Exploratory Analysis and Data Modeling in Functional Neuroimaging (Neural Information Processing)

Functional imaging tools such as fMRI (functional magnetic resonance imaging), PET (positron emission tomography), EEG (electro-encephalogram), and MEG (magneto-encephalogram) allow researchers to record activity in the working brain and draw inferences about how the brain functions. This book provides a survey of theoretical and computational approaches to neuroimaging, including inferential, exploratory, and causal methods of data analysis; theories of cerebral function; and biophysical and computational models of neural networks. It also emphasizes the close relationships between different approaches, for example, between causal data analysis and biophysical modeling, and between functional theories and computational models. An overview of theoretical and computational approaches to neuroimaging.Functional imaging tools such as fMRI (functional magnetic resonance imaging), PET (positron emission tomography), EEG (electro-encephalogram), and MEG (magneto-encephalogram) allow researchers to record activity in the working brain and draw inferences about how the brain functions. This book provides a survey of theoretical and computational approaches to neuroimaging, including inferential, exploratory, and causal methods of data analysis; theories of cerebral function; and biophysical and computational models of neural nets. It also emphasizes the close relationships between different approaches, for example, between causal data analysis and biophysical modeling, and between functional theories and computational models. Functional imaging tools such as fMRI (functional magnetic resonance imaging), PET (positron emission tomography), EEG (electro-encephalogram) and MEG (magneto-encephalogram) allow researchers to record activity in the working brain and draw inferences about how the brain functions. This book provides a survey of theoretical and computational approaches to neuroimaging, including inferential, exploratory and causal methods of data analysis; theories of cerebral function; and biophysical and computational models of neural nets. It also emphasizes the close relationship between different approaches, for example, between causal data analysis and biophysical modelling, and between functional theories, and computational models.