Task- and resting-state fMRI studies in multiple sclerosis: From regions to systems and time-varying analysis. Current status and future perspective

Abstract

Multiple sclerosis (MS) is a neurological disorder affecting the central nervous system and features extensive functional brain changes that are poorly understood but relate strongly to clinical impairments. Functional magnetic resonance imaging (fMRI) is a non-invasive, powerful technique able to map activity of brain regions and to assess how such regions interact for an efficient brain network. FMRI has been widely applied to study functional brain changes in MS, allowing to investigate functional plasticity consequent to disease-related structural injury. The first studies in MS using active fMRI tasks mainly aimed to study such plastic changes by identifying abnormal activity in salient brain regions (or systems) involved by the task. In later studies the focus shifted towards resting state (RS) functional connectivity (FC) studies, which aimed to map large-scale functional networks of the brain and to establish how MS pathology impairs functional integration, eventually leading to the hypothesized network collapse as patients clinically progress. This review provides a summary of the main findings from studies using task-based and RS fMRI and illustrates how functional brain alterations relate to clinical disability and cognitive deficits in this condition. We also give an overview of longitudinal studies that used task-based and RS fMRI to monitor disease evolution and effects of motor and cognitive rehabilitation. In addition, we discuss the results of studies using newer technologies involving time-varying FC to investigate abnormal dynamism and flexibility of network configurations in MS. Finally, we show some preliminary results from two recent topics (i.e., multimodal MRI analysis and artificial intelligence) that are receiving increasing attention. Together, these functional studies could provide new (conceptual) insights into disease stage-specific mechanisms underlying progression in MS, with recommendations for future research.

Keywords: Functional MRI; Multiple sclerosis; Resting-state fMRI; Task fMRI.

Fig. 1

Schematic representation of findings from the main studies using task-based functional magnetic resonance imaging (fMRI) to investigate reorganization of brain activity in people with multiple sclerosis (MS). A) During upper limb motor tasks, the sensorimotor system usually shows an increased fMRI activation of primary sensorimotor regions in early MS, which is followed by increased activation of supplementary motor areas and fronto-parietal areas devoted to motor control in mildly disabled people with MS. At later disease stages and in progressive MS, a decreased fMRI activity in the classical motor circuit is detected, together with increased fMRI activations of high-order, integrative areas. B) During cognitive tasks, an increased fMRI activity of fronto-parietal regions is usually detected in people with MS and intact task performance or no cognitive impairment. The same circuit shows decreased fMRI activity in people with MS and cognitive deficits. Abbreviations: SMC = sensorimotor cortex; SMA = supplementary motor area; IFG = inferior frontal gyrus; IPL = inferior parietal lobule; MTG = middle temporal gyrus; MFG = middle frontal gyrus; ACC = anterior cingulate cortex.

Fig. 2

Schematic representation of the behavior of network functional connectivity (FC), assessed using graph theoretical analysis, in relation to cognitive impairment in people with multiple sclerosis (MS) (see (Schoonheim et al., 2015) for details). At the beginning of the disease and/or when structural damage is still limited, network metrics show some compensatory abnormalities, mainly consisting in a loss of long-range connections and increased modularity, as well as regional hyperactivation, which contribute to maintain network efficiency. As disease and structural damage progresses, further loss of functional connections leads to a loss of network efficiency and eventually a network collapse and cognitive impairment.