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A brain–computer interface (BCI), sometimes called a brain–machine interface (BMI), is a direct communication link between the brain's electrical activity and an external device, most commonly a computer or robotic limb.
Brain–body interactions are patterns of neural activity in the central nervous system to coordinate the activity between the brain and body. The nervous system consists of central and peripheral nervous systems and coordinates the actions of an animal by transmitting signals to and from different parts of its body.
The term ongoing brain activity is used in electroencephalography and magnetoencephalography for those signal components that are not associated with the processing of a stimulus or the occurrence of specific other events, such as moving a body part, i.e. events that do not form evoked potentials/evoked fields, or induced activity.
Synaptic communication is distinct from an ephaptic coupling, in which communication between neurons occurs via indirect electric fields. An autapse is a chemical or electrical synapse that forms when the axon of one neuron synapses onto dendrites of the same neuron.
In August 2020 scientists reported that bi-directional connections, or added appropriate feedback connections, can accelerate and improve communication between and in modular neural networks of the brain's cerebral cortex and lower the threshold for their successful communication. They showed that adding feedback connections between a resonance ...
A brain–computer interface (BCI), is a direct communication pathway between an enhanced or wired brain and an external device. BCI differs from neuromodulation in that it allows for bidirectional information flow. BCIs are often directed at researching, mapping, assisting, augmenting, or repairing human cognitive or sensory-motor functions.
Some brain implants involve creating interfaces between neural systems and computer chips. This work is part of a wider research field called brain–computer interfaces. (Brain–computer interface research also includes technology such as EEG arrays that allow interface between mind and machine but do not require direct implantation of a device.)
The connectome will significantly increase our understanding of how functional brain states emerge from their underlying structural substrate, and will provide new mechanistic insights into how brain function is affected if this structural substrate is disrupted. [4] In his 2005 Ph.D. thesis, From diffusion MRI to brain connectomics, Hagmann wrote: