Significant progress has been made in recent years in studying the dynamics of the diseased brain at both microscopic and macroscopic levels. Electrical recordings of the diseased brain activity show (in)-coherent dynamic phenomena at scales ranging from local networks (thousands of neurons) to entire brain regions (millions of neurons). Our understanding of these spatial and temporal scales and resolutions continues to increase as evidence suggests close relationships between local field potentials recorded in the cortex (with electroencephalography or multi-unit recordings) and blood flow signals (measured with fMRI).

Application of multi-scale computational models as integrative principles that bridge the single neuron dynamics (monitored with intracellular recordings) with the dynamics of local and distant brain regions observed using human EEG, ERPs, MEG, LFPs and fMRI can further enhance our understanding of the diseased brain dynamics.

The goal of this book is to provide a focused series of papers on computational models of brain disorders combining multiple levels and types of computation with multiple types of data in an effort to improve understanding, prediction and treatment of brain and mental illness.

The volume aims to bring together physiologists and anatomists studying cortical circuits, cognitive neuroscientists studying brain dynamics and behaviour via EEG and functional magnetic resonance imaging (fMRI), and computational neuroscientists using neural modelling techniques to explore local and large-scale disordered brain dynamics. The thematic focus is expected to be appealing to a diverse group of investigators and have a high impact on the medical, neuroscience and computer science fields.

Zusammenfassung

This book focuses on our current understanding of brain dynamics in various brain disorders (e.g. epilepsy, Alzheimer's and Parkinson's disease) and how the multi-scale, multi-level tools of computational neuroscience can enhance this understanding.

In recent years, there have been significant advances in the study of the dynamics of the disordered brain at both the microscopic and the macroscopic levels. This understanding can be furthered by the application of multi-scale computational models as integrative principles that may link single neuron dynamics and the dynamics of local and distant brain regions observed using human EEG, ERPs, MEG, LFPs and fMRI.

Focusing on the computational models that are used to study movement, memory and cognitive disorders as well as epilepsy and consciousness related diseases, the book brings together physiologists and anatomists investigating cortical circuits; cognitive neuroscientists studying brain dynamics and behavior by means of EEG and functional magnetic resonance imaging (fMRI); and computational neuroscientists using neural modeling techniques to explore local and large-scale disordered brain dynamics.

Covering topics that have a significant impact on the field of medicine, neuroscience and computer science, the book appeals to a diverse group of investigators.

Inhalt

Part I              Movement Disorders

A neuro-computational model of Pallidal vs. Subthalamic Deep Brain Stimulation Effect on synchronization at Tremor frequency in Parkinson's disease

Alekhya Mandali, Srinivasa Chakravarthy V, Ahmed A. Moustafa****

Dynamics of Basal Ganglia and Thalamus in Parkinsonian Tremor

Jan Moren, Jun Igarashi, Osamu Shouno, Junichiro Yoshimoto, and Kenji Doya****

A neural mass model for abnormal beta-rebound in schizophrenia

Aine Byrne, Stephen Coombes, and Peter F Liddle

Basal ganglio-thalamo-cortico-spino-muscular model of Parkinson's disease bradykinesia

Vassilis Cutsuridis Network Models of the Basal Ganglia in Parkinson's Disease: Advances in Deep Brain Stimulation through Model-Based Optimization Karthik Kumaravelu1, Warren M. Grill

Neural synchronization in Parkinson's disease on different time-scales

Sungwoo Ahn, Choongseok Park, Leonid L. Rubchinsky

Obsessive compulsive tendencies and action sequence complexity: An Information Theory Analysis

Mustafa Zeki, Fuat Balc, Tutku Öztel, Ahmed A. Moustafa

Part II            Cognitive Disorders

Cortical disinhibition, attractor dynamics and belief updating in schizophrenia

Rick A Adams

Modelling cognitive processing of healthy controls and obsessive compulsive disorder subjects in the antisaccade task

Vassilis Cutsuridis

Simulating cognitive deficits in Parkinson's disease

Sébastien Hélie and Zahra Sajedinia

Attentional deficits in Alzheimer's disease: investigating the role of acetylcholine with computational modelling

Eirini Mavritsaki, Howard Bowman, Li Su

A computational hypothesis on how serotonin regulates catecholamines in the pathogenesis of depressive apathy Massimo Silvetti, Gianluca Baldassarre, Daniele Caligiore

Autism Spectrum Disorder and deep attractors in neurodynamics.

Wodzisaw Duch

Part III           Memory Disorders

Alzheimer's disease: rhythms, local circuits and model-experiment interactions

Frances K Skinner, Alexandra Chatzikalymniou

Using A Neurocomputational Autobiographical Memory Model to Study Memory Loss

Di Wang, Ahmed A. Moustafa, Ah-Hwee Tan, Chunyan Miao

Part IV           Epilepsy and Consciousness Related Disorders

How can computer modeling help understanding the dynamics of absence epilepsy?

Piotr Suffczynski, Stiliyan Kalitzin, Fernando H. Lopes da Silva

Data-driven modeling of normal and pathological oscillations in the hippocampus

Ivan Raikov, Ivan Soltesz

Shaping brain rhythms: dynamic and control-theoretic perspectives on periodic brain stimulation for treatment of neurological disorders**** John D. Griffiths, Jérémie Lefebvre

Brain connectivity reduction reflects disturbed self-organisation of the brain: Neural disorders and General Anesthesia

Axel Hutt