Factors associated with material deprivation in persons with multiple sclerosis in Switzerland: Cross-sectional data from the Swiss Multiple Sclerosis Registry.

BACKGROUND: Multiple sclerosis (MS) impacts education, future career pathways and working capability and therefore may negatively impact the financial situation of persons with MS (pwMS) in Switzerland. We therefore investigated the financial situation and its influencing sociodemographic and disease-specific factors of pwMS compared to the general Swiss population with focus on material deprivation (MD). METHODS: Data on the financial situation of pwMS were collected via a specific questionnaire added to the regular, semi-annual follow-up assessments of the Swiss Multiple Sclerosis Registry. Questions were taken in an unmodified format from the standardized "Statistics on Income and Living Conditions" (SILC) questionnaire 2019 of the Federal Statistical Office of Switzerland which evaluates the financial situation of the general Swiss population, enabling a direct comparison of pwMS with the general Swiss population. RESULTS: PwMS were 1.5 times more frequently affected by MD than the general Swiss population (6.3% of pwMS versus 4.2% of the general Swiss population) which was confirmed in a multivariable logistic regression analysis of pooled SILC and Swiss Multiple Sclerosis Registry (SMSR) data. High symptom burden, having only mandatory schooling, well as having a pending disability insurance application (as opposed to no application or receiving benefits) were associated with a higher odds of MD whereas higher education, older age, having a Swiss citizenship, living with a spouse or a partner or being currently employed were independently associated with a lower odds of MD. CONCLUSION: MS has a negative impact on the financial situation and is associated with MD. PwMS with a high symptom burden at the transition from work force to receiving disability benefits appeared to be vulnerable for MD. Higher education, older age, having a Swiss citizenship, living with a spouse or a partner or being currently employed were independently associated with a lower odds of MD.

Whole-brain estimates of directed connectivity for human connectomics.

Connectomics is essential for understanding large-scale brain networks but requires that individual connection estimates are neurobiologically interpretable. In particular, a principle of brain organization is that reciprocal connections between cortical areas are functionally asymmetric. This is a challenge for fMRI-based connectomics in humans where only undirected functional connectivity estimates are routinely available. By contrast, whole-brain estimates of effective (directed) connectivity are computationally challenging, and emerging methods require empirical validation. Here, using a motor task at 7T, we demonstrate that a novel generative model can infer known connectivity features in a whole-brain network (>200 regions, >40,000 connections) highly efficiently. Furthermore, graph-theoretical analyses of directed connectivity estimates identify functional roles of motor areas more accurately than undirected functional connectivity estimates. These results, which can be achieved in an entirely unsupervised manner, demonstrate the feasibility of inferring directed connections in whole-brain networks and open new avenues for human connectomics.

A generative model of whole-brain effective connectivity.

The development of whole-brain models that can infer effective (directed) connection strengths from fMRI data represents a central challenge for computational neuroimaging. A recently introduced generative model of fMRI data, regression dynamic causal modeling (rDCM), moves towards this goal as it scales gracefully to very large networks. However, large-scale networks with thousands of connections are difficult to interpret; additionally, one typically lacks information (data points per free parameter) for precise estimation of all model parameters. This paper introduces sparsity constraints to the variational Bayesian framework of rDCM as a solution to these problems in the domain of task-based fMRI. This sparse rDCM approach enables highly efficient effective connectivity analyses in whole-brain networks and does not require a priori assumptions about the network's connectivity structure but prunes fully (all-to-all) connected networks as part of model inversion. Following the derivation of the variational Bayesian update equations for sparse rDCM, we use both simulated and empirical data to assess the face validity of the model. In particular, we show that it is feasible to infer effective connection strengths from fMRI data using a network with more than 100 regions and 10,000 connections. This demonstrates the feasibility of whole-brain inference on effective connectivity from fMRI data - in single subjects and with a run-time below 1 min when using parallelized code. We anticipate that sparse rDCM may find useful application in connectomics and clinical neuromodeling - for example, for phenotyping individual patients in terms of whole-brain network structure.

Allostatic Self-efficacy: A Metacognitive Theory of Dyshomeostasis-Induced Fatigue and Depression.

This paper outlines a hierarchical Bayesian framework for interoception, homeostatic/allostatic control, and meta-cognition that connects fatigue and depression to the experience of chronic dyshomeostasis. Specifically, viewing interoception as the inversion of a generative model of viscerosensory inputs allows for a formal definition of dyshomeostasis (as chronically enhanced surprise about bodily signals, or, equivalently, low evidence for the brain's model of bodily states) and allostasis (as a change in prior beliefs or predictions which define setpoints for homeostatic reflex arcs). Critically, we propose that the performance of interoceptive-allostatic circuitry is monitored by a metacognitive layer that updates beliefs about the brain's capacity to successfully regulate bodily states (allostatic self-efficacy). In this framework, fatigue and depression can be understood as sequential responses to the interoceptive experience of dyshomeostasis and the ensuing metacognitive diagnosis of low allostatic self-efficacy. While fatigue might represent an early response with adaptive value (cf. sickness behavior), the experience of chronic dyshomeostasis may trigger a generalized belief of low self-efficacy and lack of control (cf. learned helplessness), resulting in depression. This perspective implies alternative pathophysiological mechanisms that are reflected by differential abnormalities in the effective connectivity of circuits for interoception and allostasis. We discuss suitably extended models of effective connectivity that could distinguish these connectivity patterns in individual patients and may help inform differential diagnosis of fatigue and depression in the future.

Neurophysiological correlates of relatively enhanced local visual search in autistic adolescents.

Previous studies found normal or even superior performance of autistic patients on visuospatial tasks requiring local search, like the Embedded Figures Task (EFT). A well-known interpretation of this is "weak central coherence", i.e. autistic patients may show a reduced general ability to process information in its context and may therefore have a tendency to favour local over global aspects of information processing. An alternative view is that the local processing advantage in the EFT may result from a relative amplification of early perceptual processes which boosts processing of local stimulus properties but does not affect processing of global context. This study used functional magnetic resonance imaging (fMRI) in 12 autistic adolescents (9 Asperger and 3 high-functioning autistic patients) and 12 matched controls to help distinguish, on neurophysiological grounds, between these two accounts of EFT performance in autistic patients. Behaviourally, we found autistic individuals to be unimpaired during the EFT while they were significantly worse at performing a closely matched control task with minimal local search requirements. The fMRI results showed that activations specific for the local search aspects of the EFT were left-lateralised in parietal and premotor areas for the control group (as previously demonstrated for adults), whereas for the patients these activations were found in right primary visual cortex and bilateral extrastriate areas. These results suggest that enhanced local processing in early visual areas, as opposed to impaired processing of global context, is characteristic for performance of the EFT by autistic patients.

Context-dependent interactions of left posterior inferior frontal gyrus in a local visual search task unrelated to language.

The Embedded Figures Task (EFT) involves search for a target hidden in a complex geometric pattern. Even though the EFT is designed to probe local visual search functions, not language-related processes, neuropsychological studies have demonstrated a strong association between aphasia and impairment on this task. A potential explanation for this relationship was offered by a recent functional MRI study (Manjaly et al., 2003), which demonstrated that a part of the left posterior inferior frontal gyrus (pIFG), overlapping with Broca's region, is crucially involved in the execution of the EFT. This result suggested that pIFG, an area strongly associated with language-related functions, is also part of a network subserving cognitive functions unrelated to language. In this study, we tested this conjecture by analysing the data of Manjaly et al. for context-dependent functional interactions of the pIFG during execution of the EFT. The results showed that during EFT, compared to a similar visual matching task with minimal local search components, pIFG changed its interactions with areas commonly involved in visuospatial processing: Increased contributions to neural activity in left posterior parietal cortex, cerebellar vermis, and extrastriate areas bilaterally, as well as decreased contributions to bilateral temporo-parietal cortex, posterior cingulate cortex, and left dorsal premotor cortex were found. These findings demonstrate that left pIFG can be involved in nonlanguage processes. More generally, however, they provide a concrete example of the notion that there is no general one-to-one mapping between cognitive functions and the activations of individual areas. Instead, it is the spatiotemporal pattern of functional interactions between areas that is linked to a particular cognitive context.

In search of the hidden: an fMRI study with implications for the study of patients with autism and with acquired brain injury.

The Embedded Figures Task involves a search for a target hidden in a more complex visual pattern. The task has been used to study local perception and visual search in a range of normal and pathological populations. After acquired brain damage, impairment on embedded figures is strongly associated with aphasia; in the context of developmental disorder, people with autism or with Asperger's syndrome are reliably found to be better than normal controls on the task. The current study employed functional MRI with healthy volunteers to elucidate the brain regions that are specifically involved in the local search aspects of the Embedded Figures Task. We did so by analyzing the neural activations that are implicated in the task over and above those involved in an easier visual search task and in a straightforward shape recognition task. Significant activations (P < 0.05, corrected) specific in the above sense to the Embedded Figures Task were found in left inferior and left superior parietal cortex and in left ventral premotor cortex (inferior frontal gyrus). By contrast, comparing the overall effect of visual search within geometric figures to pure recognition of geometric shapes revealed more widespread activations in parietal, occipital, cerebellar, and frontal areas bilaterally. The implications of these findings for some developmental and acquired pathologies of perceptual functioning are outlined. We also relate our results to studies of local/global processing in other tasks.