Walter Freeman

The scalp and cortex lie like pages of an open book on which the cortex enciphers vast quantities of information and knowledge. They are recorded and analyzed as temporal and spatial patterns in the electroencephalogram and electrocorticogram. This book describes basic tools and concepts needed to measure and decipher the patterns extracted from the EEG and ECoG. This book emphasizes the need for single trial analysis using new methods and paradigms, as well as large, high-density spatial arrays of electrodes for pattern sampling. The deciphered patterns reveal neural mechanisms by which brains process sensory information into precepts and concepts. It describes the brain as a thermodynamic system that uses chemical energy to construct knowledge. The results are intended for use in the search for the neural correlates of intention, attention, perception and learning; in the design of human brain-computer interfaces enabling mental control of machines; and in exploring and explaining the physicochemical foundation of biological intelligence.

The scalp and cortex lie like pages of an open book on which the cortex enciphers vast quantities of information and knowledge. They are recorded and analyzed as temporal and spatial patterns in the electroencephalogram and electrocorticogram. This book describes basic tools and concepts needed to measure and decipher the patterns extracted from the EEG and ECoG. This book emphasizes the need for single trial analysis using new methods and paradigms, as well as large, high-density spatial arrays of electrodes for pattern sampling. The deciphered patterns reveal neural mechanisms by which brains process sensory information into precepts and concepts. It describes the brain as a thermodynamic system that uses chemical energy to construct knowledge. The results are intended for use in the search for the neural correlates of intention, attention, perception and learning; in the design of human brain-computer interfaces enabling mental control of machines; and in exploring and explaining the physicochemical foundation of biological intelligence.

Foreword by Walter J. Freeman. The induction of unconsciousness using anesthetic agents demonstrates that the cerebral cortex can operate in two very different behavioral modes: alert and responsive vs. unaware and quiescent. But the states of wakefulness and sleep are not single-neuron properties---they emerge as bulk properties of cooperating populations of neurons, with the switchover between states being similar to the physical change of phase observed when water freezes or ice melts. Some brain-state transitions, such as sleep cycling, anesthetic induction, epileptic seizure, are obvious and detected readily with a few EEG electrodes; others, such as the emergence of gamma rhythms during cognition, or the ultra-slow BOLD rhythms of relaxed free-association, are much more subtle. The unifying theme of this book is the notion that all of these bulk changes in brain behavior can be treated as phase transitions between distinct brain states. Modeling Phase Transitions in the Brain contains chapter contributions from leading researchers who apply state-space methods, network models, and biophysically-motivated continuum approaches to investigate a range of neuroscientifically relevant problems that include analysis of nonstationary EEG time-series; network topologies that limit epileptic spreading; saddle--node bifurcations for anesthesia, sleep-cycling, and the wake--sleep switch; prediction of dynamical and noise-induced spatiotemporal instabilities underlying BOLD, alpha-, and gamma-band Hopf oscillations, gap-junction-moderated Turing structures, and Hopf-Turing interactions leading to cortical waves.

Foreword by Walter J. Freeman. The induction of unconsciousness using anesthetic agents demonstrates that the cerebral cortex can operate in two very different behavioral modes: alert and responsive vs. unaware and quiescent. But the states of wakefulness and sleep are not single-neuron properties---they emerge as bulk properties of cooperating populations of neurons, with the switchover between states being similar to the physical change of phase observed when water freezes or ice melts. Some brain-state transitions, such as sleep cycling, anesthetic induction, epileptic seizure, are obvious and detected readily with a few EEG electrodes; others, such as the emergence of gamma rhythms during cognition, or the ultra-slow BOLD rhythms of relaxed free-association, are much more subtle. The unifying theme of this book is the notion that all of these bulk changes in brain behavior can be treated as phase transitions between distinct brain states. Modeling Phase Transitions in the Brain contains chapter contributions from leading researchers who apply state-space methods, network models, and biophysically-motivated continuum approaches to investigate a range of neuroscientifically relevant problems that include analysis of nonstationary EEG time-series; network topologies that limit epileptic spreading; saddle--node bifurcations for anesthesia, sleep-cycling, and the wake--sleep switch; prediction of dynamical and noise-induced spatiotemporal instabilities underlying BOLD, alpha-, and gamma-band Hopf oscillations, gap-junction-moderated Turing structures, and Hopf-Turing interactions leading to cortical waves.

I think, therefore I am. The legendary pronouncement of philosopher Rene Descartes lingers as accepted wisdom in the Western world nearly four centuries after its author's death. But does thought really come first? Who actually runs the show: we, our thoughts, or the neurons firing within our brains? Walter J. Freeman explores how we control our behavior and make sense of the world around us. Avoiding determinism both in sociobiology, which proposes that persons' genes control their brains' functioning, and in neuroscience, which posits that their brains' disposition is molded by chemistry and environmental forces, Freeman charts a new course-one that gives individuals due credit and responsibility for their actions. Drawing upon his five decades of research in neuroscience, Freeman utilizes the latest advances in his field as well as perspectives from disciplines as diverse as mathematics, psychology, and philosophy to explicate how different human brains act in their chosen diverse ways. He clarifies the implications of brain imaging, by which neural activity can be observed during the course of normal movements, and shows how nonlinear dynamics reveals order within the fecund chaos of brain function.

Cortical evoked potentials are of interest primarily as tests of changing neuronal excitabilities accompanying normal brain function. The first three steps in the anal­ ysis of these complex waveforms are proper placement of electrodes for recording, the proper choice of electrical or sensory stimulus parameters, and the establish­ ment of behavioral control. The fourth is development of techniques for reliable measurement. Measurement consists of comparison of an unknown entity with a set of standard scales or dimensions having numerical attributes in preassigned degree. A physical object can be described by the dimensions of size, mass, density, etc. In addition there are dimensions such as location, velocity, weight, hardness, etc. Some of these dimensions can be complex (e. g. size depends on three or more subsidiary coordi­ nates), and some can be interdependent or nonorthogonal (e. g. specification of size and mass may determine density). In each dimension the unit is defined with refer­ ence to a standard physical entity, e. g. a unit of mass or length, and the result of measurement is expressed as an equivalence between the unknown and the sum of a specified number of units of that entity. The dimensions of a complex waveform are elementary waveforms from which that waveform can be built by simple addition. Any finite single-valued function of time is admissible. They are called basis functions (lO, 15), and they can be expressed in numeric as well as geometric form.