9780195393798 - The Dynamic Brain: An Exploration of Neuronal Variability and its Functional Significance (15 resultados)

Condición: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1000grams, ISBN:9780195393798.

hardcover. Condición: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!

Condición: Hervorragend. Zustand: Hervorragend | Seiten: 392 | Sprache: Englisch | Produktart: Bücher | To understand how neurons work to bring about coherent behavior and its breakdown in disease, neuroscientists must take into account both known and unknown sources of variability, and evaluate network activities by computing interdependence measures among neurons and among different brain areas. This book examines neuronal variability from theoretical, experimental and clinical perspectives.

Hardcover. Condición: gut. 2011. The Dynamic Brain In deutscher Sprache. pages.

Condición: As New. Unread book in perfect condition.

Condición: New.

Condición: As New. Unread book in perfect condition.

Condición: New.

Hardcover. Condición: Brand New. 1st edition. 392 pages. 9.40x6.20x1.00 inches. In Stock.

Condición: new. Questo è un articolo print on demand.

Condición: New. Print on Demand pp. xviii + 374 1st Edition.

Condición: New. Print on Demand pp. xviii + 374 Illus.

Condición: New. PRINT ON DEMAND pp. xviii + 374.

Hardcover. Condición: new. Hardcover. It is a well-known fact of neurophysiology that neuronal responses to identically presented stimuli are extremely variable. This variability has in the past often been regarded as "noise." At the single neuron level, interspike interval (ISI) histograms constructed during either spontaneous or stimulus evoked activity reveal a Poisson type distribution. These observations have been taken as evidence that neurons are intrinsically "noisy" in their firingproperties. In fact, the use of averaging techniques, like post-stimulus time histograms (PSTH) or event-related potentials (ERPs) have largely been justified based on the presence of what was believed to benoise in the neuronal responses.More recent attempts to measure the information content of single neuron spike trains have revealed that a surprising amount of information can be coded in spike trains even in the presence of trial-to-trial variability. Multiple single unit recording experiments have suggested that variability formerly attributed to noise in single cell recordings may instead simply reflect system-wide changes in cellular response properties. These observationsraise the possibility that, at least at the level of neuronal coding, the variability seen in single neuron responses may not simply reflect an underlying noisy process. They further raise the verydistinct possibility that noise may in fact contain real, meaningful information which is available for the nervous system in information processing.To understand how neurons work in concert to bring about coherent behavior and its breakdown in disease, neuroscientists now routinely record simultaneously from hundreds of different neurons and from different brain areas, and then attempt to evaluate the network activities by computing various interdependence measures, including crosscorrelation, phase synchronization and spectral coherence. This book examines neuronal variability from theoretical, experimental and clinical perspectives. To understand how neurons work to bring about coherent behavior and its breakdown in disease, neuroscientists must take into account both known and unknown sources of variability, and evaluate network activities by computing interdependence measures among neurons and among different brain areas. This book examines neuronal variability from theoretical, experimental and clinical perspectives. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - It is a well-known fact of neurophysiology that neuronal responses to identically presented stimuli are extremely variable. This variability has in the past often been regarded as 'noise.' At the single neuron level, interspike interval (ISI) histograms constructed during either spontaneous or stimulus evoked activity reveal a Poisson type distribution. These observations have been taken as evidence that neurons are intrinsically 'noisy' in their firing properties. In fact, the use of averaging techniques, like post-stimulus time histograms (PSTH) or event-related potentials (ERPs) have largely been justified based on the presence of what was believed to be noise in the neuronal responses.More recent attempts to measure the information content of single neuron spike trains have revealed that a surprising amount of information can be coded in spike trains even in the presence of trial-to-trial variability. Multiple single unit recording experiments have suggested that variability formerly attributed to noise in single cell recordings may instead simply reflect system-wide changes in cellular response properties. These observations raise the possibility that, at least at the level of neuronal coding, the variability seen in single neuron responses may not simply reflect an underlying noisy process. They further raise the very distinct possibility that noise may in fact contain real, meaningful information which is available for the nervous system in information processing.To understand how neurons work in concert to bring about coherent behavior and its breakdown in disease, neuroscientists now routinely record simultaneously from hundreds of different neurons and from different brain areas, and then attempt to evaluate the network activities by computing various interdependence measures, including cross correlation, phase synchronization and spectral coherence. This book examines neuronal variability from theoretical, experimental and clinical perspectives.