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Computational Neuroscience

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The event-related potential (ERP) technique, in which neural responses to specific events are extracted from the EEG, provides a powerful noninvasive tool for exploring the human brain. This volume describes practical methods for ERP research along with the underlying theoretical rationale. It offers researchers and students an essential guide to designing, conducting, and analyzing ERP experiments. This second edition has been completely updated, with additional material, new chapters, and more accessible explanations.

Theory and Practice

This book offers a comprehensive guide to the theory and practice of analyzing electrical brain signals. It explains the conceptual, mathematical, and implementational (via Matlab programming) aspects of time-, time-frequency- and synchronization-based analyses of magnetoencephalography (MEG), electroencephalography (EEG), and local field potential (LFP) recordings from humans and nonhuman animals.

From Laboratory to Theory

Vision is one of the most active areas in biomedical research, and visual psychophysical techniques are a foundational methodology for this research enterprise. Visual psychophysics, which studies the relationship between the physical world and human behavior, is a classical field of study that has widespread applications in modern vision science. Bridging the gap between theory and practice, this textbook provides a comprehensive treatment of visual psychophysics, teaching not only basic techniques but also sophisticated data analysis methodologies and theoretical approaches.

Global State Interactions

The consideration of time or dynamics is fundamental for all aspects of mental activity—perception, cognition, and emotion—because the main feature of brain activity is the continuous change of the underlying brain states even in a constant environment. The application of nonlinear dynamics to the study of brain activity began to flourish in the 1990s when combined with empirical observations from modern morphological and physiological observations. This book offers perspectives on brain dynamics that draw on the latest advances in research in the field.

The Emerging Intersection between Control Theory and Neuroscience

Over the past sixty years, powerful methods of model-based control engineering have been responsible for such dramatic advances in engineering systems as autolanding aircraft, autonomous vehicles, and even weather forecasting. Over those same decades, our models of the nervous system have evolved from single-cell membranes to neuronal networks to large-scale models of the human brain. Yet until recently control theory was completely inapplicable to the types of nonlinear models being developed in neuroscience.

A Laboratory Study of Multimodal Semiotic Interaction in the Age of Computers

The results of fMRI brain scanning require extensive analysis in the laboratory. In Handling Digital Brains, Morana Alač shows that fMRI researchers do not sit passively staring at computer screens but actively involve their bodies in laboratory practice. Discussing fMRI visuals with colleagues, scientists animate the scans with gestures, and talk as they work with computers. Alač argues that to understand how digital scientific visuals take on meaning we must consider their dynamic coordination with gesture, speech, and working hands.

Functional magnetic resonance imaging (fMRI), which allows researchers to observe neural activity in the human brain noninvasively, has revolutionized the scientific study of the mind. An fMRI experiment produces massive amounts of highly complex data; researchers face significant challenges in analyzing the data they collect. This book offers an overview of the most widely used statistical methods of analyzing fMRI data. Every step is covered, from preprocessing to advanced methods for assessing functional connectivity.

Probabilistic Approaches to Neural Coding

A Bayesian approach can contribute to an understanding of the brain on multiple levels, by giving normative predictions about how an ideal sensory system should combine prior knowledge and observation, by providing mechanistic interpretation of the dynamic functioning of the brain circuit, and by suggesting optimal ways of deciphering experimental data.

Most neurons in the brain are covered by dendritic spines, small protrusions that arise from dendrites, covering them like leaves on a tree. But a hundred and twenty years after spines were first described by Ramón y Cajal, their function is still unclear. Dozens of different functions have been proposed, from Cajal’s idea that they enhance neuronal interconnectivity to hypotheses that spines serve as plasticity machines, neuroprotective devices, or even digital logic elements.

The field of neuroimaging has reached a watershed. Brain imaging research has been the source of many advances in cognitive neuroscience and cognitive science over the last decade, but recent critiques and emerging trends are raising foundational issues of methodology, measurement, and theory. Indeed, concerns over interpretation of brain maps have created serious controversies in social neuroscience, and, more important, point to a larger set of issues that lie at the heart of the entire brain mapping enterprise.

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