Advanced materials for neurotechnology and computing

Optimizing neural network training via multimodal fusion architectures for real-time sensor data

multimodal learning sensor fusion real-time AI heterogeneous data deep learning

Across synaptic vesicle recycling mechanisms to treat neurodegenerative disorders

synaptic vesicles neurodegeneration neurotransmitter release drug targets brain disorders

Modeling neural networks with phase-change material synapses for energy-efficient neuromorphic computing

neuromorphic computing phase-change materials artificial synapses energy efficiency memristors

Resistive RAM architectures for energy-efficient in-memory computing systems

ReRAM in-memory computing neuromorphic engineering AI accelerators non-volatile memory

Predictive motor coding models for brain-machine interface optimization

motor cortex decoding brain-computer interfaces neuroprosthetics machine learning neural engineering

Employing spectral analysis AI for early detection of neurodegenerative diseases

spectral analysis AI diagnostics neurodegenerative diseases early detection brain imaging

Bridging current and next-gen AI with resistive RAM for in-memory computing

resistive RAM in-memory computing AI acceleration neuromorphic computing energy efficiency

Closed-loop neuromodulation during deep brain stimulation for essential tremor suppression

adaptive DBS essential tremor biomarker-driven therapy thalamocortical circuits neural implants

Through quantum dot charge trapping for brain-inspired neuromorphic computing

neuromorphic computing quantum dots memristors artificial synapses nanoscale electronics

Enhancing neuromorphic computing efficiency with phase-change material synapses and terahertz oscillation frequencies

neuromorphic computing phase-change materials terahertz oscillations synaptic plasticity energy efficiency

With ferroelectric hafnium oxide for ultra-low-power neuromorphic computing

ferroelectric materials hafnium oxide neuromorphic computing low-power electronics memristors

Enhancing brain-computer interfaces with embodied active learning for real-time adaptation

neurotechnology adaptive systems machine learning neural signals human-computer interaction