Generalizable neuromarker for autism spectrum disorder across imaging sites and developmental stages: A multi-site study.

Autism spectrum disorder (ASD) is a lifelong condition, and its underlying biological mechanisms remain elusive. The complexity of various factors, including inter-site and development-related differences, makes it challenging to develop generalizable neuroimaging-based biomarkers for ASD. This study used a large-scale, multi-site dataset of 730 Japanese adults to develop a generalizable neuromarker for ASD across independent sites and different developmental stages. Our adult ASD neuromarker achieved successful generalization for the US and Belgium adults and Japanese adults. The neuromarker demonstrated significant generalization for children and adolescents. We identified 141 functional connections (FCs) important for discriminating individuals with ASD from TDCs. Finally, we mapped schizophrenia (SCZ) and major depressive disorder (MDD) onto the biological axis defined by the neuromarker and explored the biological continuity of ASD with SCZ and MDD. We observed that SCZ, but not MDD, was located proximate to ASD on the biological dimension defined by the ASD neuromarker. The successful generalization in multifarious datasets and the observed relations of ASD with SCZ on the biological dimensions provide new insights for a deeper understanding of ASD.

Generalizable neuromarker for autism spectrum disorder across imaging sites and developmental stages: A multi-site study.

Autism spectrum disorder (ASD) is a lifelong condition, and its underlying biological mechanisms remain elusive. The complexity of various factors, including inter-site and development-related differences, makes it challenging to develop generalizable neuroimaging-based biomarkers for ASD. This study used a large-scale, multi-site dataset of 730 Japanese adults to develop a generalizable neuromarker for ASD across independent sites (U.S., Belgium, and Japan) and different developmental stages (children and adolescents). Our adult ASD neuromarker achieved successful generalization for the US and Belgium adults (area under the curve [AUC] = 0.70) and Japanese adults (AUC = 0.81). The neuromarker demonstrated significant generalization for children (AUC = 0.66) and adolescents (AUC = 0.71; all P<0.05, family-wise-error corrected). We identified 141 functional connections (FCs) important for discriminating individuals with ASD from TDCs. These FCs largely centered on social brain regions such as the amygdala, hippocampus, dorsomedial and ventromedial prefrontal cortices, and temporal cortices. Finally, we mapped schizophrenia (SCZ) and major depressive disorder (MDD) onto the biological axis defined by the neuromarker and explored the biological continuity of ASD with SCZ and MDD. We observed that SCZ, but not MDD, was located proximate to ASD on the biological dimension defined by the ASD neuromarker. The successful generalization in multifarious datasets and the observed relations of ASD with SCZ on the biological dimensions provide new insights for a deeper understanding of ASD.

Exploration of electroencephalogram response to MPH treatment in ADHD patients.

Attention-deficit/hyperactivity disorder (ADHD) is known to be associated with several diagnostic resting-state electroencephalography (EEG) patterns, including the theta/beta ratio, but no objective predictive markers for each medication. In this study, we explored EEG markers with which the therapeutic efficacy of medications could be estimated at the 1st clinical visit. Thirty-two ADHD patients and thirty-one healthy subjects participated in this study. EEG was recorded during eyes-closed resting conditions, and ADHD symptoms were scored before and after the therapeutic intervention (8 ± 2 weeks). Although comparing EEG patterns between ADHD patients and healthy subjects showed significant differences, EEG dynamics, e.g., theta/beta ratio, in ADHD patients before and after MPH treatment were not significantly different despite improvements in ADHD symptoms. We demonstrated that MPH good responders and poor responders, defined by the efficacy of MPH, had significantly different theta band power in right temporal areas, alpha in left occipital and frontal areas, and beta in left frontal areas. Moreover, we showed that MPH good responders had significant improvements toward normalization in several coherence measures after MPH treatment. Our study implies the possibility of these EEG indices as predictive markers for ADHD therapeutic efficacy.

Dynamic theta/beta ratio of clinical EEG in Alzheimer's disease.

BACKGROUND: EEG of a resting state in Alzheimer disease (AD) patients and healthy controls (HC) are analyzed to identify the characteristics of EEG in AD. NEW METHOD: A dynamic box plot approach to the theta/beta ratio with various window durations is proposed to analyze EEG. RESULTS: Spectral results during a resting state in AD patients demonstrate the effect of relatively greater power in the low-frequency bands (i.e. 'slowing down' of the EEG). A significant difference is observed in the dynamic distribution of the theta/beta ratio in the AD and HC groups, which is related to the effect of 'slowing down'. There is a more obvious visual separation between the theta/beta ratio results for the AD and HC groups with increasing window durations. Variability of the theta/beta ratio can be observed with shorter window durations with a dynamic functional box plot. This provides a better classification accuracy by using the dynamic theta/beta ratio as a sensor to discriminate AD EEG from HC EEG by using the receiver operating characteristics (ROC) curve and the area under curve (AUC) with various window durations. COMPARISON WITH EXISTING METHOD(S): EEG spectral analysis and theta/beta ratio used to evaluate EEG typically rely on long time averaging. CONCLUSIONS: The dynamic box plot approach to the theta/beta ratio with various window durations provides the possibility of observing features of the EEG. The dynamic theta/beta ratio is a better sensor to discriminate AD EEG from HC EEG. Moreover, the reliability and accuracy of results can be increased by combining spectral analysis and the dynamic box plot approach to theta/beta ratio with various window durations.

Semi-Automated Biomarker Discovery from Pharmacodynamic Effects on EEG in ADHD Rodent Models.

We propose a novel semi-automatic approach to design biomarkers for capturing pharmacodynamic effects induced by pharmacological agents on the spectral power of electroencephalography (EEG) recordings. We apply this methodology to investigate the pharmacodynamic effects of methylphenidate (MPH) and atomoxetine (ATX) on attention deficit/hyperactivity disorder (ADHD), using rodent models. We inject the two agents into the spontaneously hypertensive rat (SHR) model of ADHD, the Wistar-Kyoto rat (WKY), and the Wistar rat (WIS), and record their EEG patterns. To assess individual EEG patterns quantitatively, we use an integrated methodological approach, which consists of calculating the mean, slope and intercept parameters of temporal records of EEG spectral power using a smoothing filter, outlier truncation, and linear regression. We apply Fisher discriminant analysis (FDA) to identify dominant discriminants to be heuristically consolidated into several new composite biomarkers. Results of the analysis of variance (ANOVA) and t-test show benefits in pharmacodynamic parameters, especially the slope parameter. Composite biomarker evaluation confirms their validity for genetic model stratification and the effects of the pharmacological agents used. The methodology proposed is of generic use as an approach to investigating thoroughly the dynamics of the EEG spectral power.

Combining behavior and EEG analysis for exploration of dynamic effects of ADHD treatment in animal models.

BACKGROUND: We analyze the dynamics of rodent EEG amplitude in an experiment accompanied by video recordings. Brain activity of animals is commonly acquired together with a video of behavior, but recordings are rarely combined in analysis. The data acquired is most commonly analyzed separately. To our knowledge, no study has used behavior to improve the analysis of EEG waveforms, specifically for artifact removal - other than through manual editing. COMPARISON WITH EXISTING METHOD(S): We explore two approaches: a traditional approach that relies on data preprocessing and artifact rejection by an expert; and an alternative approach that combines analysis of EEG with behavior extracted from video recordings. NEW METHOD: We use the level of activity extracted from the behavioral video as a measure of confidence in the acquired EEG waveform, and as a weighting factor in averaging and statistical comparisons. RESULTS: We find in analysis of the EEG that the two approaches lead to similar conclusions, but the analysis leveraging behavioral data achieves this while avoiding many subjective choices often required for artifact rejection and data preprocessing. CONCLUSIONS: The methods we describe allow for the inclusion of all recorded data in the analysis, thereby making statistical tests more friendly to interpretation, and making the data processing transparent and reproducible.

Topological organization of CA3-to-CA1 excitation.

The CA1-projecting axons of CA3 pyramidal cells, called Schaffer collaterals, constitute one of the major information flow routes in the hippocampal formation. Recent anatomical studies have revealed the non-random structural connectivity between CA3 and CA1, but little is known regarding the functional connectivity (i.e. how CA3 network activity is functionally transmitted downstream to the CA1 network). Using functional multi-neuron calcium imaging of rat hippocampal slices, we monitored the spatiotemporal patterns of spontaneous CA3 and CA1 burst activity under pharmacological GABAergic blockade. We found that spatially clustered CA3 activity patterns were transformed into layered CA1 activity sequences. Specifically, synchronized bursts initiated from multiple hot spots in CA3 ensembles, and CA1 neurons located deeper in the pyramidal cell layer were recruited during earlier phases of the burst events. The order of these sequential activations was maintained across the bursts, but the sequence velocity varied depending on the inter-burst intervals. Thus, CA3 axons innervate CA1 neurons in a highly topographical fashion.

Thoracotomy reduces intrinsic brain movement caused by heartbeat and respiration: a simple method to prevent motion artifact for in vivo experiments.

Recent technical advances in electrophysiological recording and functional imaging from the brain of living animals have promoted our understandings of the brain function, but these in vivo experiments are still technically demanding and often suffer from spontaneous pulsation, i.e., brain movements caused by respiration and heartbeat. Here we report that thoracotomy suppresses the motion artifact to a practically negligible level. This simple method will be useful in a wide variety of in vivo experiments, such as patch-clamp physiology, and optical imaging of neurons, glial cell, and blood vessels.

Nipkow confocal imaging from deep brain tissues.

One of the problems in imaging from brain tissues is light-scattering. Thus, multiphoton laser scanning microscopy is widely used to optically access fluorescent signals located deeply in tissues. Here we report that Nipkow-type spinning-disk one-photon confocal microscopy, which embodies high temporal resolution and slow photobleaching, is also capable of imaging tissues to a depth of up to 150 µm. Using a Nipkow-disk microscope, we conducted functional multi-cell calcium imaging of CA3 neurons from in toto intact hippocampal preparations and astrocytes from in vivo neocortical layer 1. This novel application of Nipkow-disk microscopy expands the potential usefulness of this type of microscopy and will contribute to our understanding of natural neuronal microcircuitry.

Large-scale calcium waves traveling through astrocytic networks in vivo.

Macroscopic changes in cerebral blood flow, such as those captured by functional imaging of the brain, require highly organized, large-scale dynamics of astrocytes, glial cells that interact with both neuronal and cerebrovascular networks. However, astrocyte activity has been studied mainly at the level of individual cells, and information regarding their collective behavior is lacking. In this work, we monitored calcium activity simultaneously from hundreds of mouse hippocampal astrocytes in vivo and found that almost all astrocytes participated en masse in regenerative waves that propagated from cell to cell (referred to here as "glissandi"). Glissandi emerged depending on the neuronal activity and accompanied a reduction in infraslow fluctuations of local field potentials and a decrease in the flow of red blood cells. This novel phenomenon was heretofore overlooked, probably because of the high vulnerability of astrocytes to light damage; glissandi occurred only when observed at much lower laser intensities than previously used.

Functional multineuron calcium imaging for systems pharmacology.

Functional multineuron calcium imaging (fMCI) is a large-scale technique used to access brain function on a single-neuron scale. It detects the activity of individual neurons by imaging action potential-evoked transient calcium influxes into their cell bodies. fMCI has recently been used as a high-throughput research tool to examine how neuronal activity is altered in animal models of brain diseases, for example stroke, Alzheimer's disease, and epilepsy, and to estimate how pharmacological agents act on normal and abnormal states of neuronal networks. It offers unique opportunities to discover the mechanisms underlying neurological disorders and new therapeutic targets.