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Introduction
Published in Shoogo Ueno, Bioimaging, 2020
Karl Deisseroth (1971–) in the USA and his group published a paper on millisecond-timescale, genetically targeted optical control of neural activity, and demonstrated millisecond-timescale control of neuronal spiking, as well as control of excitatory and inhibitory synaptic transmission in 2005 (Boyden et al., 2005). They adapted the naturally occurring algal protein Channelrhodopsin-2, a rapidly gated light-sensitive cation channel, by using lentiviral gene delivery in combination with high-speed optical switching to photo-stimulate mammalian neurons. Deisseroth appeals that this technology allows the use of light to alter neural processing at the level of single spikes and synaptic events, yielding a widely applicable tool for neuroscientists and biomedical engineers. Thus, Deisseroth has spearheaded “optogenetics,” a new methodological discipline in which cellular activities are controlled by light and has revolutionized systems neuroscience research.
Functional Optoacoustic Imaging
Published in Francesco S. Pavone, Shy Shoham, Handbook of Neurophotonics, 2020
Extensive research is underway to address technical challenges associated with the intriguing and highly promising combination of light and sound. Main limitations are currently associated with the lack of reliable and affordable lasers and ultrasound detection technology that can optimally address the unique needs of OA neuroimaging, such as high per-pulse laser energy or repetition rate, ultrawideband detection, high detection sensitivity, and miniaturization. Multiple frontiers are also open in the algorithmic and inverse theory areas, attempting to address challenges related to removal of skull-related image artifacts, image quantification, efficient acquisition and processing of very large data, and multi-spectral data processing. Finally, further advances in activity markers and genetic labeling tools tailored for optimal OA signal transduction are expected to greatly facilitate the application of the OA imaging technology in systems neuroscience and the study of neurological and psychiatric diseases.
Advances in Brain-Machine Interfaces
Published in Alexa Riehle, Eilon Vaadia, Motor Cortex in Voluntary Movements, 2004
Jose M. Carmena, Miguel A.L. Nicolelis
In addition to the potential clinical application, BMIs also serve as a unique tool for systems neuroscience research. The combination of multiple-site, multiple-electrode recordings with the BMI paradigm provides the experimenter with a new way to quantify neurophysiological modifications occurring in cortical networks, as animals learn motor tasks of various complexities.14
The integrated ethics and society programme of the Human Brain Project: reflecting on an ongoing experience
Published in Journal of Responsible Innovation, 2018
Christine Aicardi, Michael Reinsborough, Nikolas Rose
Computer science was to be involved in HBP neuroscience in two ways. It was argued that to successfully analyse and derive new insights from the amount and complexity of neuroscientific data, new computational infrastructure and techniques are required (The HBP Consortium 2015, 7–8; The HBP-PS Consortium 2012, 8–9). Reciprocally, the insights of neuroscientific discoveries were expected to contribute to more efficient and effective computing, generating capabilities that can be deployed in novel ways within the economy (The HBP Consortium 2015, 7–8; The HBP-PS Consortium 2012, 8–9). The HBP’s proposal emphasised that multilevel integration of neurological knowledge was key to reaching its strategic objective for future neuroscience, which was to ‘achieve a unified, multi-level understanding of the human brain that integrates data and knowledge about the healthy and diseased brain across all levels of biological organisation, from genes to behaviour; establish in silico experimentation as a foundational methodology for understanding the brain’ (European Commission 2014, 44) through interconnected information technology (IT) platforms. The HBP would be ‘putting in place a cutting-edge research infrastructure that will allow scientific and industrial researchers to advance our knowledge in the fields of neuroscience, computing, and brain-related medicine’ (Viola 2016). The project is divided into Subprojects about half of which are focused on research and the generation of strategic data resources (Mouse Brain, Human Brain, Cognitive and Systems Neuroscience, Theoretical Neuroscience) and the other half are building the IT platforms composing the infrastructure (Neuroinformatics, Brain Simulation, High Performance Analytics and Computing, Medical Informatics, Neuromorphic Computing, and Neurorobotics). Our Foresight Lab is a part of the Ethics and Society Subproject (SP12) (The HBP Consortium 2015, 48–72).