Resting-State Functional Correlates of Social Cognition in Multiple Sclerosis: An Explorative Study

The neural substrates of social cognition deficits in newly diagnosed multiple sclerosis patients

OBJECTIVE

Cognitive and affective symptoms in multiple sclerosis (MS) can be independently impaired and have different pathways of progression. Cognitive alterations have been described since the earliest MS stages; by contrast, the social cognition (SC) domain has never been investigated in the first year from MS diagnosis. We aimed to evaluate SC and unravel its neural bases in newly diagnosed MS patients.

METHODS

Seventy MS patients underwent at diagnosis a 3 T-MRI and a neuropsychological/SC assessment (median time between diagnosis and MRI/cognitive evaluation = 0 months). We tested two matched reference samples: 31 relapsing-remitting MS patients with longer course (mean ± SD disease duration = 7.0 ± 4.5 years) and 38 healthy controls (HCs). Cortical thicknesses (CTh) and volumes of brain regions were calculated.

RESULTS

Newly diagnosed MS patients performed significantly lower than HCs in facial emotion recognition (global: p < 0.001; happiness: p = 0.041, anger: p = 0.007; fear: p < 0.001; disgust: p = 0.004) and theory of mind (p = 0.005), while no difference was found between newly diagnosed and longer MS patients. Compared to lower performers, higher performers in facial emotion recognition showed greater volume of amygdala (p = 0.032) and caudate (p = 0.036); higher performers in theory of mind showed greater CTh in lingual gyrus (p = 0.006), cuneus (p = 0.024), isthmus cingulate (p = 0.038), greater volumes of putamen (p = 0.016), pallidum (p = 0.029), and amygdala (p = 0.032); patients with higher empathy showed lower cuneus CTh (p = 0.042) and putamen volume (p = 0.007).

INTERPRETATIONS

SC deficits are present in MS patients since the time of diagnosis and remain persistent along the disease course. Specific basal, limbic, and occipital areas play a significant role in the pathogenesis of these alterations.

Functional gradients reveal cortical hierarchy changes in multiple sclerosis

Functional gradient (FG) analysis represents an increasingly popular methodological perspective for investigating brain hierarchical organization but whether and how network hierarchy changes concomitant with functional connectivity alterations in multiple sclerosis (MS) has remained elusive. Here, we analyzed FG components to uncover possible alterations in cortical hierarchy using resting-state functional MRI (rs-fMRI) data acquired in 122 MS patients and 97 healthy control (HC) subjects. Cortical hierarchy was assessed by deriving regional FG scores from rs-fMRI connectivity matrices using a functional parcellation of the cerebral cortex. The FG analysis identified a primary (visual-to-sensorimotor) and a secondary (sensory-to-transmodal) component. Results showed a significant alteration in cortical hierarchy as indexed by regional changes in FG scores in MS patients within the sensorimotor network and a compression (i.e., a reduced standard deviation across all cortical parcels) of the sensory-transmodal gradient axis, suggesting disrupted segregation between sensory and cognitive processing. Moreover, FG scores within limbic and default mode networks were significantly correlated (ρ = 0.30 $$ \rho =0.30 $$ , p < .005 after Bonferroni correction for both) with the symbol digit modality test (SDMT) score, a measure of information processing speed commonly used in MS neuropsychological assessments. Finally, leveraging supervised machine learning, we tested the predictive value of network-level FG features, highlighting the prominent role of the FG scores within the default mode network in the accurate prediction of SDMT scores in MS patients (average mean absolute error of 1.22 ± 0.07 points on a hold-out set of 24 patients). Our work provides a comprehensive evaluation of FG alterations in MS, shedding light on the hierarchical organization of the MS brain and suggesting that FG connectivity analysis can be regarded as a valuable approach in rs-fMRI studies across different MS populations.

Connectome-based prediction of decreased trust propensity in older adults with mild cognitive impairment: A resting-state functional magnetic resonance imaging study

Trust propensity (TP) relies more on social than economic rationality to transform the perceived probability of betrayal into positive reciprocity expectations in older adults with normal cognition. While deficits in social rationality have been observed in older adults with mild cognitive impairment (MCI), there is limited research on TP and its associated resting-state functional connectivity (RSFC) mechanisms in this population. To measure TP and related psychological functions (affect, motivation, executive cognition, and social cognition), MCI (n = 42) and normal healthy control (NHC, n = 115) groups completed a one-shot trust game and additional assessments of related psychological functions. RSFC associated with TP was analyzed using connectome-based predictive modeling (CPM) and lesion simulations. Our behavioral results showed that the MCI group trusted less (i.e., had lower TP) than the NHC group, with lower TP associated with higher sensitivity to the probability of betrayal in the MCI group. In the MCI group, only negative CPM models (RSFC negatively correlated with TP) significantly predicted TP, with a high salience network (SN) contribution. In contrast, in the NHC group, positive CPM models (RSFC positively correlated with TP) significantly predicted TP, with a high contribution from the default mode network (DMN). In addition, the total network strength of the NHC-specific positive network was lower in the MCI group than in the NHC group. Our findings demonstrated a decrease in TP in the MCI group compared to the NHC group, which is associated with deficits in social rationality (social cognition, associated with DMN) and increased sensitivity to betrayal (affect, associated with SN) in a trust dilemma. In conclusion, our study contributes to understanding MCI-related alterations in trust and their underlying neural mechanisms.

A systematic review and meta-analysis of socio-cognitive impairments in multiple sclerose

Socio-cognitive impairment is frequent in multiple sclerosis (MS). However, little is known about the relationship between other potentially relevant clinical symptoms (i.e., cognition, depression, fatigue) and the degree of socio-cognitive impairment, and neural mechanisms underlying socio-cognitive deficits in MS. Therefore, we meta-analytically quantified socio-cognitive impairment in MS. A systematic literature search in MEDLINE Ovid, Web of Science Core Collection, CENTRAL, and PsycInfo was conducted until December 2022. Studies investigating affective or cognitive theory of mind (a/cToM), visual perspective taking (VPT) and social decision making (SDM) in MS patients relative to healthy controls were included. Risk-of-bias (RoB) was assessed using the CLARITY group "Tool for Assessing RoB in Cohort Studies". Mediation analysis investigated the contribution of clinical symptoms to socio-cognitive impairment. In total, n = 8534 studies were screened, 58 were included in the systematic review, 27 in the meta-analyses. Most studies were rated with a moderate RoB. Meta-analyses confirmed impairment of both aToM and cToM in MS patients, with larger effect sizes for aToM. Mediation analysis demonstrated that higher levels of fatigue selectively predicted the degree of cToM impairment. There was insufficient data available to quantify impairment in other socio-cognitive domains. Fourteen structural and functional imaging studies were identified and characterized by substantial heterogeneity. Summarized, this study confirmed substantial socio-cognitive impairment in MS and highlights the potential exacerbating role of comorbid clinical symptoms. We identify several evidence gaps that need to be addressed in future large-scale studies using comprehensive and coordinated assessments of socio-cognitive parameters, potential mediators, and neural correlates.Trial registration: The pre-registered review protocol can be assessed at www.crd.york.ac.uk/PROSPERO/ (ID: CRD42020206225).

The relationship between depression and cognitive performance in multiple sclerosis: A meta-analysis

Objective: Studies on the relationship between depression and cognition on patients with multiple sclerosis (MS) are inconsistent and it is not clear whether higher depression levels are associated with impairment of specific cognitive domains or processes. This meta-analytic study aimed at evaluating the possible association between depressive symptomatology and performance on cognitive tests assessing several cognitive domains (global cognition, attention, processing speed, verbal, spatial and working memory, verbal fluency, inhibitory control, set-shifting) in individuals living with MS. Method: The literature search on three electronic databases yielded 5402 studies (4333 after the duplicates removal); after the evaluation of titles, abstracts full-text articles, 37 studies were included in the meta-analytic study. A random-effect model meta-analysis was performed and mean weighted effect sizes (ESs) were calculated using Hedges' g. Results: Small ESs were found for the relationship between depression and verbal memory (g = 0.25, p < 0.001), spatial memory (g = 0.23, p < 0.001), verbal fluency (g = 0.26, p < 0.001), and inhibitory control (g = 0.32, p = 0.003). Medium ESs were found for the relationship between depression and global cognition (g = 0.46, p < 0.001), attention (g = 0.43, p < 0.001), processing speed (g = 0.47, p < 0.001) and working memory (g = 0.38, p = 0.037). The relationship between set-shifting abilities and depression was not significant (g = 0.39, p = 0.095). Conclusions: Results suggest that patients with MS and higher levels of depressive symptomatology may also show more difficulties in several aspects of cognition, especially those needed to retain, respond, and process information in one's environment, and to those needed be adequately stimulated in processing relevant information.

Disrupted network communication predicts mild cognitive impairment in end-stage renal disease: an individualized machine learning study based on resting-state fMRI

End-Stage Renal Disease (ESRD) is known to be associated with a range of brain injuries, including cognitive decline. The purpose of this study is to investigate the functional connectivity (FC) of the resting-state networks (RSNs) through resting state functional magnetic resonance imaging (MRI), in order to gain insight into the neuropathological mechanism of ESRD. A total of 48 ESRD patients and 49 healthy controls underwent resting-state functional MRI and neuropsychological tests, for which Independent Components Analysis and graph-theory (GT) analysis were utilized. With the machine learning results, we examined the connections between RSNs abnormalities and neuropsychological test scores. Combining intra/inter network FC differences and GT results, ESRD was optimally distinguished in the testing dataset, with a balanced accuracy of 0.917 and area under curve (AUC) of 0.942. Shapley additive explanations results revealed that the increased functional network connectivity between DMN and left frontoparietal network (LFPN) was the most critical predictor for ESRD associated mild cognitive impairment diagnosis. Moreover, hypoSN (salience network) was positively correlated with Attention scores, while hyperLFPN was negatively correlated with Execution scores, indicating correlations between functional disruption and cognitive impairment measurements in ESRD patients. This study demonstrated that both the loss of FC within the SN and compensatory FC within the lateral frontoparietal network coexist in ESRD. This provides a network basis for understanding the individual brain circuits and offers additional noninvasive evidence to comprehend the brain networks in ESRD.

A 20-Year Systematic Review of the 'Reading the Mind in the Eyes' Test across Neurodegenerative Conditions

Social cognition has a broad theoretical definition, which includes the ability to mentalise, i.e., recognise and infer mental states to explain and predict another's behaviour. There is growing recognition of the clinical, diagnostic, and prognostic value of assessing a person's ability to perform social cognitive tasks, particularly aspects of theory of mind, such as mentalising. One such measure of mentalising is the 'Reading the Mind in the Eyes' test (RMET). This systematic review and meta-analysis consider performance on the RMET, applied to people with neurodegenerative conditions in matched control studies, since its publication in 2001. Overall, this review includes 22 papers with data from N = 800 participants with neurodegenerative conditions: Alzheimer's disease, n = 31; Parkinson's disease, n = 221; Lewy body dementia, n = 33; motor neuron disease, n = 218; Huntington's disease n = 80; multiple sclerosis, n = 217; and N = 601 matched typical controls. Our meta-analyses show that deficits in mentalising, as measured by the RMET, are consistently reported across neurodegenerative conditions, with participants in both early and late disease stages being affected. Social cognition is an emerging field of cognitive neuroscience requiring specific and sensitive measurement across each subdomain. Adult-based meta-normative data feature, for which future groups or individuals could be compared against, and hypotheses relating to the source of these mentalising deficits are further discussed. This review was registered with PROSPERO (CRD42020182874).

Cognitive impairment in multiple sclerosis: "classic" knowledge and recent acquisitions

Multiple sclerosis (MS) is a central nervous system (CNS) disease characterized by inflammation, axonal demyelination, and neurodegeneration, which can have a strong impact on all aspects of the life of the patient. Multiple sclerosis causes motor, sensory, cerebellar, and autonomic dysfunctions, as well as cognitive and psychoemotional impairment. The most frequently compromised cognitive domains are complex attention/information processing, memory, executive and visuospatial functions. Recently, alterations have also been evidenced in complex cognitive functions, such as social cognition, moral judgment, and decision-making. Cognitive impairment is characterized by high variability and can affect work skills, social interactions, coping strategies and more generally the quality of life of patients and their families. With the use of sensitive and easy-to-administer test batteries, an increasingly accurate and early diagnosis is feasible: this allows to determine the effectiveness of possible preventive measures, to predict the future progression of the disease and to improve the quality of life of patients. There is currently limited evidence regarding the efficacy, on cognitive impairment, of disease-modifying therapies. The most promising approach, which has received strong empirical support, is cognitive rehabilitation.

Resting-state functional MRI in multicenter studies on multiple sclerosis: a report on raw data quality and functional connectivity features from the Italian Neuroimaging Network Initiative

The Italian Neuroimaging Network Initiative (INNI) is an expanding repository of brain MRI data from multiple sclerosis (MS) patients recruited at four Italian MRI research sites. We describe the raw data quality of resting-state functional MRI (RS-fMRI) time-series in INNI and the inter-site variability in functional connectivity (FC) features after unified automated data preprocessing. MRI datasets from 489 MS patients and 246 healthy control (HC) subjects were retrieved from the INNI database. Raw data quality metrics included temporal signal-to-noise ratio (tSNR), spatial smoothness (FWHM), framewise displacement (FD), and differential variation in signals (DVARS). Automated preprocessing integrated white-matter lesion segmentation (SAMSEG) into a standard fMRI pipeline (fMRIPrep). FC features were calculated on pre-processed data and harmonized between sites (Combat) prior to assessing general MS-related alterations. Across centers (both groups), median tSNR and FWHM ranged from 47 to 84 and from 2.0 to 2.5, and median FD and DVARS ranged from 0.08 to 0.24 and from 1.06 to 1.22. After preprocessing, only global FC-related features were significantly correlated with FD or DVARS. Across large-scale networks, age/sex/FD-adjusted and harmonized FC features exhibited both inter-site and site-specific inter-group effects. Significant general reductions were obtained for somatomotor and limbic networks in MS patients (vs. HC). The implemented procedures provide technical information on raw data quality and outcome of fully automated preprocessing that might serve as reference in future RS-fMRI studies within INNI. The unified pipeline introduced little bias across sites and appears suitable for multisite FC analyses on harmonized network estimates.

Emotional Recognition and Its Relation to Cognition, Mood and Fatigue in Relapsing-Remitting and Secondary Progressive Multiple Sclerosis

(1) Background: Emotional recognition (ER), the ability to read into others' minds and recognize others' emotional states, is important in social environment adaptation. Recently it has been found that ER difficulties affect patients with multiple sclerosis (pMS) and relate to different gray matter atrophy patterns from secondary progressive (SP-pMS) and relapsing-remitting (RR-pMS). The aim of this study was to compare the performances of the two MS phenotypes on the Reading the Mind in the Eyes test (RMEt) and other cognitive, mood and fatigue measures. We also examined associations between performance on the RMEt and cognitive, mood and fatigue variables. (2) Methods: A total of 43 pMS (27RR-pMS/16SP-pMS) underwent a clinical assessment, the RMEt, the cognitive battery, and completed mood and fatigue questionnaires. Both groups' performances on the RMEt were then correlated with all these measures. (3) Results: the RMEt scores of RR-pMS were significantly correlated with the impairment degree in some cognitive scores. SP-pMS scores correlated mainly with fatigue, anxiety, anger and depression. (4) Conclusions: ER performances relate to cognitive aspects in RR-pMS, whereas mainly to mood outcomes in the SP-pMS group. We can hypothesize that deficits in ER are a further sign of disease progression. Our data support the different roles of cognitive and emotional deficits related to different disease courses and lesional correlates.

Intrinsic brain activity patterns across large-scale networks predict reciprocity propensity

Reciprocity is prevalent across human societies, but individuals are heterogeneous regarding their reciprocity propensity. Although a large body of task-based brain imaging measures has shed light on the neural underpinnings of reciprocity at group level, the neural basis underlying the individual differences in reciprocity propensity remains largely unclear. Here, we combined brain imaging and machine learning techniques to individually predict reciprocity propensity from resting-state brain activity measured by fractional amplitude of low-frequency fluctuation. The brain regions contributing to the prediction were then analyzed for functional connectivity and decoding analyses, allowing for a data-driven quantitative inference on psychophysiological functions. Our results indicated that patterns of resting-state brain activity across multiple brain systems were capable of predicting individual reciprocity propensity, with the contributing regions distributed across the salience (e.g., ventrolateral prefrontal cortex), fronto-parietal (e.g., dorsolateral prefrontal cortex), default mode (e.g., ventromedial prefrontal cortex), and sensorimotor (e.g., supplementary motor area) networks. Those contributing brain networks are implicated in emotion and cognitive control, mentalizing, and motor-based processes, respectively. Collectively, these findings provide novel evidence on the neural signatures underlying the individual differences in reciprocity, and lend support the assertion that reciprocity emerges from interactions among regions embodied in multiple large-scale brain networks.

Repetitive Transcranial Magnetic Stimulation (rTMS) of Dorsolateral Prefrontal Cortex May Influence Semantic Fluency and Functional Connectivity in Fronto-Parietal Network in Mild Cognitive Impairment (MCI)

Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive neuromodulation technique that is increasingly used as a nonpharmacological intervention against cognitive impairment in Alzheimer’s disease (AD) and other dementias. Although rTMS has been shown to modify cognitive performances and brain functional connectivity (FC) in many neurological and psychiatric diseases, there is still no evidence about the possible relationship between executive performances and resting-state brain FC following rTMS in patients with mild cognitive impairment (MCI). In this preliminary study, we aimed to evaluate the possible effects of rTMS of the bilateral dorsolateral prefrontal cortex (DLPFC) in 27 MCI patients randomly assigned to two groups: one group received high-frequency (10 Hz) rTMS (HF-rTMS) for four weeks (n = 11), and the other received sham stimulation (n = 16). Cognitive and psycho-behavior scores, based on the Repeatable Battery for the Assessment of Neuropsychological Status, Beck Depression Inventory-II, Beck Anxiety Inventory, Apathy Evaluation Scale, and brain FC, evaluated by independent component analysis of resting state functional MRI (RS-fMRI) networks, together with the assessment of regional atrophy measures, evaluated by whole-brain voxel-based morphometry (VBM), were measured at baseline, after five weeks, and six months after rTMS stimulation. Our results showed significantly increased semantic fluency (p = 0.026) and visuo-spatial (p = 0.014) performances and increased FC within the salience network (p ≤ 0.05, cluster-level corrected) at the short-term timepoint, and increased FC within the left fronto-parietal network (p ≤ 0.05, cluster-level corrected) at the long-term timepoint, in the treated group but not in the sham group. Conversely, regional atrophy measures did not show significant longitudinal changes between the two groups across six months. Our preliminary findings suggest that targeting DLPFC by rTMS application may lead to a significant long-term increase in FC in MCI patients in a RS network associated with executive functions, and this process might counteract the progressive cortical dysfunction affecting this domain.

Amygdala network reorganization mediates the theory of mind performances in multiple sclerosis

Theory of mind (ToM) seems to be affected in multiple sclerosis (MS). MRI studies suggested a role of the amygdala in social cognitive performances. Therefore, we explored the role of the amygdala network in ToM using a multimodal MRI approach. In MS, patients with impaired ToM showed contradictory dysexecutive neuropsychological profile. Therefore, we compared neural networks involved in ToM and executive functions (EFs). Twenty patients with relapsing-remitting MS and 15 matched healthy controls were selected. ToM (Faux Pas test and mind stories) and EFs were assessed within and outside the scanner. All subjects underwent a battery of neuropsychological tests. Multimodal MRI with structural (diffusion imaging) and functional (resting-state and task-based) sequences was used to analyze the role and connections of the amygdala in ToM functioning. Cognitive and ToM performances were similar between patients and controls. Resting-state data revealed decreased connectivity of the left amygdala with frontal areas in patients compared to controls (p < 0.0001). During the task-based functional MRI, patients demonstrated increased connectivity between the amygdala and several cerebellar and left temporal regions (all p < 0.05). The microstructural alterations between the left amygdala and left temporal regions were associated with increased functional connectivity within the same pathway (r = 0.74; p < 0.01). No overlap was observed between functional networks involved in ToM and EFs. Our study demonstrates more connectivity recruitment between the amygdala and cerebellar and temporal regions in MS patients to reach preserved ToM performance. Microstructural abnormalities have been related to this compensatory network. Finally, different networks were involved in EFs and ToM.

Empathy and Theory of Mind in Multiple Sclerosis: A Meta-Analysis

Multiple sclerosis (MS) is an immune-mediated demyelinating disease of the central nervous system. Studies have shown that MS disrupts several social cognitive abilities [including empathy and theory of mind (ToM)]. Overall ToM deficits in MS are well documented, but how the specific ToM subcomponents and empathic capacity are affected remains unclear. For this meta-analysis, we searched PubMed, Web of Science, and Embase from inception to July 2020. Effect sizes were calculated using Hedges g with a random-effects model. Thirty-three studies were included. Relative to healthy controls (HCs), patients with MS were moderately impaired in overall empathy (g = -0.67), overall ToM (g = -74), cognitive ToM (g = -0.72), and the overlapping domains of cognitive empathy/affective ToM (g = -0.79); no group differences were identified for affective empathy (g = -0.19). Compared with HCs, patients with relapsing-remitting MS (RRMS) and progressive MS were impaired in overall empathy, overall ToM, cognitive ToM, and cognitive empathy/affective ToM, without significant RRMS-progressive MS differences in impairment degree. We conducted the first meta-analytic review investigating the empathy and ToM functioning patterns in patients with MS and examined the overlapping and distinct subcomponents of these constructs. The findings suggest differential impairment of the core aspects of social cognitive processing in patients with MS, which may importantly inform the development of structured social cognitive MS interventions.