Recovery from an acute relapse is associated with changes in motor resting-state connectivity in multiple sclerosis

Functional Connectivity in Multiple Sclerosis: Recent Findings and Future Directions

Multiple sclerosis is a debilitating disorder resulting from scattered lesions in the central nervous system. Because of the high variability of the lesion patterns between patients, it is difficult to relate existing biomarkers to symptoms and their progression. The scattered nature of lesions in multiple sclerosis offers itself to be studied through the lens of network analyses. Recent research into multiple sclerosis has taken such a network approach by making use of functional connectivity. In this review, we briefly introduce measures of functional connectivity and how to compute them. We then identify several common observations resulting from this approach: (a) high likelihood of altered connectivity in deep-gray matter regions, (b) decrease of brain modularity, (c) hemispheric asymmetries in connectivity alterations, and (d) correspondence of behavioral symptoms with task-related and task-unrelated networks. We propose incorporating such connectivity analyses into longitudinal studies in order to improve our understanding of the underlying mechanisms affected by multiple sclerosis, which can consequently offer a promising route to individualizing imaging-related biomarkers for multiple sclerosis.

Altered motor plasticity in an acute relapse of multiple sclerosis

In relapsing-remitting MS (RRMS), the symptoms of a clinical relapse subside over time. Neuroplasticity is believed to play an important compensatory role. In this study, we assessed excitability-decreasing plasticity during an acute relapse of MS and 12 weeks afterwards. Motor plasticity was examined in 19 patients with clinically isolated syndrome or RRMS during a steroid-treated relapse (t1) and 12 weeks afterwards (t2) using paired-associative stimulation (PAS10). This method combines repetitive electric nerve stimulation with transcranial magnetic stimulation of the contralateral motor cortex to model long-term synaptic depression in the human cortex. Additionally, 19 age-matched healthy controls were assessed. Motor-evoked potentials of the abductor pollicis brevis muscle were recorded before and after intervention. Clinical disability was assessed by the multiple sclerosis functional composite and the subscore of the nine-hole peg test taken as a measure of hand function. The effect of PAS10 was significantly different between controls and patients; at t1, but not at t2, baseline-normalized postinterventional amplitudes were significantly higher in patients (106 [IQR 98-137] % post10-15 and 111 [IQR 88-133] % post20-25) compared to controls (92 [IQR 85-111] % and 90 [IQR 75-102] %). Additional exploratory analysis indicated a potentially excitability-enhancing effect of PAS10 in patients as opposed to controls. Significant clinical improvement between t1 and t2 was not correlated with PAS10 effects. Our results indicate an alteration of PAS10-induced synaptic plasticity during relapse, presumably reflecting a polarity shift due to metaplastic processes within the motor cortex. Further studies will need to elucidate the functional significance of such changes for the clinical course of MS.

Rewiring of neuronal networks during synaptic silencing

Analyzing the connectivity of neuronal networks, based on functional brain imaging data, has yielded new insight into brain circuitry, bringing functional and effective networks into the focus of interest for understanding complex neurological and psychiatric disorders. However, the analysis of network changes, based on the activity of individual neurons, is hindered by the lack of suitable meaningful and reproducible methodologies. Here, we used calcium imaging, statistical spike time analysis and a powerful classification model to reconstruct effective networks of primary rat hippocampal neurons in vitro. This method enables the calculation of network parameters, such as propagation probability, path length, and clustering behavior through the measurement of synaptic activity at the single-cell level, thus providing a fuller understanding of how changes at single synapses translate to an entire population of neurons. We demonstrate that our methodology can detect the known effects of drug-induced neuronal inactivity and can be used to investigate the extensive rewiring processes affecting population-wide connectivity patterns after periods of induced neuronal inactivity.

A Comparison of Neuroimaging Abnormalities in Multiple Sclerosis, Major Depression and Chronic Fatigue Syndrome (Myalgic Encephalomyelitis): is There a Common Cause?

There is copious evidence of abnormalities in resting-state functional network connectivity states, grey and white matter pathology and impaired cerebral perfusion in patients afforded a diagnosis of multiple sclerosis, major depression or chronic fatigue syndrome (CFS) (myalgic encephalomyelitis). Systemic inflammation may well be a major element explaining such findings. Inter-patient and inter-illness variations in neuroimaging findings may arise at least in part from regional genetic, epigenetic and environmental variations in the functions of microglia and astrocytes. Regional differences in neuronal resistance to oxidative and inflammatory insults and in the performance of antioxidant defences in the central nervous system may also play a role. Importantly, replicated experimental findings suggest that the use of high-resolution SPECT imaging may have the capacity to differentiate patients afforded a diagnosis of CFS from those with a diagnosis of depression. Further research involving this form of neuroimaging appears warranted in an attempt to overcome the problem of aetiologically heterogeneous cohorts which probably explain conflicting findings produced by investigative teams active in this field. However, the ionising radiation and relative lack of sensitivity involved probably preclude its use as a routine diagnostic tool.