Kernel-based Nonlinear Manifold Learning for EEG-based Functional Connectivity Analysis and Channel Selection with Application to Alzheimer's Disease.

Dynamical, causal, and cross-frequency coupling analysis using the electroencephalogram (EEG) has gained significant attention for diagnosing and characterizing neurological disorders. Selecting important EEG channels is crucial for reducing computational complexity in implementing these methods and improving classification accuracy. In neuroscience, measures of (dis) similarity between EEG channels are often used as functional connectivity (FC) features, and important channels are selected via feature selection. Developing a generic measure of (dis) similarity is important for FC analysis and channel selection. In this study, learning of (dis) similarity information within the EEG is achieved using kernel-based nonlinear manifold learning. The focus is on FC changes and, thereby, EEG channel selection. Isomap and Gaussian Process Latent Variable Model (Isomap-GPLVM) are employed for this purpose. The resulting kernel (dis) similarity matrix is used as a novel measure of linear and nonlinear FC between EEG channels. The analysis of EEG from healthy controls (HC) and patients with mild to moderate Alzheimer's disease (AD) are presented as a case study. Classification results are compared with other commonly used FC measures. Our analysis shows significant differences in FC between bipolar channels of the occipital region and other regions (i.e. parietal, centro-parietal, and fronto-central) between AD and HC groups. Furthermore, our results indicate that FC changes between channels along the fronto-parietal region and the rest of the EEG are important in diagnosing AD. Our results and its relation to functional networks are consistent with those obtained from previous studies using fMRI, resting-state fMRI and EEG.

Cross-Frequency Multilayer Network Analysis with Bispectrum-based Functional Connectivity: A Study of Alzheimer's Disease.

Alzheimer's disease (AD) is a neurodegenerative disorder known to affect functional connectivity (FC) across many brain regions. Linear FC measures have been applied to study the differences in AD by splitting neurophysiological signals, such as electroencephalography (EEG) recordings, into discrete frequency bands and analysing them in isolation from each other. We address this limitation by quantifying cross-frequency FC in addition to the traditional within-band approach. Cross-bispectrum, a higher-order spectral analysis approach, is used to measure the nonlinear FC and is compared with the cross-spectrum, which only measures the linear FC within bands. This work reports the reconstruction of a cross-frequency FC network where each frequency band is treated as a layer in a multilayer network with both inter- and intra-layer edges. Cross-bispectrum detects cross-frequency differences, mainly increased FC in AD cases in δ-θ coupling. Overall, increased strength of low-frequency coupling and decreased level of high-frequency coupling is observed in AD cases in comparison to healthy controls (HC). We demonstrate that a graph-theoretic analysis of cross-frequency brain networks is crucial to obtain a more detailed insight into their structure and function. Vulnerability analysis reveals that the integration and segregation properties of networks are enabled by different frequency couplings in AD networks compared to HCs. Finally, we use the reconstructed networks for classification. The extra cross-frequency coupling information can improve the classification performance significantly, suggesting an important role of cross-frequency FC. The results highlight the importance of studying nonlinearity and including cross-frequency FC in characterising AD.

Ultra-high-resolution time-frequency analysis of EEG to characterise brain functional connectivity with the application in Alzheimer's disease.

Objective.This study aims to explore the potential of high-resolution brain functional connectivity based on electroencephalogram, a non-invasive low-cost technique, to be translated into a long-overdue biomarker and a diagnostic method for Alzheimer's disease (AD).Approach.The paper proposes a novel ultra-high-resolution time-frequency nonlinear cross-spectrum method to construct a promising biomarker of AD pathophysiology. Specifically, using the peak frequency estimated from a revised Hilbert-Huang transformation (RHHT) cross-spectrum as a biomarker, the support vector machine classifier is used to distinguish AD from healthy controls (HCs).Main results.With the combinations of the proposed biomarker and machine learning, we achieved a promising accuracy of 89%. The proposed method performs better than the wavelet cross-spectrum and other functional connectivity measures in the temporal or frequency domain, particularly in the Full, Delta and Alpha bands. Besides, a novel visualisation approach developed from topography is introduced to represent the brain functional connectivity, with which the difference between AD and HCs can be clearly displayed. The interconnections between posterior and other brain regions are obviously affected in AD.Significance.Those findings imply that the proposed RHHT approach could better track dynamic and nonlinear functional connectivity information, paving the way for the development of a novel diagnostic approach.

Bickerstaff brainstem encephalitis: clinical, neurophysiological, laboratory and postmortem findings of a case presenting as encephalomyelitis.

Our patient was admitted to hospital with a 1-week history of an upper respiratory tract infection and a rapidly progressive encephalopathy dominated by brainstem features and widespread areflexia. Her antiganglioside antibodies and electroencephalography were consistent with Bickerstaff brainstem encephalitis (BBE), and her postmortem examination revealed a predominantly florid brainstem encephalitis and myelitis. Her sputum and throat swabs isolated Haemophilus influenzae and Fusobacterium, respectively, the former being the most probable trigger of BBE. Our patient's death, despite the otherwise good prognosis of the disorder, may reflect the severity of the pathological changes at postmortem or the association of comorbid disorders such as sepsis-associated encephalopathy. Her poor outcome may also be an indication to treat rapidly progressive cases of BBE with more than one immune modulating drug.

Characterising Alzheimer's Disease With EEG-Based Energy Landscape Analysis.

Alzheimer's disease (AD) is one of the most common neurodegenerative diseases, with around 50 million patients worldwide. Accessible and non-invasive methods of diagnosing and characterising AD are therefore urgently required. Electroencephalography (EEG) fulfils these criteria and is often used when studying AD. Several features derived from EEG were shown to predict AD with high accuracy, e.g. signal complexity and synchronisation. However, the dynamics of how the brain transitions between stable states have not been properly studied in the case of AD and EEG. Energy landscape analysis is a method that can be used to quantify these dynamics. This work presents the first application of this method to both AD and EEG. Energy landscape assigns energy value to each possible state, i.e. pattern of activations across brain regions. The energy is inversely proportional to the probability of occurrence. By studying the features of energy landscapes of 20 AD patients and 20 age-matched healthy counterparts (HC), significant differences are found. The dynamics of AD patients' EEG are shown to be more constrained - with more local minima, less variation in basin size, and smaller basins. We show that energy landscapes can predict AD with high accuracy, performing significantly better than baseline models. Moreover, these findings are replicated in a separate dataset including 9 AD and 10 HC above 70 years old.

Sudomotor dysfunction in patients with gluten neuropathy.

BACKGROUND AND AIM: Gluten neuropathy (GN) is a common neurological manifestation of gluten sensitivity (GS), characterized by serological evidence of GS, while other risk factors for developing neuropathy are absent. The degree of small fiber dysfunction in GN has not been studied in depth to date. Small fiber involvement may lead to pain, thermal perception abnormalities, and sweat gland dysfunction. Sudomotor innervation refers to the cholinergic innervation of the sympathetic nervous system through small fibers in the sweat glands. The aim of our study was to assess the sudomotor function of GN patients. METHODS: Patients with GN were recruited. Clinical and neurophysiological data were obtained. HLA-DQ genotyping was performed. The skin electrochemical conductance (ESC) was measured with SUDOSCANTM. RESULTS: Thirty-two patients (25 males, mean age 69.5±10.2 years) were recruited. Thirteen patients (40.6%) had abnormal sudomotor function of the hands. Sixteen patients (50%) had abnormal sudomotor function of the feet. Twenty-one patients (65.6%) had abnormal sudomotor function of either the hands or feet. Sudomotor dysfunction did not correlate with the type of neuropathy (length-dependent neuropathy or sensory ganglionopathy), gluten-free diet adherence, severity of neuropathy, and duration of disease or HLA-DQ genotype. No differences in the ESC were found between patients with painful and patients with painless GN. CONCLUSION: Sudomotor dysfunction affects two-thirds of patients with GN. The lack of correlation between pain and sudomotor dysfunction suggests different patterns of small fiber involvement in patients with GN.

Glycine receptor antibodies and coeliac disease-related neurological dysfunction.

Gluten sensitivity can manifest with a spectrum of neurological dysfunction including ataxia, encephalopathy and neuropathy with or without associated coeliac disease (CD). Gluten sensitivity can also present with central nervous system (CNS) hyperexcitability and cortical myoclonus which is often accompanied with refractory CD. CNS hyperexcitability can also be associated with Glutamic Acid Decarboxylase (GAD) antibodies or much less commonly with Glycine Receptor Antibodies (GlyR-Abs) but the direct pathogenic roles of these antibodies remain debatable. We have previously reported a link between gluten sensitivity and anti-GAD associated ataxia which improves with the adoption of gluten-free diet. It is unclear if a similar link exists between gluten driven CNS hyperexcitability and the presence of GlyR-Abs. We report two cases of CD presenting with CNS hyperexcitability and associated GlyR-Abs. Apart from ataxia and cortical myoclonus, one patient had refractory CD and died from enteropathy-associated T-cell lymphoma. The other patient not only improved with strict gluten-free diet but also showed serological elimination of circulating GlyR-Abs. We conclude that there is an interaction between gluten sensitivity and GlyR-Abs-associated CNS hyperexcitability and in such patients gluten-free diet is an important therapeutic intervention. The elimination of GlyR-Abs by the adoption of gluten free diet suggests that these antibodies may represent an epiphenomenon rather than being directly implicated in the pathogenesis.

Stiff Person Syndrome and Gluten Sensitivity.

Stiff person syndrome (SPS) is a rare autoimmune disease characterised by axial stiffness and episodic painful spasms. It is associated with additional autoimmune diseases and cerebellar ataxia. Most patients with SPS have high levels of glutamic acid decarboxylase (GAD) antibodies. The aetiology of SPS remains unclear but autoimmunity is thought to play a major part. We have previously demonstrated overlap between anti-GAD ataxia and gluten sensitivity. We have also demonstrated the beneficial effect of a gluten-free diet (GFD) in patients with anti-GAD ataxia. Here, we describe our experience in the management of 20 patients with SPS. The mean age at symptom onset was 52 years. Additional autoimmune diseases were seen in 15/20. Nineteen of the 20 patients had serological evidence of gluten sensitivity and 6 had coeliac disease. Fourteen of the 15 patients who had brain imaging had evidence of cerebellar involvement. Twelve patients improved on GFD and in seven GFD alone was the only treatment required long term. Twelve patients had immunosuppression but only three remained on such medication. Gluten sensitivity plays an important part in the pathogenesis of SPS and GFD is an effective therapeutic intervention.

Chronic idiopathic axonal polyneuropathy: Electrophysiological progression and human leukocyte antigen associations.

BACKGROUND: We aimed to describe the electrophysiological progression rate of chronic idiopathic axonal polyneuropathy (CIAP) and look into the potential role of human leukocyte antigen (HLA) genetic susceptibility in its development. METHODS: We recruited 57 patients with CIAP (mean age at diagnosis 67, mean follow-up 7 years). The assessments included clinical and electrophysiological data and HLA-DQ genotyping. RESULTS: The DQA1*05 allele was found more frequently in patients than in healthy controls (odds ratio, 1.96, P = .011). In patients with length-dependent CIAP, a linear effect of time on the electrophysiological findings was found in the superficial radial (3.2% mean annual decrement, P < .001), sural (4.7% mean annual decrement, P = .002) and tibial nerve (6.1% mean annual decrement, P = .007) amplitudes, independently from age or gender. CONCLUSIONS: Patients with length-dependent CIAP, show a linear progression over time. Interesting associations of HLA-DQA1*05 allele with length-dependent CIAP and non-DQ2/DQ8 with idiopathic sensory ganglionopathy were found. These merit further investigation in larger cohorts and may suggest a role of the immune system in the pathogenesis of CIAP.

Autologous haematopoietic stem cell transplantation for refractory stiff-person syndrome: the UK experience.

Stiff Person Syndrome (SPS) is a rare immune-mediated disabling neurological disorder characterised by muscle spasms and high GAD antibodies. There are only a few case reports of autologous haematopoietic stem cell transplantation (auto-HSCT) as a treatment for SPS. OBJECTIVE: To describe the UK experience of treating refractory SPS with auto-HSCT. METHODS: Between 2015 and 2019, 10 patients with SPS were referred to our institution for consideration of auto-HSCT. Eight patients were deemed suitable for autograft and four were treated. Of the treated patients, three had classical SPS and one had the progressive encephalomyelitis with rigidity and myoclonus variant. All patients were significantly disabled and had failed conventional immunosuppressive therapy. Patients were mobilised with Cyclophosphamide (Cy) 2 g/m2 + G-CSF and conditioned with Cy 200 mg/kg + ATG followed by auto-HSCT. RESULTS: Despite their significantly reduced performance status, all patients tolerated the procedure with no unexpected toxicities. Following autograft, all patients improved symptomatically and stopped all forms of immunosuppressive therapies. Two patients were able to ambulate independently from being wheelchair dependent. One patient's walking distance improved from 300 meters to 5 miles and one patient's ambulation improved from being confined to a wheelchair to be able to walk with a frame. Two patients became seronegative for anti-GAD antibodies and normalised their neurophysiological abnormalities. CONCLUSIONS: Auto-HSCT is an intensive but well tolerated and effective treatment option for patients with SPS refractory to conventional immunotherapy. Further work is warranted to optimise patient selection and establish the efficacy, long-term safety, and cost-effectiveness of this treatment.

Safety, Tolerability, and Nocebo Phenomena During Transcranial Magnetic Stimulation: A Systematic Review and Meta-Analysis of Placebo-Controlled Clinical Trials.

BACKGROUND: The methodology used for the application of repetitive transcranial magnetic stimulation (TMS) is such that it may induce a placebo effect. Respectively, adverse events (AEs) can occur when using a placebo, a phenomenon called nocebo. The primary aim of our meta-analysis is to establish the nocebo phenomena during TMS. Safety and tolerability of TMS were also studied. METHODS: After a systematic Medline search for TMS randomized controlled trials (RCTs), we assessed the number of patients reporting at least one AE and the number of discontinuations because of AE in active and sham TMS groups. RESULTS: Data were extracted from 93 RCTs. The overall pooled estimate of active TMS and placebo treated patients who discontinued treatment because of AEs was 2.5% (95% CI 1.9%-3.2%) and 2.7% (95% CI 2.0%-3.5%), respectively. The pooled estimate of active TMS and placebo treated patients experiencing at least one AE was 29.3% (95% CI 19.0%-22.6%) and 13.6% (95% CI 11.6%-15.8%), respectively, suggesting that the odds of experiencing an AE is 2.60 times higher (95% CI 1.75-3.86) in the active treatment group compared to placebo (p < 0.00001). The most common AE was headache, followed by dizziness. Secondary meta-analyses in depression and psychotic disorders showed that the odds of experiencing an AE is 3.98 times higher (95% CI 2.14-7.40) and 2.93 times higher (95% CI 1.41-6.07), respectively, in the active treatment groups compared to placebo. CONCLUSIONS: TMS is a safe and well-tolerated intervention. Nocebo phenomena do occur during TMS treatment and should be acknowledged during clinical trial design and daily clinical practice.

Imaging of Nonlinear and Dynamic Functional Brain Connectivity Based on EEG Recordings With the Application on the Diagnosis of Alzheimer's Disease.

Since age is the most significant risk factor for the development of Alzheimer's disease (AD), it is important to understand the effect of normal ageing on brain network characteristics before we can accurately diagnose the condition based on information derived from resting state electroencephalogram (EEG) recordings, aiming to detect brain network disruption. This article proposes a novel brain functional connectivity imaging method, particularly targeting the contribution of nonlinear dynamics of functional connectivity, on distinguishing participants with AD from healthy controls (HC). We describe a parametric method established upon a Nonlinear Finite Impulse Response model, and a revised orthogonal least squares algorithm used to estimate the linear, nonlinear and combined connectivity between any two EEG channels without fitting a full model. This approach, where linear and non-linear interactions and their spatial distribution and dynamics can be estimated independently, offered us the means to dissect the dynamic brain network disruption in AD from a new perspective and to gain some insight into the dynamic behaviour of brain networks in two age groups (above and below 70) with normal cognitive function. Although linear and stationary connectivity dominates the classification contributions, quantitative results have demonstrated that nonlinear and dynamic connectivity can significantly improve the classification accuracy, barring the group of participants below the age of 70, for resting state EEG recorded during eyes open. The developed approach is generic and can be used as a powerful tool to examine brain network characteristics and disruption in a user friendly and systematic way.

A Novel Pathogenic Variant in MT-CO2 Causes an Isolated Mitochondrial Complex IV Deficiency and Late-Onset Cerebellar Ataxia.

Both nuclear and mitochondrial DNA defects can cause isolated cytochrome c oxidase (COX; complex IV) deficiency, leading to the development of the mitochondrial disease. We report a 52-year-old female patient who presented with a late-onset, progressive cerebellar ataxia, tremor and axonal neuropathy. No family history of neurological disorder was reported. Although her muscle biopsy demonstrated a significant COX deficiency, there was no clinical and electromyographical evidence of myopathy. Electrophysiological studies identified low frequency sinusoidal postural tremor at 3 Hz, corroborating the clinical finding of cerebellar dysfunction. Complete sequencing of the mitochondrial DNA genome in muscle identified a novel MT-CO2 variant, m.8163A>G predicting p.(Tyr193Cys). We present several lines of evidence, in proving the pathogenicity of this heteroplasmic mitochondrial DNA variant, as the cause of her clinical presentation. Our findings serve as an important reminder that full mitochondrial DNA analysis should be included in the diagnostic pipeline for investigating individuals with spinocerebellar ataxia.

Pain in Chronic Inflammatory Demyelinating Polyradiculoneuropathy: A Systematic Review and Meta-Analysis.

INTRODUCTION: Although chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) predominantly affects large myelinated fibers, many patients have pain. The aim of this paper is to systematically review the current literature regarding CIDP with a particular focus on epidemiological and clinical characteristics of painful CIDP. METHODS: A systematic literature search was conducted on PubMed database. RESULTS: Our search strategy identified 146 articles. Thirty-eight papers, reporting on 991 patients, met the inclusion criteria and were used for this review. The pooled estimate of the prevalence of pain at any point within the course of CIDP was 46% (95% CI 36-57%). Immune treatment of CIDP might be adequate as monotherapy for the management of pain. Treatment specific to pain currently shows effectiveness as adjuvant treatment when CIDP is treated and pain persists. CONCLUSIONS: Pain in CIDP is an underexplored field. Future research should focus on the natural history, phenomenology, and management of pain in CIDP.

A Dementia Classification Framework Using Frequency and Time-Frequency Features Based on EEG Signals.

Alzheimer's disease (AD) accounts for 60%-70% of all dementia cases, and clinical diagnosis at its early stage is extremely difficult. As several new drugs aiming to modify disease progression or alleviate symptoms are being developed, to assess their efficacy, novel robust biomarkers of brain function are urgently required. This paper aims to explore a routine to gain such biomarkers using the quantitative analysis of electroencephalography (QEEG). This paper proposes a supervised classification framework that uses EEG signals to classify healthy controls (HC) and AD participants. The framework consists of data augmentation, feature extraction, K-nearest neighbor (KNN) classification, quantitative evaluation, and topographic visualization. Considering the human brain either as a stationary or a dynamical system, both the frequency-based and time-frequency-based features were tested in 40 participants. The results show that: 1) the proposed method can achieve up to a 99% classification accuracy on short (4s) eyes open EEG epochs, with the KNN algorithm that has best performance when compared with alternative machine learning approaches; 2) the features extracted using the wavelet transform produced better classification performance in comparison to the features based on FFT; and 3) in the spatial domain, the temporal and parietal areas offer the best distinction between healthy controls and AD. The proposed framework can effectively classify HC and AD participants with high accuracy, meanwhile offering identification and the localization of significant QEEG features. These important findings and the proposed classification framework could be used for the development of a biomarker for the diagnosis and monitoring of disease progression in AD.

Neurologic Deficits in Patients With Newly Diagnosed Celiac Disease Are Frequent and Linked With Autoimmunity to Transglutaminase 6.

BACKGROUND & AIMS: Celiac disease is an autoimmune disorder induced by ingestion of gluten that affects 1% of the population and is characterized by gastrointestinal symptoms, weight loss, and anemia. We evaluated the presence of neurologic deficits and investigated whether the presence of antibodies to Transglutaminase 6 (TG6) increases the risk of neurologic defects in patients with a new diagnosis of celiac disease. METHODS: We performed a prospective cohort study at a secondary-care gastroenterology center of 100 consecutive patients who received a new diagnosis of celiac disease based on gastroscopy and duodenal biopsy. We collected data on neurologic history, and patients were evaluated in a clinical examination along with magnetic resonance imaging of the brain, magnetic resonance (MR) spectroscopy of the cerebellum, and measurements of antibodies against TG6 in serum samples. The first 52 patients recruited underwent repeat MR spectroscopy at 1 year after a gluten-free diet (GFD). The primary aim was to establish if detection of antibodies against TG6 can be used to identify patients with celiac disease and neurologic dysfunction. RESULTS: Gait instability was reported in 24% of the patients, persisting sensory symptoms in 12%, and frequent headaches in 42%. Gait ataxia was found in 29% of patients, nystagmus in 11%, and distal sensory loss in 10%. Sixty percent of patients had abnormal results from magnetic resonance imaging, 47% had abnormal results from MR spectroscopy of the cerebellum, and 25% had brain white matter lesions beyond that expected for their age group. Antibodies against TG6 were detected in serum samples from 40% of patients-these patients had significant atrophy of subcortical brain regions compared with patients without TG6 autoantibodies. In patients with abnormal results from MR spectroscopy of the cerebellum, those on the GFD had improvements detected in the repeat MR spectroscopy 1 year later. CONCLUSIONS: In a prospective cohort study of patients with a new diagnosis of celiac disease at a gastroenterology clinic, neurologic deficits were common and 40% had circulating antibodies against TG6. We observed a significant reduction in volume of specific brain regions in patients with TG6 autoantibodies, providing evidence for a link between autoimmunity to TG6 and brain atrophy in patients with celiac disease. There is a need for early diagnosis, increased awareness of the neurologic manifestations among clinicians, and reinforcement of adherence to a strict GFD by patients to avoid permanent neurologic disability.

Chronic idiopathic axonal polyneuropathy: Prevalence of pain and impact on quality of life.

BACKGROUND AND AIM: Chronic idiopathic axonal polyneuropathy (CIAP) is a term describing axonal neuropathies of insidious onset, with slow or no progression of the disease over at least 6 months and with no etiology being identified despite appropriate investigations. We aimed to establish the prevalence of pain in patients with CIAP and investigate the impact of pain on quality of life (QoL). METHODS: All consecutive patients with CIAP attending a specialist neuropathy clinic were invited to participate. Pain was assessed via the DN4 questionnaire and the visual analogue scale (VAS). Overall Neuropathy Limitations Scale (ONLS) was used to assess the severity of neuropathy. The SF-36 questionnaire was used to measure participants' quality of life. RESULTS: Fifty-five patients with CIAP were recruited (63.6% male, mean age 73.4 ± 8.7 years). Based on the DN4 questionnaire, peripheral neuropathic pain was present in 33 patients (60.0%). After having adjusted for age, gender and disease severity pain showed significant negative correlations with the energy/fatigue domain of QoL (ß = -0.259, p = 0.049), with the emotional well-being domain (ß = -0.368, p = 0.007) and the general health perception domain (ß = -0.356, p = 0.007). CONCLUSION: Pain is very prevalent in CIAP and is associated with poorer emotional well-being, worse general health perception, and increased fatigue.

The Significance of Low Titre Antigliadin Antibodies in the Diagnosis of Gluten Ataxia.

BACKGROUND: Patients with gluten ataxia (GA) without enteropathy have lower levels of antigliadin antibodies (AGA) compared to patients with coeliac disease (CD). Magnetic Resonance Spectroscopy (NAA/Cr area ratio) of the cerebellum improves in patients with GA following a strict gluten-free diet (GFD). This is associated with clinical improvement. We present our experience of the effect of a GFD in patients with ataxia and low levels of AGA antibodies measured by a commercial assay. METHODS: Consecutive patients with ataxia and serum AGA levels below the positive cut-off for CD but above a re-defined cut-off in the context of GA underwent MR spectroscopy at baseline and after a GFD. RESULTS: Twenty-one consecutive patients with GA were included. Ten were on a strict GFD with elimination of AGA, 5 were on a GFD but continued to have AGA, and 6 patients did not go on a GFD. The NAA/Cr area ratio from the cerebellar vermis increased in all patients on a strict GFD, increased in only 1 out of 5 (20%) patients on a GFD with persisting circulating AGA, and decreased in all patients not on a GFD. CONCLUSION: Patients with ataxia and low titres of AGA benefit from a strict GFD. The results suggest an urgent need to redefine the serological cut-off for circulating AGA in diagnosing GA.

A Pilot Study Investigating a Novel Non-Linear Measure of Eyes Open versus Eyes Closed EEG Synchronization in People with Alzheimer's Disease and Healthy Controls

BACKGROUND: The incidence of Alzheimer disease (AD) is increasing with the ageing population. The development of low cost non-invasive diagnostic aids for AD is a research priority. This pilot study investigated whether an approach based on a novel dynamic quantitative parametric EEG method could detect abnormalities in people with AD. METHODS: 20 patients with probable AD, 20 matched healthy controls (HC) and 4 patients with probable fronto temporal dementia (FTD) were included. All had detailed neuropsychology along with structural, resting state fMRI and EEG. EEG data were analyzed using the Error Reduction Ratio-causality (ERR-causality) test that can capture both linear and nonlinear interactions between different EEG recording areas. The 95% confidence intervals of EEG levels of bi-centroparietal synchronization were estimated for eyes open (EO) and eyes closed (EC) states. RESULTS: In the EC state, AD patients and HC had very similar levels of bi-centro parietal synchronization; but in the EO resting state, patients with AD had significantly higher levels of synchronization (AD = 0.44; interquartile range (IQR) 0.41 vs. HC = 0.15; IQR 0.17, p < 0.0001). The EO/EC synchronization ratio, a measure of the dynamic changes between the two states, also showed significant differences between these two groups (AD ratio 0.78 versus HC ratio 0.37 p < 0.0001). EO synchronization was also significantly different between AD and FTD (FTD = 0.075; IQR 0.03, p < 0.0001). However, the EO/EC ratio was not informative in the FTD group due to very low levels of synchronization in both states (EO and EC). CONCLUSION: In this pilot work, resting state quantitative EEG shows significant differences between healthy controls and patients with AD. This approach has the potential to develop into a useful non-invasive and economical diagnostic aid in AD.