Interspike interval

Figure 7.3 Interspike interval (ISI) histograms of midbrain dopamine neural firing in behaving rats (reproduced with permission from (Miller et al. 1983)). Note the nearly identical mean intervals, consistent with reported mean firing rate similarities between SWS and REM sleep, as opposed to the broader ISI range observed in REM sleep, reflective of the burst firing in a significant subpopulation of neurons (contrast the widths of the dashed bars above the histograms).

Fig. 7.10 Computer simulation of two gap-junction coupled neurons which originally are operating at different dynamic states, one in the tonic firing regime and the other one in the bursting regime (also indicated in Fig. 6.8b by the points T and B, respectively with the arrow S pointing on the completely synchronized state), (a) Bifurcation diagrams of interspike intervals (ISI) of the originally...

Trains of action potentials recorded extracellularly from a neuron in the rostral portion of the nucleus of the solitary tract (NST) of a rat. About 10s of activity is shown for each stimulus, the application of which is indicated by the arrowheads. This cell did not respond to the sweet-tasting stimuli (sucrose and fructose), but showed robust responses to sodium salts, nonsodium salts, acids, and all the 10 bitter stimuli applied to the tongue and palate. Arrowheads indicated the time of stimulus application. The interspike interval histogram shown at the lower left indicates that no spikes fell within the neuron s refractory period, demonstrating that the spikes are recorded from a single neuron. Data from Lemon and Smith (2005)... 

We mention that the interspike interval distribution densities for the FHN system in the different dynamical regimes, including excitable behavior, were already presented in [9]. The calculations were performed under the assumption of a perfect time scale separation and linearization of the... 

Fig. 2.10. Relation between mean system frequency v and driving frequency i/ (top) and number of locked cycles Ni ck (bottom) of the excitable model as a function of driving frequency v. Lines show dependence as solutions of eqs. (2.36) and (2.37). The + symbols present results from simulations of the discrete system and circles correspond to data from simulations of the FHN system. Parameters for the FHN system eq. (2.11) ao = 0.405, ai = 0.5, = 0.001, D = 10 , Sx(t) = 0, Sy t) = A with A = 0.015. Parameters for the two state model (theory and simulations) from simulations of the interspike interval distribution density (cf. Fig. 2.6) T ss 2620, ro 0.0087 and n 8.3 10- . [15]...

To get deeper insight into the effect noise has on the time scales and coherence of the system we determine the interval between two consecutive excitations and calculate the mean interspike-interval (T). In Fig. 5.11(b) (top) the decrease of (T) as a function of D is shown thus demonstrating that the mean interspike-interval is strongly controlled by the noise intensity especially at lower values of the latter. This is very important in terms of experiments, where noise can induce oscillations by forcing stationary fronts to move. The corresponding spectral peak frequency / shows a linear scaling for small D. As a measure for coherence we use the normalized fluctuations of pulse duration [10]... 

The use of interspike interval histograms and auto-correlations for the detection of temporal patterns in recorded responses of single cells has been described by Perkel et al. (1967) and has recently been applied by Dethier and Crnjar (1982) to the analysis of recordings from contact chemoreceptor cells of Manduca sexta. 

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