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      Validating Neuro-Computational Models of Neurological and Psychiatric Disorders [electronic resource] / edited by Basabdatta Sen Bhattacharya, Fahmida N. Chowdhury.

      Contributor(s): Material type: TextTextSeries: Springer Series in Computational Neuroscience ; 14Publisher: Cham : Springer International Publishing : Imprint: Springer, 2015Edition: 1st ed. 2015Description: XVIII, 315 p. 110 illus., 77 illus. in color. online resourceContent type:
      • text
      Media type:
      • computer
      Carrier type:
      • online resource
      ISBN:
      • 9783319200378
      Subject(s): Additional physical formats: Printed edition:: No titleDDC classification:
      • 612.8 23
      LOC classification:
      • RC321-580
      Online resources:
      Contents:
      Introduction -- Discovery and validation of biomarkers based on computational models of normal and pathological hippocampal rhythms -- DCM, Conductance based models and Clinical applications -- Computational Models of Closed-loop Deep Brain Stimulation -- A multiscale 'working brain' model -- How to render Neural Fields more realistic -- Multilevel computational modeling in epilepsy: classical studies and recent advances -- Computational modeling of neuronal dysfunction at molecular level reveals the role of single neurons in circuit functions in cerebellum granule layer -- Modeling Cortical and Thalamocortical Synaptic Loss and Compensation Mechanisms in Alzheimer's disease -- Toward Networks from Spikes -- Epileptogenic networks: applying network analysis techniques to human seizure activity.
      In: Springer eBooksSummary: This book is a collection of articles by leading researchers working at the cutting edge of neuro-computational modelling of neurological and psychiatric disorders. Each article contains model validation techniques used in the context of the specific problem being studied. Validation is essential for neuro-inspired computational models to become useful tools in the understanding and treatment of disease conditions. Currently, the immense diversity in neuro-computational modelling approaches for investigating brain diseases has created the need for a structured and coordinated approach to benchmark and standardise validation methods and techniques in this field  of research. This book serves as a step towards a systematic approach to validation of neuro-computational models used for studying brain diseases, and should be useful for all neuro-computational modellers.
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      Introduction -- Discovery and validation of biomarkers based on computational models of normal and pathological hippocampal rhythms -- DCM, Conductance based models and Clinical applications -- Computational Models of Closed-loop Deep Brain Stimulation -- A multiscale 'working brain' model -- How to render Neural Fields more realistic -- Multilevel computational modeling in epilepsy: classical studies and recent advances -- Computational modeling of neuronal dysfunction at molecular level reveals the role of single neurons in circuit functions in cerebellum granule layer -- Modeling Cortical and Thalamocortical Synaptic Loss and Compensation Mechanisms in Alzheimer's disease -- Toward Networks from Spikes -- Epileptogenic networks: applying network analysis techniques to human seizure activity.

      This book is a collection of articles by leading researchers working at the cutting edge of neuro-computational modelling of neurological and psychiatric disorders. Each article contains model validation techniques used in the context of the specific problem being studied. Validation is essential for neuro-inspired computational models to become useful tools in the understanding and treatment of disease conditions. Currently, the immense diversity in neuro-computational modelling approaches for investigating brain diseases has created the need for a structured and coordinated approach to benchmark and standardise validation methods and techniques in this field  of research. This book serves as a step towards a systematic approach to validation of neuro-computational models used for studying brain diseases, and should be useful for all neuro-computational modellers.

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