Differences In Connectivity Patterns Research Articles

Structural and functional sex differences in medial temporal lobe subregions at midlife

BackgroundResearch has increasingly recognized sex differences in aging and Alzheimer’s Disease (AD) susceptibility. However, sex effects on the medial temporal lobe (MTL), a crucial region affected by aging and AD, remain poorly understood when it comes to the intricacies of morphology and functional connectivity. This study aimed to systematically analyze structural and functional connectivity among MTL subregions, which are known to exhibit documented morphological sex differences, during midlife, occurring before the putative pivotal age of cerebral decline. The study sought to explore the hypothesis that these differences in MTL subregion volumes would manifest in sex-related functional distinctions within the broader brain network.Methods201 cognitively unimpaired adults were included and stratified into four groups according to age and sex (i.e., Women and Men aged 40–50 and 50–60). These participants underwent comprehensive high-resolution structural MRI as well as resting-state functional MRI (rsfMRI). Utilizing established automated segmentation, we delineated MTL subregions and assessed morphological differences through an ANOVA. Subsequently, the CONN toolbox was employed for conducting ROI-to-ROI and Fractional Amplitude of Low-Frequency Fluctuations (fALFF) analyses to investigate functional connectivity within the specific MTL subregions among these distinct groups.ResultsSignificant differences in volumetric measurements were found primarily between women aged 40–50 and men of all ages, in the posterior hippocampus (pHPC) and the parahippocampal (PHC) cortex (p < 0.001), and, to a lesser extent, between women aged 50–60 and men of all ages (p < 0.05). Other distinctions were observed, but no significant differences in connectivity patterns or fALFF scores were detected between these groups.DiscussionDespite notable sex-related morphological differences in the posterior HPC and PHC regions, women and men appear to share a common pattern of brain connectivity at midlife. Longitudinal analyses are necessary to assess if midlife morphological sex differences in the MTL produce functional changes over time and thus, their potential role in cerebral decline.Clinical trial numberNot applicable.

Exploring the impact of biological sex on intrinsic connectivity networks in PTSD: A data-driven approach

IntroductionSex as a biological variable (SABV) may help to account for the differential development and expression of post-traumatic stress disorder (PTSD) symptoms among trauma-exposed males and females. Here, we investigate the impact of SABV on PTSD-related neural alterations in resting-state functional connectivity (rsFC) within three core intrinsic connectivity networks (ICNs): the salience network (SN), central executive network (CEN), and default mode network (DMN). MethodsUsing an independent component analysis (ICA), we compared rsFC of the SN, CEN, and DMN between males and females, with and without PTSD (n = 47 females with PTSD, n = 34 males with PTSD, n = 36 healthy control females, n = 20 healthy control males) via full factorial ANCOVAs. Additionally, linear regression analyses were conducted with clinical variables (i.e., PTSD and depression symptoms, childhood trauma scores) in order to determine intrinsic network connectivity characteristics specific to SABV. Furthermore, we utilized machine learning classification models to predict the biological sex and PTSD diagnosis of individual participants based on intrinsic network activity patterns. ResultsOur findings revealed differential network connectivity patterns based on SABV and PTSD diagnosis. Males with PTSD exhibited increased intra-SN (i.e., SN-anterior insula) rsFC and increased DMN-right superior parietal lobule/precuneus/superior occipital gyrus rsFC as compared to females with PTSD. There were also differential network connectivity patterns for comparisons between the PTSD and healthy control groups for males and females, separately. We did not observe significant correlations between clinical measures of interest and brain region clusters which displayed significant between group differences as a function of biological sex, thus further reinforcing that SABV analyses are likely not confounded by these variables. Furthermore, machine learning classification models accurately predicted biological sex and PTSD diagnosis among novel/unseen participants based on ICN activation patterns. ConclusionThis study reveals groundbreaking insights surrounding the impact of SABV on PTSD-related ICN alterations using data-driven methods. Our discoveries contribute to further defining neurobiological markers of PTSD among females and males and may offer guidance for differential sex-related treatment needs.

Associations between differential connectivity patterns of executive control networks and APOE ɛ4 in the Alzheimer continuum

The APOE ɛ4 allele and age are risk factors for Alzheimer’s disease (AD) and contribute to decreased executive function. However, the influence of APOE ɛ4 on the executive control network (ECN) in the AD continuum is still unclear. This study included 269 participants aged between 50 and 95 years old, based on ADNI data, including 104 cognitively normal (CN) individuals, 72 individuals with early mild cognitive impairment (EMCI), 55 individuals with late mild cognitive impairment (LMCI), and 38 AD patients. Within each disease group, participants were subdivided into APOE ɛ4 carriers and non-carriers. We explored brain regions within the ECN affected by the interactions between genes and disease states by resting-state functional magnetic resonance imaging (fMRI) and voxel-based two-way analysis of variance (ANOVA). Subsequently, functional connectivity (FC) between seeds and peak clusters were extracted and correlated with the cognitive performance. We found that the damages of carrying APOE ɛ4 in ECNs mainly distributed in the fronto-parietal and parietal-temporal systems. Functional network intergroup differences indicated increased intrafrontal and fronto-parietal connectivity at the early stage of AD and increased connectivity between the parietal lobe and related regions at late disease in these APOE ɛ4 carriers. Our conclusion is that the functional connectivity in the ECN exhibits different distinguishably patterns of impairment in the AD continuum under the influence of the APOE ɛ4 allele. Patients with different genotypes showed heterogeneity in functional network changes in the early stages of disease, which may be a potential biomarker for early AD.

Gender differences in connectivity patterns: Exploring autism traits, sleep disturbances, alexithymia, and aggression: A general population survey

BackgroundThe prevalence of elevated alexithymia trait is notably high among individuals with autism spectrum disorder (ASD), which will cause emotional and behavioral issues, especially aggressive behavior. However, few studies explored the inter links between autistic traits, alexithymia, sleep disturbance and aggression. Using network analysis, current study explores relationships between these symptoms within a general population sample. MethodSeven hundred and sixty-one (age 18–30, 351 male, 410 female) participants were recruited through an online platform. Network analysis was used to clarify relationship between these symptoms, and network comparison was conducted to determine whether network pattern differed between male and female. ResultsDiscernible patterns linking autistic traits to alexithymia, sleep disturbance and aggression. These patterns exhibited a satisfactory level of stability and consistency when tested and retested. Among the nodes examined, the node with the highest centrality and expected influence in the network is aggression. Network constructed using male and female data show different patterns of structure and strength. ConclusionUnderstanding the association between autism traits and other behavioral and emotional issues, as well as the possible role of gender, can help optimize targeted interventions and improve the quality of life of individuals with autism.

White matter alterations predict outcomes of comprehensive behavioral intervention for tics in children with Tourette syndrome: A diffusion MRI study

AimTourette syndrome (TS) is a neurodevelopmental disorder that cause sudden uncontrolled rapid and repeated vocal sounds or movements called tics. Herein, diffusion magnetic resonance imaging (dMRI) connectometry was implemented to evaluate the white matter connectivity differences among TS patients. MethodsA total of 63 TS and 77 typically developed (TD) individuals were enrolled in the present study. dMRI connectometry was utilized to identify differences in connectivity patterns of white matter tracts in TS patients based on quantitative anisotropy (QA). QA was compared between TS and TD patients and correlated with severity scores such as Yale Global Tic Severity Scale (YGTSS) and Premonitory Urge for Tics Scale (PUTS). ResultsHigher white matter connectivity of corpus callosum and bilateral cingulum as well as lower connectivity of corticothalamic and corticostriatal pathways were evident in TS relative to TD. The baseline YGTSS motor, YGTSS total, and PUTS were negatively correlated with corticostriatal pathway, corticothalamic pathway, and bilateral cingulum integrity, respectively. The changes in tic severity scores were also positively correlated with alterations in the white matter integrity of these brain regions following behavioral therapy. ConclusionPatients with TS have several abnormalities in their white matter microstructure particularly in the cortico-striato-thalamo-cortical (CSTC) circuit, correlated with the severity of the disease. Besides, the post-behavioral therapy changes in the white matter integrity of these regions are demonstrated as response predictors.

Differential patterns of functional connectivity in tremor dominant Parkinson's disease and essential tremor plus.

Tremor dominant Parkinson's disease (TDPD) and essential tremor plus (ETP) syndrome are commonly encountered tremor dominant neurological disorders. Although the basal ganglia thalamocortical (BGTC) and cerebello thalamocortical (CTC) networks are implicated in tremorogenesis, the extent of functional connectivity alterations across disorders is uncertain. This study aims to evaluate functional connectivity of the BGTC and CTC in TDPD and ETP. Resting state functional MRI was acquired for 25 patients with TDPD, ETP and 22 healthy controls (HC). Following pre-processing and denoising, seed-to-voxel based connectivity was carried out at FDR < 0.05 using ROIs belonging to the BGTC and CTC. Fahn-Tolosa-Marin tremor rating scale (FTMRS) was correlated with the average connectivity values at FDR < 0.05. Compared to HC, TDPD showed decreased connectivity between cerebellum and pre, post central gyrus. While, ETP showed decreased connectivity between pallidum and occipital cortex, precuneus, cuneus compared to HC. In comparison to ETP, TDPD showed increased connectivity between precentral gyrus, pallidum, SNc with the default mode network (DMN), and decreased connectivity between cerebellum with superior, middle frontal gyrus was observed. Tremor severity positively correlated with connectivity between SNc and DMN in TDPD, and negatively correlated with pallidal connectivity in ETP. Pattern of BGTC, CTC involvement is differential i.e., higher connectivity of the BGTC nodes in TDPD, and higher connectivity of cerebellar nodes in ETP. The interesting observation of pallidal involvement in ETP suggests the role of BGTC in the pathogenesis of ETP, and indicated similarities in concepts of tremor genesis in TDPD and ETP.

An electroencephalographic signature predicts craving for methamphetamine

Craving is central to methamphetamine use disorder (MUD) and both characterizes the disease and predicts relapse. However, there is currently a lack of robust and reliable biomarkers for monitoring craving and diagnosing MUD. Here, we seek to identify a neurobiological signature of craving based on individual-level functional connectivity pattern differences between healthy control and MUD subjects. We train high-density electroencephalography (EEG)-based models using data recorded during the resting state and then calculate imaginary coherence features between the band-limited time series across different brain regions of interest. Our prediction model demonstrates that eyes-open beta functional connectivity networks have significant predictive value for craving at the individual level and can also identify individuals with MUD. These findings advance the neurobiological understanding of craving through an EEG-tailored computational model of the brain connectome. Dissecting neurophysiological features provides a clinical avenue for personalized treatment of MUD.

A hybrid graph network model for ASD diagnosis based on resting-state EEG signals

Autism spectrum disorder (ASD) is a common neurodevelopmental disorder and early diagnosis is crucial for effective treatment. Stable and effective biomarkers are essential for understanding the underlying causes of the disorder and improving diagnostic accuracy. Electroencephalography (EEG) signals have proven to be reliable biomarkers for diagnosing ASD. Extracting stable connectivity patterns from EEG signals helps ensure robustness in ASD diagnostic systems. In this study, we propose a hybrid graph convolutional network framework called Rest-HGCN, which utilizes resting-state EEG signals to capture differential patterns of brain connectivity between normal children and ASD patients using graph learning strategies. The Rest-HGCN combines brain network analysis techniques and data-driven strategies to extract discriminative graph features from resting-state EEG signals. By automatically extracting differential graph patterns from these signals, the Rest-HGCN achieves reliable ASD diagnosis. To evaluate the performance of Rest-HGCN, we conducted ASD diagnosis experiments using k-fold cross-validation on the public ABC-CT resting EEG dataset. The proposed Rest-HGCN model achieved accuracies of 87.12 % and 85.32 % in single-subject and cross-experiment analyses, respectively. The results suggest that Rest-HGCN can effectively capture discriminant graph patterns from resting EEG signals and achieve robust ASD diagnosis. This may provide an effective and convenient tool for clinical ASD diagnosis.

The Dichotomy of Threat and Deprivation as Subtypes of Childhood Maltreatment: Differential Functional Connectivity Patterns of Threat and Reward Circuits in an Adult Trauma Sample

BackgroundChildhood maltreatment is associated with reduced activation of the nucleus accumbens, a central region in the reward network, and overactivity in the amygdala, a key region in threat processing. However, the long-lasting impact of these associations in the context of later-life stress is not well understood. The current study explored the association between childhood threat and deprivation and functional connectivity of threat and reward regions in an adult trauma sample. MethodsTrauma survivors (N = 169; mean age [SD] = 32.2 [10.3] years; female = 55.6%) were recruited from a level I trauma center. Two weeks after injury, participants completed the Childhood Trauma Questionnaire (measuring experiences of threat and deprivation) and underwent resting-state functional magnetic resonance imaging. Seed-to-voxel analyses evaluated the effect of childhood threat and deprivation on amygdala and nucleus accumbens resting-state connectivity. ResultsHigher levels of threat were associated with increased connectivity between the right nucleus accumbens with temporal fusiform gyrus/parahippocampal gyrus and the left amygdala and the precuneus (false discovery rate–corrected p < .05). After controlling for posttraumatic symptoms 2 weeks posttrauma and lifetime trauma exposure, only the nucleus accumbens findings survived. There were no significant relationships between experiences of childhood deprivation and amygdala or nucleus accumbens connectivity. ConclusionsExperiences of threat are associated with increased nucleus accumbens and amygdala connectivity, which may reflect a preparedness to detect salient and visual stimuli. This may also reflect a propensity toward dysregulated reward processing. Overall, these results suggest that childhood threat may be contributing to aberrant neural baseline reward and threat sensitivity later in life in an adult trauma sample.

Connectivity and molecular profiles of Foxp2- and Dbx1-lineage neurons in the accessory olfactory bulb and medial amygdala.

In terrestrial vertebrates, the olfactory system is divided into main (MOS) and accessory (AOS) components that process both volatile and nonvolatile cues to generate appropriate behavioral responses. While much is known regarding the molecular diversity of neurons that comprise the MOS, less is known about the AOS. Here, focusing on the vomeronasal organ (VNO), the accessory olfactory bulb (AOB), and the medial amygdala (MeA), we reveal that populations of neurons in the AOS can be molecularly subdivided based on their ongoing or prior expression of the transcription factors Foxp2 or Dbx1, which delineate separate populations of GABAergic output neurons in the MeA. We show that a majority of AOB neurons that project directly to the MeA are of the Foxp2 lineage. Using single-neuron patch-clamp electrophysiology, we further reveal that in addition to sex-specific differences across lineage, the frequency of excitatory input to MeA Dbx1- and Foxp2-lineage neurons differs between sexes. Together, this work uncovers a novel molecular diversity of AOS neurons, and lineage and sex differences in patterns of connectivity.

Functional connectivity differences in healthy individuals with different well-being states

Well-being (WB) is defined as a healthy state of mind and body. It is a state in which an individual is able to contribute to its society, able to work productively and overcome the normal stress of life. WB is a multi-dimensional concept and covers different aspects, including life satisfaction and quality of life. Little is known as to whether there are differences in connectivity patterns between healthy individuals with different WB states. We evaluated the WB state of healthy individuals with no prior diagnosis of any psychological disorder using the “General habitual WB questionnaire”, covering mental, physical and social domains. Subjects with mean age 25±4 years were divided into two groups, high WB state (n = 18) and low WB state (n = 14). We investigated and compared the groups for their resting state (rs-fMRI) functional connectivity (FC) patterns using DPARSF compiled with SPM12 toolbox. WB specific seeds were chosen for FC analysis. In the high WB group we found significantly increased connectivity between bilateral angular gyrus and frontal regions comprising the orbitofrontal cortex (OFC), right frontal superior gyrus and left precuneus. The low-WB group showed increased connectivity between the bilateral amygdala and the occipital lobe and the right anterior OFC. To conclude connectivity results with a quantitative approach, suggest differences in cognitive and decision-making processing between people with varying WB states. The high-WB group when compared to low-WB group had higher cognitive processing and decision making based on their internal mental processes and self-referential processing, whereas connectivity between amygdala and OFC relates to decreased attentional processing and promotes effective emotional regulation that may be a lead to rumination.

Sex-dependent differences in connectivity patterns are related to episodic memory recall.

Previous studies have shown that females typically outperform males on episodic memory tasks. In this study, we investigated if (1) there are differences between males and females in their connectome characteristics, (2) if these connectivity patterns are associated with memory performance, and (3) if these brain connectome characteristics contribute to the differences in episodic memory performance between sexes. In a sample of 655 healthy young subjects (n = 391 females; n = 264 males), we derived brain network characteristics from diffusion-weighted imaging (DWI) data using models of crossing fibers within each voxel of the brain and probabilistic tractography (graph strength, shortest path length, global efficiency, and weighted transitivity). Group differences were analysed with linear models and mediation analyses were used to explore how connectivity patterns might relate to sex-dependent differences in memory performance. Our results show significant sex-dependent differences in weighted transitivity (d = 0.42), with males showing higher values. Further, we observed a negative association between weighted transitivity and memory performance (r = -0.12). Finally, these distinct connectome characteristics partially mediated the observed differences in memory performance (effect size of the indirect effect r = 0.02). Our findings indicate a higher interconnectedness in females compared to males. Additionally, we demonstrate that the sex-dependent differences in episodic memory performance can be partially explained by the differences in this connectome measure. These results further underscore the importance of sex-dependent differences in brain connectivity and their impact on cognitive function.

Polymorphism of heterometallic Bi/Cu halide complexes: Experimental examination of crystal structures, thermal stability and optical properties

Two polymorphs of heterometallic Bi/Cu complex, (1-Me-3,5-ClPy)2[Bi2Cu2I10] (1–2), were obtained. They feature differences in connectivity patterns in their anionic parts. By means of X-ray diffraction, features of crystal packing were studied. These two compounds were also investigated by differential scanning spectroscopy and thermogravimetric analysis, confirming that there are no thermally induced 1-to-2 phase transitions. Band gaps, determined via diffuse reflectance spectroscopy, are 1.85 eV for both compounds.

Altered within- and between-network functional connectivity in atypical Alzheimer's disease.

Posterior cortical atrophy and logopenic progressive aphasia are atypical clinical presentations of Alzheimer's disease. Resting-state functional connectivity studies have shown functional network disruptions in both phenotypes, particularly involving the language network in logopenic progressive aphasia and the visual network in posterior cortical atrophy. However, little is known about how connectivity differs both within and between brain networks in these atypical Alzheimer's disease phenotypes. A cohort of 144 patients was recruited by the Neurodegenerative Research Group at Mayo Clinic, Rochester, MN, USA, and underwent structural and resting-state functional MRI. Spatially preprocessed data were analysed to explore the default mode network and the salience, sensorimotor, language, visual and memory networks. The data were analysed at the voxel and network levels. Bayesian hierarchical linear models adjusted for age and sex were used to analyse within- and between-network connectivity. Reduced within-network connectivity was observed in the language network in both phenotypes, with stronger evidence of reductions in logopenic progressive aphasia compared to controls. Only posterior cortical atrophy showed reduced within-network connectivity in the visual network compared to controls. Both phenotypes showed reduced within-network connectivity in the default mode and sensorimotor networks. No significant change was noted in the memory network, but a slight increase in the salience within-network connectivity was seen in both phenotypes compared to controls. Between-network analysis in posterior cortical atrophy showed evidence of reduced visual-to-language network connectivity, with reduced visual-to-salience network connectivity, compared to controls. An increase in visual-to-default mode network connectivity was noted in posterior cortical atrophy compared to controls. Between-network analysis in logopenic progressive aphasia showed evidence of reduced language-to-visual network connectivity and an increase in language-to-salience network connectivity compared to controls. Findings from the voxel-level and network-level analysis were in line with the Bayesian hierarchical linear model analysis, showing reduced connectivity in the dominant network based on diagnosis and more crosstalk between networks in general compared to controls. The atypical Alzheimer's disease phenotypes were associated with disruptions in connectivity, both within and between brain networks. Phenotype-specific differences in connectivity patterns were noted in the visual network for posterior cortical atrophy and the language network for logopenic progressive aphasia.

MicroRNA-dependent regulation of gene expression in GABAergic interneurons.

Information processing within neuronal circuits relies on their proper development and a balanced interplay between principal and local inhibitory interneurons within those circuits. Gamma-aminobutyric acid (GABA)ergic inhibitory interneurons are a remarkably heterogeneous population, comprising subclasses based on their morphological, electrophysiological, and molecular features, with differential connectivity and activity patterns. microRNA (miRNA)-dependent post-transcriptional control of gene expression represents an important regulatory mechanism for neuronal development and plasticity. miRNAs are a large group of small non-coding RNAs (21-24 nucleotides) acting as negative regulators of mRNA translation and stability. However, while miRNA-dependent gene regulation in principal neurons has been described heretofore in several studies, an understanding of the role of miRNAs in inhibitory interneurons is only beginning to emerge. Recent research demonstrated that miRNAs are differentially expressed in interneuron subclasses, are vitally important for migration, maturation, and survival of interneurons during embryonic development and are crucial for cognitive function and memory formation. In this review, we discuss recent progress in understanding miRNA-dependent regulation of gene expression in interneuron development and function. We aim to shed light onto mechanisms by which miRNAs in GABAergic interneurons contribute to sculpting neuronal circuits, and how their dysregulation may underlie the emergence of numerous neurodevelopmental and neuropsychiatric disorders.

Altered Resting-State functional connectivity in the anterior and posterior hippocampus in Post-traumatic stress disorder: The central role of the anterior hippocampus

BackgroundPost-traumatic stress disorder can be viewed as a memory disorder, with trauma-related flashbacks being a core symptom. Given the central role of the hippocampus in autobiographical memory, surprisingly, there is mixed evidence concerning altered hippocampal functional connectivity in PTSD. We shed light on this discrepancy by considering the distinct roles of the anterior versus posterior hippocampus and examine how this distinction may map onto whole-brain resting-state functional connectivity patterns among those with and without PTSD. MethodsWe first assessed whole-brain between-group differences in the functional connectivity profiles of the anterior and posterior hippocampus within a publicly available data set of resting-state fMRI data from 31 male Vietnam war veterans diagnosed with PTSD (mean age = 67.6 years, sd = 2.3) and 29 age-matched combat-exposed male controls (age = 69.1 years, sd = 3.5). Next, the connectivity patterns of each subject within the PTSD group were correlated with their PTSD symptom scores. Finally, the between-group differences in whole-brain functional connectivity profiles discovered for the anterior and posterior hippocampal seeds were used to prescribe post-hoc ROIs, which were then used to perform ROI-to-ROI functional connectivity and graph-theoretic analyses. ResultsThe PTSD group showed increased functional connectivity of the anterior hippocampus with affective brain regions (anterior/posterior insula, orbitofrontal cortex, temporal pole) and decreased functional connectivity of the anterior/posterior hippocampus with regions involved in processing bodily self-consciousness (supramarginal gyrus). Notably, decreased anterior hippocampus connectivity with the posterior cingulate cortex/precuneus was associated with increased PTSD symptom severity. The left anterior hippocampus also emerged as a central locus of abnormal functional connectivity, with graph-theoretic measures suggestive of a more central hub-like role for this region in those with PTSD compared to trauma-exposed controls. ConclusionsOur results highlight that the anterior hippocampus plays a critical role in the neurocircuitry underlying PTSD and underscore the importance of the differential roles of hippocampal sub-regions in serving as biomarkers of PTSD. Future studies should investigate whether the differential patterns of functional connectivity stemming from hippocampal sub-regions is observed in PTSD populations other than older war veterans.

Altered functional connectivity networks in logopenic progressive aphasia and posterior cortical atrophy

AbstractBackgroundResting state functional connectivity (rsfMRI) studies have shown functional network disruptions in logopenic progressive aphasia (LPA) (reduced connectivity within the left temporal language network) and posterior cortical atrophy (PCA) (reduced connectivity within ventral visual network). However, little is known about how these networks compare and how connectivity differs within and between networks in these atypical Alzheimer’s Disease (AD) phenotypes.MethodFifty‐nine amyloid‐positive PCA patients and eighty‐five amyloid‐positive LPA patients were recruited by the Neurodegenerative Research Group at Mayo Clinic, Rochester, MN, and underwent structural and resting state functional MRI. Spatially preprocessed data was analyzed using the CONN functional connectivity toolbox to explore the default mode network (DMN), salience, sensorimotor, left language, visual and memory networks, which were generated by averaging multiple regions‐of‐interest (ROI) within each network. The data was analyzed at both the voxel‐level and network‐level (ROI‐ROI).ResultVoxel‐level differences in functional connectivity between PCA and LPA were observed in all networks (p&lt;0.05; cluster size, FWE=0.05). PCA showed reduced connectivity in the occipital lobe in visual and memory networks, parietal lobe in language and DMN, and sensorimotor strip in sensorimotor network, particularly on the right, compared to LPA. Conversely, LPA showed reduced connectivity in the frontal cortex in salience, memory, visual and sensorimotor networks, inferior parietal lobe in visual network, and anterior temporal pole and sensorimotor cortex in the language network, compared to PCA. Between network differences (p&lt;0.05; cluster size, FDR=0.05) were observed between groups, with PCA showing reduced connectivity between the visual and sensorimotor networks, while LPA showed reduced connectivity between the language and sensorimotor networks. The DMN was anti‐correlated to the language network in PCA, while it was positively correlated to the language network in LPA. In both phenotypes, the DMN was anticorrelated with the salience network. The visual network in PCA showed connections to all networks, while in LPA, it was only connected to the salience, language and DMN.ConclusionThe atypical AD phenotypes were associated with multiple disruptions in connectivity, both within and between brain networks. Phenotype specific differences in connectivity patterns were noted in visual network for PCA and language network for LPA.

Altered functional connectivity networks in logopenic progressive aphasia and posterior cortical atrophy

AbstractBackgroundResting state functional connectivity (rsfMRI) studies have shown functional network disruptions in logopenic progressive aphasia (LPA) (reduced connectivity within the left temporal language network) and posterior cortical atrophy (PCA) (reduced connectivity within ventral visual network). However, little is known about how these networks compare and how connectivity differs within and between networks in these atypical Alzheimer’s Disease (AD) phenotypes.MethodFifty‐nine amyloid‐positive PCA patients and eighty‐five amyloid‐positive LPA patients were recruited by the Neurodegenerative Research Group at Mayo Clinic, Rochester, MN, and underwent structural and resting state functional MRI. Spatially preprocessed data was analyzed using the CONN functional connectivity toolbox to explore the default mode network (DMN), salience, sensorimotor, left language, visual and memory networks, which were generated by averaging multiple regions‐of‐interest (ROI) within each network. The data was analyzed at both the voxel‐level and network‐level (ROI‐ROI).ResultVoxel‐level differences in functional connectivity between PCA and LPA were observed in all networks (p&lt;0.05; cluster size, FWE=0.05). PCA showed reduced connectivity in the occipital lobe in visual and memory networks, parietal lobe in language and DMN, and sensorimotor strip in sensorimotor network, particularly on the right, compared to LPA. Conversely, LPA showed reduced connectivity in the frontal cortex in salience, memory, visual and sensorimotor networks, inferior parietal lobe in visual network, and anterior temporal pole and sensorimotor cortex in the language network, compared to PCA. Between network differences (p&lt;0.05; cluster size, FDR=0.05) were observed between groups, with PCA showing reduced connectivity between the visual and sensorimotor networks, while LPA showed reduced connectivity between the language and sensorimotor networks. The DMN was anti‐correlated to the language network in PCA, while it was positively correlated to the language network in LPA. In both phenotypes, the DMN was anticorrelated with the salience network. The visual network in PCA showed connections to all networks, while in LPA, it was only connected to the salience, language and DMN.ConclusionThe atypical AD phenotypes were associated with multiple disruptions in connectivity, both within and between brain networks. Phenotype specific differences in connectivity patterns were noted in visual network for PCA and language network for LPA.

Topographic organization of the human caudate functional connectivity and age-related changes with resting-state fMRI.

The striatum is postulated to play a central role in gating cortical processing during goal-oriented behavior. While many human neuroimaging studies have treated the striatum as an undivided whole or several homogeneous compartments, some recent studies showed that its circuitry is topographically organized and has more complex relations with the cortical networks than previously assumed. Here, we took a gradient functional connectivity mapping approach that utilizes the entire anatomical space of the caudate nucleus to examine the organization of its functional relationship with the rest of the brain and how its topographic mapping changes with age. We defined the topography of the caudate functional connectivity using three publicly available resting-state fMRI datasets. We replicated and extended previous findings. First, we found two stable gradients of caudate connectivity patterns along its medial-lateral (M-L) and anterior-posterior (A-P) axes, supporting findings from previous tract-tracing studies of non-human primates that there are at least two main organizational principles within the caudate nucleus. Second, unlike previous emphasis of the A-P topology, we showed that the differential connectivity patterns along the M-L gradient of caudate are more clearly organized with the large-scale neural networks; such that brain networks associated with internal vs. external orienting behavior are respectively more closely linked to the medial vs. lateral extent of the caudate. Third, the caudate's M-L organization showed greater age-related reduction in integrity, which was further associated with age-related changes in behavioral measures of executive functions. In sum, our analysis confirmed a sometimes overlooked M-L functional connectivity gradient within the caudate nucleus, with its lateral longitudinal zone more closely linked to the frontoparietal cortical circuits and age-related changes in cognitive control. These findings provide a more precise mapping of the human caudate functional connectivity, both in terms of the gradient organization with cortical networks and age-related changes in such organization.

Resting-State Functional Connectivity in Relapsing-Remitting Multiple Sclerosis with Mild Disability: A Data-Driven, Whole-Brain Multivoxel Pattern Analysis Study.

Background: Multivoxel pattern analysis (MVPA) has emerged as a powerful unbiased approach for generating seed regions of interest (ROIs) in resting-state functional connectivity (RSFC) analysis in a data-driven manner. Studies exploring RSFC in multiple sclerosis have produced diverse and often incongruent results. Objectives: The aim of the present study was to investigate RSFC differences between people with relapsing-remitting multiple sclerosis (RRMS) and healthy controls (HC). Methods: We performed a whole-brain connectome-wide MVPA in 50 RRMS patients with expanded disability status scale ≤4 and 50 age and gender-matched HCs. Results: Significant group differences were noted in RSFC in three clusters distributed in the following regions: anterior cingulate gyrus, right middle frontal gyrus, and frontal medial cortex. Whole-brain seed-to-voxel RSFC characterization of these clusters as seed ROIs revealed network-specific abnormalities, specifically in the anterior cingulate cortex and the default mode network. Conclusions: The network-wide RSFC abnormalities we report agree with the previous findings in RRMS, the cognitive and clinical implications of which are discussed herein. Impact statement This study investigated resting-state functional connectivity (RSFC) in relapsing-remitting multiple sclerosis (RRMS) people with mild disability (expanded disability status scale ≤4). Whole-brain connectome-wide multivoxel pattern analysis was used for assessing RSFC. Compared with healthy controls, we were able to identify three regions of interest for significant differences in connectivity patterns, which were then extracted as a mask for whole-brain seed-to-voxel analysis. A reduced connectivity was noted in the RRMS group, particularly in the anterior cingulate cortex and the default mode network regions, providing insights into the RSFC abnormalities in RRMS.