NeuroProcessor (eBook)

An Integrated Interface to Biological Neural Networks
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2008 | 2008
VIII, 122 Seiten
Springer Netherlands (Verlag)
978-1-4020-8726-4 (ISBN)

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NeuroProcessor -  Ran Ginosar,  Yevgeny Perelman
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Understanding brain structure and principles of operation is one of the major challengesofmodernscience.SincetheexperimentsbyGalvanionfrogmuscle contraction in 1792, it is known that electrical impulses lie at the core of the brain activity. The technology of neuro-electronic interfacing, besides its importance for neurophysiological research, has also clinical potential, so called neuropr- thetics. Sensory prostheses are intended to feed sensory data into patient's brain by means of neurostimulation. Cochlear prostheses [1] are one example of sensory prostheses that are already used in patients. Retinal prostheses are currently under research [2]. Recent neurophysiological experiments [3, 4] show that brain signals recorded from motor cortex carry information regarding the movement of subject's limbs (Fig. 1.1). These signals can be further used to control ext- nal machines [4] that will replace missing limbs, opening the ?eld of motor prosthetics, devices that will restore lost limbs or limb control. Fig. 1.1. Robotic arm controlled by monkey motor cortex signals. MotorLab, U- versity of Pittsburgh. Prof Andy Schwartz, U. Pitt 2 1 Introduction Another group of prostheses would provide treatment for brain diseases, such as prevention of epileptic seizure or the control of tremor associated with Parkinson disease [5]. Brain implants for treatment of Epilepsy and Parkinson symptoms (Fig. 1.2) are already available commercially [6, 7]. Fig. 1.2. Implantable device for Epilepsy seizures treatment [7]. Cyberonics, Inc.
Understanding brain structure and principles of operation is one of the major challengesofmodernscience.SincetheexperimentsbyGalvanionfrogmuscle contraction in 1792, it is known that electrical impulses lie at the core of the brain activity. The technology of neuro-electronic interfacing, besides its importance for neurophysiological research, has also clinical potential, so called neuropr- thetics. Sensory prostheses are intended to feed sensory data into patient's brain by means of neurostimulation. Cochlear prostheses [1] are one example of sensory prostheses that are already used in patients. Retinal prostheses are currently under research [2]. Recent neurophysiological experiments [3, 4] show that brain signals recorded from motor cortex carry information regarding the movement of subject's limbs (Fig. 1.1). These signals can be further used to control ext- nal machines [4] that will replace missing limbs, opening the ?eld of motor prosthetics, devices that will restore lost limbs or limb control. Fig. 1.1. Robotic arm controlled by monkey motor cortex signals. MotorLab, U- versity of Pittsburgh. Prof Andy Schwartz, U. Pitt 2 1 Introduction Another group of prostheses would provide treatment for brain diseases, such as prevention of epileptic seizure or the control of tremor associated with Parkinson disease [5]. Brain implants for treatment of Epilepsy and Parkinson symptoms (Fig. 1.2) are already available commercially [6, 7]. Fig. 1.2. Implantable device for Epilepsy seizures treatment [7]. Cyberonics, Inc.

1 Introduction. 1.1 Overview of the Book. 2 Recording from Biological Neural Networks. 2.1 The Neuron. 2.2 Interfacing Neurons Electrically. 2.3 Neuronal Probes for Extracellular Recording. 2.4 Recording from Cultured Neural Networks. 2.5 Typical Multi-Electrode Recording Setup. 2.6 Recorded Signal Information Content. 3 The Neuroprocessor. 3.1 Datarate Reduction in Neuronal Interfaces. 3.2 Neuroprocessor Overview. 4 Integrated Front-end for Neuronal Recording. 4.1 Background. 4.2 NPR01: First Front-end Generation. 4.3 NPR02: Analog Front-end with Sprike/LFP Separation. 5 NPR03: Mixed-Signal Integrated Front-end for Neuronal Recording. 5.1 Overview. 5.2 NPR03 Architecture. 5.3 Host Interface. 5.4 NPR03 Channel. 5.5 Analog-to-Digital Converter. 5.6 Integrated Preamplifier with DC Blocking. 5.7 NPR03 Measurements. 5.8 An NPR03 -Based Miniature Headstage. 5.9 A Novel Opamp for the Front-end Preamplifier. 5.10 Conclusions. 6 Algorithms for Neuroprocessor Spike Sorting. 6.1 Introduction. 6.2 Spike Sorting in a Neuroprocessor. 6.3 Spike Sorting Algorithms. 6.4 Detection and Alignment Algorithms. 7 MEA on Chip: In-Vitro Neuronal Interfaces. 7.1 Prototype Sensor. 7.2 Temperature sensor and heater. 7.3 Post-Processing and Bath Formation. 7.4 Conclusions and Future Work. 8 Conclusions. 8.1 Research Contributions. 8.2 Future Work. A NPR02 Technical Details. A.1 NPR02 Preamp Sizing. A.2 NPR02 Testboard Output Channel. B NPR03 Technical Details. B.1 NPR03 Instruction Set. B.2 NPR03 Registers. B.3 NPR03 Preamp Sizing. B.4 Measurements of Additional NPR03 Channel Circuits. References. Index.

Erscheint lt. Verlag 20.8.2008
Zusatzinfo VIII, 122 p.
Verlagsort Dordrecht
Sprache englisch
Themenwelt Informatik Software Entwicklung User Interfaces (HCI)
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Medizin / Pharmazie Pflege
Medizin / Pharmazie Physiotherapie / Ergotherapie Orthopädie
Naturwissenschaften Biologie Humanbiologie
Naturwissenschaften Biologie Zoologie
Technik Bauwesen
Technik Elektrotechnik / Energietechnik
Technik Medizintechnik
Schlagworte algorithms • Artificial Intelligence • Brain-computer interfaces • brain-machine interfaces • Mixed signal digital and analog integrated circuits • Neuronal recording • neurons • Neuroprocessor • VLSI
ISBN-10 1-4020-8726-8 / 1402087268
ISBN-13 978-1-4020-8726-4 / 9781402087264
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