Change in PASAT performance correlates with change in P3 ERP amplitude over a 12-month period in multiple sclerosis patients

Feasibility of source-level motor imagery classification for people with multiple sclerosis

Objective.There is limited work investigating brain-computer interface (BCI) technology in people with multiple sclerosis (pwMS), a neurodegenerative disorder of the central nervous system. Present work is limited to recordings at the scalp, which may be significantly altered by changes within the cortex due to volume conduction. The recordings obtained from the sensors, therefore, combine disease-related alterations and task-relevant neural signals, as well as signals from other regions of the brain that are not relevant. The current study aims to unmix signals affected by multiple sclerosis (MS) progression and BCI task-relevant signals using estimated source activity to improve classification accuracy.Approach.Data was collected from eight participants with a range of MS severity and ten neurotypical participants. This dataset was used to report the classification accuracy of imagined movements of the hands and feet at the sensor-level and the source-level in the current study.K-means clustering of equivalent current dipoles was conducted to unmix temporally independent signals. The location of these dipoles was compared between MS and control groups and used for classification of imagined movement. Linear discriminant analysis classification was performed at each time-frequency point to highlight differences in frequency band delay.Main Results.Source-level signal acquisition significantly improved decoding accuracy of imagined movement vs rest and movement vs movement classification in pwMS and controls. There was no significant difference found in alpha (7-13 Hz) and beta (13-30 Hz) band classification delay between the neurotypical control and MS group, including imagery of limbs with weakness or paralysis.Significance.This study is the first to demonstrate the advantages of source-level analysis for BCI applications in pwMS. The results highlight the potential for enhanced clinical outcomes and emphasize the need for longitudinal studies to assess the impact of MS progression on BCI performance, which is crucial for effective clinical translation of BCI technology.

Neurophysiological methods for assessing and treating cognitive impairment in multiple sclerosis: A scoping review of the literature

In recent years, there has been a growing interest in exploring the non-classical symptoms of multiple sclerosis (MS), with a particular focus on cognitive impairments associated with the disease's progression. These cognitive symptoms are now recognized as crucial elements in the assessment of disease activity. In this context, neurophysiology has emerged as a valuable and accessible tool for studying and addressing cognitive decline in individuals with MS. This scoping literature review investigates the role of neurophysiology in assessing and treating cognitive impairment in MS patients. The review focuses on Electroencephalography (EEG), Non-Invasive Brain Stimulation (NIBS), and magnetoencephalography (MEG) to assess cognitive decline in MS patients. Moreover, we discuss all the papers that tried to treat this cognitive impairment with NIBS techniques. While several neurophysiological markers show potential, standardization of protocols is essential for enhancing the reliability and consistency of these approaches. Further research is warranted to explore other NIBS techniques and deepen our understanding of the neurophysiological underpinnings of cognitive deficits in MS.

Multimodal Evoked Potentials as Potential Biomarkers of Disease Activity in Patients With Clinically Isolated Syndrome

Objective

There is an ongoing search for markers useful in monitoring and predicting disease activity at the early stage of multiple sclerosis (MS). The goals of this study were to prospectively evaluate the changes in parameters of multimodal evoked potentials (EP) and cognition within a 3-year follow-up period in patients with clinically isolated syndrome (CIS), and to assess the prognostic value of baseline findings with regard to the disease outcomes.

Methods

In 29 patients (20 women, nine men, mean age 31.1) multimodal (visual, brainstem auditory, somatosensory, event-related) EP and neuropsychological tests (NT) were performed at baseline (T0) and after 1 (T1) and 3 (T3) years. Their results were compared longitudinally between baseline, T1, and T3. Baseline results confirmed conversion of CIS into multiple sclerosis (MS) and disability level at T1 and T3 using multiple comparisons and a logistic regression model.

Results

Apart from mean N13/P16 SEP (somatosensory evoked potentials) amplitude (lower at T1 and T3 than at baseline (T0 1.02 ± 0.37 μV, T1 0.90 ± 0.26 μV, T3 0.74 ± 0.32 μV, p < 0.05 for both comparisons), no significant changes of EP or NT parameters were found in longitudinal assessment. Baseline P300 Pz latency was longer for the patients with MS than for those with CIS at T1 (352.69 vs. 325.56 ms). No predictive value was shown for any of the analyzed baseline variables with regard to conversion from CIS into MS.

Significance

Baseline ERP abnormalities were associated with their short-term conversion into MS. ERP are worth considering in multimodal EP evaluation at the early stage of MS.

Deficits in Early Sensory and Cognitive Processing Are Related to Phase and Nonphase EEG Activity in Multiple Sclerosis Patients

Currently, there is scarce knowledge about the relation between spectral bands modulations and the basis of cognitive impairment in multiple sclerosis (MS). In this sense, analyzing the evoked or phase activity can confirm results from traditional event-related potential (ERP) studies. However, studying the induced or nonphase activity may be necessary to elucidate hidden compensatory or affected cognitive mechanisms. In this study, 30 remitting-relapsing multiple sclerosis patients and 30 healthy controls (HCs) matched in sociodemographic variables performed a visual oddball task. The main goal was to analyze phase and nonphase alpha and gamma bands by applying temporal spectral evolution (TSE) and its potential relation with cognitive impairment in these patients. The behavioural results showed slower reaction time and poorer accuracy in MS patients compared to controls. In contrast, the time-frequency analysis of electroencephalography (EEG) revealed a delay in latency and lower amplitude in MS patients in evoked and induced alpha compared to controls. With respect to the gamma band, there were no differences between the groups. In summary, MS patients showed deficits in early sensorial (evoked alpha activity) and cognitive processing (induced alpha activity in longer latencies), whereas the induced gamma band supported the hypothesis of its role in translation of attentional focus (induced activity) and did not show strong activity in this paradigm (visual oddball).

Altered individual behavioral and EEG parameters are related to the EDSS score in relapsing-remitting multiple sclerosis patients

Functional neuroanatomy of cognitive impairment in multiple sclerosis is currently still a challenge. During the progression of the disease, several cognitive mechanisms deteriorate thus diminishing the patient’s quality of life. A primary objective in the cognitive assessment of multiple sclerosis (MS) patients is to find reliable measures utilizing diverse neuroimaging techniques. Moreover, especially relevant in the clinical environment is finding technical approaches that could be applied to individual participants and not only for group analysis. A 64-channel electroencephalographic recording (EEG) was made with thirty participants divided into three groups of equivalent size (N = 10) (healthy control, low-EDSS (1–2.5) and moderate-EDSS (4–6)). Correlation analysis was applied to multiple measures: behavior, neuropsychological tests (Paced Auditory Serial Addition Test, 3 seconds (PASAT-3s) and the Symbol Digit Modality Test (SDMT)), Expanded Disability Status Scale (EDSS), even-related potential (P3) and event-related desynchronization (ERD) parameters and the correlation scores between individual participant’s P3/ERD maps and the healthy grand average P3/ERDmaps. Statistical analysis showed that diverse parameters exhibited significant correlations. A remarkable correlation was the moderate score found between SDMT and EDSS (r = −0.679, p = 0.0009). However, the strongest correlation was between the value of integrated measures (reaction time, P3 and ERD latency) and EDSS (r = 0.699, p = 0.0006). In regard to correlations for grand average maps between groups, the P3 component exhibited a lower score according to a more deteriorated condition (higher EDSS). In contrast, ERD maps remained stable with an increase of EDSS. Lastly, a Z-transformation of individual values of all variables included in the study exhibited heterogeneity in cognitive alterations in the multiple sclerosis participants.

Machine Learning EEG to Predict Cognitive Functioning and Processing Speed Over a 2-Year Period in Multiple Sclerosis Patients and Controls

Event-related potentials (ERPs) show promise to be objective indicators of cognitive functioning. The aim of the study was to examine if ERPs recorded during an oddball task would predict cognitive functioning and information processing speed in Multiple Sclerosis (MS) patients and controls at the individual level. Seventy-eight participants (35 MS patients, 43 healthy age-matched controls) completed visual and auditory 2- and 3-stimulus oddball tasks with 128-channel EEG, and a neuropsychological battery, at baseline (month 0) and at Months 13 and 26. ERPs from 0 to 700 ms and across the whole scalp were transformed into 1728 individual spatio-temporal datapoints per participant. A machine learning method that included penalized linear regression used the entire spatio-temporal ERP to predict composite scores of both cognitive functioning and processing speed at baseline (month 0), and months 13 and 26. The results showed ERPs during the visual oddball tasks could predict cognitive functioning and information processing speed at baseline and a year later in a sample of MS patients and healthy controls. In contrast, ERPs during auditory tasks were not predictive of cognitive performance. These objective neurophysiological indicators of cognitive functioning and processing speed, and machine learning methods that can interrogate high-dimensional data, show promise in outcome prediction.

Delayed P100-Like Latencies in Multiple Sclerosis: A Preliminary Investigation Using Visual Evoked Spread Spectrum Analysis

Conduction along the optic nerve is often slowed in multiple sclerosis (MS). This is typically assessed by measuring the latency of the P100 component of the Visual Evoked Potential (VEP) using electroencephalography. The Visual Evoked Spread Spectrum Analysis (VESPA) method, which involves modulating the contrast of a continuous visual stimulus over time, can produce a visually evoked response analogous to the P100 but with a higher signal-to-noise ratio and potentially higher sensitivity to individual differences in comparison to the VEP. The main objective of the study was to conduct a preliminary investigation into the utility of the VESPA method for probing and monitoring visual dysfunction in multiple sclerosis. The latencies and amplitudes of the P100-like VESPA component were compared between healthy controls and multiple sclerosis patients, and multiple sclerosis subgroups. The P100-like VESPA component activations were examined at baseline and over a 3-year period. The study included 43 multiple sclerosis patients (23 relapsing-remitting MS, 20 secondary-progressive MS) and 42 healthy controls who completed the VESPA at baseline. The follow-up sessions were conducted 12 months after baseline with 24 MS patients (15 relapsing-remitting MS, 9 secondary-progressive MS) and 23 controls, and again at 24 months post-baseline with 19 MS patients (13 relapsing-remitting MS, 6 secondary-progressive MS) and 14 controls. The results showed P100-like VESPA latencies to be delayed in multiple sclerosis compared to healthy controls over the 24-month period. Secondary-progressive MS patients had most pronounced delay in P100-like VESPA latency relative to relapsing-remitting MS and controls. There were no longitudinal P100-like VESPA response differences. These findings suggest that the VESPA method is a reproducible electrophysiological method that may have potential utility in the assessment of visual dysfunction in multiple sclerosis.

Contingent negative variation is associated with cognitive dysfunction and secondary progressive disease course in multiple sclerosis

BACKGROUND AND PURPOSE

The relationship between contingent negative variation (CNV), which is an event-related potential, and cognition in multiple sclerosis (MS) has not been examined previously. The primary objective of the present study was thus to determine the association between CNV and cognition in a sample of MS patients.

METHODS

The subjects of this study comprised 66 MS patients [50 with relapsing-remitting MS (RRMS) and 16 with secondary progressive MS (SPMS)] and 40 matched healthy volunteers. A neuropsychological battery was administered to all of the subjects; CNV recordings were made from the Cz, Fz, and Pz electrodes, and the amplitude and area under the curve (AUC) were measured at each electrode.

RESULTS

RRMS patients exhibited CNVs with lower amplitudes and smaller AUCs than the controls at Pz. SPMS patients exhibited CNVs with lower amplitudes and smaller AUCs than the controls, and CNVs with a smaller amplitude than the RRMS patients at both Cz and Pz. After correcting for multiple comparisons, a lower CNV amplitude at Pz was significantly associated with worse performance on measures of speed of information processing, verbal fluency, verbal learning, and verbal recall.

CONCLUSIONS

CNV may serve as a marker for disease progression and cognitive dysfunction in MS. Further studies with larger samples and wider electrode coverage are required to fully assess the value of CNV in these areas.

Neural correlates of alerting and orienting impairment in multiple sclerosis patients

BACKGROUND

A considerable percentage of multiple sclerosis patients have attentional impairment, but understanding its neurophysiological basis remains a challenge. The Attention Network Test allows 3 attentional networks to be studied. Previous behavioural studies using this test have shown that the alerting network is impaired in multiple sclerosis. The aim of this study was to identify neurophysiological indexes of the attention impairment in relapsing-remitting multiple sclerosis patients using this test.

RESULTS

After general slowing had been removed in patients group to isolate the effects of each condition, some behavioral differences between them were obtained. About Contingent Negative Variation, a statistically significant decrement were found in the amplitude for Central and Spatial Cue Conditions for patient group (p<0.05). ANOVAs showed for the patient group a significant latency delay for P1 and N1 components (p<0.05) and a decrease of P3 amplitude for congruent and incongruent stimuli (p<0.01). With regard to correlation analysis, PASAT-3s and SDMT showed significant correlations with behavioral measures of the Attention Network Test (p<0.01) and an ERP parameter (CNV amplitude).

CONCLUSIONS

Behavioral data are highly correlated with the neuropsychological scores and show that the alerting and orienting mechanisms in the patient group were impaired. Reduced amplitude for the Contingent Negative Variation in the patient group suggests that this component could be a physiological marker related to the alerting and orienting impairment in relapsing-remitting multiple sclerosis. P1 and N1 delayed latencies are evidence of the demyelination process that causes impairment in the first steps of the visual sensory processing. Lastly, P3 amplitude shows a general decrease for the pathological group probably indexing a more central impairment. These results suggest that the Attention Network Test give evidence of multiple levels of attention impairment, which could help in the assessment and treatment of relapsing-remitting multiple sclerosis patients.

Graph theoretical analysis indicates cognitive impairment in MS stems from neural disconnection

BACKGROUND

The mechanisms underlying cognitive impairment in MS are still poorly understood. However, due to the specific pathology of MS, one can expect alterations in connectivity leading to physical and cognitive impairment.

AIM

In this study we aimed at assessing connectivity differences in EEG between cognitively impaired (CI) and cognitively preserved (CP) MS patients. We also investigated the influence of the measures used to construct networks.

METHODS

We included 308 MS patients and divided them into two groups based on their cognitive score. Graph theoretical network analyses were conducted based on networks constructed using different connectivity measures, i.e. correlation, correlation in the frequency domain, coherence, partial correlation, the phase lag index and the imaginary part of coherency. The most commonly encountered network parameters were calculated and compared between the two groups using Wilcoxon's rank test. Clustering coefficients and path lengths were normalized to a randomized mean clustering coefficient and path length for each patient. False discovery rate was used to correct for the multiple comparisons and Cohen's d effect sizes are reported.

RESULTS

Coherence analysis suggests that theta and delta connectivity is significantly smaller in cognitively impaired patients. Small-worldness differences are found in networks based on correlation, theta and delta coherence and correlation in the frequency domain. Modularity was related to age but not to cognition.

CONCLUSION

Cognitive deterioration in MS is a symptom that seems to be caused by neural disconnections, probably the white matter tracts connecting both hemispheres, and leads to a wide range in network differences which can be assessed by applying GTA to EEG data. In the future, these results may lead to cheaper and more objective assessments of cognitive impairment in MS.

Only low frequency event-related EEG activity is compromised in multiple sclerosis: insights from an independent component clustering analysis

Cognitive impairment (CI), often examined with neuropsychological tests such as the Paced Auditory Serial Addition Test (PASAT), affects approximately 65% of multiple sclerosis (MS) patients. The P3b event-related potential (ERP), evoked when an infrequent target stimulus is presented, indexes cognitive function and is typically compared across subjects' scalp electroencephalography (EEG) data. However, the clustering of independent components (ICs) is superior to scalp-based EEG methods because it can accommodate the spatiotemporal overlap inherent in scalp EEG data. Event-related spectral perturbations (ERSPs; event-related mean power spectral changes) and inter-trial coherence (ITCs; event-related consistency of spectral phase) reveal a more comprehensive overview of EEG activity. Ninety-five subjects (56 MS patients, 39 controls) completed visual and auditory two-stimulus P3b event-related potential tasks and the PASAT. MS patients were also divided into CI and non-CI groups (n = 18 in each) based on PASAT scores. Data were recorded from 128-scalp EEG channels and 4 IC clusters in the visual, and 5 IC clusters in the auditory, modality were identified. In general, MS patients had significantly reduced ERSP theta power versus controls, and a similar pattern was observed for CI vs. non-CI MS patients. The ITC measures were also significantly different in the theta band for some clusters. The finding that MS patients had reduced P3b task-related theta power in both modalities is a reflection of compromised connectivity, likely due to demyelination, that may have disrupted early processes essential to P3b generation, such as orientating and signal detection. However, for posterior sources, MS patients had a greater decrease in alpha power, normally associated with enhanced cognitive function, which may reflect a compensatory mechanism in response to the compromised early cognitive processing.