* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Download Abstract
Nonsynaptic plasticity wikipedia , lookup
Neuroethology wikipedia , lookup
Human brain wikipedia , lookup
Brain morphometry wikipedia , lookup
Convolutional neural network wikipedia , lookup
Neuromarketing wikipedia , lookup
Mirror neuron wikipedia , lookup
Neuroesthetics wikipedia , lookup
Functional magnetic resonance imaging wikipedia , lookup
Aging brain wikipedia , lookup
Artificial neural network wikipedia , lookup
Brain–computer interface wikipedia , lookup
Neurolinguistics wikipedia , lookup
History of neuroimaging wikipedia , lookup
Stimulus (physiology) wikipedia , lookup
Artificial general intelligence wikipedia , lookup
Biochemistry of Alzheimer's disease wikipedia , lookup
Neuropsychology wikipedia , lookup
Recurrent neural network wikipedia , lookup
Neurophilosophy wikipedia , lookup
Neuroinformatics wikipedia , lookup
Types of artificial neural networks wikipedia , lookup
Brain Rules wikipedia , lookup
Haemodynamic response wikipedia , lookup
Neural coding wikipedia , lookup
Activity-dependent plasticity wikipedia , lookup
Neuroeconomics wikipedia , lookup
Central pattern generator wikipedia , lookup
Holonomic brain theory wikipedia , lookup
Mind uploading wikipedia , lookup
Cognitive neuroscience wikipedia , lookup
Molecular neuroscience wikipedia , lookup
Electrophysiology wikipedia , lookup
Feature detection (nervous system) wikipedia , lookup
Neuroplasticity wikipedia , lookup
Circumventricular organs wikipedia , lookup
Clinical neurochemistry wikipedia , lookup
Premovement neuronal activity wikipedia , lookup
Synaptic gating wikipedia , lookup
Multielectrode array wikipedia , lookup
Pre-Bötzinger complex wikipedia , lookup
Neural correlates of consciousness wikipedia , lookup
Neural oscillation wikipedia , lookup
Neural engineering wikipedia , lookup
Single-unit recording wikipedia , lookup
Development of the nervous system wikipedia , lookup
Neuroanatomy wikipedia , lookup
Nervous system network models wikipedia , lookup
Neural binding wikipedia , lookup
Optogenetics wikipedia , lookup
Metastability in the brain wikipedia , lookup
Field: Medical/Neuroscience Session Topic: Optical Measurement and Control of Neuronal Activity Chair: Hajime HIRASE, RIKEN Amazing abilities of our brain, such as sensation, cognition, learning, memory, and even consciousness are thought to be realized through complex interactions of streams of millisecond-order electrical spikes (known as action potentials) generated by billions of neurons. How can one investigate such a complicated organ? As action potentials are electric signals mediated by flows of ions across cellular membranes, activity of neurons can be measured by inserting microelectrodes into the brain in vivo. One major advance in last century’s neuroscience was the emergence of sophisticated electronic technologies to measure occurrences of action potentials in response to sensory or neural circuit stimulation. This classical method led to many landmark discoveries such as identification of different functional brain areas and receptive field of sensory neurons. Today, use of silicon fabricated multi-site electrode arrays allows simultaneous monitoring of action potential activities from over one hundred individual neurons. Information obtained through these recordings is paving the way to ongoing attempts to help recreate meaningful brain activity to regain control of motor activity in physically disabled patients using brain-machine interface-based prosthesis. Notwithstanding these advances, electrophysiological measurements of neural activity are critically limited by a few notable factors. First, the inherently invasive nature of the method imposes a physical limit on the number of electrodes one can insert in the brain. Second, it is difficult to target the microelectrode only to a pre-determined precise location and/or a specific type of neurons. Finally, electrophysiological methods have no access to intra- and intercellular signaling cascades, protein dynamics and gene transcription networks of neurons. These biochemical networks operate at minute to hour time scales, and are critical to long-term changes in neuronal circuit properties such as memory formation. Recent advent of revolutionary quantitative biological microscopy technologies, such as two-photon excitation microscopy, in combination with new chemical and genetically encoded fluorescent probes opens avenues to break these limitations. The non-linear optical principle of two-photon microscopy enables the use of longer infrared wavelength to excite fluorescent molecules, resulting in a significantly improved tissue penetration depth to investigate cerebral cortical neurons in vivo. Highly quantitative chemical fluorescent probes such as calcium-sensitive or voltage-sensitive dyes are available to monitor millisecond time scale neural activities without use of invasive electrodes. Many useful fluorescent indicator proteins that reflect changes of membrane potential, ionic concentrations, protein conformational changes, protein-protein interactions, protein lifetimes, or gene expression have been developed and constantly improved. These proteins can be targeted to a subarea of the brain or to a specific subset of neurons by viral or transgenic technologies. Light can also be used to control neural activity. Caged (that is, chemically inert) excitatory or inhibitory neurotransmitters are ‘uncaged (and thus made active)’ upon illumination of a defined wavelength laser beam, thereby providing rigorous spatio-temporal control of neural activity. Even further, light sensitive ion channels or transporters have recently been cloned and modified so that the activity of the neurons expressing these proteins is under precise optical control. Electrophysiological methods still remain powerful and practical as they have some advantages, such as superior time resolution and ease of chronic recordings. The challenge of a growing generation of neuroscientists and medical/biological engineers is therefore to integrate conventional electrophysiological approaches with smart use of optics and photo-manipulatable probes, to dissect and possibly recreate neural circuit dynamics. The combination of the new and conventional methods shall generate a synergistic effect to further push the frontiers of our understanding on how our brain works.