Dennis Glanzman Phd (15 results)

Hardcover. Condition: As New. 1st Edition. New book. Hard cover on front bottom right shows faint shelfwear from storage, but hard covers otherwise in excellent condition, no markings or underlining, spine unbroken, pages clean and crisp, book is unread. 0619B.

Hardcover. Condition: Fine. Leichte Rillen / Abschürfungen / Risse / Knicke. Neuronal responses to identical stimuli exhibit significant variability, often previously labeled as "noise." At the single neuron level, interspike interval (ISI) histograms during spontaneous or stimulus-evoked activity show a Poisson distribution, suggesting that neurons have intrinsic firing variability. Traditional averaging techniques, such as post-stimulus time histograms (PSTH) and event-related potentials (ERPs), have been used based on the assumption of noise in neuronal responses. However, recent studies measuring the information content of single neuron spike trains indicate that substantial information can be encoded even amid trial-to-trial variability. Experiments involving multiple single-unit recordings suggest that variability once deemed noise may reflect broader changes in cellular response properties. This raises the intriguing possibility that variability in neuronal responses could contain meaningful information for the nervous system's processing. To explore how neurons collaborate for coherent behavior and its disruptions in disease, neuroscientists now record simultaneously from hundreds of neurons across different brain areas, analyzing network activities through interdependence measures like cross-correlation, phase synchronization, and spectral coherence. This work delves into neuronal variability from theoretical, experimental, and clinical angles.

Condition: New. pp. xviii + 374 1st Edition.

Condition: New. pp. xviii + 374 Illus.

Condition: New. pp. xviii + 374.

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Condition: 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.

Condition: As New. Unread book in perfect condition.

Condition: As New. Unread book in perfect condition.

Condition: New.

Condition: New.

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

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Hardcover. Condition: 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. Condition: 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.