Electrophysiological assessment methodology of sensory processing dysfunction in schizophrenia and dementia of the Alzheimer type

A High-Resolution LED Stimulator for Steady-State Visual Stimulation: Customizable, Affordable, and Open Source

Visually evoked steady-state potentials (SSVEPs) are neural responses elicited by visual stimuli oscillating at specific frequencies. In this study, we introduce a novel LED stimulator system explicitly designed for steady-state visual stimulation, offering precise control over visual stimulus parameters, including frequency resolution, luminance, and the ability to control the phase at the end of the stimulation. The LED stimulator provides a personalized, modular, and affordable option for experimental setups. Based on the Teensy 3.2 board, the stimulator utilizes direct digital synthesis and pulse width modulation techniques to control the LEDs. We validated its performance through four experiments: the first two measured LED light intensities directly, while the last two assessed the stimulator's impact on EEG recordings. The results demonstrate that the stimulator can deliver a stimulus suitable for generating SSVEPs with the desired frequency and phase resolution. As an open source resource, we provide comprehensive documentation, including all necessary codes and electrical diagrams, which facilitates the system's replication and adaptation for specific experimental requirements, enhancing its potential for widespread use in the field of neuroscience setups.

Digital behavioural signatures reveal trans-diagnostic clusters of Schizophrenia and Alzheimer's disease patients

The current neuropsychiatric nosological categories underlie pragmatic treatment choice, regulation and clinical research but does not encompass biological rationale. However, subgroups of patients suffering from schizophrenia or Alzheimer's disease have more in common than the neuropsychiatric nature of their condition, such as the expression of social dysfunction. The PRISM project presents here initial quantitative biological insights allowing the first steps toward a novel trans-diagnostic classification of psychiatric and neurological symptomatology intended to reinvigorate drug discovery in this area. In this study, we applied spectral clustering on digital behavioural endpoints derived from passive smartphone monitoring data in a subgroup of Schizophrenia and Alzheimer's disease patients, as well as age matched healthy controls, as part of the PRISM clinical study. This analysis provided an objective social functioning characterization with three differential clusters that transcended initial diagnostic classification and was shown to be linked to quantitative neurobiological parameters assessed. This emerging quantitative framework will both offer new ways to classify individuals in biologically homogenous clusters irrespective of their initial diagnosis, and also offer insights into the pathophysiological mechanisms underlying these clusters.

Effects of the mGlu2/3 receptor agonist LY379268 on two models of disturbed auditory evoked brain oscillations in mice

Cognitive impairment is a core feature of schizophrenia and is poorly addressed by currently available medication. This is partly because the underlying circuits are insufficiently understood, and available animal models for brain dysfunction do not adequately mimic human pathology. To improve the translatability of animal studies and complement behavioral data, EEG measurements are being increasingly used in preclinical research. Brain oscillations are similar across species and can be impaired via several means. In this study, we used two approaches to impair early sensory processing and cortical oscillations in mice: a pharmacological model targeting NMDA receptor function in the whole brain via systemic MK-801 application and an optogenetic model targeting parvalbumin-positive (PV+) interneurons locally in the medial prefrontal cortex (mPFC). We evoked brain activity using auditory stimulation, a tool with high translatability from mouse to human. We then investigated the effect of LY379268, an agonist of mGlu2/3 receptors, a potential therapeutic target for schizophrenia, on single neuron and EEG responses. LY379268 was able to rescue MK-801-induced deficits for a variety of clinically relevant early sensory EEG biomarkers. Single neuron recordings revealed a strong effect of LY379268 on the signal-to-noise ratio during auditory stimulation and optogenetic inhibition of PV+ interneurons. Our results contribute to a better understanding of how group II metabotropic glutamate receptors modulate neuronal population and network activity under sensory stimulation while challenged pharmacologically or optogenetically.

EEG signals classification using a new radial basis function neural network and jellyfish meta-heuristic algorithm

The purpose of this paper is to investigate a new method for EEG signals classification. A powerful method for detecting these signals can greatly contribute to areas such as making robotic arms for disabled people, mind reading and lie detection tools. To this end, this study makes two interesting contributions. As a major contribution, a new classifier based on a radial basis function neural network (RBFNN) is presented. As the center determination method of a RBFNN classifier has a high impact on the final classification results, we have adopted Jellyfish search (JS) algorithm for choosing the centers of the Gaussian functions in the hidden layer of the RBFNN classifier. Additionally, Locally Linear Embedding (LLE) technique is investigated for reducing the dimensionality of EEG signals. Two series of various experiments are designed to validate our proposals. In the first set of the experiments, the proposed RBFNN classifier is compared with other state-of-the-art RBFNN classifiers. In the second set of the experiments, the performances of the proposed EEG signals classifications are evaluated on a challenging dataset for EEG signals classification. The experimental results demonstrate the superiority of our proposed method even compared to the methods based on the convolutional neural networks.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12065-022-00802-2.

Greater tau pathology is associated with altered predictive coding

Altered predictive coding may underlie the reduced auditory mismatch negativity amplitude observed in patients with dementia. We hypothesized that accumulating dementia-associated pathologies, including amyloid and tau, lead to disturbed predictions of our sensory environment. This would manifest as increased reliance on 'observed' sensory information with an associated increase in feedforward, and decrease in feedback, signalling. To test this hypothesis, we studied a cross-sectional cohort of participants who underwent PET imaging and high-density EEG during an oddball paradigm, and used dynamic casual modelling and Bayesian statistics to make inferences about the neuronal architectures (generators) and mechanisms (effective connectivity) underlying the observed auditory-evoked responses. Amyloid-β imaging with [C-11] Pittsburgh Compound-B PET was qualitatively rated using established criteria. Tau-positive PET scans, with [F-18]MK-6240, were defined by an MK-6240 standardized uptake value ratio positivity threshold at 2 standard deviations above the mean of the Amyloid(-) group in the entorhinal cortex (entorhinal MK-6240 standardized uptake value ratio > 1.27). The cross-sectional cohort included a total of 56 participants [9 and 13 participants in the Tau(+) and Amyloid(+) subgroups, respectively: age interquartile range of (73.50-75.34) and (70.5-75.34) years, 56 and 69% females, respectively; 46 and 43 participants in the Tau(-) and Amyloid(-) subgroups, respectively: age interquartile range of (62.72-72.5) and (62.64-72.48) years, 67 and 65% females, respectively]. Mismatch negativity amplitudes were significantly smaller in Tau+ subgroup than Tau- subgroup (cluster statistics corrected for multiple comparisons: P = 0.028). Dynamic causal modelling showed that tau pathology was associated with increased feedforward connectivity and decreased feedback connectivity, with increased excitability of superior temporal gyrus but not inferior frontal regions. This effect on superior temporal gyrus was consistent with the distribution of tau disease on PET in these participants, indicating that the observed differences in mismatch negativity reflect pathological changes evolving in preclinical dementia. Exclusion of participants with diagnosed mild cognitive impairment or dementia did not affect the results. These observational data provide proof of concept that abnormalities in predictive coding may be detected in the preclinical phase of Alzheimer's disease. This framework also provides a construct to understand how progressive impairments lead to loss of orientation to the sensory world in dementia. Based on our modelling results, plus animal models indicating that Alzheimer's disease pathologies produce hyperexcitability of higher cortical regions through local disinhibition, mismatch negativity might be a useful monitor to deploy as strategies that target interneuron dysfunction are developed.

Abnormality of Functional Connections in the Resting State Brains of Schizophrenics

To explore the change of brain connectivity in schizophrenics (SCZ), the resting-state EEG source functional connections of SCZ and healthy control (HC) were investigated in this paper. Different band single-layer networks, multilayer networks, and improved multilayer networks were constructed and their topological attributes were extracted. The topological attributes of SCZ and HC were automatically distinguished using ensemble learning methods called Ensemble Learning based on Trees and Soft voting method, and the effectiveness of different network construction methods was compared based on the classification accuracy. The results showed that the classification accuracy was 89.38% for α band network, 82.5% for multilayer network, and 86.88% for improved multilayer network. Comparing patients with SCZ to those with Alzheimer’s disease (AD), the classification accuracy of improved multilayer network was the highest, which was 88.12%. The power spectrum in the α band of SCZ was significantly lower than HC, whereas there was no significant difference between SCZ and AD. This indicated that the improved multilayer network can effectively distinguish SCZ and other groups not only when their power spectrum was significantly different. The results also suggested that the improved multilayer topological attributes were regarded as biological markers in the clinical diagnosis of patients with schizophrenia and even other mental disorders.

Pure Tone Audiometry and Hearing Loss in Alzheimer's Disease: A Meta-Analysis

An association between age-related hearing loss (ARHL) and Alzheimer's Disease (AD) has been widely reported. However, the nature of this relationship remains poorly understood. Quantification of hearing loss as it relates to AD is imperative for the creation of reliable, hearing-related biomarkers for earlier diagnosis and development of ARHL treatments that may slow the progression of AD. Previous studies that have measured the association between peripheral hearing function and AD have yielded mixed results. Most of these studies have been small and underpowered to reveal an association. Therefore, in the current report, we sought to estimate the degree to which AD patients have impaired hearing by performing a meta-analysis to increase statistical power. We reviewed 248 published studies that quantified peripheral hearing function using pure-tone audiometry for subjects with AD. Six studies, with a combined total of 171 subjects with AD compared to 222 age-matched controls, met inclusion criteria. We found a statistically significant increase in hearing threshold as measured by pure tone audiometry for subjects with AD compared to controls. For a three-frequency pure tone average calculated for air conduction thresholds at 500-1,000-2,000 Hz (0.5-2 kHz PTA), an increase of 2.3 decibel hearing level (dB HL) was found in subjects with AD compared to controls (p = 0.001). Likewise, for a four-frequency pure tone average calculated at 500-1,000-2,000-4,000 (0.5-4 kHz PTA), an increase of 4.5 dB HL was measured (p = 0.002), and this increase was significantly greater than that seen for 0.5-2 kHz PTA. There was no difference in the average age of the control and AD subjects. These data confirm the presence of poorer hearing ability in AD subjects, provided a quantitative estimate of the magnitude of hearing loss, and suggest that the magnitude of the effect is greater at higher sound frequencies. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/, identifier: CRD42021288280.

Using Biomarkers to Predict Memantine Effects in Alzheimer's Disease: A Proposal and Proof-Of-Concept Demonstration

Memantine's benefits in Alzheimer's disease (AD) are modest and heterogeneous. We tested the feasibility of using sensitivity to acute memantine challenge to predict an individual's clinical response. Eight participants completed a double-blind challenge study of memantine (placebo versus 20 mg) effects on autonomic, subjective, cognitive, and neurophysiological measures, followed by a 24-week unblinded active-dose therapeutic trial (10 mg bid). Study participation was well tolerated. Subgroups based on memantine sensitivity on specific laboratory measures differed in their clinical response to memantine, some by large effect sizes. It appears feasible to use biomarkers to predict clinical sensitivity to memantine.

Mismatch negativity as EEG biomarker supporting CNS drug development: a transnosographic and translational study

The lack of translation from basic research into new medicines is a major challenge in CNS drug development. The need to use novel approaches relying on (i) patient clustering based on neurobiology irrespective to symptomatology and (ii) quantitative biomarkers focusing on evolutionarily preserved neurobiological systems allowing back-translation from clinical to nonclinical research has been highlighted. Here we sought to evaluate the mismatch negativity (MMN) response in schizophrenic (SZ) patients, Alzheimer's disease (AD) patients, and age-matched healthy controls. To evaluate back-translation of the MMN response, we developed EEG-based procedures allowing the measurement of MMN-like responses in a rat model of schizophrenia and a mouse model of AD. Our results indicate a significant MMN attenuation in SZ but not in AD patients. Consistently with the clinical findings, we observed a significant attenuation of deviance detection (~104.7%) in rats subchronically exposed to phencyclidine, while no change was observed in APP/PS1 transgenic mice when compared to wild type. This study provides new insight into the cross-disease evaluation of the MMN response. Our findings suggest further investigations to support the identification of neurobehavioral subtypes that may help patients clustering for precision medicine intervention. Furthermore, we provide evidence that MMN could be used as a quantitative/objective efficacy biomarker during both preclinical and clinical stages of SZ drug development.

Reliability of mismatch negativity event-related potentials in a multisite, traveling subjects study

OBJECTIVE

To determine the optimal methods for measuring mismatch negativity (MMN), an auditory event-related potential (ERP), and quantify sources of MMN variance in a multisite setting.

METHODS

Reliability of frequency, duration, and double (frequency + duration) MMN was determined from eight traveling subjects, tested on two occasions at eight laboratory sites. Deviant-specific variance components were estimated for MMN peak amplitude and latency measures using different ERP processing methods. Generalizability (G) coefficients were calculated using two-facet (site and occasion), fully-crossed models and single-facet (occasion) models within each laboratory to assess MMN reliability.

RESULTS

G-coefficients calculated from two-facet models indicated fair (0.4 < G<=0.6) duration MMN reliability at electrode Fz, but poor (G < 0.4) double and frequency MMN reliability. Single-facet G-coefficients averaged across laboratory resulted in improved reliability (G > 0.5). MMN amplitude reliability was greater than latency reliability, and reliability with mastoid referencing significantly outperformed nose-referencing.

CONCLUSIONS

EEG preprocessing methods have an impact on the reliability of MMN amplitude. Within site MMN reliability can be excellent, consistent with prior single site studies.

SIGNIFICANCE

With standardized data collection and ERP processing, MMN can be reliably obtained in multisite studies, providing larger samples sizeswithin rare patient groups.

Neurovascular decoupling in type 2 diabetes mellitus without mild cognitive impairment: Potential biomarker for early cognitive impairment

Type 2 diabetes mellitus (T2DM) is a significant risk factor for mild cognitive impairment (MCI) and the acceleration of MCI to dementia. The high glucose level induce disturbance of neurovascular (NV) coupling is suggested to be one potential mechanism, however, the neuroimaging evidence is still lacking. To assess the NV decoupling pattern in early diabetic status, 33 T2DM without MCI patients and 33 healthy control subjects were prospectively enrolled. Then, they underwent resting state functional MRI and arterial spin labeling imaging to explore the hub-based networks and to estimate the coupling of voxel-wise cerebral blood flow (CBF)-degree centrality (DC), CBF-mean amplitude of low-frequency fluctuation (mALFF) and CBF- mean regional homogeneity (mReHo). We further evaluated the relationship between NV coupling pattern and cognitive performance (false discovery rate corrected). T2DM without MCI patients displayed significant decrease in the absolute CBF-mALFF, CBF-mReHo coupling of CBFnetwork and in the CBF-DC coupling of DCnetwork. Besides, networks which involved CBF and DC hubs mainly located in the default mode network (DMN). Furthermore, less severe disease and better cognitive performance in T2DM patients were significantly correlated with higher coupling of CBF-DC, CBF-mALFF or CBF-mReHo, especially for the cognitive dimensions of general function and executive function. Thus, coupling of CBF-DC, CBF-mALFF and CBF-mReHo may serve as promising indicators to reflect NV coupling state and to explain the T2DM related early cognitive impairment.