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Classification of Parkinson’s disease severity using gait stance signals in a spatiotemporal deep learning classifier
AbstractParkinson’s disease (PD) is a degenerative nervous system disorder involving motor disturbances. Motor alterations affect the gait according...
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High-throughput spatiotemporal monitoring of single-cell secretions via plasmonic microwell arrays
Methods for the analysis of cell secretions at the single-cell level only provide semiquantitative endpoint readouts. Here we describe a microwell...
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Risk factors for tick attachment in companion animals in Great Britain: a spatiotemporal analysis covering 2014–2021
BackgroundTicks are an important driver of veterinary health care, causing irritation and sometimes infection to their hosts. We explored...
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Impact Exploration of Spatiotemporal Feature Derivation and Selection on Machine Learning-Based Predictive Models for Post-Embolization Cerebral Aneurysm Recanalization
PurposeTo enhance the performance of machine learning (ML) models for the post-embolization recanalization of cerebral aneurysms, we evaluated the...
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Migraine aura discrimination using machine learning: an fMRI study during ictal and interictal periods
Functional magnetic resonance imaging (fMRI) studies on migraine with aura are challenging due to the rarity of patients with triggered cases. This...
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Brain-inspired multisensory integration neural network for cross-modal recognition through spatiotemporal dynamics and deep learning
The integration and interaction of cross-modal senses in brain neural networks can facilitate high-level cognitive functionalities. In this work, we...
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Temporal and spatial variability of dynamic microstate brain network in early Parkinson’s disease
Changes of brain network dynamics reveal variations in macroscopic neural activity patterns in behavioral and cognitive aspects. Quantification and...
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Machine classification of spatiotemporal patterns: automated parameter search in a rebounding spiking network
Various patterns of electrical activities, including travelling waves, have been observed in cortical experimental data from animal models as well as...
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Autism spectrum disorder recognition based on multi-view ensemble learning with multi-site fMRI
Autism spectrum disorders (ASD) is a neurodevelopmental disorder that causes repetitive stereotyped behavior and social difficulties, early diagnosis...
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Decoding motor plans using a closed-loop ultrasonic brain–machine interface
Brain–machine interfaces (BMIs) enable people living with chronic paralysis to control computers, robots and more with nothing but thought. Existing...
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Buffy coat signatures of breast cancer risk in a prospective cohort study
BackgroundEpigenetic alterations are a near-universal feature of human malignancy and have been detected in malignant cells as well as in easily...
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Feature-based Quality Assessment of Middle Cerebral Artery Occlusion Using 18F-Fluorodeoxyglucose Positron Emission Tomography
In animal experiments, ischemic stroke is usually induced through middle cerebral artery occlusion (MCAO), and quality assessment of this procedure...
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Neuromelanin and T2*-MRI for the assessment of genetically at-risk, prodromal, and symptomatic Parkinson’s disease
MRI was suggested as a promising method for the diagnosis and assessment of Parkinson’s Disease (PD). We aimed to assess the sensitivity of...
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Gait classification for early detection and severity rating of Parkinson’s disease based on hybrid signal processing and machine learning methods
Parkinson’s disease (PD) is one of the cognitive degenerative disorders of the central nervous system that affects the motor system. Gait dysfunction...
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Categorizing objects from MEG signals using EEGNet
Magnetoencephalography (MEG) signals have demonstrated their practical application to reading human minds. Current neural decoding studies have made...
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Design of auditory P300-based brain-computer interfaces with a single auditory channel and no visual support
Non-invasive brain-computer interfaces (BCIs) based on an event-related potential (ERP) component, P300, elicited via the oddball paradigm, have been...
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Rapid and stain-free quantification of viral plaque via lens-free holography and deep learning
A plaque assay—the gold-standard method for measuring the concentration of replication-competent lytic virions—requires staining and usually more...
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Identification of the DNA methylation signature of Mowat-Wilson syndrome
Mowat-Wilson syndrome (MOWS) is a rare congenital disease caused by haploinsufficiency of ZEB2 , encoding a transcription factor required for...
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Classification algorithm for motor imagery fusing CNN and attentional mechanisms based on functional near-infrared spectroscopy brain image
With the continuing development of brain–computer interface technology, the analysis and interpretation of brain signals are becoming increasingly...
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Antipsychotic drug efficacy correlates with the modulation of D1 rather than D2 receptor-expressing striatal projection neurons
Elevated dopamine transmission in psychosis is assumed to unbalance striatal output through D1- and D2-receptor-expressing spiny-projection neurons...
