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Closed Loop Neuroscience

  • ID: 3627082
  • Book
  • 304 Pages
  • Elsevier Science and Technology
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Closed Loop Neuroscience addresses the technical aspects of closed loop neurophysiology, presenting the implementation of these approaches spanning several domains of neuroscience, from cellular and network neurophysiology, through sensory and motor systems, and then clinical therapeutic devices.

Although closed-loop approaches have long been a part of the neuroscientific toolbox, these techniques are only now gaining popularity in research and clinical applications. As there is not yet a comprehensive methods book addressing the topic as a whole, this volume fills that gap, presenting state-of-the-art approaches and the technical advancements that enable their application to different scientific problems in neuroscience.

  • Presents the first volume to offer researchers a comprehensive overview of the technical realities of employing closed loop techniques in their work
  • Offers application to in-vitro, in-vivo, and hybrid systems
  • Contains an emphasis on the actual techniques used rather than on specific results obtained
  • Includes exhaustive protocols and descriptions of software and hardware, making it easy for readers to implement the proposed methodologies
  • Encompasses the clinical/neuroprosthetic aspect and how these systems can also be used to contribute to our understanding of basic neurophysiology
  • Edited work with chapters authored by leaders in the field from around the globe - the broadest, most expert coverage available

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Theoretical Axis 1. Adaptive Bayesian methods for closed-loop neurophysiology 2. Information geometric analysis of neurophysiological data 3. Control theory for closed loop neurophysiology 4. Testing the theory of practopoiesis using closed loops 5. Local field potential analysis for closed loop neuromodulation 6. Online event detection requirements in closed-loop neuroscience 7. Closing Dewey's Circuit 8. Stochastic optimal control of spike times in single neurons 9. Hybrid systems neuroscience 10. Computational Complexity and the Function-Structure-Environment Loop of the Brain 11. Subjective Physics 12. Contextual emergence in neuroscience

Experimental Axis 13. Closed loop methodologies for cellular electrophysiology 14. Bidirectional Brain-Machine Interfaces 15. Real time movement prediction for closed loop neurotechnology 16. Adaptive brain stimulation for Parkinson's disease 17. Closed loop neuroprosthetics 18. Closed Loop Limbic Neurostimulation 19. Conscious brain-to-brain communication

Philosophical Axis 20. Philosophical aspects of closed loop neuroscience 21. Closed Loops in Neuroscience and Computation: What It Means and Why It Matters

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El Hady, Ahmed
Ahmed El Hady is currently a Howard Hughes Medical Institute postdoctoral research associate at the Princeton neuroscience Institute where he is studying the neural substrates of decision making. Before moving to Princeton, he held a postdoctoral position at the Max Planck Institute for Biophysical chemistry in the Nanobiophotonics department where he investigated the nanoscale structure of the neuronal cytoskeleton. His PhD work spanned the interface of theoretical and experimental neuroscience in a collaborative project between the Max Planck Institute for Dynamics and Self Organization, the Max Planck Institute for experimental medicine and the Max Planck Institute for Biophysics during which he used optogenetic neurostimulation and microarray technology to study neuronal network dynamics. Ahmed holds a bachelor degree in pharmaceutical sciences from Cairo University and has attended the International Max Planck Research School of Neurosciences in Goettingen. Beside his outstanding academic achievements, Ahmed has organized the first Arab-Israeli-German computational and systems neuroscience meeting that took place in Goettingen during July 2014.
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