Autism Spectrum Disorder and deep attractors in neurodynamics.
Włodzisław 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
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.