Challenging functional connectivity data: machine learning application on essential tremor recognition.

BACKGROUND AND AIMS: This paper aimed to investigate the usefulness of applying machine learning on resting-state fMRI connectivity data to recognize the pattern of functional changes in essential tremor (ET), a disease characterized by slight brain abnormalities, often difficult to detect using univariate analysis. METHODS: We trained a support vector machine with a radial kernel on the mean signals extracted by 14 brain networks obtained from resting-state fMRI scans of 18 ET and 19 healthy control (CTRL) subjects. Classification performance between pathological and control subjects was evaluated using a tenfold cross-validation. Recursive feature elimination was performed to rank the importance of the extracted features. Moreover, univariate analysis using Mann-Whitney U test was also performed. RESULTS: The machine learning algorithm achieved an AUC of 0.75, with four networks (language, primary visual, cerebellum, and attention), which have an essential role in ET pathophysiology, being selected as the most important features for classification. By contrast, the univariate analysis was not able to find significant results among these two conditions. CONCLUSION: The machine learning approach identifies the changes in functional connectivity of ET patients, representing a promising instrument to discriminate specific pathological conditions and find novel functional biomarkers in resting-state fMRI studies.

Cognitive functioning in essential tremor without dementia: a clinical and imaging study.

BACKGROUND AND AIMS: To explore the cognitive functioning of ET patients without dementia and delineate its imaging counterpart. METHODS: We enrolled 99 subjects (49 non-demented ET patients and 50 education-matched healthy controls) that underwent neuropsychological and MRI evaluation. In order to identify the cognitive parameters that better reflect the profile of ET patients, we used a double statistical approach: (i) direct comparison between groups and (ii) machine learning approach with feature selection. Then, to evaluate the correlation between cognitive performances and the degree of brain atrophy in the ET group, we included the results derived from the uni- and multivariate analysis in whole-brain voxel-based morphometry (VBM) model. RESULTS: In ET patients, the univariate analysis showed differences in cognitive tests evaluating executive functions (FAB, MCST-CA), verbal memory-delayed recall (RAVLT-DR), and working memory (Digit Span B). The relative scores were significantly worse compared to controls, although within the normal range (subclinical dysfunctions). The machine learning approach also provided similar findings: tests exploring the executive functions, verbal memory, and language (RAVLT-DR, FAB, COWAT, RAVLT-IR, TOKEN) showed the highest importance rank in classification's task. Regardless of the explored test, the MRI analysis revealed a correlation (p < 0.005 uncorrected, whole brain) between test scores and widespread areas including cerebellum, inferior and middle frontal cortices, cingulate cortices, and temporal cortex. CONCLUSION: This study improves the knowledge on cognitive impairment in ET, as our findings demonstrate a heterogeneous pattern of cognitive dysfunction involving memory, executive function, and language domains in the ET group. This clinical profile relates with the deep involvement of the cerebellum and its connections with large-scale brain structures, suggesting that changes spreading in wide-ranging brain pathways may contribute to the physiopathology of cognitive dysfunction in ET.

One Hour-Post-load Plasma Glucose ≥155 mg/dl in Healthy Glucose Normotolerant Subjects Is Associated With Subcortical Brain MRI Alterations and Impaired Cognition: A Pilot Study.

Background: Glucose alterations are associated with impaired cognition. The 1-h-post-load plasma glucose ≥155 mg/dl in non-diabetic subjects confers an increased risk of cardiovascular events and diabetes. This pilot study aimed to investigate whether the 1-h-post-load plasma glucose ≥155 mg/dl negatively affects the subcortical regions of the brain and the cognitive functions. Methods: We enrolled 32 non-diabetic subjects. Patients were divided into two groups based on 1-h- post-load plasma glucose value > or < 155 mg/dl: normal glucose tolerance (NGT) 1-h-high and NGT 1-h-low subjects. All subjects underwent 3 Tesla MRI and standard neuropsychological tests. Results: NGT 1-h-high subjects showed significantly lower values of both right (4.9 ± 0.9 vs. 5.1 ± 0.9 ml) and left (4.8 ± 1.1 vs. 5.1 ± 1.1 ml) hippocampal hemisphere volume, while right hemisphere hippocampal diffusivity was lower in the NGT 1-h-high group (10.0 ± 0.6 vs. 10.6 ± 0.5 10-4 mm2s-1). NGT 1-h-high subjects also showed a poorer memory performance. In particular, for both Rey Auditory Verbal Learning Task (RAVLT)-immediate-recall and Free and Cued Selective Reminding Test (FCSRT)-delayed total recall, we found lower cognitive test scores in the NGT-1 h-high group (26.5 ± 6.3 and 10.4 ± 0.3, respectively). Conclusions: One-hour-post-load hyperglycemia is associated with morpho-functional subcortical brain alterations and poor memory performance tests.

Neuropsychological assessment could distinguish among different clinical phenotypes of progressive supranuclear palsy: A Machine Learning approach.

Progressive supranuclear palsy (PSP) is a rare, rapidly progressive neurodegenerative disease. Richardson's syndrome (PSP-RS) and predominant parkinsonism (PSP-P) are characterized by wide range of cognitive and behavioural disturbances, but these variants show similar cognitive pattern of alterations, leading difficult differential diagnosis. For this reason, we explored with an Artificial Intelligence approach, whether cognitive impairment could differentiate the phenotypes. Forty Parkinson's disease (PD) patients, 25 PSP-P, 40 PSP-RS, and 34 controls were enrolled following the consensus criteria diagnosis. Participants were evaluated with neuropsychological battery for cognitive domains. Random Forest models were used for exploring the discriminant power of the cognitive tests in distinguishing among the four groups. The classifiers for distinguishing diseases from controls reached high accuracies (86% for PD, 95% for PSP-P, 99% for PSP-RS). Regarding the differential diagnosis, PD was discriminated from PSP-P with 91% (important variables: HAMA, MMSE, JLO, RAVLT_I, BDI-II) and from PSP-RS with 92% (important variables: COWAT, JLO, FAB). PSP-P was distinguished from PSP-RS with 84% (important variables: JLO, WCFST, RAVLT_I, Digit span_F). This study revealed that PSP-P, PSP-RS and PD had peculiar cognitive deficits compared with healthy subjects, from which they were discriminated with optimal accuracies. Moreover, high accuracies were reached also in differential diagnosis. Most importantly, Machine Learning resulted to be useful to the clinical neuropsychologist in choosing the most appropriate neuropsychological tests for the cognitive evaluation of PSP patients.

Hippocampal impairment in patients with Essential Tremor.

INTRODUCTION: There is growing evidence that a proportion of patients with Essential Tremor (ET) may develop a memory impairment over time. However, no studies have evaluated whether hippocampal damage really occur in ET. This study investigated the macro and micro-structural integrity of the hippocampus in ET subjects using a multimodal MRI approach. METHODS: Neuropsychological and MRI data were acquired from 110 participants (60 patients with ET and 50 age-, sex-, and education-matched healthy controls [HC]). Whole-brain T1-weighted and Diffusion Tensor Imaging (DTI) were performed to assess macro-and microstructural alterations. MRI parameters (volume; mean diffusivity [MD]; fractional anisotropy [FA]) of bilateral hippocampi were obtained. In order to evaluate the relationship between MRI alterations and neurocognitive impairment, hippocampal parameters were also correlated with cognitive test scores. RESULTS: Compared to controls, ET patients showed a subclinical memory impairment with significantly lower memory scores, but within the normal ranges. Despite the subclinical damage, however, ET patients showed a significant increase in MD values in the bilateral hippocampi in comparison with HC. A significant correlation was also found between MD and memory scores in ET. CONCLUSION: This study improves the knowledge on memory impairment in ET, as our results demonstrate for the first time the hippocampal microstructural damage related to subclinical memory impairment in ET patients. Further studies are needed before these findings can be considered predictive of a distinct ET subtype or suggestive of a co-occurent dementia.

The embodiment of language in tremor-dominant Parkinson's disease patients.

According to embodied cognition, processing language with motor content involves a simulation of this content by the brain motor system. Patients with brain lesions involving the motor system are characterized by deficits in action verbs processing in the absence of dementia. We sought to assess whether action verbs interfere with the motor behavior of patients with Parkinson's disease (PD) having tremor dominant symptoms. PD tremor is considered to result from dysfunction of cortical-subcortical motor circuits driven by dopamine depletion. In addition, PD tremor is reduced during active movement execution. Therefore, likewise movement execution, the motor simulation of bodily actions predicted by the embodiment may show to be effective in modifying tremor by interfering with a dysfunctional motor system. Here, we asked to simply read and repeat words expressing a hand-related bodily action. Abstract verbs served as control. Changes in tremor kinematics were evaluated using a monoaxial accelerometer. Seventeen PD patients with rest tremor of the upper limbs were enrolled. Tremor amplitude was significantly smaller when reading action verbs as compared to abstract verbs. We provide empirical evidence supporting the embodied cognition theory by showing that circuits mediating tremor of PD patients are distinctively affected by processing action language.

Functional activity changes in memory and emotional systems of healthy subjects with déjà vu.

Déjà vu (DV) is a fascinating and mysterious human experience that has attracted interest from psychologists and neuroscientists for over a century. In recent years, several studies have been conducted to unravel the psychological and neurological correlates of this phenomenon. However, the neural mechanisms underlying the DV experience in benign manifestations are still poorly understood. Thirty-three healthy volunteers completed an extensive neuropsychiatric and neuropsychological battery including personality evaluation. The presence of DV was assessed with the Inventory for Deja vu Experiences Assessment. Participants underwent episodic memory learning test, and 2 days later during event-related functional magnetic resonance imaging (fMRI), they are asked to rate old and new pictures as a novel, moderately/very familiar, or recollected. We identified 18 subjects with DV (DV+) and 15 without DV (DV-) matched for demographical, neuropsychological, and personality characteristics. At a behavioral level, no significant difference was detected in the episodic memory tasks between DV+ and DV-. Functional magnetic resonance imaging analysis revealed that DV+, independently from task conditions, were characterized by increased activity of the bilateral insula coupled with reduced activation in the right parahippocampal, both hippocampi, superior/middle temporal gyri, thalami, caudate nuclei, and superior frontal gyri with respect to DV-. Our study demonstrates that individuals who experienced DV are not characterized by different performance underlying familiarity/recollection memory processes. However, fMRI results provide evidence that the physiological DV experience is associated with the employment of different neural responses of brain regions involved in memory and emotional processes.

REM-Sleep Behavior Disorder in Patients With Essential Tremor: What Is Its Clinical Significance?

Objective: REM sleep behavior disorder (RBD) is an important risk factor for the dementia development and for the deterioration of autonomic functions in patients with Parkinson's Disease. RBD has also been reported in patients with Essential Tremor (ET). However, its clinical significance in ET remains still unknown. We aimed to investigate clinical, neuropsychological and cardiac autonomic scintigraphic differences between ET patients with and without RBD. Methods: To assess RBD symptoms, RBD Single-Question has been administered in a cohort of 55 patients with a clinical diagnosis of ET. Patients with clinical RBD underwent polysomnography (PSG) confirmation. All patients completed a battery of neuropsychological assessment of memory, executive function, attention, language, and visuospatial function. Cardiac MIBG scintigraphy was performed in order to measure the cardiac autonomic innervation. Results: Ten ET patients (18%) had a PSG-confirmed RBD (ETRBD+). Compared to ET patients without RBD (ETRBD-), significantly reduced scores on memory domain tests such as Rey auditory verbal learning test immediate recall (p = 0.015) and Rey auditory verbal learning test delayed recall (p = 0.004) and phonemic fluency test (p = 0.028) were present in ETRBD+. By contrast, no other significant clinical difference has emerged from the comparison between two ET groups. Similarly, ETRBD+ patients have cardiac MIBG tracer uptake in the normal value range as occurred in those with ETRBD-. Conclusions: This study improves the knowledge on clinical significance of RBD symptoms in ET patients. Our preliminary findings demonstrate that presence of RBD in ET is associated with neurocognitive impairment, but not with cardiac autonomic dysfunction. Further longitudinal studies are needed to investigate whether ET patients with RBD will develop a frank dementia over the time.

Evaluation of machine learning algorithms performance for the prediction of early multiple sclerosis from resting-state FMRI connectivity data.

Machine Learning application on clinical data in order to support diagnosis and prognostic evaluation arouses growing interest in scientific community. However, choice of right algorithm to use was fundamental to perform reliable and robust classification. Our study aimed to explore if different kinds of Machine Learning technique could be effective to support early diagnosis of Multiple Sclerosis and which of them presented best performance in distinguishing Multiple Sclerosis patients from control subjects. We selected following algorithms: Random Forest, Support Vector Machine, Naïve-Bayes, K-nearest-neighbor and Artificial Neural Network. We applied the Independent Component Analysis to resting-state functional-MRI sequence to identify brain networks. We found 15 networks, from which we extracted the mean signals used into classification. We performed feature selection tasks in all algorithms to obtain the most important variables. We showed that best discriminant network between controls and early Multiple Sclerosis, was the sensori-motor I, according to early manifestation of motor/sensorial deficits in Multiple Sclerosis. Moreover, in classification performance, Random Forest and Support Vector Machine showed same 5-fold cross-validation accuracies (85.7%) using only this network, resulting to be best approaches. We believe that these findings could represent encouraging step toward the translation to clinical diagnosis and prognosis.

In vivo evidence for decreased scyllo-inositol levels in the supplementary motor area of patients with Progressive Supranuclear Palsy: A proton MR spectroscopy study.

INTRODUCTION: Several structural and functional neuroimaging studies have shown that the Supplementary Motor Area (SMA) is affected by tau pathology in patients with Progressive Supranuclear Palsy (PSP). The aim of the study was to investigate the biochemical profile of SMA in PSP patients, using proton magnetic resonance spectroscopy (1H-MRS). METHODS: Sixteen PSP patients and 18 healthy controls participated in this study. 1H-MRS was performed by using a Point RESolving Spectroscopy (PRESS) single-voxel sequence implemented on a 3-T scanner. A voxel of 25 × 25 × 15 mm involving the right and left SMA was acquired in all subjects. Peak areas of N-acetyl-aspartate + N-acetyl-aspartyl-glutamate (NAA), creatine with phosphocreatine (Cr), glycerophosphocholine + phosphocholine (Cho), glutamate + glutamine (Glx), glutathione (GSH), myo-Inositol (mI) and Scyllo-Inositol (Scyllo) were calculated using a version 6.3-1K of the fitting program LCModel. Comparative analysis was performed on both absolute concentrations and ratio values relative to Cr. RESULTS: PSP patients showed a significant decrease in Scyllo concentration and Scyllo/Cr ratio values in SMA, compared to controls, whereas no difference between groups was found for the other ratio values. Of note, the attention and working memory functions were positively related to Scyllo and Scyllo/Cr values in PSP patients. CONCLUSIONS: Our study demonstrates that Scyllo and Scyllo/Cr were significantly reduced in the SMA of PSP patients. Because Scyllo seems to be able to protect against formation of toxic fibrils of amyloid-beta fragments and tau oligomers deposition, these preliminary findings may open new perspectives to investigate Scyllo as a new potential disease-modifying therapy for PSP.

A new MR imaging index for differentiation of progressive supranuclear palsy-parkinsonism from Parkinson's disease.

INTRODUCTION: Differentiating clinically progressive supranuclear palsy-parkinsonism (PSP-P) from Parkinson's disease (PD) may be challenging, especially in the absence of vertical supranuclear gaze palsy (VSGP). The Magnetic Resonance Parkinsonism Index (MRPI) has been reported to accurately distinguish between PSP and PD, yet few data exist on the usefulness of this biomarker for the differentiation of PSP-P from PD. METHODS: Thirty-four patients with PSP-P, 46 with PSP-Richardson's syndrome (PSP-RS), 53 with PD, and 53 controls were enrolled. New consensus criteria for the clinical diagnosis of PSP were used as the reference standard. The MRPI, and a new index termed MRPI 2.0 including the measurement of the third ventricle width (MRPI multiplied by third ventricle width/frontal horns width ratio), were calculated on T1-weighted MR images. RESULTS: The MRPI differentiated patients with PSP-P from those with PD with sensitivity and specificity of 73.5% and 98.1%, respectively, while the MRPI 2.0 showed higher sensitivity (100%) and similar specificity (94.3%) in differentiating between these two groups. Both biomarkers showed excellent performance in differentiating PSP-P patients with VSGP from those with PD, but the MRPI 2.0 was much more accurate (95.8%) than MRPI in differentiating PSP-P patients with slowness of vertical saccades from PD patients. CONCLUSION: The MRPI 2.0 accurately differentiated PSP-P patients from those with PD. This new index was more powerful than MRPI in differentiating PSP patients in the early stage of the disease with slowness of vertical saccades from patients with PD, thus helping clinicians to consolidate the diagnosis based on clinical features, in vivo.

Multimodal assessment of normal-appearing corpus callosum is a useful marker of disability in relapsing-remitting multiple sclerosis: an MRI cluster analysis study.

BACKGROUND AND PURPOSE: Corpus callosum (CC) is frequently involved in relapsing-remitting multiple sclerosis (RRMS). Magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) allow to study CC macrostructural and microstructural tissue integrity. Here, we applied a data-driven approach to MRI and DTI data of normal-appearing CC in RRMS subjects, and subsequently evaluated if differences in tissue integrity corresponded to different levels of physical disability and cognitive impairment. METHODS: 74 RRMS patients and 20 healthy controls (HC) underwent 3 T MRI and DTI. Thickness and fractional anisotropy (FA) along midsagittal CC were extracted, and values from RRMS patients were fed to a hierarchical clustering algorithm. We then used ANOVA to test for differences in clinical and cognitive variables across the imaging-based clusters and HC. RESULTS: We found three distinct MRI-based subgroups of RRMS patients with increasing severity of CC damage. The first subgroup showed callosal integrity similar to HC (Cluster 1); Cluster 2 had milder callosal damage; a third subgroup showed the most severe callosal damage (Cluster 3). Cluster 3 included patients with longer disease duration and worst scores in Expanded Disability Status Scale. Cognitive domains of verbal memory, executive functions and processing speed were impaired in Cluster 3 and Cluster 2 compared to Cluster 1 and HC. CONCLUSIONS: Within the same homogeneous cohort of patients, we could identify three neuroimaging RRMS clusters characterized by different involvement of normal-appearing CC. Interestingly, these corresponded to three distinct levels of clinical and cognitive disability.

Relationship between Hippocampal Subfields and Category Cued Recall in AD and PDD: A Multimodal MRI Study.

Alzheimer's disease (AD) and Parkinson's disease with dementia (PDD) are characterized by a different mnesic failure, particularly in memory cued recall. Although hippocampal involvement has been shown in both these diseases, it remains unknown whether a selective damage of specific subfields within the hippocampus may be responsible for the peculiar mnesic profile observed in AD and PDD. To explore this topic, we combined a multimodal 3 T-MRI hippocampal evaluation (whole-brain T1-weighted and diffusion tensor imaging) with a hippocampal-targeted neuropsychological assessment (Free and Cued Selective Reminding Test [FCSRT]) in 22 AD subjects, 18 PDD and 17 healthy controls. Macro- and microstructural features (volume; shape; mean diffusivity [MD]; fractional anisotropy [FA]) of bilateral hippocampi (whole and subfields) were obtained. Correlations between MRI-derived parameters and neuropsychological evaluations were performed. In the comparison between AD and PDD, the multimodal analysis allowed us to identify that subiculum, CA1 and CA4-DG were differently involved in these diseases and correlated with immediate and delayed total recall items of FCSRT. Moreover, compared to controls, AD showed a reduction in almost all subfields, with a MD increase in the same regions, whereas PDD displayed a volume loss, less severe than AD, more evident in the CA2-3 and presubiculum subfields. Our study provides new evidence that hippocampal subregions had different vulnerability to damage related to AD and PDD. The combination of the in vivo analysis of hippocampal subfields with the FCSRT paradigm provided important insights into whether changes within specific hippocampal subfields are related to the different mnesic profile in AD and PDD patients.

Processing graspable object images and their nouns is impaired in Parkinson's disease patients.

According to embodiment, the recruitment of the motor system is necessary to process language material expressing a motor content. Coherently, an impairment of the motor system should affect the capacity to process language items with a motor content. The aim of the present study was to assess the capacity to process graspable objects and their nouns in Parkinson's disease (PD) patients and healthy controls. Participants saw photos and nouns depicting graspable and non-graspable objects. Scrambled images and pseudo-words served as control stimuli. At 150 msec after stimulus presentation, they had to respond when the stimulus referred to a real object, and refrain from responding when it was meaningless (go-no go paradigm). In the control group, participants gave slower motor responses for stimuli (both photos and nouns) related to graspable objects as compared to non-graspable ones. This in keeping with data obtained in a previous study with young healthy participants. In the PD group, motor responses were similar for both graspable and non-graspable items. Moreover, error number was significantly greater than in controls. These findings support the notion that when the motor circuits are lesioned, like in PD, patients do not show the typical modulation of motor responses and have troubles in processing graspable objects and their nouns.

MR parkinsonism index predicts vertical supranuclear gaze palsy in patients with PSP-parkinsonism.

OBJECTIVE: To identify a biomarker for predicting the appearance of vertical supranuclear gaze palsy (VSGP) in patients affected by progressive supranuclear palsy-parkinsonism (PSP-P). METHODS: Twenty-four patients with PSP-P were enrolled in the current study. Patients were clinically followed up every 6 months until the appearance of VSGP or the end of the follow-up (4 years). Participants underwent MRI at baseline and at the end of follow-up. Magnetic resonance parkinsonism index (MRPI), an imaging measure useful for diagnosing PSP, was calculated. RESULTS: Twenty-one patients with PSP-P completed follow-up, and 3 patients dropped out. Eleven of 21 patients with PSP-P developed VSGP after a mean follow-up period of 28.5 months (range 6-48 months), while the remaining 10 patients with PSP-P did not develop VSGP during the 4-year follow-up period. At baseline, patients with PSP-P who later developed VSGP had MRPI values significantly higher than those of patients not developing VSGP without overlapping values between the 2 groups. MRPI showed a higher accuracy (100%) in predicting VSGP than vertical ocular slowness (accuracy 33.3%) or postural instability with or without vertical ocular slowness (accuracy 71.4% and 42.9%, respectively). CONCLUSIONS: Our study demonstrates that MRPI accurately predicted, on an individual basis, the appearance of VSGP in patients with PSP-P, thus confirming clinical diagnosis in vivo.

Cerebellar involvement in essential tremor with and without resting tremor: A Diffusion Tensor Imaging study.

OBJECTIVE: Essential Tremor with resting tremor (rET) is a debated and poorly understood clinical phenotype. Converging evidences show that neurodegeneration of the cerebellum underlies the pathophysiology of ET, but it is not known if cerebellar changes also occurs in patients with rET. The aim of our study was to evaluate cerebellar microstructure in patients with ET with- (rET) and without resting tremor (ETwr) in comparison to healthy controls by MR Diffusion Tensor Imaging (DTI). METHODS: We studied 67 patients with ET (rET: 29 and ETwr: 38) and 39 age-matched healthy controls (HC). DTI was performed to measure fractional anisotropy (FA) and mean diffusivity (MD) of white and grey matter (WM, GM) in the entire cerebellum and in right and left cerebellar hemispheres. RESULTS: MD was significantly higher in the cerebellar GM of ET total group (10.39 ± 0.87) in comparison with HC (9.90 ± 0.71) (p = 0.0027). Interestingly, MD was significantly different when ETwr (10.48 ± 0.77) were compared with HC (p = 0.0017), whereas a trend toward significance were found between rET (10.29 ± 0.99) and HC (p = 0.067). No differences among groups were found in MD of cerebellar WM and in FA values neither in the WM nor in the GM. CONCLUSION: Our results demonstrate the presence of microstructural changes in the cerebellum of patients with ET. It is noteworthy that rET showed intermediate values compared to HC and ETwr, suggesting that rET shares part of the pathophysiological mechanisms of ETwr, but cerebellar involvement seems do not fully account for rET. In addition to the cerebellar loops, other networks may play a role in rET pathophysiology.

Individual differences in depression are associated with abnormal function of the limbic system in multiple sclerosis patients.

BACKGROUND: Depression is common in patients with multiple sclerosis (MS), although the brain mechanisms of this psychiatric condition in MS are poorly understood. Specifically, it remains to be determined whether depression in MS is related to altered activity and functional connectivity patterns within limbic circuits. METHODS: Seventy-seven MS patients with variable levels of depression (as assessed via the Beck Depression Inventory) underwent functional magnetic resonance imaging while performing an emotional processing task. To conduct the functional connectivity analyses, the bilateral amygdala and hippocampus, two areas critically involved in the pathophysiology of depression, were chosen as 'seed' regions. Multiple regression models were used to assess how depression in MS patients was correlated with the activity and functional connectivity patterns within the limbic system. RESULTS: Depression scores in MS patients were negatively correlated: (1) with the activity in the subgenual cingulate cortex; (2) with the functional connectivity between the hippocampus and orbitofrontal cortex as well as the dorsolateral prefrontal cortex, and (3) with the functional connectivity between the amygdala and dorsolateral prefrontal cortex. CONCLUSIONS: Our study showed that individual differences in depression in MS patients were significantly associated with altered regional activity and functional connectivity patterns within the limbic system.

The relationship between regional microstructural abnormalities of the corpus callosum and physical and cognitive disability in relapsing-remitting multiple sclerosis.

Significant corpus callosum (CC) involvement has been found in relapsing-remitting multiple sclerosis (RRMS), even if conventional magnetic resonance imaging measures have shown poor correlation with clinical disability measures. In this work, we tested the potential of multimodal imaging of the entire CC to explain physical and cognitive disability in 47 patients with RRMS. Values of thickness, fractional anisotropy (FA) and mean diffusivity (MD) were extracted from 50 regions of interest (ROIs) sampled along the bundle. The relationships between clinical, neuropsychological and imaging variables were assessed by using Spearman's correlation. Multiple linear regression analysis was employed in order to identify the relative importance of imaging metrics in modeling different clinical variables. Regional fiber composition of the CC differentially explained the response variables (Expanded Disability Status Scale [EDSS], cognitive impairment). Increases in EDSS were explained by reductions in CC thickness and MD. Cognitive impairment was mainly explained by FA reductions in the genu and splenium. Regional CC imaging properties differentially explained disability within RRMS patients revealing strong, distinct patterns of correlation with clinical and cognitive status of patients affected by this specific clinical phenotype.