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Perinatal exposure to infection/inflammation is highly associated with neural injury, and subsequent impaired cortical growth, disturbances in neuronal connectivity, and impaired neurodevelopment. However, our understanding of the pathophysiological substrate underpinning these changes in brain structure and function is limited. The objective of this review is to summarize the growing evidence from animal trials and human cohort studies that suggest exposure to infection/ inflammation during the perinatal period promotes regional impairments in neuronal maturation and function, including loss of high-frequency electroencephalographic activity, and reduced growth and arborization of cortical dendrites and dendritic spines resulting in reduced cortical volume.

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This work explores use of a few-shot transfer learning method to train and implement a convolutional spiking neural network (CSNN) on a BrainChip Akida AKD1000 neuromorphic system-on-chip for developing individual-level, instead of traditionally used group-level, models using electroencephalographic data. The efficacy of the method is studied on an advanced driver assist system related task of predicting braking intention. \emph{Approach}: Data are collected from participants operating an NVIDIA JetBot on a testbed simulating urban streets for three different scenarios.

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Background: Acute encephalopathy with biphasic seizures and late reduced diffusion (AESD) is clinically characterized by biphasic seizures associated with mild to severe neurological sequelae and is the most common subtype of acute encephalopathy in Japan, accounting for around 30 % of cases. The present study retrospectively analyzed the utility of electroencephalography (EEG) in determining the optimal method of diagnosing AESD at the early stage.

Methods: This study explores early power value differences to differentiate acute encephalopathy from prolonged febrile seizure (FS).

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Introduction: Major Depressive Disorder (MDD) leads to dysfunction and impairment in neurological structures and cognitive functions. Despite extensive research, the pathophysiological mechanisms and effects of MDD on the brain remain unclear. This study aims to assess the impact of MDD on brain activity using EEG power spectral analysis and asymmetry metrics.

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Extended performance of cognitively demanding tasks induces cognitive fatigue manifested with an overall deterioration of behavioral performance. In particular, long practice with tasks requiring impulse control is typically followed by a decrease in self-control efficiency, leading to performance instability. Here, we show that this is due to changes in activation modalities of key task-related areas occurring if these areas previously underwent intensive use.

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