Classification accuracy of TMS for the diagnosis of mild cognitive impairment

Exploring the potential of combining transcranial magnetic stimulation and electroencephalography to investigate mild cognitive impairment and Alzheimer's disease: a systematic review

Transcranial magnetic stimulation (TMS) and electroencephalography (EEG) are non-invasive techniques used for neuromodulation and recording brain electrical activity, respectively. The integration of TMS-EEG has emerged as a valuable tool for investigating the complex mechanisms involved in age-related disorders, such as mild cognitive impairment (MCI) and Alzheimer's disease (AD). By systematically synthesizing TMS-EEG studies, this review aims to shed light on the neurophysiological mechanisms underlying MCI and AD, while also exploring the practical applications of TMS-EEG in clinical settings. PubMed, ScienceDirect, and PsychInfo were selected as the databases for this review. The 22 eligible studies included a total of 592 individuals with MCI or AD as well as 301 cognitively normal adults. TMS-EEG assessments unveiled specific patterns of corticospinal excitability, plasticity, and brain connectivity that distinguished individuals on the AD spectrum from cognitively normal older adults. Moreover, the TMS-induced EEG features were observed to be correlated with cognitive performance and the presence of AD pathological biomarkers. The comprehensive examination of the existing studies demonstrates that the combination of TMS and EEG has yielded valuable insights into the neurophysiology of MCI and AD. This integration shows great potential for early detection, monitoring disease progression, and anticipating response to treatment. Future research is of paramount importance to delve into the potential utilization of TMS-EEG for treatment optimization in individuals with MCI and AD.

Modern neurophysiological techniques indexing normal or abnormal brain aging

Brain aging is associated with a decline in cognitive performance, motor function and sensory perception, even in the absence of neurodegeneration. The underlying pathophysiological mechanisms remain incompletely understood, though alterations in neurogenesis, neuronal senescence and synaptic plasticity are implicated. Recent years have seen advancements in neurophysiological techniques such as electroencephalography (EEG), magnetoencephalography (MEG), event-related potentials (ERP) and transcranial magnetic stimulation (TMS), offering insights into physiological and pathological brain aging. These methods provide real-time information on brain activity, connectivity and network dynamics. Integration of Artificial Intelligence (AI) techniques promise as a tool enhancing the diagnosis and prognosis of age-related cognitive decline. Our review highlights recent advances in these electrophysiological techniques (focusing on EEG, ERP, TMS and TMS-EEG methodologies) and their application in physiological and pathological brain aging. Physiological aging is characterized by changes in EEG spectral power and connectivity, ERP and TMS parameters, indicating alterations in neural activity and network function. Pathological aging, such as in Alzheimer's disease, is associated with further disruptions in EEG rhythms, ERP components and TMS measures, reflecting underlying neurodegenerative processes. Machine learning approaches show promise in classifying cognitive impairment and predicting disease progression. Standardization of neurophysiological methods and integration with other modalities are crucial for a comprehensive understanding of brain aging and neurodegenerative disorders. Advanced network analysis techniques and AI methods hold potential for enhancing diagnostic accuracy and deepening insights into age-related brain changes.

Decreased short-latency afferent inhibition in individuals with mild cognitive impairment: A TMS-EEG study

TMS combined with EEG (TMS-EEG) is a tool to characterize the neurophysiological dynamics of the cortex. Among the TMS paradigms, short-latency afferent inhibition (SAI) allows the investigation of inhibitory effects mediated by the cholinergic system. The aim of this study was to compare cholinergic function in the DLPFC between individuals with mild cognitive impairment (MCI) and healthy controls (HC) using TMS-EEG with the SAI paradigm. In this study, 30 MCI and 30 HC subjects were included. The SAI paradigm consisted of 80 single pulse TMS and 80 SAI stimulations applied to the left DLPFC. N100 components, global mean field power (GMFP) and total power were calculated. As a result, individuals with MCI showed reduced inhibitory effects on N100 components and GMFP at approximately 100 ms post-stimulation and on β-band activity at 200 ms post-stimulation compared to HC. Individuals with MCI showed reduced SAI, suggesting impaired cholinergic function in the DLPFC compared to the HC group. We conclude that these findings underscore the clinical applicability of the TMS-EEG method as a powerful tool for assessing cholinergic function in individuals with MCI.

Transcranial Magnetic Stimulation Across the Lifespan: Impact of Developmental and Degenerative Processes

Transcranial magnetic stimulation (TMS) has emerged as a pivotal noninvasive technique for investigating cortical excitability and plasticity across the lifespan, offering valuable insights into neurodevelopmental and neurodegenerative processes. In this review, we explore the impact of TMS applications on our understanding of normal development, healthy aging, neurodevelopmental disorders, and adult-onset neurodegenerative diseases. By presenting key developmental milestones and age-related changes in TMS measures, we provide a foundation for understanding the maturation of neurotransmitter systems and the trajectory of cognitive functions throughout the lifespan. Building on this foundation, the paper delves into the pathophysiology of neurodevelopmental disorders, including autism spectrum disorder, attention-deficit/hyperactivity disorder, Tourette syndrome, and adolescent depression. Highlighting recent findings on altered neurotransmitter circuits and dysfunctional cortical plasticity, we underscore the potential of TMS as a valuable tool for unraveling underlying mechanisms and informing future therapeutic interventions. We also review the emerging role of TMS in investigating and treating the most common adult-onset neurodegenerative disorders and late-onset depression. By outlining the therapeutic applications of noninvasive brain stimulation techniques in these disorders, we discuss the growing body of evidence supporting their use as therapeutic tools for symptom management and potentially slowing disease progression. The insights gained from TMS studies have advanced our understanding of the underlying mechanisms in both healthy and disease states, ultimately informing the development of more targeted diagnostic and therapeutic strategies for a wide range of neuropsychiatric conditions.

Transcranial magnetic stimulation neurophysiology in patients with non-Alzheimer's neurodegenerative diseases: A systematic review and meta-analysis

Non-Alzheimer's dementia (NAD) accounts for 30% of all neurodegenerative conditions and is characterized by cognitive decline beyond mere memory dysfunction. Diagnosing NAD remains challenging due to the lack of established biomarkers. Transcranial magnetic stimulation (TMS) is a non-invasive neurophysiological tool that enables the investigation of cortical excitability in the human brain. Paired-pulse TMS paradigms include short- and long-interval intracortical inhibition (SICI/LICI), intracortical facilitation (ICF), and short-latency afferent inhibition (SAI), which can assess neurophysiological functions of GABAergic, glutamatergic, and cholinergic neural circuits, respectively. We conducted the first systematic review and meta-analysis to compare these TMS indices among patients with NAD and healthy controls. Our meta-analyses indicated that TMS neurophysiological examinations revealed decreased glutamatergic function in patients with frontotemporal dementia (FTD) and decreased GABAergic function in patients with FTD, progressive supranuclear palsy, Huntington's disease, cortico-basal syndrome, and multiple system atrophy-parkinsonian type. In addition, decreased cholinergic function was found in dementia with Lewy body and vascular dementia. These results suggest the potential of TMS as an additional diagnostic tool to differentiate NAD.

Cortico-spinal tDCS in amyotrophic lateral sclerosis: A randomized, double-blind, sham-controlled trial followed by an open-label phase

BACKGROUND

Amyotrophic lateral sclerosis (ALS) is a progressive disease for which no curative treatment is currently available.

OBJECTIVE

This study aimed to investigate whether cortico-spinal transcranial direct current stimulation (tDCS) could mitigate symptoms in ALS patients via a randomized, double-blind, sham-controlled trial, followed by an open-label phase.

METHODS

Thirty-one participants were randomized into two groups for the initial controlled phase. At baseline (T0), Group 1 received placebo stimulation (sham tDCS), while Group 2 received cortico-spinal stimulation (real tDCS) for five days/week for two weeks (T1), with an 8-week (T2) follow-up (randomized, double-blind, sham-controlled phase). At the 24-week follow-up (T3), all participants (Groups 1 and 2) received a second treatment of anodal bilateral motor cortex and cathodal spinal stimulation (real tDCS) for five days/week for two weeks (T4). Follow-up evaluations were performed at 32-weeks (T5) and 48-weeks (T6) (open-label phase). At each time point, clinical assessment, blood sampling, and intracortical connectivity measures using transcranial magnetic stimulation (TMS) were evaluated. Additionally, we evaluated survival rates.

RESULTS

Compared to sham stimulation, cortico-spinal tDCS significantly improved global strength, caregiver burden, and quality of life scores, which correlated with the restoration of intracortical connectivity measures. Serum neurofilament light levels decreased among patients who underwent real tDCS but not in those receiving sham tDCS. The number of completed 2-week tDCS treatments significantly influenced patient survival.

CONCLUSIONS

Cortico-spinal tDCS may represent a promising therapeutic and rehabilitative approach for patients with ALS. Further larger-scale studies are necessary to evaluate whether tDCS could potentially impact patient survival.

CLINICAL TRIAL REGISTRATION

NCT04293484.

Home-based transcranial alternating current stimulation (tACS) in Alzheimer's disease: rationale and study design

BACKGROUND

Gamma (γ) brain oscillations are dysregulated in Alzheimer's disease (AD) and can be modulated using transcranial alternating stimulation (tACS). In the present paper, we describe the rationale and design of a study assessing safety, feasibility, clinical and biological efficacy, and predictors of outcome of a home-based intervention consisting of γ-tACS over the precuneus.

METHODS

In a first phase, 60 AD patients will be randomized into two arms: ARM1, 8-week precuneus γ-tACS (frequency: 40 Hz, intensity: 2 mA, duration: 5 60-min sessions/week); and ARM2, 8-week sham tACS (same parameters as the real γ-tACS, with the current being discontinued 5 s after the beginning of the stimulation). In a second phase, all participants will receive 8-week γ-tACS (same parameters as the real γ-tACS in the first phase). The study outcomes will be collected at several timepoints throughout the study duration and include information on safety and feasibility, neuropsychological assessment, blood sampling, electroencephalography, transcranial magnetic stimulation neurotransmitter measures, and magnetic resonance imaging or amyloid positron emission tomography.

RESULTS

We expect that this intervention is safe and feasible and results in the improvement of cognition, entrainment of gamma oscillations, increased functional connectivity, reduction of pathological burden, and increased cholinergic transmission.

CONCLUSIONS

If our expected results are achieved, home-based interventions using γ-tACS, either alone or in combination with other therapies, may become a reality for treating AD.

TRIAL REGISTRATION

PNRR-POC-2022-12376021.

Three novel methods for determining motor threshold with transcranial magnetic stimulation outperform conventional procedures

Objective. Thresholding of neural responses is central to many applications of transcranial magnetic stimulation (TMS), but the stochastic aspect of neuronal activity and motor evoked potentials (MEPs) challenges thresholding techniques. We analyzed existing methods for obtaining TMS motor threshold and their variations, introduced new methods from other fields, and compared their accuracy and speed.Approach. In addition to existing relative-frequency methods, such as the five-out-of-ten method, we examined adaptive methods based on a probabilistic motor threshold model using maximum-likelihood (ML) or maximuma-posteriori(MAP) estimation. To improve the performance of these adaptive estimation methods, we explored variations in the estimation procedure and inclusion of population-level prior information. We adapted a Bayesian estimation method which iteratively incorporated information of the TMS responses into the probability density function. A family of non-parametric stochastic root-finding methods with different convergence criteria and stepping rules were explored as well. The performance of the thresholding methods was evaluated with an independent stochastic MEP model.Main Results. The conventional relative-frequency methods required a large number of stimuli, were inherently biased on the population level, and had wide error distributions for individual subjects. The parametric estimation methods obtained the thresholds much faster and their accuracy depended on the estimation method, with performance significantly improved when population-level prior information was included. Stochastic root-finding methods were comparable to adaptive estimation methods but were much simpler to implement and did not rely on a potentially inaccurate underlying estimation model.Significance. Two-parameter MAP estimation, Bayesian estimation, and stochastic root-finding methods have better error convergence compared to conventional single-parameter ML estimation, and all these methods require significantly fewer TMS pulses for accurate estimation than conventional relative-frequency methods. Stochastic root-finding appears particularly attractive due to the low computational requirements, simplicity of the algorithmic implementation, and independence from potential model flaws in the parametric estimators.

Advances in the treatment and management of frontotemporal dementia

INTRODUCTION

Frontotemporal dementia (FTD) is a complex neurodegenerative disorder, characterized by a wide range of pathological conditions associated with the buildup of proteins such as tau and TDP-43. With a strong hereditary component, FTD often results from genetic variants in three genes - MAPT, GRN, and C9orf72.

AREAS COVERED

In this review, the authors explore abnormal protein accumulation in FTD and forthcoming treatments, providing a detailed analysis of new diagnostic advancements, including innovative markers. They analyze how these discoveries have influenced therapeutic strategies, particularly disease-modifying treatments, which could potentially transform FTD management. This comprehensive exploration of FTD from its molecular underpinnings to its therapeutic prospects offers a compelling overview of the current state of FTD research.

EXPERT OPINION

Notable challenges in FTD management involve identifying reliable biomarkers for early diagnosis and response monitoring. Genetic forms of FTD, particularly those linked to C9orf72 and GRN, show promise, with targeted therapies resulting in substantial progress in disease-modifying strategies. The potential of neuromodulation techniques, like tDCS and rTMS, is being explored, requiring further study. Ongoing trials and multi-disciplinary care highlight the continued push toward effective FTD treatments. With increasing understanding of FTD's molecular and clinical intricacies, the hope for developing effective interventions grows.

Deficient GABABergic and glutamatergic excitability in the motor cortex of patients with long-COVID and cognitive impairment

OBJECTIVE

Attention, working memory and executive processing have been reported to be consistently impaired in Neuro-Long coronavirus disease (COVID). On the hypothesis of abnormal cortical excitability, we investigated the functional state of inhibitory and excitatory cortical regulatory circuits by single "paired-pulse" transcranial magnetic stimulation (ppTMS) and Short-latency Afferent Inhibition (SAI).

METHODS

We compared clinical and neurophysiological data of 18 Long COVID patients complaining of persistent cognitive impairment with 16 Healthy control (HC) subjects. Cognitive status was evaluated by means of the Montreal Cognitive Assessment (MoCA) and a neuropsychological evaluation of the executive function domain; fatigue was scored by the Fatigue Severity Scale (FSS). Resting motor threshold (RMT), the amplitude of the motor evoked potential (MEP), Short Intra-cortical Inhibition (SICI), Intra-cortical Facilitation (ICF), Long-interval Intracortical Inhibition (LICI) and Short-afferent inhibition (SAI) were investigated over the motor (M1) cortex.

RESULTS

MoCA corrected scores were significantly different between the two groups (p = 0.023). The majority of the patients' performed sub-optimally in the neuropsychological assessment of the executive functions. The majority (77.80%) of the patients reported high levels of perceived fatigue in the FSS. RMT, MEPs, SICI and SAI were not significantly different between the two groups. On the other hand, Long COVID patients showed a reduced amount of inhibition in LICI (p = 0.003) and a significant reduction in ICF (p < 0.001).

CONCLUSIONS

Neuro-Long COVID patients performing sub-optimally in the executive functions showed a reduction of LICI related to GABAb inhibition and a reduction of ICF related to glutamatergic regulation. No alteration in cholinergic circuits was found.

SIGNIFICANCE

These findings can help to better understand the neurophysiological characteristics of Neuro-Long COVID, and in particular, motor cortex regulation in people with "brain fog".

Clinical diagnostic utility of transcranial magnetic stimulation in neurological disorders. Updated report of an IFCN committee

The review provides a comprehensive update (previous report: Chen R, Cros D, Curra A, Di Lazzaro V, Lefaucheur JP, Magistris MR, et al. The clinical diagnostic utility of transcranial magnetic stimulation: report of an IFCN committee. Clin Neurophysiol 2008;119(3):504-32) on clinical diagnostic utility of transcranial magnetic stimulation (TMS) in neurological diseases. Most TMS measures rely on stimulation of motor cortex and recording of motor evoked potentials. Paired-pulse TMS techniques, incorporating conventional amplitude-based and threshold tracking, have established clinical utility in neurodegenerative, movement, episodic (epilepsy, migraines), chronic pain and functional diseases. Cortical hyperexcitability has emerged as a diagnostic aid in amyotrophic lateral sclerosis. Single-pulse TMS measures are of utility in stroke, and myelopathy even in the absence of radiological changes. Short-latency afferent inhibition, related to central cholinergic transmission, is reduced in Alzheimer's disease. The triple stimulation technique (TST) may enhance diagnostic utility of conventional TMS measures to detect upper motor neuron involvement. The recording of motor evoked potentials can be used to perform functional mapping of the motor cortex or in preoperative assessment of eloquent brain regions before surgical resection of brain tumors. TMS exhibits utility in assessing lumbosacral/cervical nerve root function, especially in demyelinating neuropathies, and may be of utility in localizing the site of facial nerve palsies. TMS measures also have high sensitivity in detecting subclinical corticospinal lesions in multiple sclerosis. Abnormalities in central motor conduction time or TST correlate with motor impairment and disability in MS. Cerebellar stimulation may detect lesions in the cerebellum or cerebello-dentato-thalamo-motor cortical pathways. Combining TMS with electroencephalography, provides a novel method to measure parameters altered in neurological disorders, including cortical excitability, effective connectivity, and response complexity.

TMS-EEG perturbation biomarkers for Alzheimer's disease patients classification

The combination of TMS and EEG has the potential to capture relevant features of Alzheimer's disease (AD) pathophysiology. We used a machine learning framework to explore time-domain features characterizing AD patients compared to age-matched healthy controls (HC). More than 150 time-domain features including some related to local and distributed evoked activity were extracted from TMS-EEG data and fed into a Random Forest (RF) classifier using a leave-one-subject out validation approach. The best classification accuracy, sensitivity, specificity and F1 score were of 92.95%, 96.15%, 87.94% and 92.03% respectively when using a balanced dataset of features computed globally across the brain. The feature importance and statistical analysis revealed that the maximum amplitude of the post-TMS signal, its Hjorth complexity and the amplitude of the TEP calculated in the window 45-80 ms after the TMS-pulse were the most relevant features differentiating AD patients from HC. TMS-EEG metrics can be used as a non-invasive tool to further understand the AD pathophysiology and possibly contribute to patients' classification as well as longitudinal disease tracking.

Biomarkers of diagnosis, prognosis, pathogenesis, response to therapy: Convergence or divergence? Lessons from Alzheimer's disease and synucleinopathies

Alzheimer's disease (AD) is the most common disorder associated with cognitive impairment. Recent observations emphasize the pathogenic role of multiple factors inside and outside the central nervous system, supporting the notion that AD is a syndrome of many etiologies rather than a "heterogeneous" but ultimately unifying disease entity. Moreover, the defining pathology of amyloid and tau coexists with many others, such as α-synuclein, TDP-43, and others, as a rule, not an exception. Thus, an effort to shift our AD paradigm as an amyloidopathy must be reconsidered. Along with amyloid accumulation in its insoluble state, β-amyloid is becoming depleted in its soluble, normal states, as a result of biological, toxic, and infectious triggers, requiring a shift from convergence to divergence in our approach to neurodegeneration. These aspects are reflected-in vivo-by biomarkers, which have become increasingly strategic in dementia. Similarly, synucleinopathies are primarily characterized by abnormal deposition of misfolded α-synuclein in neurons and glial cells and, in the process, depleting the levels of the normal, soluble α-synuclein that the brain needs for many physiological functions. The soluble to insoluble conversion also affects other normal brain proteins, such as TDP-43 and tau, accumulating in their insoluble states in both AD and dementia with Lewy bodies (DLB). The two diseases have been distinguished by the differential burden and distribution of insoluble proteins, with neocortical phosphorylated tau deposition more typical of AD and neocortical α-synuclein deposition peculiar to DLB. We propose a reappraisal of the diagnostic approach to cognitive impairment from convergence (based on clinicopathologic criteria) to divergence (based on what differs across individuals affected) as a necessary step for the launch of precision medicine.

Cognitive deficit in post-acute COVID-19: an opportunity for EEG evaluation?

BACKGROUND AND PURPOSE

Among the most common post-COVID symptoms, many patients experienced subjective cognitive deficit, commonly named "brain fog," that might be present also in those individuals without severe acute COVID-19 respiratory involvement. Some studies have investigated some of the mechanisms that might be associated with the brain fog with objective techniques including transcranial magnetic stimulation and neuroimaging.

METHODS

The aim of this study was to investigate the presence of electroencephalographic (EEG) alterations in people with post-COVID self-reported cognitive deficit.

RESULTS

Out of the 90 patients attending the post-COVID neurology ambulatory service, twenty patients presenting brain fog at least 4 weeks after acute non-severe COVID-19 infection, and without previous history of epilepsy, were investigated with 19-channel EEG, Montreal Cognitive Assessment (MoCA), and magnetic resonance imaging (MRI). EEG was found altered in 65% of the sample, among which 69% presented a slowing activity and 31% were characterized by epileptic discharges principally in the frontal areas. None of the patients showed DWI MRI lesions.

CONCLUSIONS

These findings highlight the usefulness of EEG analysis to objectively describe possible neurophysiological abnormalities in post-COVID patients presenting subjective cognitive deficit.

Cortical hyperexcitability and plasticity in Alzheimer's disease: developments in understanding and management

INTRODUCTION

Transcranial magnetic stimulation (TMS) is a non-invasive neurophysiological tool that provides important insights into Alzheimer's Disease (AD). A significant body of work utilizing TMS techniques has explored the pathophysiological relevance of cortical hyperexcitability and plasticity in AD and their modulation in novel therapies.

AREAS COVERED

This review examines the technique of TMS, the use of TMS to examine specific features of cortical excitability and the use of TMS techniques to modulate cortical function. A search was performed utilizing the PubMed database to identify key studies utilizing TMS to examine cortical hyperexcitability and plasticity in Alzheimer's dementia. We then translate this understanding to the study of Alzheimer's disease pathophysiology, examining the underlying neurophysiologic links contributing to these twin signatures, cortical hyperexcitability and abnormal plasticity, in the cortical dysfunction characterizing AD. Finally, we examine utilization of TMS excitability to guide targeted therapies and, through the use of repetitive TMS (rTMS), modulate cortical plasticity.

EXPERT OPINION

The examination of cortical hyperexcitability and plasticity with TMS has potential to optimize and expand the window of therapeutic interventions in AD, though remains at relatively early stage of development.

Classification accuracy of blood-based and neurophysiological markers in the differential diagnosis of Alzheimer's disease and frontotemporal lobar degeneration

BACKGROUND

In the last decade, non-invasive blood-based and neurophysiological biomarkers have shown great potential for the discrimination of several neurodegenerative disorders. However, in the clinical workup of patients with cognitive impairment, it will be highly unlikely that any biomarker will achieve the highest potential predictive accuracy on its own, owing to the multifactorial nature of Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD).

METHODS

In this retrospective study, performed on 202 participants, we analysed plasma neurofilament light (NfL), glial fibrillary acidic protein (GFAP), and tau phosphorylated at amino acid 181 (p-Tau181) concentrations, as well as amyloid β42 to 40 ratio (Aβ1-42/1-40) ratio, using the ultrasensitive single-molecule array (Simoa) technique, and neurophysiological measures obtained by transcranial magnetic stimulation (TMS), including short-interval intracortical inhibition (SICI), intracortical facilitation (ICF), long-interval intracortical inhibition (LICI), and short-latency afferent inhibition (SAI). We assessed the diagnostic accuracy of combinations of both plasma and neurophysiological biomarkers in the differential diagnosis between healthy ageing, AD, and FTLD.

RESULTS

We observed significant differences in plasma NfL, GFAP, and p-Tau181 levels between the groups, but not for the Aβ1-42/Aβ1-40 ratio. For the evaluation of diagnostic accuracy, we adopted a two-step process which reflects the clinical judgement on clinical grounds. In the first step, the best single biomarker to classify "cases" vs "controls" was NfL (AUC 0.94, p < 0.001), whilst in the second step, the best single biomarker to classify AD vs FTLD was SAI (AUC 0.96, p < 0.001). The combination of multiple biomarkers significantly increased diagnostic accuracy. The best model for classifying "cases" vs "controls" included the predictors p-Tau181, GFAP, NfL, SICI, ICF, and SAI, resulting in an AUC of 0.99 (p < 0.001). For the second step, classifying AD from FTD, the best model included the combination of Aβ1-42/Aβ1-40 ratio, p-Tau181, SICI, ICF, and SAI, resulting in an AUC of 0.98 (p < 0.001).

CONCLUSIONS

The combined assessment of plasma and neurophysiological measures may greatly improve the differential diagnosis of AD and FTLD.

Assessment of cortical inhibition depends on inter individual differences in the excitatory neural populations activated by transcranial magnetic stimulation

Transcranial magnetic stimulation (TMS) is used to probe inhibitory intracortical neurotransmission and has been used to infer the neurobiological dysfunction that may underly several neurological disorders. One technique, short-interval intracortical inhibition (SICI), indexes gamma-aminobutyric acid (GABA) mediated inhibitory activity and is a promising biomarker. However emerging evidence suggests SICI does not exclusively represent GABAergic activity because it may be influenced by inter-individual differences in the specific excitatory neural populations activated by TMS. Here we used the latency of TMS motor evoked potentials (MEPs) to index these inter-individual differences, and found that a significant proportion of the observed variability in SICI magnitude was accounted for by MEP latency, r = − 0.57, r² = 0.33, p = .014. We conclude that SICI is influenced by inter-individual differences in the excitatory neural populations activated by TMS, reducing the precision of this GABAergic probe. Interpreting SICI measures in the context of MEP latency may facilitate a more precise assessment of GABAergic intracortical inhibition. The reduced cortical inhibition observed in some neuropathologies could be influenced by reduced activity in specific excitatory neural populations. Including MEP latency assessment in research investigating SICI in clinical groups could assist in differentiating the cortical circuits impacted by neurological disorders.

Diagnostic Accuracy of the Five-Word Test for Mild Cognitive Impairment Due to Alzheimer's Disease

New diagnostic methods have been developed for the early diagnosis of Alzheimer’s disease (AD) with the primary purpose of intercepting the transition-phase (mild cognitive impairment, MCI) between normal aging and dementia. We aimed to explore whether the five-word test (FWT) and the mini-mental state examination (MMSE) are predictive for the early diagnosis of MCI due to AD (AD-MCI). We computed ROC analyses to evaluate the sensitivity and specificity of MMSE and FWT in predicting abnormal CSF (t-Tau, p-Tau181, Aβ1−42) and amyloid-PET biomarkers. AD-MCI patients showed lower MMSE and FWT scores (all p < 0.001) than non-AD-MCI. The best predictor of amyloid plaques’ presence at amyloid-PET imaging was the encoding sub-score of the FWT (AUC = 0.84). Both FWT and MMSE had low/moderate accuracy for the detection of pathological CSF Aβ42, t-Tau and p-Tau181 values, with higher accuracy for the t-Tau/Aβ1−42 ratio. In conclusion, the FWT, as a single-domain cognitive screening test, seems to be prompt and moderately accurate tool for the identification of an underlying AD neuropathological process in patients with MCI, supporting the importance of associating biomarkers evaluation in the work-up of patients with dementing neurodegenerative disorders.

Altered motor cortex physiology and dysexecutive syndrome in patients with fatigue and cognitive difficulties after mild COVID-19

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.

Neurophysiological Correlates of Motor and Cognitive Dysfunction in Prodromal and Overt Dementia with Lewy Bodies

Background: The neurophysiological correlates of cognitive and motor symptoms in prodromal and overt dementia with Lewy bodies (DLB) are still to be elucidated. Objective: To evaluate if cognitive and motor features of patients with prodromal and overt DLB are associated with the impairment of specific neurotransmitter circuits, evaluated in vivo with transcranial magnetic stimulation (TMS). Methods: Fifty-one patients with DLB (twenty-five prodromal; twenty-six with dementia) underwent neuropsychological and clinical evaluation, with twenty-five patients having at least one follow-up evaluation. All patients were assessed with TMS at baseline, with protocols assessing cholinergic circuits (short latency afferent inhibition, SAI), GABAergic circuits (short interval intracortical inhibition, SICI), and glutamatergic circuits (intracortical facilitation, ICF). Results: Compared to HC, SICI, ICF, and SAI resulted significantly impaired in both prodromal and overt DLB, with the latter showing a reduced SICI and SAI also compared to prodromal DLB. There was a significant correlation between motor deficits, evaluated with the UPDRS-III, and the impairment of GABAergic (SICI) (r = 0.729, p <  0.001) and glutamatergic (ICF) (r –0.608, p <  0.001) circuits; global cognition, evaluated with the Mini-Mental State Examination, correlated with the impairment of cholinergic (SAI) circuits (r=–0.738, p <  0.001). Worsening of cognitive functions at follow-up was associated with reduced cholinergic functions at baseline (R2  = 0.53%, p <  0.001). Conclusion: These results suggest that motor and cognitive dysfunctions in prodromal and overt DLB depend on specific and independent neurotransmitter circuits.

Egocentric spatial orientation differences between Alzheimer's disease at early stages and mild cognitive impairment: a diagnostic aid

Alzheimer's disease (AD) is a growing global crisis. Egocentric spatial orientation deteriorates with age and more significantly with AD. A simple and quick virtual reality (VR) localization and target finding technique is presented as a diagnostic aid to screen mild cognitive impairment (MCI) from AD. Spatial orientation data from 93 individuals (65 AD at a mild stage, 20 MCI, and 8 other dementia types) based on VR localization of a target on a landmark-less cubic 3-story building were analyzed. We hypothesize AD and MCI groups' performances are significantly different. AD and MCI spatial performances were statistically significantly (p < 0.001) different. These results plus the longitudinal tracking of three patients who developed AD over a period of 5 years suggest the proposed spatial tests may be used as a quick and simple clinical diagnostic aid to separate AD at early to mild stages from MCI.

Tetromino pattern based accurate EEG emotion classification model

Nowadays, emotion recognition using electroencephalogram (EEG) signals is becoming a hot research topic. The aim of this paper is to classify emotions of EEG signals using a novel game-based feature generation function with high accuracy. Hence, a multileveled handcrafted feature generation automated emotion classification model using EEG signals is presented. A novel textural features generation method inspired by the Tetris game called Tetromino is proposed in this work. The Tetris game is one of the famous games worldwide, which uses various characters in the game. First, the EEG signals are subjected to discrete wavelet transform (DWT) to create various decomposition levels. Then, novel features are generated from the decomposed DWT sub-bands using the Tetromino method. Next, the maximum relevance minimum redundancy (mRMR) features selection method is utilized to select the most discriminative features, and the selected features are classified using support vector machine classifier. Finally, each channel's results (validation predictions) are obtained, and the mode function-based voting method is used to obtain the general results. We have validated our developed model using three databases (DREAMER, GAMEEMO, and DEAP). We have attained 100% accuracies using DREAMER and GAMEEMO datasets. Furthermore, over 99% of classification accuracy is achieved for DEAP dataset. Thus, our developed emotion detection model has yielded the best classification accuracy rate compared to the state-of-the-art techniques and is ready to be tested for clinical application after validating with more diverse datasets. Our results show the success of the presented Tetromino pattern-based EEG signal classification model validated using three public emotional EEG datasets.

The Multimodal Sentiment Analysis of Online Product Marketing Information Using Text Mining and Big Data

Currently, the internet is increasingly popular. More people are used to sharing their feelings about various things on the internet. Online product marketing information is also growing. How to mine the required information from the massive information with the support of big data technology has become a big problem. Thereby, based on the text mining of online product marketing information, this work discusses the text preprocessing methods and the temporal convolution network (TCN) based on a convolutional neural network (CNN). Moreover, on this basis, multimodal attention mechanism (AM) and cross-modal transformer structure are added to build a TCN based on AM (AM-TCN) model to analyze the multimodal emotion of online product marketing information. The results show that the accuracy of the AM-TCN model is 2.88% higher than that of the TCN model alone, and F1 is 3.47% higher. Moreover, the accuracy rate of the AM-TCN is 1.22% higher than that of the next highest recurrent multistage fusion network, and the F1 value is 0.95% higher.

Classification of Cognitive Impairment and Healthy Controls Based on Transcranial Magnetic Stimulation Evoked Potentials

Backgrounds: Nowadays, risks of Cognitive Impairment (CI) [highly suspected Alzheimer's disease (AD) in this study] threaten the quality of life for more older adults as the population ages. The emergence of Transcranial Magnetic Stimulation-Electroencephalogram (TMS-EEG) enables noninvasive neurophysiological investi-gation of the human cortex, which might be potentially used for CI detection. Objectives: The aim of this study is to explore whether the spatiotemporal features of TMS Evoked Potentials (TEPs) could classify CI from healthy controls (HC). Methods: Twenty-one patients with CI and 22 HC underwent a single-pulse TMS-EEG stimulus in which the pulses were delivered to the left dorsolateral prefrontal cortex (left DLPFC). After preprocessing, seven regions of interest (ROIs) and two most reliable TEPs' components: N100 and P200 were selected. Next, seven simple and interpretable linear features of TEPs were extracted for each region, three common machine learning algorithms including Support Vector Machine (SVM), Random Forest (RF), and K-Nearest Neighbor (KNN) were used to detect CI. Meanwhile, data augmentation and voting strategy were used for a more robust model. Finally, the performance differences of features in classifiers and their contributions were investigated. Results: 1. In the time domain, the features of N100 had the best performance in the SVM classifier, with an accuracy of 88.37%. 2. In the aspect of spatiality, the features of the right frontal region and left parietal region had the best performance in the SVM classifier, with an accuracy of 83.72%. 3. The Local Mean Field Power (LMFP), Average Value (AVG), Latency and Amplitude contributed most in classification. Conclusions: The TEPs induced by TMS over the left DLPFC has significant differences spatially and temporally between CI and HC. Machine learning based on the spatiotemporal features of TEPs have the ability to separate the CI and HC which suggest that TEPs has potential as non-invasive biomarkers for CI diagnosis.

Association of Superficial White Matter Alterations with Cerebrospinal Fluid Biomarkers and Cognitive Decline in Neurodegenerative Dementia

BACKGROUND

Superficial white matter (SWM) alterations correlated with cognitive decline have been described in Alzheimer's disease (AD).

OBJECTIVE

The study aims to extend the investigation of the SWM alterations to AD and non-AD neurodegenerative dementia (ND) and explore the relationship with cerebrospinal fluid (CSF) biomarkers and clinical data.

METHODS

From a database of 323 suspected dementia cases, we retrospectively recruited 55 ND with abnormal amyloid-β42 (AD) and 38 ND with normal amyloid-β42 (non-AD) and collected clinical data, CSF biomarkers, and magnetic resonance images. Ten healthy controls (HC) were recruited for imaging and Mini-Mental State Examination (MMSE). Diffusion tensor imaging (DTI) measurements were performed in the lobar SWM regions and Kruskal Wallis tests were used for among-group comparison. Spearman's correlation tests were performed between DTI measures, CSF biomarkers, and clinical data.

RESULTS

AD and non-AD showed significant differences in the DTI measures across the SWM compared to HC. Significant differences between AD and non-AD were detected in the left parietal lobe. DTI measures correlated with amyloid-β42 and MMSE diffusely in the SWM, less extensively with total-tau and phosphorylated tau, and with disease duration in the parietal lobe bilaterally.

CONCLUSION

Widespread SWM alterations occur in both AD and non-AD ND and AD shows appreciably more severe alterations in the parietal SWM. Notably, the alterations in the SWM are strongly linked not only to the cognitive decline but also to the diagnostic CSF biomarkers. Further studies are encouraged to evaluate the DTI measures in the SWM as in vivo non-invasive biomarkers in the preclinical phase.

Diagnostic contribution and therapeutic perspectives of transcranial magnetic stimulation in dementia

Transcranial magnetic stimulation (TMS) is a powerful tool to probe in vivo brain circuits, as it allows to assess several cortical properties such asexcitability, plasticity and connectivity in humans. In the last 20 years, TMS has been applied to patients with dementia, enabling the identification of potential markers of thepathophysiology and predictors of cognitive decline; moreover, applied repetitively, TMS holds promise as a potential therapeutic intervention. The objective of this paper is to present a comprehensive review of studies that have employed TMS in dementia and to discuss potential clinical applications, from the diagnosis to the treatment. To provide a technical and theoretical framework, we first present an overview of the basic physiological mechanisms of the application of TMS to assess cortical excitability, excitation and inhibition balance, mechanisms of plasticity and cortico-cortical connectivity in the human brain. We then review the insights gained by TMS techniques into the pathophysiology and predictors of progression and response to treatment in dementias, including Alzheimer's disease (AD)-related dementias and secondary dementias. We show that while a single TMS measure offers low specificity, the use of a panel of measures and/or neurophysiological index can support the clinical diagnosis and predict progression. In the last part of the article, we discuss the therapeutic uses of TMS. So far, only repetitive TMS (rTMS) over the left dorsolateral prefrontal cortex and multisite rTMS associated with cognitive training have been shown to be, respectively, possibly (Level C of evidence) and probably (Level B of evidence) effective to improve cognition, apathy, memory, and language in AD patients, especially at a mild/early stage of the disease. The clinical use of this type of treatment warrants the combination of brain imaging techniques and/or electrophysiological tools to elucidate neurobiological effects of neurostimulation and to optimally tailor rTMS treatment protocols in individual patients or specific patient subgroups with dementia or mild cognitive impairment.

Transcranial Magnetic Stimulation as a Diagnostic and Therapeutic Tool in Various Types of Dementia

Dementia is recognized as a healthcare and social burden and remains challenging in terms of proper diagnosis and treatment. Transcranial magnetic stimulation (TMS) is a diagnostic and therapeutic tool in various neurological diseases that noninvasively investigates cortical excitability and connectivity and can induce brain plasticity. This article reviews findings on TMS in common dementia types as well as therapeutic results. Alzheimer’s disease (AD) is characterized by increased cortical excitability and reduced cortical inhibition, especially as mediated by cholinergic neurons and as documented by impairment of short latency inhibition (SAI). In vascular dementia, excitability is also increased. SAI may have various outcomes, which probably reflects its frequent overlap with AD. Dementia with Lewy bodies (DLB) is associated with SAI decrease. Motor cortical excitability is usually normal, reflecting the lack of corticospinal tract involvement. DLB and other dementia types are also characterized by impairment of short interval intracortical inhibition. In frontotemporal dementia, cortical excitability is increased, but SAI is normal. Repetitive transcranial magnetic stimulation has the potential to improve cognitive function. It has been extensively studied in AD, showing promising results after multisite stimulation. TMS with electroencephalography recording opens new possibilities for improving diagnostic accuracy; however, more studies are needed to support the existing data.

Experimental Disease-Modifying Agents for Frontotemporal Lobar Degeneration

Frontotemporal dementia is a clinically, genetically and pathologically heterogeneous neurodegenerative disorder, enclosing a wide range of different pathological entities, associated with the accumulation of proteins such as tau and TPD-43. Characterized by a high hereditability, mutations in three main genes, MAPT, GRN and C9orf72, can drive the neurodegenerative process. The connection between different genes and proteinopathies through specific mechanisms has shed light on the pathophysiology of the disease, leading to the identification of potential pharmacological targets. New experimental strategies are emerging, in both preclinical and clinical settings, which focus on small molecules rather than gene therapy. In this review, we provide an insight into the aberrant mechanisms leading to FTLD-related proteinopathies and discuss recent therapies with the potential to ameliorate neurodegeneration and disease progression.

A Scoping Review of Neuromodulation Techniques in Neurodegenerative Diseases: A Useful Tool for Clinical Practice?

Background and Objectives: Neurodegenerative diseases that typically affect the elderly such as Alzheimer’s disease, Parkinson’s disease and frontotemporal dementia are typically characterised by significant cognitive impairment that worsens significantly over time. To date, viable pharmacological options for the cognitive symptoms in these clinical conditions are lacking. In recent years, various studies have employed neuromodulation techniques to try and contrast patients’ decay. Materials and Methods: We conducted an in-depth literature review of the state-of-the-art of the contribution of these techniques across these neurodegenerative diseases. Results: The present review reports that neuromodulation techniques targeting cognitive impairment do not allow to draw yet any definitive conclusion about their clinical efficacy although preliminary evidence is very encouraging. Conclusions: Further and more robust studies should evaluate the potentialities and limitations of the application of these promising therapeutic tools to neurodegenerative diseases.