Neural responses to syllable-induced P1m and social impairment in children with autism spectrum disorder and typically developing Peers.

In previous magnetoencephalography (MEG) studies, children with autism spectrum disorder (ASD) have been shown to respond differently to speech stimuli than typically developing (TD) children. Quantitative evaluation of this difference in responsiveness may support early diagnosis and intervention for ASD. The objective of this research is to investigate the relationship between syllable-induced P1m and social impairment in children with ASD and TD children. We analyzed 49 children with ASD aged 40-92 months and age-matched 26 TD children. We evaluated their social impairment by means of the Social Responsiveness Scale (SRS) and their intelligence ability using the Kaufman Assessment Battery for Children (K-ABC). Multiple regression analysis with SRS score as the dependent variable and syllable-induced P1m latency or intensity and intelligence ability as explanatory variables revealed that SRS score was associated with syllable-induced P1m latency in the left hemisphere only in the TD group and not in the ASD group. A second finding was that increased leftward-lateralization of intensity was correlated with higher SRS scores only in the ASD group. These results provide valuable insights but also highlight the intricate nature of neural mechanisms and their relationship with autistic traits.

Autism Detection in Children using Common Spatial Patterns of MEG Signals.

Autism exhibits a wide range of developmental disabilities and is associated with aberrant anatomical and functional neural patterns. To detect autism in young children (4-7 years) in an automatic and non-invasive fashion, we have recorded magnetoencephalogram (MEG) signals from 30 autistic and 30 age-matched typically developing (TD) children. We have used a machine learning classification framework with common spatial pattern (CSP)-based logarithmic band power (LBP) features. When comparing the LBP feature to the conventional logarithmic variance (LV) spatial pattern, CSP + LBP (92.77%) has performed better than CSP + LV (90.66%) in the 1-100 Hz frequency range for distinguishing autistic children from TD children. In frequency band-wise analysis using our proposed method, the high gamma frequency band (50-100 Hz) has shown the highest classification accuracy (97.14%). Our findings reveal that the occipital lobe exhibits the most distinct spatial pattern in autistic children over the whole frequency range. This study shows that spatial brain activation patterns can be utilized as potential biomarkers of autism in young children. The improved performance signifies the clinical relevance of the work for autism detection using MEG signals.

Effect of transcranial direct current stimulation on the functionality of 40 Hz auditory steady state response brain network: graph theory approach.

Introduction: Measuring whole-brain networks of the 40 Hz auditory steady state response (ASSR) is a promising approach to describe the after-effects of transcranial direct current stimulation (tDCS). The main objective of this study was to evaluate the effect of tDCS on the brain network of 40 Hz ASSR in healthy adult males using graph theory. The second objective was to identify a population in which tDCS effectively modulates the brain network of 40 Hz ASSR. Methods: This study used a randomized, sham-controlled, double-blinded crossover approach. Twenty-five adult males (20-24 years old) completed two sessions at least 1 month apart. The participants underwent cathodal or sham tDCS of the dorsolateral prefrontal cortex, after which 40 Hz ASSR was measured using magnetoencephalography. After the signal sources were mapped onto the Desikan-Killiany brain atlas, the statistical relationships between localized activities were evaluated in terms of the debiased weighted phase lag index (dbWPLI). Weighted and undirected graphs were constructed for the tDCS and sham conditions based on the dbWPLI. Weighted characteristic path lengths and clustering coefficients were then measured and compared between the tDCS and sham conditions using mixed linear models. Results: The characteristic path length was significantly lower post-tDCS simulation (p = 0.04) than after sham stimulation. This indicates that after tDCS simulation, the whole-brain networks of 40 Hz ASSR show a significant functional integration. Simple linear regression showed a higher characteristic path length at baseline, which was associated with a larger reduction in characteristic path length after tDCS. Hence, a pronounced effect of tDCS is expected for those who have a less functionally integrated network of 40 Hz ASSR. Discussion: Given that the healthy brain is functionally integrated, we conclude that tDCS could effectively normalize less functionally integrated brain networks rather than enhance functional integration.

Detection of the 40 Hz auditory steady-state response with optically pumped magnetometers.

Magnetoencephalography (MEG) is a functional neuroimaging technique that noninvasively detects the brain magnetic field from neuronal activations. Conventional MEG measures brain signals using superconducting quantum interference devices (SQUIDs). SQUID-MEG requires a cryogenic environment involving a bulky non-magnetic Dewar flask and the consumption of liquid helium, which restricts the variability of the sensor array and the gap between the cortical sources and sensors. Recently, miniature optically pumped magnetometers (OPMs) have been developed and commercialized. OPMs do not require cryogenic cooling and can be placed within millimeters from the scalp. In the present study, we arranged six OPM sensors on the temporal area to detect auditory-related brain responses in a two-layer magnetically shielded room. We presented the auditory stimuli of 1 kHz pure-tone bursts with 200 ms duration and obtained the M50 and M100 components of auditory-evoked fields. We delivered the periodic stimuli with a 40 Hz repetition rate and observed the gamma-band power changes and inter-trial phase coherence of auditory steady-state responses at 40 Hz. We found that the OPM sensors have a performance comparable to that of conventional SQUID-MEG sensors, and our results suggest the feasibility of using OPM sensors for functional neuroimaging and brain-computer interface applications.

Alterations in brain networks in children with sub-threshold autism spectrum disorder: A magnetoencephalography study.

Individuals with sub-threshold autism spectrum disorder (ASD) are those who have social communication difficulties but do not meet the full ASD diagnostic criteria. ASD is associated with an atypical brain network; however, no studies have focused on sub-threshold ASD. Here, we used the graph approach to investigate alterations in the brain networks of children with sub-threshold ASD, independent of a clinical diagnosis. Graph theory is an effective approach for characterizing the properties of complex networks on a large scale. Forty-six children with ASD and 31 typically developing children were divided into three groups (i.e., ASD-Unlikely, ASD-Possible, and ASD-Probable groups) according to their Social Responsiveness Scale scores. We quantified magnetoencephalographic signals using a graph-theoretic index, the phase lag index, for every frequency band. Resultantly, the ASD-Probable group had significantly lower small-worldness (SW) in the delta, theta, and beta bands than the ASD-Unlikely group. Notably, the ASD-Possible group exhibited significantly higher SW than the ASD-Probable group and significantly lower SW than the ASD-Unlikely group in the delta band only. To our knowledge, this was the first report of the atypical brain network associated with sub-threshold ASD. Our findings indicate that magnetoencephalographic signals using graph theory may be useful in detecting sub-threshold ASD.

Effect of CNTNAP2 polymorphism on receptive language in children with autism spectrum disorder without language developmental delay.

AIM: The receptive language ability of individuals with autism spectrum disorder (ASD) seems to lag behind expressive language ability. Several autism-related genes may influence this developmental delay. Polymorphism of one such gene, namely, the contactin-associated protein-like 2 gene (CNTNAP2), affects receptive language in individuals with language delay. However, the association between CNTNAP2 polymorphism and receptive language in individuals with no language delay remains unclear. METHODS: We included 59 children with ASD and 57 children with typical development in this study and investigated this association using coarse-grained exact matching. RESULTS: We present the first evidence of an association between CNTNAP2 rs2710102 (A-allele carrier) and reduced receptive language ability in children with ASD whose language development was not delayed. Similarly, among children with typical development, A-allele carriers had lower receptive language ability, but the difference was non-significant. CONCLUSIONS: It is possible that the effect of rs2710102 on receptive language ability is larger in the presence of autism-related genes. Consequently, we speculate that the effect of rs2710102 on receptive language ability would be exerted in combination with other genes. These findings provide new insights into the genetic interactions between mutations associated with common language disorders and ASD and identify molecular mechanisms and risk alleles that contribute to receptive vocabulary. These findings also provide practical guidance in terms of providing candidate genetic markers that may provide opportunities for targeted early intervention to stratify risk and improve prognosis for poor receptive language development in children with ASD.

Prominent gamma band activity during visual motion perception in early-stage Alzheimer's disease.

INTRODUCTION: Alzheimer's disease (AD) affects multiple neural pathways and regions, resulting in various visual impairments such as motion perception. Generally, gamma-band activities during visual motion perception have been thought to reflect ongoing cognitive processes. Nevertheless, few studies have specifically examined induced gamma band activity during visual motion perception in AD patients. Therefore, after performing magnetoencephalography (MEG) recording during apparent motion (AM) stimulation for the left hemi-visual field in patients diagnosed as having AD in the early stage, we compared the results with findings of cognitive performance. METHODS: Seventeen AD patients in the early stage and 17 controls matched for age, sex, and educational attainment participated in this study. For each participant, memory performance was assessed with the Mini-Mental State Examination (MMSE) and the Wechsler Memory Scale-Revised (WMS-R). For MEG analysis, we examined power changes induced in a higher frequency range (20-100 Hz) after AM stimuli. RESULTS: The power of induced gamma band activities was significantly higher in AD patients. The power of induced gamma band activities was associated with higher performance on both MMSE and WMS-R tests for attention and concentration in AD patients. CONCLUSIONS: Given that neuronal dysfunction in AD is associated with excitotoxic neurodegeneration, and given that subsequent development of compensatory inhibitory mechanisms also contributes to pathology in AD patients, elevated gamma band oscillations might reflect an imbalance of inhibitory and excitatory activity in AD patients. Moreover, positive correlation between induced gamma activity and cognitive performance might signify a compensating mechanism of inhibitory neurons which preserve the pyramidal neuron from excitotoxicity in a posterior association area.

Relation between acquisition of lexical concept and joint attention in children with autism spectrum disorder without severe intellectual disability.

In children with autism spectrum disorder (ASD), impairment of joint attention and language function are observed frequently from early childhood. Earlier reports have described these two phenomena as mutually related. For this study, developing past research, the relation between joint attention and the ability of conceptual inference is examined in 113 Japanese children (67.9 months mean age, 75% male) with ASD. We calculated Pearson's correlation coefficients between their Joint attention abnormality evaluated by ADOS-2 and "Riddle" subscale in K-ABC, then they are negatively correlated: r (104) = -.285. A larger abnormality of joint attention is associated with a lower ability of conceptual inference. New findings were obtained indicating that, in children of this age group with ASD, the degree of joint attention impairment is correlated negatively with conceptual inference ability, but not with expressive and receptive language abilities. Consideration of the mechanism of this relation is presented in this report.

A common variant of CNTNAP2 is associated with sub-threshold autistic traits and intellectual disability.

Sub-threshold autistic traits are common in the general population. Children with sub-threshold autistic traits have difficulties with social adaptation. Contactin-associated protein-like 2 (CNTNAP2) is associated with the development of Autism spectrum disorder (ASD) and the single-nucleotide polymorphism rs2710102 (G/A) of CNTNAP2 is suggested to contribute to sub-threshold social impairments and intellectual disabilities. We recruited 67 children with Autistic disorder (AD) (49 boys, 18 girls, aged 38-98 months) and 57 typically developing (TD) children (34 boys, 23 girls, aged 53-90 months). We assessed the participants' intelligence and social reciprocity using the Kaufman Assessment Battery for Children (K-ABC) and the Social Responsiveness Scale (SRS), respectively. Genomic DNA was extracted from the buccal mucosa and genotyped for rs2710102. A chi-square test revealed a significant association between genotype and group [χ2(2) = 6.56, p = 0.038]. When a co-dominant model was assumed, the results from linear regression models demonstrated that TD children with A-carriers (AA + AG) presented higher SRS T-scores [t(55) = 2.11, p = 0.039] and lower simultaneous processing scale scores of K-ABC [t(55) = -2.19, p = 0.032] than those with GG homozygotes. These associations were not significant in children with ASD. TD children with the rs2710102 A-allele may have more sub-threshold autistic traits than those with GG homozygotes, reflected in higher SRS scores and lower simultaneous processing scale scores. These results support the use of genetic evidence to detect sub-threshold autistic traits.

Atypical Resting State Functional Neural Network in Children With Autism Spectrum Disorder: Graph Theory Approach.

Measuring whole brain networks is a promising approach to extract features of autism spectrum disorder (ASD), a brain disorder of widespread regions. Objectives of this study were to evaluate properties of resting-state functional brain networks in children with and without ASD and to evaluate their relation with social impairment severity. Magnetoencephalographic (MEG) data were recorded for 21 children with ASD (7 girls, 60-89 months old) and for 25 typically developing (TD) control children (10 girls, 60-91 months old) in a resting state while gazing at a fixation cross. After signal sources were localized onto the Desikan-Killiany brain atlas, statistical relations between localized activities were found and evaluated in terms of the phase lag index. After brain networks were constructed and after matching with intelligence using a coarsened exact matching algorithm, ASD and TD graph theoretical measures were compared. We measured autism symptoms severity using the Social Responsiveness Scale and investigated its relation with altered small-worldness using linear regression models. Children with ASD were found to have significantly lower small-worldness in the beta band (p = 0.007) than TD children had. Lower small-worldness in the beta band of children with ASD was associated with higher Social Responsiveness Scale total t-scores (p = 0.047). Significant relations were also inferred for the Social Awareness (p = 0.008) and Social Cognition (p = 0.015) sub-scales. Results obtained using graph theory demonstrate a difference between children with and without ASD in MEG-derived resting-state functional brain networks, and the relation of that difference with social impairment. Combining graph theory and MEG might be a promising approach to establish a biological marker for ASD.

Epileptiform discharges relate to altered functional brain networks in autism spectrum disorders.

Many individuals with autism spectrum disorders have comorbid epilepsy. Even in the absence of observable seizures, interictal epileptiform discharges are common in individuals with autism spectrum disorders. However, how these interictal epileptiform discharges are related to autistic symptomatology remains unclear. This study used magnetoencephalography to investigate the relation between interictal epileptiform discharges and altered functional brain networks in children with autism spectrum disorders. Instead of particularly addressing individual brain regions, we specifically examine network properties. For this case-control study, we analysed 70 children with autism spectrum disorders (52 boys, 18 girls, 38-92 months old) and 19 typically developing children (16 boys, 3 girls, 48-88 months old). After assessing the participants' social reciprocity using the Social Responsiveness Scale, we constructed graphs of functional brain networks from frequency band separated task-free magnetoencephalography recordings. Nodes corresponded to Desikan-Killiany atlas-based 68 brain regions. Edges corresponded to phase lag index values between pairs of brain regions. To elucidate the effects of the existence of interictal epileptiform discharges on graph metrics, we matched each of three pairs from three groups (typically developing children, children with autism spectrum disorders who had interictal epileptiform discharges and those who did not) in terms of age and sex. We used a coarsened exact matching algorithm and applied adjusted regression analysis. We also investigated the relation between social reciprocity and the graph metric. Results show that, in children with autism spectrum disorders, the average clustering coefficient in the theta band was significantly higher in children who had interictal epileptiform discharges. Moreover, children with autism spectrum disorders who had no interictal epileptiform discharges had a significantly lower average clustering coefficient in the theta band than typically developing children had. However, the difference between typically developing children and children with autism spectrum disorder who had interictal epileptiform discharges was not significant. Furthermore, the higher average clustering coefficient in the theta band corresponded to severe autistic symptoms in children with autism spectrum disorder who had interictal epileptiform discharges. However, the association was not significant in children with autism spectrum disorders who had no interictal epileptiform discharge. In conclusion, results demonstrate that alteration of functional brain networks in children with autism spectrum disorders depends on the existence of interictal epileptiform discharges. Interictal epileptiform discharges might 'normalize' the deviation of altered brain networks in autism spectrum disorders, increasing the clustering coefficient. However, when the effect exceeds tolerance, it actually exacerbates autistic symptoms.

Japanese local government management of compulsory hospitalization for patients with mental disorders and comorbid COVID-19.

Administering medical treatment or managing quarantine for a patient is particularly difficult when a patient harming others or causing self-harm because of severe depression, a manic state, or psychomotor agitation is also infected with COVID-19. Kanazawa University Hospital is the only facility able to manage such difficult cases occurring in Ishikawa prefecture, a local administrative area in Japan. The hospital has arranged a negative pressure apparatus in a psychiatric ward with two protection rooms. This report describes an urgently established but viable system in one prefecture of Japan for treating COVID-19-infected patients with severe psychiatric symptoms during the COVID-19 pandemic.

Joint attention and intelligence in children with autism spectrum disorder without severe intellectual disability.

In children with autism spectrum disorder (ASD), joint attention is regarded as a predictor of language function, social skills, communication, adaptive function, and intelligence. However, existing information about the association between joint attention and intelligence is limited. Most such studies have examined children with low intelligence. For this study, we investigated whether joint attention is related to intelligence in young children with autism spectrum disorder (ASD) without severe intellectual disability. We analyzed 113 children with ASD aged 40-98 months. Their Kaufman Assessment Battery (K-ABC) Mental Processing Index (MPI) scores are 60 and more (mean 93.4). We evaluated their intelligence using K-ABC and evaluated their joint attention using ADOS-2. After we performed simple regression analyses using K-ABC MPI and its nine subscales as dependent variables, using joint attention as the independent variable, we identified joint attention as a positive predictor of the MPI and its two subscales. From this result, we conclude that joint attention is related to intelligence in young children with ASD without severe intellectual disability. This result suggests a beneficial effect of early intervention targeting joint attention for children with ASD. LAY SUMMARY: Joint attention is the ability to coordinate visual attention with another person and then shift one's gaze toward an object or event. Impairment of joint attention is regarded as an early marker of autism spectrum disorder (ASD). This study revealed impairment of joint attention as associated with lower intelligence in ASD children. These results are expected to constitute a rationale for future studies, particularly addressing beneficial effects of early intervention targeting joint attention for children with ASD.

Decreased grey matter volumes in unaffected mothers of individuals with autism spectrum disorder reflect the broader autism endophenotype.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with an early onset and a strong genetic origin. Unaffected relatives may present similar but subthreshold characteristics of ASD. This broader autism phenotype is especially prevalent in the parents of individuals with ASD, suggesting that it has heritable factors. Although previous studies have demonstrated brain morphometry differences in ASD, they are poorly understood in parents of individuals with ASD. Here, we estimated grey matter volume in 45 mothers of children with ASD (mASD) and 46 age-, sex-, and handedness-matched controls using whole-brain voxel-based morphometry analysis. The mASD group had smaller grey matter volume in the right middle temporal gyrus, temporoparietal junction, cerebellum, and parahippocampal gyrus compared with the control group. Furthermore, we analysed the correlations of these brain volumes with ASD behavioural characteristics using autism spectrum quotient (AQ) and systemizing quotient (SQ) scores, which measure general autistic traits and the drive to systemize. Smaller volumes in the middle temporal gyrus and temporoparietal junction correlated with higher SQ scores, and smaller volumes in the cerebellum and parahippocampal gyrus correlated with higher AQ scores. Our findings suggest that atypical grey matter volumes in mASD may represent one of the neurostructural endophenotypes of ASD.

Complexity of Body Movements during Sleep in Children with Autism Spectrum Disorder.

Recently, measuring the complexity of body movements during sleep has been proven as an objective biomarker of various psychiatric disorders. Although sleep problems are common in children with autism spectrum disorder (ASD) and might exacerbate ASD symptoms, their objectivity as a biomarker remains to be established. Therefore, details of body movement complexity during sleep as estimated by actigraphy were investigated in typically developing (TD) children and in children with ASD. Several complexity analyses were applied to raw and thresholded data of actigraphy from 17 TD children and 17 children with ASD. Determinism, irregularity and unpredictability, and long-range temporal correlation were examined respectively using the false nearest neighbor (FNN) algorithm, information-theoretic analyses, and detrended fluctuation analysis (DFA). Although the FNN algorithm did not reveal determinism in body movements, surrogate analyses identified the influence of nonlinear processes on the irregularity and long-range temporal correlation of body movements. Additionally, the irregularity and unpredictability of body movements measured by expanded sample entropy were significantly lower in ASD than in TD children up to two hours after sleep onset and at approximately six hours after sleep onset. This difference was found especially for the high-irregularity period. Through this study, we characterized details of the complexity of body movements during sleep and demonstrated the group difference of body movement complexity across TD children and children with ASD. Complexity analyses of body movements during sleep have provided valuable insights into sleep profiles. Body movement complexity might be useful as a biomarker for ASD.

Influence of oxytocin administration on somatosensory evoked magnetic fields induced by median nerve stimulation during hand action observation in healthy male volunteers.

Watching another person's hand movement modulates somatosensory evoked magnetic fields (SEFs). Assuming that the mirror neuron system may have a role in this phenomenon, oxytocin should enhance these effects. This single-blinded, placebo-controlled, crossover study therefore used magnetoencephalography (MEG) to investigate SEFs following electrical stimulation of the right median nerve in 20 healthy male participants during hand movement observation, which were initially presented as static images followed by moving images. The participants were randomly assigned to receive either oxytocin or saline during the first trial, with the treatment being reversed during a second trial. Log-transformed ratios of the N20 and N30 amplitudes were calculated and compared between moving and static images observations. Phase locking (calculated using intertrial phase coherence) of brain oscillations was also analyzed to evaluate alpha, beta and gamma rhythm changes after oxytocin administration. Log N30 ratios showed no significant changes after placebo administration but showed a decreasing tendency (albeit not significant) after placebo administration, which may suggest mirror neuron system involvement. In contrast, log N20 ratios were increased after placebo administration, but showed no significant change after oxytocin administration. Interestingly, the gamma band activity around N20 increased after placebo administration, suggesting that oxytocin exerted an analgesic effect on median nerve stimulation, and inhibited the gamma band increase. Oxytocin might therefore modulate not only the mirror neuron system, but also the sensory processing associated with median nerve stimulation.

Aberrant brain oscillatory coupling from the primary motor cortex in children with autism spectrum disorders.

Autism spectrum disorder (ASD) often involves dysfunction in general motor control and motor coordination, in addition to core symptoms. However, the neural mechanisms underlying motor dysfunction in ASD are poorly understood. To elucidate this issue, we focused on brain oscillations and their coupling in the primary motor cortex (M1). We recorded magnetoencephalography in 18 children with ASD, aged 5 to 7 years, and 19 age- and IQ-matched typically-developing children while they pressed a button during a video-game-like motor task. The motor-related gamma (70 to 90 Hz) and pre-movement beta oscillations (15 to 25 Hz) were analyzed in the primary motor cortex using an inverse method. To determine the coupling between beta and gamma oscillations, we applied phase-amplitude coupling to calculate the statistical dependence between the amplitude of fast oscillations and the phase of slow oscillations. We observed a motor-related gamma increase and a pre-movement beta decrease in both groups. The ASD group exhibited a reduced motor-related gamma increase and enhanced pre-movement beta decrease in the ipsilateral primary motor cortex. We found phase-amplitude coupling, in which high-gamma activity was modulated by the beta rhythm in the primary motor cortex. Phase-amplitude coupling in the ipsilateral primary motor cortex was reduced in the ASD group compared with the control group. Using oscillatory changes and their couplings, linear discriminant analysis classified the ASD and control groups with high accuracy (area under the receiver operating characteristic curve: 97.1%). The current findings revealed alterations in oscillations and oscillatory coupling, reflecting the dysregulation of motor gating mechanisms in ASD. These results may be helpful for elucidating the neural mechanisms underlying motor dysfunction in ASD, suggesting the possibility of developing a biomarker for ASD diagnosis.

tDCS-induced modulation of GABA concentration and dopamine release in the human brain: A combination study of magnetic resonance spectroscopy and positron emission tomography.

BACKGROUND: Transcranial direct current stimulation (tDCS) to the dorsolateral prefrontal cortex (DLPFC) hypothetically modulates cognitive functions by facilitating or inhibiting neuronal activities chiefly in the cerebral cortex. The effect of tDCS in the deeper brain region, the basal ganglia-cortical circuit, remains unknown. OBJECTIVE: To investigate the interaction between γ-aminobutyric acid (GABA) concentrations and dopamine release following tDCS. METHOD: This study used a randomized, placebo-controlled, double-blind, crossover design. Seventeen healthy male subjects underwent active and sham tDCS (13 min twice at an interval of 20 min) with the anode placed at the left DLPFC and the cathode at the right DLPFC, followed by examinations with [11C]-raclopride positron emission topography (PET) and GABA-magnetic resonance spectroscopy (MRS). MRS voxels were set in the left DLPFC and bilateral striata. Paired t-tests and regression analyses were performed for PET and MRS parameters. RESULTS: MRS data analyses showed elevations in GABA in the left striatum along with moderate reductions in the right striatum and the left DLPFC after active tDCS. PET data analyses showed that reductions in [11C]-raclopride binding potentials (increase in dopamine release) in the right striatum were inversely correlated with those in the left striatum after active tDCS. GABA reductions in the left DLPFC positively correlated with elevations in GABA in the left striatum and with increases in right striatal dopamine release and negatively correlated with increases in left striatal dopamine release. CONCLUSION: The present results suggest that tDCS to the DLPFC modulates dopamine-GABA functions in the basal ganglia-cortical circuit.

Decomposed Temporal Complexity Analysis of Neural Oscillations and Machine Learning Applied to Alzheimer's Disease Diagnosis.

Despite growing evidence of aberrant neuronal complexity in Alzheimer's disease (AD), it remains unclear how this variation arises. Neural oscillations reportedly comprise different functions depending on their own properties. Therefore, in this study, we investigated details of the complexity of neural oscillations by decomposing the oscillations into frequency, amplitude, and phase for AD patients. We applied resting-state magnetoencephalography (MEG) to 17 AD patients and 21 healthy control subjects. We first decomposed the source time series of the MEG signal into five intrinsic mode functions using ensemble empirical mode decomposition. We then analyzed the temporal complexities of these time series using multiscale entropy. Results demonstrated that AD patients had lower complexity on short time scales and higher complexity on long time scales in the alpha band in temporal regions of the brain. We evaluated the alpha band complexity further by decomposing it into amplitude and phase using Hilbert spectral analysis. Consequently, we found lower amplitude complexity and higher phase complexity in AD patients. Correlation analyses between spectral complexity and decomposed complexities revealed scale-dependency. Specifically, amplitude complexity was positively correlated with spectral complexity on short time scales, whereas phase complexity was positively correlated with spectral complexity on long time scales. Regarding the relevance of cognitive function to the complexity measures, the phase complexity on the long time scale was found to be correlated significantly with the Mini-Mental State Examination score. Additionally, we examined the diagnostic utility of the complexity characteristics using machine learning (ML) methods. We prepared a feature pool using multiple sparse autoencoders (SAEs), chose some discriminating features, and applied them to a support vector machine (SVM). Compared to the simple SVM and the SVM after feature selection (FS + SVM), the SVM with multiple SAEs (SAE + FS + SVM) had improved diagnostic accuracy. Through this study, we 1) advanced the understanding of neuronal complexity in AD patients using decomposed temporal complexity analysis and 2) demonstrated the effectiveness of combining ML methods with information about signal complexity for the diagnosis of AD.