior central gyrus (PoCG.L) and left inferior temporal gyrus (ITG.L) and higher DC in the bilateral PoCG (Gaussian random field correction, voxel-level P < 0.001, and cluster-level P < 0.05). Both PoCG and ITG.L in the UC group showed stronger FC with multiple brain regions, mainly located in the occipital and temporal lobes, compared to the HC or WC group, while the WC group showed decreased or similar FC compared to the HC group. Excessive enhancement of brain functional activity or connecting intensity in ASM-naïve patients with NDE may be associated with a higher risk of poor drug response.

Stability of transcranial magnetic stimulation electroencephalogram evoked potentials in pediatric epilepsy

Transcranial magnetic stimulation paired with electroencephalography (TMS–EEG) can measure local excitability and functional connectivity. To address trial-to-trial variability, responses to multiple TMS pulses are recorded to obtain an average TMS evoked potential (TEP). Balancing adequate data acquisition to establish stable TEPs with feasible experimental duration is critical when applying TMS–EEG to clinical populations. Here we aim to investigate the minimum number of pulses (MNP) required to achieve stable TEPs in children with epilepsy. Eighteen children with Self-Limited Epilepsy with Centrotemporal Spikes, a common epilepsy arising from the motor cortices, underwent multiple 100-pulse blocks of TMS to both motor cortices over two days. TMS was applied at 120% of resting motor threshold (rMT) up to a maximum of 100% maximum stimulator output. The average of all 100 pulses was used as a “gold-standard” TEP to which we compared “candidate” TEPs obtained by averaging subsets of pulses. We defined TEP stability as the MNP needed to achieve a concordance correlation coefficient of 80% between the candidate and “gold-standard” TEP. We additionally assessed whether experimental or clinical factors affected TEP stability. Results show that stable TEPs can be derived from fewer than 100 pulses, a number typically used for designing TMS-EEG experiments. The early segment (15–80 ms) of the TEP was less stable than the later segment (80–350 ms). Global mean field amplitude derived from all channels was less stable than local TEP derived from channels overlying the stimulated site. TEP stability did not differ depending on stimulated hemisphere, block order, or antiseizure medication use, but was greater in older children. Stimulation administered with an intensity above the rMT yielded more stable local TEPs. Studies of TMS-EEG in pediatrics have been limited by the complexity of experimental set-up and time course. This study serves as a critical starting point, demonstrating the feasibility of designing efficient TMS–EEG studies that use a relatively small number of pulses to study pediatric epilepsy and potentially other pediatric groups.

The contribution of EEG to assess and treat motor disorders in multiple sclerosis

ObjectiveElectroencephalography (EEG) can highlight significant changes in spontaneous electrical activity of the brain produced by altered brain network connectivity linked to inflammatory demyelinating lesions and neuronal loss occurring in multiple sclerosis (MS). In this review, we describe the main EEG findings reported in the literature to characterize motor network alteration in term of local activity or functional connectivity changes in patients with MS (pwMS). MethodsA comprehensive literature search was conducted to include articles with quantitative analyses of resting-state EEG recordings (spectrograms or advanced methods for assessing spatial and temporal dynamics, such as coherence, theory of graphs, recurrent quantification, microstates) or dynamic EEG recordings during a motor task, with or without connectivity analyses. ResultsIn this systematic review, we identified 26 original articles using EEG in the evaluation of MS-related motor disorders. Various resting or dynamic EEG parameters could serve as diagnostic biomarkers of motor control impairment to differentiate pwMS from healthy subjects or be related to a specific clinical condition (fatigue) or neuroradiological aspects (lesion load). ConclusionsWe highlight some key EEG patterns in pwMS at rest and during movement, both suggesting an alteration or disruption of brain connectivity, more specifically involving sensorimotor networks. SignificanceSome of these EEG biomarkers of motor disturbance could be used to design future therapeutic strategies in MS based on neuromodulation approaches, or to predict the effects of motor training and rehabilitation in pwMS.

A Local-Ascending-Global Learning Strategy for Brain-Computer Interface

Neuroscience research indicates that the interaction among different functional regions of the brain plays a crucial role in driving various cognitive tasks. Existing studies have primarily focused on constructing either local or global functional connectivity maps within the brain, often lacking an adaptive approach to fuse functional brain regions and explore latent relationships between localization during different cognitive tasks. This paper introduces a novel approach called the Local-Ascending-Global Learning Strategy (LAG) to uncover higher-level latent topological patterns among functional brain regions. The strategy initiates from the local connectivity of individual brain functional regions and develops a K-Level Self-Adaptive Ascending Network (SALK) to dynamically capture strong connectivity patterns among brain regions during different cognitive tasks. Through the step-by-step fusion of brain regions, this approach captures higher-level latent patterns, shedding light on the progressively adaptive fusion of various brain functional regions under different cognitive tasks. Notably, this study represents the first exploration of higher-level latent patterns through progressively adaptive fusion of diverse brain functional regions under different cognitive tasks. The proposed LAG strategy is validated using datasets related to fatigue (SEED-VIG), emotion (SEED-IV), and motor imagery (BCI_C_IV_2a). The results demonstrate the generalizability of LAG, achieving satisfactory outcomes in independent-subject experiments across all three datasets. This suggests that LAG effectively characterizes higher-level latent patterns associated with different cognitive tasks, presenting a novel approach to understanding brain patterns in varying cognitive contexts.

Alterations in degree centrality and functional connectivity in tension-type headache: a resting-state fMRI study.

Previous studies have provided evidence of structural and functional changes in the brains of patients with tension-type headache (TTH). However, investigations of functional connectivity alterations in TTH have been inconclusive. The present study aimed to investigate abnormal intrinsic functional connectivity patterns in patients with TTH through the voxel-wise degree centrality (DC) method as well as functional connectivity (FC) analysis. A total of 33 patients with TTH and 30 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (rs-fMRI) scanning and were enrolled in the final study. The voxel-wise DC method was performed to quantify abnormalities in the local functional connectivity hubs. Nodes with abnormal DC were used as seeds for further FC analysis to evaluate alterations in functional connectivity patterns. In addition, correlational analyses were performed between abnormal DC and FC values and clinical features. Compared with HCs, patients with TTH had higher DC values in the left middle temporal gyrus (MTG.L) and lower DC values in the left anterior cingulate and paracingulate gyri (ACG.L) (GRF, voxel-wise p < 0.05, cluster-wise p < 0.05, two-tailed). Seed-based FC analyses revealed that patients with TTH showed greater connections between ACG.L and the right cerebellum lobule IX (CR-IX.R), and smaller connections between ACG.L and ACG.L. The MTG.L showed increased FC with the ACG.L, and decreased FC with the right caudate nucleus (CAU.R) and left precuneus (PCUN.L) (GRF, voxel-wise p < 0.05, cluster-wise p < 0.05, two-tailed). Additionally, the DC value of the MTG.L was negatively correlated with the DASS-depression score (p = 0.046, r=-0.350). This preliminary study provides important insights into the pathophysiological mechanisms of TTH.

Comparison of local activation, functional connectivity, and structural connectivity in the N-back task.

The N-back task is widely used to investigate working memory. Previous functional magnetic resonance imaging (fMRI) studies have shown that local brain activation depends on the difficulty of the N-back task. Recently, changes in functional connectivity and local activation during a task, such as a single-hand movement task, have been reported to give the distinct information. However, previous studies have not investigated functional connectivity changes in the entire brain during N-back tasks. In this study, we compared alterations in functional connectivity and local activation related to the difficulty of the N-back task. Because structural connectivity has been reported to be associated with local activation, we also investigated the relationship between structural connectivity and accuracy in a N-back task using diffusion tensor imaging (DTI). Changes in functional connectivity depend on the difficulty of the N-back task in a manner different from local activation, and the 2-back task is the best method for investigating working memory. This indicates that local activation and functional connectivity reflect different neuronal events during the N-back task. The top 10 structural connectivities associated with accuracy in the 2-back task were locally activated during the 2-back task. Therefore, structural connectivity as well as fMRI will be useful for predicting the accuracy of the 2-back task.

Preliminary study on early diagnosis of Alzheimer's disease in APP/PS1 transgenic mice using multimodal magnetic resonance imaging.

Alzheimer's disease (AD) has an insidious onset and lacks clear early diagnostic markers, and by the time overt dementia symptoms appear, the disease is already in the mid-to-late stages. The search for early diagnostic markers of AD may open a critical window for Alzheimer's treatment and facilitate early intervention to slow the progression of AD. In this study, we aimed to explore the imaging markers for early diagnosis of AD through the combined application of structural magnetic resonance imaging (sMRI), resting-state functional magnetic resonance imaging (rs-fMRI), and 1H-magnetic resonance spectroscopy (1H-MRS) multimodal magnetic resonance imaging (MRI) techniques at the animal experimental level, with the aim to provide a certain reference for early clinical diagnosis of AD. First, sMRI scans were performed on 4-month-old amyloid beta precursor protein/presenilin 1 (APP/PS1) transgenic AD model mice and wild type mice of the same litter using a 7.0 T animal MRI scanner to analyze the differential brain regions with structural changes in the gray matter of the brain by voxel-based morphometry (VBM). Next, rs-fMRI scans were performed to analyze the differential brain regions between groups for local spontaneous brain activity and functional connectivity (FC) between brain regions. Finally, 1H-MRS scans were performed to quantify and analyze intergroup differences in the relative concentrations of different metabolites within regions of interest (cortex and hippocampus). Compared with wild type mice, the volume of the left hippocampus, and right olfactory bulb of APP/PS1 transgenic AD model mice were reduced, the functional activity of the bilateral hippocampus, right piriform cortex and right caudate putamen was reduced, the functional network connectivity of the hippocampus was impaired, and the relative content of N-acetylaspartate (NAA)in the hippocampus was decreased. In addition, this study found that imaging changes in olfactory-related brain regions were closely associated with AD diagnosis, and these findings may provide some reference for the early diagnosis of AD.

Abnormal Static and Dynamic Local Functional Connectivity in First-Episode Schizophrenia: A Resting-State fMRI Study.

Dynamic functional connectivity (FC) analyses have provided ample information on the disturbances of global functional brain organization in patients with schizophrenia. However, our understanding about the dynamics of local FC in never-treated first episode schizophrenia (FES) patients is still rudimentary. Dynamic Regional Phase Synchrony (DRePS), a newly developed dynamic local FC analysis method that could quantify the instantaneous phase synchronization in local spatial scale, overcomes the limitations of commonly used sliding-window methods. The current study performed a comprehensive examination on both the static and dynamic local FC alterations in FES patients (N = 74) from healthy controls (HCs, N = 41) with resting-state functional magnetic resonance imaging using DRePS, and compared the static local FC metrics derived from DRePS with those calculated from two commonly used regional homogeneity (ReHo) analysis methods that are defined based on Kendall's coefficient of concordance (KCC-ReHo) and frequency coherence (Cohe-ReHo). Symptom severities of FES patients were assessed with a set of clinical scales. Cognitive functions of FES patients and HCs were assessed with the MATRICS consensus cognitive battery. Group-level analysis revealed that compared with HCs, FES patients exhibited increased static local FC in right superior, middle temporal gyri, hippocampus, parahippocampal gyrus, putamen, and bilateral caudate nucleus. Nonetheless, the dynamic local FC metrics did not show any significant differences between the two groups. The associations between all local FC metrics and clinical characteristics manifested scores were explored using a relevance vector machine. Results showed that the Global Assessment of Functioning score highest in past year and the Brief Visuospatial Memory Test-Revised task score were statistically significantly predicted by a combination of all static and dynamic features. The diagnostic abilities of different local FC metrics and their combinations were compared by the classification performance of linear support vector machine classifiers. Results showed that the inclusion of zero crossing ratio of DRePS, one of the dynamic local FC metrics, alongside static local FC metrics improved the classification accuracy compared to using static metrics alone. These results enrich our understanding of the neurocognitive mechanisms underlying schizophrenia, and demonstrate the potential of developing diagnostic biomarker for schizophrenia based on DRePS.

Repeated passive visual experience modulates spontaneous and non-familiar stimuli-evoked neural activity

Familiarity creates subjective memory of repeated innocuous experiences, reduces neural and behavioral responsiveness to those experiences, and enhances novelty detection. The neural correlates of the internal model of familiarity and the cellular mechanisms of enhanced novelty detection following multi-day repeated passive experience remain elusive. Using the mouse visual cortex as a model system, we test how the repeated passive experience of a 45° orientation-grating stimulus for multiple days alters spontaneous and non-familiar stimuli evoked neural activity in neurons tuned to familiar or non-familiar stimuli. We found that familiarity elicits stimulus competition such that stimulus selectivity reduces in neurons tuned to the familiar 45° stimulus; it increases in those tuned to the 90° stimulus but does not affect neurons tuned to the orthogonal 135° stimulus. Furthermore, neurons tuned to orientations 45° apart from the familiar stimulus dominate local functional connectivity. Interestingly, responsiveness to natural images, which consists of familiar and non-familiar orientations, increases subtly in neurons that exhibit stimulus competition. We also show the similarity between familiar grating stimulus-evoked and spontaneous activity increases, indicative of an internal model of altered experience.

Persistent post-COVID headache is associated with suppression of scale-free functional brain dynamics in non-hospitalized individuals.

Post-acute coronavirus disease 2019 (COVID-19) syndrome (PACS) is a growing concern, with headache being a particularly debilitating symptom with high prevalence. The long-term effects of COVID-19 and post-COVID headache on brain function remain poorly understood, particularly among non-hospitalized individuals. This study focused on the power-law scaling behavior of functional brain dynamics, indexed by the Hurst exponent (H). This measure is suppressed during physiological and psychological distress and was thus hypothesized to be reduced in individuals with post-COVID syndrome, with greatest reductions among those with persistent headache. Resting-state blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging data were collected for 57 individuals who had COVID-19 (32 with no headache, 14 with ongoing headache, 11 recovered) and 17 controls who had cold and flu-like symptoms but tested negative for COVID-19. Individuals were assessed an average of 4-5 months after COVID testing, in a cross-sectional, observational study design. No significant differences in H values were found between non-headache COVID-19 and control groups., while those with ongoing headache had significantly reduced H values, and those who had recovered from headache had elevated H values, relative to non-headache groups. Effects were greatest in temporal, sensorimotor, and insular brain regions. Reduced H in these regions was also associated with decreased BOLD activity and local functional connectivity. These findings provide new insights into the neurophysiological mechanisms that underlie persistent post-COVID headache, with reduced BOLD scaling as a potential biomarker that is specific to this debilitating condition.

Altered local and remote functional connectivity in mild Alzheimer's disease patients with sleep disturbances.

This study aimed to investigate local and remote functional connectivity in mild Alzheimer's disease patients with sleep disturbances (ADSD) and those without sleep disturbances (ADNSD). Thirty eight mild AD patients with sleep disturbances and 21 mild AD patients without sleep disturbances participated in this study. All subjects underwent neuropsychological assessments and 3.0 Tesla magnetic resonance scanning. Static and dynamic regional homogeneity (ReHo) were used to represent the local functional connectivity. Seed-based whole-brain functional connectivity was used to represent the remote functional connectivity. The seed was chosen based on the results of ReHo. Compared to ADNSD, ADSD showed decreased static ReHo in the left posterior central gyrus and the right cuneus and increased dynamic ReHo in the left posterior central gyrus. As for the remote functional connectivity, comparing ADSD to ADNSD, it was found that there was a decreased functional connection between the left posterior central gyrus and the left cuneus as well as the left calcarine. The current study demonstrated that, compared with ADNSD, ADSD is impaired in both local and remote functional connectivity, manifested as reduced functional connectivity involving the primary sensory network and the primary visual network. The abnormality of the above functional connectivity is one of the reasons why sleep disorders promote cognitive impairment in AD. Moreover, sleep disorders change the temporal sequence of AD pathological damage to brain functional networks, but more evidence is needed to support this conclusion.

Exploring the Potential "Brain-Cognition-Behavior" Relationship in Children With ADHD Based on Resting-State Brain Local Activation and Functional Connectivity.

Exploring how abnormal brain function in children with ADHD affects executive function and ultimately leads to behavioral impairment provides a theoretical basis for clinically targeted neurotherapy and cognitive training. Amplitude of low frequency fluctuations (ALFF), regional homogeneity (ReHo), and seed-based FC were analyzed in 53 ADHD and 52 healthy controls. The "brain-cognition-behavior" relationship was further explored using mediation analysis. ADHD showed abnormal local activation in the middle temporal gyrus (MTG), inferior occipital gyrus and inferior frontal gyrus (IFG) and reduced FC between the IFG and the cerebellum. ADHD diagnosis may affect ALFF of MTG and further modulate shift and finally affect inattentive symptoms. It may also affect the total symptoms through the FC of the IFG with the cerebellum. ADHD showed extensive spontaneous activity abnormalities and frontal-cerebellar FC impairments. Localized functional abnormalities in the MTG may affect the shift in EF, resulting in attention deficit behavior.

Local signal variability and functional connectivity: Sensitive measures of the excitation-inhibition ratio?

The online version contains supplementary material available at 10.1007/s11571-023-10003-x.

Beyond alpha band: prestimulus local oscillation and interregional synchrony of the beta band shape the temporal perception of the audiovisual beep-flash stimulus.

&#xD;Sensory integration is modulated by local prestimulus ongoing oscillatory activity which was suggested to play a role in organizing general neural processes such as attention and neuronal excitability and relatively longer inter-areal poststimulus phase coupling, especially in the 8-12 Hz alpha band. Previous work has examined the modulation effect of phase in audiovisual temporal integration, but there is no unified conclusion whether there is phasic modulation in the visual leading condition (sound-flash pairs). Moreover, it is unknown whether temporal integration is also subject to prestimulus inter-areal phase coupling between localizer-defined auditory and visual regions. Here, we recorded brain activity with EEG while human participants of both sexes performed a simultaneity judgment (SJ) task with the beep-flash stimuli to explore the functional role of the ongoing local oscillation and inter-areal coupling in temporal integration.&#xD;Main results:&#xD;We found that the power and ITC of the alpha-band are larger in synchronous response in both the visual and auditory leading conditions in their respective occipital and central channels, suggesting that neuronal excitability and attention play a role in temporal integration. Critically, the simultaneous judgment was modulated by the phases of low beta (14-20 Hz) oscillations quantified by the phase bifurcation index (PBI). Posthoc Rayleigh test indicated that the beta phase encodes different time information rather than neuronal excitability. Furthermore, we also found the stronger spontaneous high beta (21-28 Hz) phasic coupling between audiovisual cortices for synchronous response in auditory leading condition. Together, these results demonstrate that spontaneous local low-frequency (< 30 Hz) neural oscillations and functional connectivity between auditory and visual brain regions especially in the beta band collectively influence audiovisual temporal integration.&#xD.

Relationships between reading performance and regional spontaneous brain activity following surgical removal of primary left-hemisphere tumors: A resting-state fMRI study

Left-hemisphere intraparenchymal primary brain tumor patients are at risk of developing reading difficulties that may be stable, improve or deteriorate after surgery. Previous studies examining language organization in brain tumor patients have provided insights into neural plasticity supporting recovery. Only a single study, however, has examined the role of white matter tracts in preserving reading ability post-surgery and none have examined the functional reading network. The current study aimed to investigate the regional spontaneous brain activity associated with reading performance in a group of 36 adult patients 6–24 months following left-hemisphere tumor resection. Spontaneous brain activity was assessed using resting-state fMRI (rs-fMRI) regional homogeneity (ReHo) and fractional amplitude low frequency fluctuation (fALFF) metrics, which measure local functional connectivity and activity, respectively. ReHo in the left occipito-temporal and right superior parietal regions was negatively correlated with reading performance. fALFF in the putamen bilaterally and the left cerebellum was negatively correlated with reading performance, and positively correlated in the right superior parietal gyrus. These findings are broadly consistent with reading networks reported in healthy participants, indicating that reading ability following brain tumor surgery might not involve substantial functional re-organization.

Dysfunction of basal ganglia functional connectivity associated with subjective and cognitive fatigue in multiple sclerosis.

Central fatigue is one of the most common symptoms in multiple sclerosis (MS). It has a profound impact on quality of life and a negative effect on cognition. Despite its widespread impact, fatigue is poorly understood and very difficult to measure. Whilst the basal ganglia has been implicated in fatigue the nature of its role and involvement with fatigue is still unclear. The aim of the present study was to establish the role of the basal ganglia in MS fatigue using functional connectivity measures. The present study examined the functional connectivity (FC) of the basal ganglia in a functional MRI study with 40 female participants with MS (mean age = 49.98 (SD = 9.65) years) and 40 female age-matched (mean age = 49.95 (SD = 9.59) years) healthy controls (HC). To measure fatigue the study employed the subjective self-report Fatigue Severity Scale and a performance measure of cognitive fatigue using an alertness-motor paradigm. To distinguish physical and central fatigue force measurements were also recorded. The results suggest that decreased local FC within the basal ganglia plays a key role in cognitive fatigue in MS. Increased global FC between the basal ganglia and the cortex may sub serve a compensatory mechanism to reduce the impact of fatigue in MS. The current study is the first to show that basal ganglia functional connectivity is associated with both subjective and objective fatigue in MS. In addition, the local FC of the basal ganglia during fatigue inducing tasks could provide a neurophysiological biomarker of fatigue.

Impact of APOE ε4 allele on associations between sub‐threshold, positive Amyloid‐β retention, brain function, and cognitive performances in cognitively normal older adults

AbstractBackgroundA growing body of evidence suggests a deteriorating effect of sub‐threshold amyloid‐beta (Aβ) accumulation on cognition before the onset of clinical symptoms of Alzheimer’s disease. Despite the association between the Aβ‐dependent pathway and the APOE ε4 allele, the impact of this allele on the progression from the sub‐threshold Aβ deposits to cognitive function impairment is unclear. Furthermore, the comparative analysis of positive Aβ accumulation in the preclinical phase is lacking. This study aimed to explore the differential effect of the APOE ε4 allele on the association between Aβ retention, brain function, and cognitive performance in cognitively healthy older adults, depending on the Aβ burden status.MethodOne hundred and eighty‐two older adults with normal cognition who underwent resting‐state functional magnetic resonance imaging were enrolled. They were dichotomized using [18F]‐labeled flutemetamol positron emission tomography into subjects with sub‐threshold (cognitively normal [CN] sub‐Aβ, n = 110; [APOE ε4 carrier, n = 30; non‐carrier, n = 80] and positive Aβ deposits [CN Aβ+ group, n = 72; APOE ε4 carrier, n = 34; non‐carrier, n = 38]).ResultWe found (i) distinct effects of the APOE ε4 allele and relationships with cognitive function in the preclinical phase; (ii) differences in local functional connectivity (FC) of the brain regions in networks vulnerable to Alzheimer’s disease according to the APOE ε4 allele, which was associated with higher executive and memory function; (iii) a differential association between regional Aβ retention and local FC according to the APOE ε4 allele; and (iv) a significant interaction between APOE ε4 allele and local FC for the remote inter‐network FC between the default‐mode and central‐executive network in the CN sub‐Aβ group, contributing a compensatory role for cognitive performance. Finally, these results were modulated according to Aβ positivity.ConclusionThis study is the first attempt to thoroughly examine the mechanism at play in the earliest phase of Alzheimer’s disease, focusing on the influence of the APOE ε4 allele from the sub‐threshold to positive Aβ retention during the preclinical phase.

Decreased functional integration in higher‐order association areas in individuals with autosomal‐dominant Alzheimer’s disease: Findings from the Colombia‐Boston (COLBOS) biomarker study

AbstractBackgroundThe disruption of brain functional connections has been linked to cognitive impairment in Alzheimer’s disease. The functional architecture of the brain can be modeled using graph theory, which provides metrics to describe both local and global network properties. Autosomal dominant Alzheimer’s disease (ADAD) provides a unique opportunity to study brain changes in preclinical AD since carriers of ADAD mutations are destined to develop dementia at young age and have a well‐characterized disease trajectory. Here, we applied a graph theory approach to examine the functional network topology in Presenilin‐1 (PSEN1) E280A carriers and non‐carriers.MethodsA total of 43 cognitively‐unimpaired individuals (18 PSEN1 carriers, 25 non‐carriers; mean age = 36.6±5.2) from the Colombia‐Boston biomarker study were included. Participants underwent resting‐state fMRI in a 3T scanner, and a comprehensive multi‐domain neuropsychological battery. fMRI data were preprocessed using C‐PAC. Global functional connectivity (FC) was derived from the nodal strength of the Pearson correlation matrix between time‐series of 400 ROIs [Shaeffer‐2016] within 6 different functional networks [Yeo‐2011]. The strength of within‐ (z) and between‐network (h) functional integration was derived from a consensus modularity analysis [Dwyer‐2014]. Differences in cognitive variables were evaluated using Mann‐Whitney tests. Differences in FC were assessed using permutation methods: global FC using FSL‐randomize and integration parameters were based on a consensus analysis applied to random controlled matrices. Both methods were repeated 1000 times, with a p&lt;0.05 significance threshold.ResultsThere were no group differences in cognitive variables. Compared to non‐carriers, carriers exhibited decreased local FC in higher‐order association areas, and increased connectivity in somatosensory areas. There were no group differences in the within‐network integration. Carriers showed decreased between‐network integration, especially in higher‐order association networks, mainly the default mode network (Fig.1).ConclusionsFindings support the hypothesis that alterations of functional network topology are evident in preclinical ADAD, primarily in the higher‐order cognitive networks. Early identification of abnormalities within these networks may be useful in understanding how FC changes may lead to subsequent cognitive decline in individuals at increased risk for AD. Future work with larger samples should investigate the relationships between FC changes and the neurobiological factors underlying AD.

The impact of wearing a KN95 face mask on human brain function: evidence from resting state functional magnetic resonance imaging.

Face masks are widely used in daily life because of the COVID-19 pandemic. The objective of this study was to explore the impact of wearing face masks on brain functions by using resting-state functional MRI (RS-fMRI). Scanning data from 15 healthy subjects (46.20 ± 6.67 years) were collected in this study. Each subject underwent RS-fMRI scans under two comparative conditions, wearing a KN95 mask and natural breathing (no mask). The amplitude of low frequency fluctuation (ALFF) and functional connectivity under the two conditions were analyzed and then compared using the paired t-test. Compared with those of the no-mask condition, the ALFF activities when wearing masks were increased significantly in the right middle frontal gyrus, bilateral precuneus, right superior marginal gyrus, left inferior parietal gyrus, and left supplementary motor area and decreased significantly in the anterior cingulate gyrus, right fusiform gyrus, left superior temporal gyrus, bilateral lingual gyrus, and bilateral calcarine cortex (p < 0.05). Taking the posterior cingulate cortex area as a seed point, the correlations with the occipital cortex, prefrontal lobe, and motor sensory cortex were sensitive to wearing masks compared with not wearing masks (p < 0.05). Taking the medial prefrontal cortex region as a seed point, the functional connectivity with the bilateral temporal lobe, bilateral motor sensory cortex, and occipital lobe was influenced by wearing a KN95 mask (p < 0.05). This study demonstrated that wearing a KN95 face mask can cause short-term changes in human resting brain function. Both local neural activities and functional connectivity in brain regions were sensitive to mask wearing. However, the neural mechanism causing these changes and its impact on cognitive function still need further investigation.

Stratifying ASD and characterizing the functional connectivity of subtypes in resting-state fMRI

Although stratifying autism spectrum disorder (ASD) into different subtypes is a common effort in the research field, few papers have characterized the functional connectivity alterations of ASD subgroups classified by their clinical presentations. This is a case-control rs-fMRI study, based on large samples of open database (Autism Brain Imaging Data Exchange, ABIDE). The rs-MRI data from n=415 ASD patients (males n=357), and n=574 typical development (TD) controls (males n=410) were included. Clinical features of ASD were extracted and classified using data from each patient's Autism Diagnostic Interview-Revised (ADI-R) evaluation. Each subtype of ASD was characterized by local functional connectivity using regional homogeneity (ReHo) for assessment, remote functional connectivity using voxel-mirrored homotopic connectivity (VMHC) for assessment, the whole-brain functional connectivity, and graph theoretical features. These identified imaging properties from each subtype were integrated to create a machine learning model for classifying ASD patients into the subtypes based on their rs-fMRI data, and an independent dataset was used to validate the model. All ASD participants were classified into Cluster-1 (patients with more severe impairment) and Cluster-2 (patients with moderate impairment) according to the dimensional scores of ADI-R. When compared to the TD group, Cluster-1 demonstrated increased local connection and decreased remote connectivity, and widespread hyper- and hypo-connectivity variations in the whole-brain functional connectivity. Cluster-2 was quite similar to the TD group in both local and remote connectivity. But at the level of whole-brain functional connectivity, the MCC-related connections were specifically impaired in Cluster-2. These properties of functional connectivity were fused to build a machine learning model, which achieved ~75% for identifying ASD subtypes (Cluster-1 accuracy = 81.75%; Cluster-2 accuracy = 76.48%). The stratification of ASD by clinical presentations can help to minimize disease heterogeneity and highlight the distinguished properties of brain connectivity in ASD subtypes.