Structural Connectivity Measures Research Articles

Mapping of Structure-Function Age-Related Connectivity Changes on Cognition Using Multimodal MRI

The relationship between age-related changes in brain structural connectivity (SC) and functional connectivity (FC) with cognition is not well understood. Furthermore, it is not clear whether cognition is represented via a similar spatial pattern of FC and SC or instead is mapped by distinct sets of distributed connectivity patterns. To this end, we used a longitudinal, within-subject, multimodal approach aiming to combine brain data from diffusion-weighted MRI (DW-MRI), and functional MRI (fMRI) with behavioral evaluation, to better understand how changes in FC and SC correlate with changes in cognition in a sample of older adults. FC and SC measures were derived from the multimodal scans acquired at two time points. Change in FC and SC was correlated with 13 behavioral measures of cognitive function using Partial Least Squares Correlation (PLSC). Two of the measures indicate an age-related change in cognition and the rest indicate baseline cognitive performance. FC and SC—cognition correlations were expressed across several cognitive measures, and numerous structural and functional cortical connections, mainly cingulo-opercular, dorsolateral prefrontal, somatosensory and motor, and temporo-parieto-occipital, contributed both positively and negatively to the brain-behavior relationship. Whole-brain FC and SC captured distinct and independent connections related to the cognitive measures. Overall, we examined age-related function-structure associations of the brain in a comprehensive and integrated manner, using a multimodal approach. We pointed out the behavioral relevance of age-related changes in FC and SC. Taken together, our results highlight that the heterogeneity in distributed FC and SC connectivity patterns provide unique information about the variable nature of healthy cognitive aging.

Reduced asymmetry of the hand knob area and decreased sensorimotor u-fiber connectivity in middle-aged adults with autism

Individuals with autism spectrum disorder (ASD) frequently present with impairments in motor skills (e.g., limb coordination, handwriting and balance), which are observed across the lifespan but remain largely untreated. Many adults with ASD may thus experience adverse motor outcomes in aging, when physical decline naturally occurs. The ‘hand knob’ of the sensorimotor cortex is an area that is critical for motor control of the fingers and hands. However, this region has received little attention in ASD research, especially in adults after midlife. The hand knob area of the precentral (PrChand) and postcentral (PoChand) gyri was semi-manually delineated in 49 right-handed adults (25 ASD, 24 typical comparison [TC] participants, aged 41–70 years). Using multimodal (T1-weighted, diffusion-weighted, and resting-state functional) MRI, we examined the morphology, ipsilateral connectivity and laterality of these regions. We also explored correlations between hand knob measures with motor skills and autism symptoms, and between structural and functional connectivity measures. Bayesian analyses indicated moderate evidence of group effects with greater right PrChand volume and reduced leftward laterality of PrChand and PoChand volume in the ASD relative to TC group. Furthermore, the right PoC-PrChand u-fibers showed increased mean diffusivity in the ASD group. In the ASD group, right u-fiber volume positively correlated with corresponding functional connectivity but did not survive multiple comparisons correction. Correlations of hand knob measures and behavior were observed in the ASD group but did not survive multiple comparisons correction. Our findings suggest that morphological laterality and u-fiber connectivity of the sensorimotor network, putatively involved in hand motor/premotor function, may be diminished in middle-aged adults with ASD, perhaps rendering them more vulnerable to motor decline in old age. The altered morphology may relate to atypical functional motor asymmetries found in ASD earlier in life, possibly reflecting altered functional asymmetries over time.

Structural brain connectivity in patients with restless legs syndrome: a diffusion tensor imaging study.

To evaluate alterations of global and local structural brain connectivity in patients with restless legs syndrome (RLS). Patients with primary RLS and healthy controls were recruited at a sleep center where they underwent diffusion tensor imaging (DTI) of the brain. We calculated the network measures of global and local structural brain connectivity based on the DTI in both groups using DSI studio program and a graph theory. A total of 69 patients with primary RLS and 51 healthy controls were included in the study. We found a significant difference in the global structural connectivity between the groups. The transitivity in the patients with RLS was lower than that in healthy controls (0.031 vs. 0.033, p = 0.035). Additionally, there were significant differences in the local structural connectivity between the groups. The characteristic path length (r = 0.283, p = 0.018), radius of graph (r = 0.260, p = 0.030), and diameter of graph (r = 0.280, p = 0.019) were all positively correlated with RLS severity, whereas the mean clustering coefficient (r = -0.327, p = 0.006), global efficiency (r = -0.272, p = 0.023), small-worldness index (r = -0.325, p = 0.006), and transitivity (r = -0.351, p = 0.003) were negatively correlated with RLS severity. We identified changes in the global structural connectivity of patients with RLS using graph theory based on DTI, which showed decreased segregation in the brain network compared to healthy controls. These changes are well correlated with RLS severity. We also found changes in local structural connectivity, especially in regions involved in sensorimotor function, which suggests that these areas play a pivotal role in RLS. These findings contribute to a better understanding of the pathophysiology of RLS symptoms.

Actigraphy-estimated physical activity is associated with functional and structural brain connectivity among older adults

Higher physical activity levels are associated with reduced cognitive decline among older adults; however, current understanding of underlying brain mechanisms is limited. This cross-sectional study investigated the relationship between actigraphy-estimated total volume of physical activity (TVPA) and magnetic resonance imaging (MRI) measures of white matter hyperintensities (WMH), and functional and structural brain connectivity, measured by resting-state functional MRI and diffusion tensor imaging. Study participants (N = 156, mean age = 71 years) included 136 with normal cognition and 20 with Mild Cognitive Impairment. Higher TVPA was associated with greater functional connectivity within the default-mode network and greater network modularity (a measure of network specialization), as well as with greater anisotropy and lower radial diffusion in white matter, suggesting better structural connectivity. These associations with functional and structural connectivity were independent of one another and independent of the level of vascular risk, APOE-ε4 status, cognitive reserve, and WMH volume, which were not associated with TVPA. Findings suggest that physical activity is beneficial for brain connectivity among older individuals with varying levels of risk for cognitive decline.

Complex negative emotions induced by electrical stimulation of the human hypothalamus

BackgroundStimulation of the ventromedial hypothalamic region in animals has been reported to cause attack behavior labeled as sham-rage without offering information about the internal affective state of the animal being stimulated. ObjectiveTo examine the causal effect of electrical stimulation near the ventromedial region of the human hypothalamus on the human subjective experience and map the electrophysiological connectivity of the hypothalamus with other brain regions. MethodsWe examined a patient (Subject S20_150) with intracranial electrodes implanted across 170 brain regions, including the hypothalamus. We combined direct electrical stimulation with tractography, cortico-cortical evoked potentials (CCEP), and functional connectivity using resting state intracranial electroencephalography (EEG). ResultsRecordings in the hypothalamus did not reveal any epileptic abnormalities. Electrical stimulations near the ventromedial hypothalamus induced profound shame, sadness, and fear but not rage or anger. When repeated single-pulse stimulations were delivered to the hypothalamus, significant responses were evoked in the amygdala, hippocampus, ventromedial-prefrontal and orbitofrontal cortices, anterior cingulate, as well as ventral-anterior and dorsal-posterior insula. The time to first peak of these evoked responses varied and earliest propagations correlated best with the measures of resting-state EEG connectivity and structural connectivity. ConclusionThis patient's case offers details about the affective state induced by the stimulation of the human hypothalamus and provides causal evidence relevant to current theories of emotion. The complexity of affective state induced by the stimulation of the hypothalamus and the profile of hypothalamic electrophysiological connectivity suggest that the hypothalamus and its connected structures ought to be seen as causally important for human affective experience.

White matter abnormalities in the amputation variant of body integrity dysphoria

“Body integrity dysphoria” (BID) is a severe condition affecting nonpsychotic individuals. In the amputation variant of BID, a limb may be experienced as not being part of the body, despite normal anatomical development and intact sensorimotor functions. We previously demonstrated altered brain structural (gray matter) and functional connectivity in 16 men with BID with a long-lasting and exclusive desire for left leg amputation. Here, we aimed to identify, in the same sample, altered patterns of white matter structural connectivity. Fractional anisotropy (FA), derived from diffusion tensor imaging data, was considered as a measure of structural connectivity. Results showed reduced structural connectivity of: (i) the right superior parietal lobule (rSPL) with the right cuneus, with the superior occipital and with the posterior cingulate gyri, (ii) the pars orbitalis of the right middle frontal gyrus (rMFGOrb) with the putamen, and (iii) the left middle temporal gyrus (lMTG) with the pars triangularis of the left inferior frontal gyrus. Increased connectivity was found between the right paracentral lobule (rPLC) and the right caudate nucleus. By using a complementary method of investigation, we confirmed and extended previous results from the same sample of individuals with BID, showing structural alterations between areas tuned to the processing of the sensorimotor representations of the affected leg (rPCL), and to higher-order components of bodily representation such as the body image (rSPL) and visual processing. Alongside this network for bodily awareness, other networks such as the limbic (rMFGOrb) and the mirror (lMTG) systems showed alterations in structural connectivity. These findings consolidate current understanding of the neural correlates of the amputation variant of BID, which might in turn guide diagnostics and rehabilitative treatments.

An interdisciplinary computational model for predicting traumatic brain injury: Linking biomechanics and functional neural networks

The brain is a complex network consisting of neuron cell bodies in the gray matter and their axonal projections, forming the white matter tracts. These neurons are supported by an equally complex vascular network as well as glial cells. Traumatic brain injury (TBI) can lead to the disruption of the structural and functional brain networks due to disruption of both neuronal cell bodies in the gray matter as well as their projections and supporting cells. To explore how an impact can alter the function of brain networks, we integrated a finite element (FE) brain mechanics model with linked models of brain dynamics (Kuramoto oscillator) and vascular perfusion (Balloon-Windkessel) in this study. We used empirical resting-state functional magnetic resonance imaging (MRI) data to optimize the fit of our brain dynamics and perfusion models to clinical data. Results from the FE model were used to mimic injury in these optimized brain dynamics models: injury to the nodes (gray matter) led to a decrease in the nodal oscillation frequency, while damage to the edges (axonal connections/white matter) progressively decreased coupling among connected nodes. A total of 53 cases, including 33 non-injurious and 20 concussive head impacts experienced by professional American football players were simulated using this integrated model. We examined the correlation of injury outcomes with global measures of structural connectivity, neural dynamics, and functional connectivity of the brain networks when using different lesion methods. Results show that injurious head impacts cause significant alterations in global network topology regardless of lesion methods. Changes between the disrupted and healthy functional connectivity (measured by Pearson correlation) consistently correlated well with injury outcomes (AUC≥0.75), although the predictive performance is not significantly different (p>0.05) to that of traditional kinematic measures (angular acceleration). Intriguingly, our lesion model for gray matter damage predicted increases in global efficiency and clustering coefficient with increases in injury risk, while disrupting axonal connections led to lower network efficiency and clustering. When both injury mechanisms were combined into a single injury prediction model, the injury prediction performance depended on the thresholds used to determine neurodegeneration and mechanical tolerance for axonal injury. Together, these results point towards complex effects of mechanical trauma to the brain and provide a new framework for understanding brain injury at a causal mechanistic level and developing more effective diagnostic methods and therapeutic interventions.

Transdiagnostic symptom subtypes across autism spectrum disorders and attention deficit hyperactivity disorder: validated by measures of neurocognition and structural connectivity

BackgroundsAutism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD) are neurodevelopmental disorders that exhibit within-disorder heterogeneity and cross-disorder phenotypic overlap, thus suggesting that the current disease categories may not fully represent the etiologic essence of the disorders, especially for highly comorbid neurodevelopmental disorders. In this study, we explored the subtypes of a combined sample of ASD and ADHD by integrating measurements of behavior, cognition and brain imaging.MethodsA total of 164 participants, including 65 with ASD, 47 with ADHD, and 52 controls, were recruited. Unsupervised machine learning with an agglomerative hierarchical clustering algorithm was used to identify transdiagnostic symptom clusters. Neurocognition and brain structural connectivity measurements were used to assess symptom clusters. Mediation analysis was used to explore the relationship between transdiagnostic symptoms, neurocognition and brain structural connectivity.ResultsWe identified three symptom clusters that did not fall within the diagnostic boundaries of DSM. External measurements from neurocognition and neuroimaging domains supported distinct profiles, including fine motor function, verbal fluency, and structural connectivity in the corpus callosum between these symptom clusters, highlighting possible biomarkers for ASD and ADHD. Additionally, fine motor function was shown to mediate the relationship between the corpus callosum and perseveration symptoms.ConclusionsIn this transdiagnostic study on ASD and ADHD, we identified three subtypes showing meaningful associations between symptoms, neurocognition and brain white matter structural connectivity. The fine motor function and structural connectivity of corpus callosum might be used as biomarkers for neurodevelopmental disorders with social skill symptoms. The results of this study highlighted the importance of precise phenotyping and further supported the effects of fine motor intervention on ASD and ADHD.

Glymphatic system function in patients with newly diagnosed focal epilepsy.

IntroductionThe aim of this study was to analyze the glymphatic system function and its relationship with clinical characteristics, global diffusion tensor imaging (DTI) parameters, and global structural connectivity in treatment‐naïve patients with newly diagnosed focal epilepsy.MethodsThis retrospective single‐center study investigated patients with focal epilepsy and healthy controls. All participants underwent routine brain magnetic resonance imaging and DTI. DTI analysis along the perivascular space (DTI‐ALPS) was used to evaluate glymphatic system function. We also calculated the measures of global DTI parameters, including whole‐brain fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD), and performed a graph theoretical network analysis to measure global structural connectivity.ResultsA total of 109 patients with focal epilepsy and 88 healthy controls were analyzed. There were no significant differences in the DTI‐ALPS index (1.67 vs. 1.68, p = 0.861) between the groups. However, statistically significant associations were found between the DTI‐ALPS index and age (r = ‐0.242, p = 0.01), FA (r = 0.257, p = 0.007), MD (r = −0.469, p < 0.001), AD (r = −0.303, p = 0.001), RD (r = −0.434, p < 0.001), and the assortative coefficient (r = 0.230, p = 0.016) in patients with focal epilepsy.ConclusionThe main finding of this study is that DTI‐ALPS index is significantly correlated with global DTI parameters and structural connectivity measures of the brain in patients with focal epilepsy. In addition, DTI‐ALPS index decreases with age in these patients. We conclude that the DTI‐ALPS index can be used to investigate glymphatic system function in patients with focal epilepsy.

Neural signatures of data-driven psychopathology dimensions at the transition to adolescence.

One of the challenges in human neuroscience is to uncover associations between brain organization and psychopathology in order to better understand the biological underpinnings of mental disorders. Here, we aimed to characterize the neural correlates of psychopathology dimensions obtained using two conceptually different data-driven approaches. Dimensions of psychopathology that were either maximally dissociable or correlated were respectively extracted by independent component analysis (ICA) and exploratory factor analysis (EFA) applied to the Childhood Behavior Checklist items from 9- to 10-year-olds (n=9983; 47.8% female, 50.8% white) participating in the Adolescent Brain Cognitive Development study. The patterns of brain morphometry, white matter integrity and resting-state connectivity associated with each dimension were identified using kernel-based regularized least squares and compared between dimensions using Spearman's correlation coefficient. ICA identified three psychopathology dimensions, representing opposition-disinhibition, cognitive dyscontrol, and negative affect, with distinct brain correlates. Opposition-disinhibition was negatively associated with cortical surface area, cognitive dyscontrol was negatively associated with anatomical and functional dysconnectivity while negative affect did not show discernable associations with any neuroimaging measure. EFA identified three dimensions representing broad externalizing, neurodevelopmental, and broad Internalizing problems with partially overlapping brain correlates. All EFA-derived dimensions were negatively associated with cortical surface area, whereas measures of functional and structural connectivity were associated only with the neurodevelopmental dimension. This study highlights the importance of cortical surface area and global connectivity for psychopathology in preadolescents and provides evidence for dissociable psychopathology dimensions with distinct brain correlates.

Neural substrates of psychosis revealed by altered dependencies between brain activity and white-matter architecture in individuals with 22q11 deletion syndrome

BackgroundDysconnectivity has been consistently proposed as a major key mechanism in psychosis. Indeed, disruptions in large-scale structural and functional brain networks have been associated with psychotic symptoms. However, brain activity is largely constrained by underlying white matter pathways and the study of function-structure dependency, compared to conventional unimodal analysis, allows a biologically relevant assessment of neural mechanisms. The 22q11.2 deletion syndrome (22q11DS) constitutes a remarkable opportunity to study the pathophysiological processes of psychosis. Methods58 healthy controls and 57 deletion carriers, aged from 16 to 32 years old,underwent resting-state functional and diffusion-weighted magnetic resonance imaging. Deletion carriers were additionally fully assessed for psychotic symptoms. Firstly, we used a graph signal processing method to combine brain activity and structural connectivity measures to obtain regional structural decoupling indexes (SDIs). We use SDI to assess the differences of functional structural dependency (FSD) across the groups. Subsequently we investigated how alterations in FSDs are associated with the severity of positive psychotic symptoms in participants with 22q11DS. ResultsIn line with previous findings, participants in both groups showed a spatial gradient of FSD ranging from sensory-motor regions (stronger FSD) to regions involved in higher-order function (weaker FSD). Compared to controls, in participants with 22q11DS, and further in deletion carriers with more severe positive psychotic symptoms, the functional activity was more strongly dependent on the structure in parahippocampal gyrus and subcortical dopaminergic regions, while it was less dependent within the cingulate cortex. This analysis revealed group differences not otherwise detected when assessing the structural and functional nodal measures separately. ConclusionsOur findings point toward a disrupted modulation of functional activity on the underlying structure, which was further associated to psychopathology for candidate critical regions in 22q11DS. This study provides the first evidence for the clinical relevance of function-structure dependency and its contribution to the emergence of psychosis.

Structural and functional connectivity uniquely contribute to explained variance in episodic memory performance in cognitively normal older adults

AbstractBackgroundGiven mounting evidence that AD‐related neuropathological changes may be present in cognitively normal individuals, there is a need to examine brain biomarkers related to variability in cognition that may precede cognitive decline. Although prior studies demonstrate age‐related changes in structural connectivity (SC) and functional connectivity (FC) separately (Contreras et al., 2015), few have adopted a multimodal approach to test the potential interplay between SC and FC, and their relative associations with cognition. Here, we examined the independent contributions of SC and FC to individual differences in episodic memory performance in cognitively normal older adults.MethodThis cross‐sectional study included 107 cognitively normal participants from the BIOCARD study. SC was indexed using radial diffusivity (RD) and mean diffusivity (MD) of two limbic white matter tracts (fornix and hippocampal cingulum), as measured by diffusion‐weighted MRI. FC within five large‐scale brain networks (control, default, limbic, dorsal attention, and salience/ventral attention) was derived using resting state fMRI. Hierarchical linear regression was utilized to directly compare the relative contributions of SC and FC to individual variability in a composite delayed episodic memory score, while also accounting for age, sex, cerebrospinal fluid (CSF) Aß42 and total tau, and gray matter volumes of the entorhinal cortex and hippocampus.ResultsWhen all five FC networks were included in the regression, only the salience network emerged as a significant FC predictor. Therefore, we performed a follow‐up analysis with salience network connectivity as the only FC measure of interest. In this model, the addition of both SC and FC measures (but not CSF or gray matter volumes) significantly increased the proportion of explained variance in memory performance, and all three measures (fornix/hippocampal cingulum microstructure, and salience network connectivity) were significant independent predictors of memory performance.ConclusionThese findings demonstrate that both connectivity modalities make unique contributions to episodic memory performance, but CSF and gray mater volumes do not. Furthermore, the highest proportion of explained variance was achieved when both modalities were included in the model, suggesting that the combination of SC and FC markers best accounts for individual variability in episodic memory in cognitively normal older adults.

Schizophrenia Classification Using Resting State EEG Functional Connectivity: Source Level Outperforms Sensor Level.

Disrupted functional and structural connectivity measures have been used to distinguish schizophrenia patients from healthy controls. Classification methods based on functional connectivity derived from EEG signals are limited by the volume conduction problem. Recorded time series at scalp electrodes capture a mixture of common sources signals, resulting in spurious connections. We have transformed sensor level resting state EEG times series to source level EEG signals utilizing a source reconstruction method. Functional connectivity networks were calculated by computing phase lag values between brain regions at both the sensor and source level. Brain complex network analysis was used to extract features and the best features were selected by a feature selection method. A logistic regression classifier was used to distinguish schizophrenia patients from healthy controls at five different frequency bands. The best classifier performance was based on connectivity measures derived from the source space and the theta band.The transformation of scalp EEG signals to source signals combined with functional connectivity analysis may provide superior features for machine learning applications.

Targeting Default Mode Network Dysfunction in Persons at Risk of Alzheimer's Disease with Transcranial Magnetic Stimulation (NEST4AD): Rationale and Study Design.

Default mode network (DMN) dysfunction is well established in Alzheimer's disease (AD) and documented in both preclinical stages and at-risk subjects, thus representing a potential disease target. Multi-sessions of repetitive transcranial magnetic stimulation (rTMS) seem capable of modulating DMN dynamics and memory in healthy individuals and AD patients; however, the potential of this approach in at-risk subjects has yet to be tested. This study will test the effect of rTMS on the DMN in healthy older individuals carrying the strongest genetic risk factor for AD, the Apolipoprotein E (APOE) ɛ4 allele. We will recruit 64 older participants without cognitive deficits, 32 APOE ɛ4 allele carriers and 32 non-carriers as a reference group. Participants will undergo four rTMS sessions of active (high frequency) or sham DMN stimulation. Multimodal imaging exam (including structural, resting-state, and task functional MRI, and diffusion tensor imaging), TMS with concurrent electroencephalography (TMS-EEG), and cognitive assessment will be performed at baseline and after the stimulation sessions. We will assess changes in DMN connectivity with resting-state functional MRI and TMS-EEG, as well as changes in memory performance in APOE ɛ4 carriers. We will also investigate the mechanisms underlying DMN modulation through the assessment of correlations with measures of neuronal activity, excitability, and structural connectivity with multimodal imaging. The results of this study will inform on the physiological and cognitive outcomes of DMN stimulation in subjects at risk for AD and on the possible mechanisms. These results may outline the design of future non-pharmacological preventive interventions for AD.

Brain networks in migraine with and without aura: An exploratory arterial spin labeling MRI study.

The aim of this exploratory study was to investigate the underlying pathomechanisms of migraine with aura (MA) and migraine without aura (MO) in the interictal phase using a connectivity analysis. We prospectively enrolled patients who were newly diagnosed with migraine. All patients underwent brain MRI, including diffusion tensor imaging and arterial spin labeling perfusion MRI. We analyzed the differences between patients with MA and those with MO in structural connectivity based on diffusion tensor imaging and functional connectivity based on arterial spin labeling perfusion MRI using a graph theoretical analysis. We enrolled 58 patients with migraine (11 patients with MA and 47 patients with MO). There were no differences between patients with MA and those with MO in the network measures of global structural connectivity. However, differences in global functional connectivity were found between the two groups. The assortative coefficient was lower in patients with MA than in those with MO (-0.050 vs. -0.012, p=.017). There were no differences in local structural and functional connectivity between patients with MA and those with MO. We found differences in global functional connectivity between patients with MO and those with MA. The study of MA and MO using a connectivity analysis may shed light on migraine pathophysiology. We suggest it is worthwhile to investigate if changes in functional connectivity may serve as novel biomarkers in MA. In this regard, ASL MRI appears to be valuable in the context of network analysis, but further studies are needed to confirm our findings.

Disrupted Structural Brain Connectome Is Related to Cognitive Impairment in Patients With Ischemic Leukoaraiosis.

Ischemic leukoaraiosis (ILA) is related to cognitive impairment and vascular dementia in the elderly. One possible mechanism could be the disruption of white matter (WM) tracts and network function that connect distributed brain regions involved in cognition. The purpose of this study was to investigate the relationship between structural connectome and cognitive functions in ILA patients. A total of 89 patients with ILA (Fazekas score ≥ 3) and 90 healthy controls (HCs) underwent comprehensive neuropsychological examinations and diffusion tensor imaging scans. The tract-based spatial statistics approach was employed to investigate the WM integrity. Graph theoretical analysis was further applied to construct the topological architecture of the structural connectome in ILA patients. Partial correlation analysis was used to investigate the relationships between network measures and cognitive performances in the ILA group. Compared with HCs, the ILA patients showed widespread WM integrity disruptions. The ILA group displayed increased characteristic path length (Lp) and decreased global network efficiency at the level of the whole brain relative to HCs, and reduced nodal efficiencies, predominantly in the frontal–subcortical and limbic system regions. Furthermore, these structural connectomic alterations were associated with cognitive impairment in ILA patients. The association between WM changes (i.e., fractional anisotropy and mean diffusivity measures) and cognitive function was mediated by the structural connectivity measures (i.e., local network efficiency and Lp). In conclusion, cognitive impairment in ILA patients is related to microstructural disruption of multiple WM fibers and topological disorganization of structural networks, which have implications in understanding the relationship between ILA and the possible attendant cognitive impairment.

Temporal lobe epilepsy with or without hippocampal sclerosis: Structural and functional connectivity using advanced MRI techniques.

The aim of this study was to investigate the differences in structural connectivity based on diffusion tensor imaging (DTI) and functional connectivity based on arterial spin labeling (ASL) MRI between temporal lobe epilepsy (TLE) patients with and without hippocampal sclerosis (HS). We enrolled 50 patients with TLE, including 25 patients with HS and 25 patients without HS, who underwent brain MRI, including DTI and ASL. We calculated the network parameters of structural connectivity based on DTI and functional connectivity based on ASL using a graph theoretical analysis. The parameters included global network measures (radius, diameter, characteristic path length, global efficiency, local efficiency, mean clustering coefficient, transitivity, assortative coefficient, and small-worldness index) and a local network measure (betweenness centrality). The global and local network measures of structural connectivity were not different between TLE patients with and without HS. However, significant differences in functional connectivity existed between the two groups. The radius and diameter of the global network measures in the TLE patients with HS were significantly increased compared with those without HS (4.140 vs. 3.140, p = 0.045; 6.812 vs. 5.132, p = 0.049; respectively). No differences were detected between other global network measures of functional connectivity and local network measure. Significant differences in global network measures of functional connectivity based on ASL existed between TLE patients with and without HS. These findings suggest that TLE patients with HS exhibit a more disconnected functional brain network than those without HS.

Evaluation of a connectivity-based imaging metric that reflects functional decline in Multiple Sclerosis.

Cognitive impairment is a common symptom in individuals with Multiple Sclerosis (MS), but meaningful, reliable biomarkers relating to cognitive decline have been elusive, making evaluation of the impact of therapeutics on cognitive function difficult. Here, we combine pathway-based MRI measures of structural and functional connectivity to construct a metric of functional decline in MS. The Structural and Functional Connectivity Index (SFCI) is proposed as a simple, z-scored metric of structural and functional connectivity, where changes in the metric have a simple statistical interpretation and may be suitable for use in clinical trials. Using data collected at six time points from a 2-year longitudinal study of 20 participants with MS and 9 age- and sex-matched healthy controls, we probe two common symptomatic domains, motor and cognitive function, by measuring structural and functional connectivity in the transcallosal motor pathway and posterior cingulum bundle. The SFCI is significantly lower in participants with MS compared to controls (p = 0.009) and shows a significant decrease over time in MS (p = 0.012). The change in SFCI over two years performed favorably compared to measures of brain parenchymal fraction and lesion volume, relating to follow-up measures of processing speed (r = 0.60, p = 0.005), verbal fluency (r = 0.57, p = 0.009), and score on the Multiple Sclerosis Functional Composite (r = 0.67, p = 0.003). These initial results show that the SFCI is a suitable metric for longitudinal evaluation of functional decline in MS.

Neural substrates of neuropsychological profiles in dystrophynopathies: A pilot study of diffusion tractography imaging.

IntroductionCognitive difficulties and neuropsychological alterations in Duchenne and Becker muscular dystrophy (DMD, BMD) boys are not yet sufficiently explored, although this topic could have a relevant impact, finding novel biomarkers of disease both at genetics and neuroimaging point of view. The current study aims to: 1) analyze the neuropsychological profile of a group of DMD and BMD boys without cognitive impairment with an assessment of their executive functions; 2) explore the structural connectivity in DMD, BMD, and age-matched controls focusing on cortico-subcortical tracts that connect frontal cortex, basal ganglia, and cerebellum via the thalamus; 3) explore possible correlations between altered structural connectivity and clinical neuropsychological measures.Materials and methodsThis pilot study included 15 boys (5 DMD subjects, 5 BMD subjects, and 5 age-matched typically developing, TD). They were assessed using a neuropsychological assessment protocol including cognitive and executive functioning assessment and performed a 1.5T MRI brain exam including advance Diffusion Weighted Imaging (DWI) method for tractography. Structural connectivity measurements were extracted along three specific tracts: Cortico-Ponto-Cerebellar Tract (CPCT), Cerebellar-Thalamic Tract (CTT), and Superior Longitudinal Fasciculus (SLF). Cortical-Spinal Tract (CST) was selected for reference, as control tract.ResultsRegarding intellectual functioning, a major impairment in executive functions compared to the general intellectual functioning was observed both for DMD (mean score = 86.20; SD = 11.54) and for BMD children (mean score = 88; SD = 3.67). Mean FA resulted tendentially always lower in DMD compared to both BMD and TD groups for all the examined tracts. The differences in FA were statistically significant for the right CTT (DMD vs BMD, p = 0.002, and DMD vs TD, p = 0.0015) and the right CPCT (DMD vs TD, p = 0.008). Concerning DMD, significant correlations emerged between FA-R-CTT and intellectual quotients (FIQ, p = 0.044; ρs = 0.821), and executive functions (Denomination Total, p = 0.044, ρs = 0.821; Inhibition Total, p = 0.019, ρs = 0.900). BMD showed a significant correlation between FA-R-CPCT and working memory index (p = 0.007; ρs = 0.949).Discussion and conclusionIn this pilot study, despite the limitation of sample size, the findings support the hypothesis of the involvement of a cerebellar-thalamo-cortical loop for the neuropsychological profile of DMD, as the CTT and the CPCT are involved in the network and the related brain structures are known to be implied in executive functions. Our results suggest that altered WM connectivity and reduced fibre organization in cerebellar tracts, probably due to the lack of dystrophin in the brain, may render less efficient some neuropsychological functions in children affected by dystrophinopathies. The wider multicentric study could help to better establish the role of cerebellar connectivity in neuropsychological profile for dystrophinopathies, identifying possible novel diagnostic and prognostic biomarkers.

Multimodal neurocognitive markers of frontal lobe epilepsy: Insights from ecological text processing

The pressing call to detect sensitive cognitive markers of frontal lobe epilepsy (FLE) remains poorly addressed. Standard frameworks prove nosologically unspecific (as they reveal deficits that also emerge across other epilepsy subtypes), possess low ecological validity, and are rarely supported by multimodal neuroimaging assessments. To bridge these gaps, we examined naturalistic action and non-action text comprehension, combined with structural and functional connectivity measures, in 19 FLE patients, 19 healthy controls, and 20 posterior cortex epilepsy (PCE) patients. Our analyses integrated inferential statistics and data-driven machine-learning classifiers. FLE patients were selectively and specifically impaired in action comprehension, irrespective of their neuropsychological profile. These deficits selectively and specifically correlated with (a) reduced integrity of the anterior thalamic radiation, a subcortical structure underlying motoric and action-language processing as well as epileptic seizure spread in this subtype; and (b) hypoconnectivity between the primary motor cortex and the left-parietal/supramarginal regions, two putative substrates of action-language comprehension. Moreover, machine-learning classifiers based on the above neurocognitive measures yielded 75% accuracy rates in discriminating individual FLE patients from both controls and PCE patients. Briefly, action-text assessments, combined with structural and functional connectivity measures, seem to capture ecological cognitive deficits that are specific to FLE, opening new avenues for discriminatory characterizations among epilepsy types.