Background and purpose: Fatigue and cognitive difficulties are reported as the most frequently persistent symptoms in patients after mild SARS‐CoV‐2 infection. An extensive neurophysiological and neuropsychological assessment of such patients was performed focusing on motor cortex physiology and executive cognitive functions.Methods: Sixty‐seven patients complaining of fatigue and/or cognitive difficulties after resolution of mild SARS‐CoV‐2 infection were enrolled together with 22 healthy controls (HCs). Persistent clinical symptoms were investigated by means of a 16‐item questionnaire. Fatigue, exertion, cognitive difficulties, mood and ‘well‐being’ were evaluated through self‐administered tools. Utilizing transcranial magnetic stimulation of the primary motor cortex (M1) resting motor threshold, motor evoked potential amplitude, cortical silent period duration, short‐interval intracortical inhibition, intracortical facilitation, long‐interval intracortical inhibition and short‐latency afferent inhibition were evaluated. Global cognition and executive functions were assessed with screening tests. Attention was measured with computerized tasks.Results: Post COVID‐19 patients reported a mean of 4.9 persistent symptoms, high levels of fatigue, exertion, cognitive difficulties, low levels of well‐being and reduced mental well‐being. Compared to HCs, patients presented higher resting motor thresholds, lower motor evoked potential amplitudes and longer cortical silent periods, concurring with reduced M1 excitability. Long‐interval intracortical inhibition and short‐latency afferent inhibition were also impaired, indicating altered GABA_B‐ergic and cholinergic neurotransmission. Short‐interval intracortical inhibition and intracortical facilitation were not affected. Patients also showed poorer global cognition and executive functions compared to HCs and a clear impairment in sustained and executive attention.Conclusions: Patients with fatigue and cognitive difficulties following mild COVID‐19 present altered excitability and neurotransmission within M1 and deficits in executive functions and attention.

An established method to assess effective brain connectivity is the combined use of transcranial magnetic stimulation with simultaneous electroencephalography (TMS–EEG) because TMS-induced cortical responses propagate to distant anatomically connected brain areas. Alzheimer’s disease (AD) and other dementias are associated with changes in brain networks and connectivity, but the underlying pathophysiology of these processes is poorly defined. We performed here a systematic review of the studies employing TMS–EEG co-registration in patients with dementias. TMS–EEG studies targeting the motor cortex have revealed a significantly reduced TMS-evoked P30 in AD patients in the temporo-parietal cortex ipsilateral to stimulation side as well as in the contralateral fronto-central area, and we have demonstrated a deep rearrangement of the sensorimotor system even in mild AD patients. TMS–EEG studies targeting other cortical areas showed alterations of effective dorsolateral prefrontal cortex connectivity as well as an inverse correlation between prefrontal-to-parietal connectivity and cognitive impairment. Moreover, TMS–EEG analysis showed a selective increase in precuneus neural activity. TMS–EEG co-registrations can also been used to investigate whether different drugs may affect cognitive functions in patients with dementias.

The assessment of cognitive deficits is pivotal for diagnosis and management in patients with parkinsonisms. Low levels of correspondence are observed between evaluations assessed with screening cognitive tests in comparison with those assessed with in-depth neuropsychological batteries. A new tool, we named CoMDA (Cognition in Movement Disorders Assessment), was composed by merging Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Frontal Assessment Battery (FAB). In total, 500 patients (400 with Parkinson’s disease, 41 with vascular parkinsonism, 31 with progressive supranuclear palsy, and 28 with multiple system atrophy) underwent CoMDA (level 1–L1) and in-depth neuropsychological battery (level 2–L2). Machine learning was developed to classify the CoMDA score and obtain an accurate prediction of the cognitive profile along three different classes: normal cognition (NC), mild cognitive impairment (MCI), and impaired cognition (IC). The classification accuracy of CoMDA, assessed by ROC analysis, was compared with MMSE, MoCA, and FAB. The area under the curve (AUC) of CoMDA was significantly higher than that of MMSE, MoCA and FAB (p < 0.0001,p = 0.028 andp = 0.0007, respectively). Among 15 different algorithmic methods, the Quadratic Discriminant Analysis algorithm (CoMDA-ML) showed higher overall-metrics performance levels in predictive performance. Considering L2 as a 3-level continuous feature, CoMDA-ML produces accurate and generalizable classifications: micro-average ROC curve, AUC = 0.81; and AUC = 0.85 for NC, 0.67 for MCI, and 0.83 for IC. CoMDA and COMDA-ML are reliable and time-sparing tools, accurate in classifying cognitive profile in parkinsonisms.This study has been registered on ClinicalTrials.gov (NCT04858893).

Background: Attention is crucial to voluntary perform actions in Parkinson’s disease (PD), allowing patients to bypass the impaired habitual motor control. The asymmetrical degeneration of the dopaminergic system could affect the attentional functions. Objective: To investigate the relationship between the asymmetric dopaminergic degeneration and the attentional resources in Parkinsonian patients with right-side (RPD) and left-side (LPD) motor symptoms predominance. Methods: 50 RPD, 50 LPD, and 34 healthy controls underwent visual (V), auditory (A), and multiple choices (MC) reaction time (RTs) tasks. For PD patients, these tasks were performed before and after a 4-week intensive, motor-cognitive rehabilitation treatment (MIRT). The effectiveness of treatment was evaluated assessing Unified Parkinson’s disease Rating Scale (UPDRS) III and Timed-up and Go Test (TUG). Results: RTs did not differ between PD patients and healthy controls. Before MIRT, no differences between LPD and RPD patients were observed in RTs (p = 0.20), UPDRS III (p = 0.60), and TUG (p = 0.38). No differences in dopaminergic medication were found between groups (p = 0.44 and p = 0.66 before and after MIRT, respectively). After MIRT, LPD patients showed a significant reduction in MC RTs (p = 0.05), V RTs (p = 0.02), and MC-V RTs. A significant association between changes in RTs and improvements in UPDRS III and TUG was observed in LPD patients. Conclusion: attention does not differ among RPD patients, LPD patients and healthy controls. Only LPD patients improved their performances on attentional tasks after MIRT. We argue that the increased early susceptibility of the left nigrostriatal system to degeneration affects differently the cognitive modifiability and the neuroplastic potential. Our results could provide insight into new therapeutic approaches, highlighting the importance to design different treatments for RPD patients and LPD patients.

In post-COVID-19 syndrome (PCS), neurocognitive symptoms and fatigue are often associated with alterations in electroencephalographic (EEG) activity. The present study investigates the brain source activity at rest in PCS patients (PCS-pts) perceiving cognitive deficits and fatigue. A total of 18 PCS-pts and 18 healthy controls (HCs) were enrolled. A Montreal Cognitive Assessment (MoCA), Perceived Cognitive Difficulties Scale (PDCS) and Fatigue Severity Scale (FSS) were administered for assessing the symptoms’ severity. Brain activity at rest, both with open (OE) and closed eyes (CE), was recorded by high-density EEG (Hd-EEG) and localized by source estimation. Compared to HCs, PCS-pts exhibited worse performance in executive functions, language and memory, and reported higher levels of fatigue. At resting OE state, PCS-pts showed lower delta source activity over brain regions known to be associated with executive processes, and these changes were negatively associated with PDCS scores. Consistent with recent literature data, our findings could indicate a dysfunction in the neuronal networks involved in executive functions in PCS-pts complaining of fatigue and cognitive impairment.