Revealing single-neuron and network-activity interaction by combining high-density microelectrode array and optogenetics.

The synchronous activity of neuronal networks is considered crucial for brain function. However, the interaction between single-neuron activity and network-wide activity remains poorly understood. This study explored this interaction within cultured networks of rat cortical neurons.

Improving the accuracy of decoding monkey brain-machine interface data by estimating the state of unobserved cell assemblies.

Background: The brain-machine interface is a technology that has been used for improving the quality of life of individuals with physical disabilities and also healthy individuals. It is important to improve the methods used for decoding the brain-machine interface data as the accuracy and speed of movements achieved using the existing technology are not comparable to the normal body.

Comparison With The Existing Method: Decoding of brain-machine interface data using the proposed method resulted in improved decoding accuracy compared to the existing method.

Coupling of Neocortical-Hippocampal Coculture Bursts Induces Different Spike Rhythms in Individual Networks.

Brain-state alternation is important for long-term memory formation. Each brain state can be identified with a specific process in memory formation, e.g.

Recording Saltatory Conduction Along Sensory Axons Using a High-Density Microelectrode Array.

Myelinated fibers are specialized neurological structures used for conducting action potentials quickly and reliably, thus assisting neural functions. Although demyelination leads to serious functional impairments, little is known the relationship between myelin structural change and increase in conduction velocity during myelination and demyelination processes. There are no appropriate methods for the long-term evaluation of spatial characteristics of saltatory conduction along myelinated axons.

Observing Cell Assemblies From Spike Train Recordings Based on the Biological Basis of Synaptic Connectivity.

Cell assemblies are difficult to observe because they consist of many neurons. We aimed to observe cell assemblies based on biological statistics, such as synaptic connectivity. We developed an estimation method to estimate the activity and synaptic connectivity of cell assemblies from spike trains using mathematical models of individual neurons and cell assemblies.

Functional Scaffolding for Brain Implants: Engineered Neuronal Network by Microfabrication and iPSC Technology.

Neuroengineering methods can be effectively used in the design of new approaches to treat central nervous system and brain injury caused by neurotrauma, ischemia, or neurodegenerative disorders. During the last decade, significant results were achieved in the field of implant (scaffold) development using various biocompatible and biodegradable materials carrying neuronal cells for implantation into the injury site of the brain to repair its function. Neurons derived from animal or human induced pluripotent stem (iPS) cells are expected to be an ideal cell source, and induction methods for specific cell types have been actively studied to improve efficacy and specificity.