期刊
JOURNAL OF COMPUTATIONAL NEUROSCIENCE
卷 27, 期 2, 页码 277-290出版社
SPRINGER
DOI: 10.1007/s10827-009-0142-x
关键词
Noise; Gain; f-I curve; Stimulus fluctuations; Single neuron; Time scales; Dynamical systems; Phase portrait; Hodgkin-Huxley; Slow adaptation; Slow AHP
资金
- Burroughs-Wellcome Careers at the Scientific Interface
- McKnight Scholar Award
- National Institute of Neurological Disorders and Stroke [F30NS055650]
- Medical Scientist Training Program
- National Institute of General Medical Sciences
- ARCS fellowship
- VA Merit Review
- NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE [F30NS055650] Funding Source: NIH RePORTER
- Veterans Affairs [I01BX000386] Funding Source: NIH RePORTER
Neuronal responses are often characterized by the firing rate as a function of the stimulus mean, or the f-I curve. We introduce a novel classification of neurons into Types A, B-, and B+ according to how f-I curves are modulated by input fluctuations. In Type A neurons, the f-I curves display little sensitivity to input fluctuations when the mean current is large. In contrast, Type B neurons display sensitivity to fluctuations throughout the entire range of input means. Type B- neurons do not fire repetitively for any constant input, whereas Type B+ neurons do. We show that Type B+ behavior results from a separation of time scales between a slow and fast variable. A voltage-dependent time constant for the recovery variable can facilitate sensitivity to input fluctuations. Type B+ firing rates can be approximated using a simple energy barrier model.
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