Understanding of physiological neural firing patterns through dynamical bifurcation machineries

Yang, Minghao; An, Shu-Cheng; Gu, Huaguang; Liu, Zhiqiang; Ren, Wei

doi:10.1097/01.wnr.0000224770.74528.d6

Cited by 27 publications

(21 citation statements)

References 16 publications

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“…The dynamics of neural firing patterns and the bifurcations of firing patterns were of fundamental importance to the elucidation of neural coding mechanism (Braun et al 1994;Yang et al 2006). Various firing patterns, such as periodic firing, chaotic firing and stochastic resonance induced stochastic firing, were inspected in different nervous system (Chay 1985;Braun et al 1994;Ren et al 1997;Gu et al 2001Gu et al , 2003Gu et al , 2011aJia et al 2011;Du et al 2010;Guo 2011).…”

Section: Introductionmentioning

confidence: 99%

Dynamics of period-doubling bifurcation to chaos in the spontaneous neural firing patterns

Jia

et al. 2011

Cogn Neurodyn

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Period-doubling bifurcation to chaos were discovered in spontaneous firings of Onchidium pacemaker neurons. In this paper, we provide three cases of bifurcation processes related to period-doubling bifurcation cascades to chaos observed in the spontaneous firing patterns recorded from an injured site of rat sciatic nerve as a pacemaker. Period-doubling bifurcation cascades to period-4 (π(2,2)) firstly, and then to chaos, at last to a periodicity, which can be period-5, period-4 (π(4)) and period-3, respectively, in different pacemakers. The three bifurcation processes are labeled as case I, II and III, respectively, manifesting procedures different to those of period-adding bifurcation. Higher-dimensional unstable periodic orbits (UPOs) can be detected in the chaos, built close relationships to the periodic firing patterns. Case III bifurcation process is similar to that discovered in the Onchidium pacemaker neurons and simulated in theoretical model-Chay model. The extra-large Feigenbaum constant manifesting in the period-doubling bifurcation process, induced by quasi-discontinuous characteristics exhibited in the first return maps of both ISI series and slow variable of Chay model, shows that higher-dimensional periodic behaviors appeared difficult within the period-doubling bifurcation cascades. The results not only provide examples of period-doubling bifurcation to chaos and chaos with higher-dimensional UPOs, but also reveal the dynamical features of the period-doubling bifurcation cascades to chaos.

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Section: Introductionmentioning

confidence: 99%

Dynamics of period-doubling bifurcation to chaos in the spontaneous neural firing patterns

Jia

et al. 2011

Cogn Neurodyn

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“…[1][2][3][4][5][6][7][8][9][10] Dynamics underpinning various neuronal firing patterns have been eventually revealed by theoretical analysis in neuronal models, while mechanisms underlying the transitions between different firing patterns are being elucidated by means of bifurcation theory. [1][2][3][4]8 For example, neural excitable membranes have been demonstrated to transit from resting state to tonic firing through Hopf bifurcation and saddle-node bifurcation, respectively.…”

Section: Introductionmentioning

confidence: 99%

“…[2][3][4] The bifurcation procedures of neural firing activities exhibit the way in which a neuron changes its firing rhythms in response to regulatory parameter changes, and thus are essential for understanding the mechanisms of neural coding. 9 In studies of nonlinear dynamics of neuronal firing activities, the transition from resting state to tonic firing is an important issue, because during this transition most neurons generate their significant output signals. In transition from resting to firing, noise has been found to play critical roles and may generate stochastic firing patterns by its interplay with the dynamics of the neuronal systems.…”

Section: Introductionmentioning

confidence: 99%

Coherence Resonance–induced Stochastic Neural Firing at a Saddle-Node Bifurcation

Zhang

Wei

et al. 2011

Int. J. Mod. Phys. B

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Coherence resonance at a saddle-node bifurcation point and the corresponding stochastic firing patterns are simulated in a theoretical neuronal model. The characteristics of noise-induced neural firing pattern, such as exponential decay in histogram of interspike interval (ISI) series, independence and stochasticity within ISI series are identified. Firing pattern similar to the simulated results was discovered in biological experiment on a neural pacemaker. The difference between this firing and integer multiple firing generated at a Hopf bifurcation point is also given. The results not only revealed the stochastic dynamics near a saddle-node bifurcation, but also gave practical approaches to identify the saddle-node bifurcation and to distinguish it from the Hopf bifurcation in neuronal system. In addition, many previously observed firing patterns can be attribute to stochastic firing pattern near such a saddle-node bifurcation.

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“…It was also reported that, even if blood pressure is in the physiological range, some baroreceptors generate a temporal pattern in which they stop firing (i.e., rest) in the systolic phase but resume firing in the diastolic phase [14,15]. The results indicate that at least some baroreceptors can stop firing as blood pressure increases in the systolic phase.…”

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confidence: 96%

Individual aortic baroreceptors are sensitive to different ranges of blood pressures

Chen

Yang

Han

et al. 2014

Sci. China Life Sci.

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Many receptors, including thermal receptors and mechanical receptors, are only activated by stimuli within a clearly defined range of intensities. Differences in the receptive ranges enable individual receptors and their sensory centers to precisely detect the intensity of the stimulus and changes in intensity. Baroreceptors are the sensory terminals of the baroreflex. It is well understood that an increasing number of baroreceptors are recruited to produce afferent action potentials as the blood pressure increases, indicating that individual baroreceptors have different pressure thresholds. The present study revealed that individual baroreceptors could stop their afferent signals when the blood pressure exceeds a certain level, indicating that individual baroreceptors are sensitive to a specific range of blood pressure. The receptive ranges of individual baroreceptors differ in terms of the total range, the lower threshold, and the upper threshold. Of 85 baroreceptors examined in this study, the upper thresholds for about half were within the physiological blood pressure range. These results indicate that supraphysiological blood pressure is unlikely to be encoded by the recruitment of more baroreceptors. Instead, supraphysiological blood pressure levels might be signaled by an increase in the frequency of action potentials or by other mechanisms. In conclusion, our results indicate that rabbit baroreceptors are activated by blood pressure levels within specific receptive ranges. These findings should encourage further studies to examine the role of population coding of blood pressure by baroreceptors in the baroreflex. The baroreflex is the major physiological mechanism involved in the rapid regulation of blood pressure. Stretching of the aorta following an increase in blood pressure activates baroreceptors located in the carotid sinus and aorta, causing stronger afferent signal to the blood pressure regulatory center. The reflex system lowers blood pressure by decreasing the heart rate and the peripheral resistance. This reflex is also known as the depressure reflex [1,2]. Baroreceptors, sensory nerve terminals located beneath the vascular adventitia, are the sensory components of the depressure reflex. Variations in blood pressure cause changes in vascular extension and thus the stress on baroreceptors. Afferent neural impulses generated by the baroreceptors then convey information regarding the changes in blood pressure to the central nervous system [3]. It is well established that, within the physiological range of blood pressure, the frequency of impulses generated by individual baroreceptors is positively correlated with vascular extension, with an S-shaped correlation between the frequency of afferent impulses and blood pressure [4][5][6][7]. As blood pressure increases, more baroreceptors are recruited and changes in blood pressure are coded by the frequency of action potentials derived from the individual afferent nerve fibers and the number of the recruited active fibers. These

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Understanding of physiological neural firing patterns through dynamical bifurcation machineries

Cited by 27 publications

References 16 publications

Dynamics of period-doubling bifurcation to chaos in the spontaneous neural firing patterns

Dynamics of period-doubling bifurcation to chaos in the spontaneous neural firing patterns

Coherence Resonance–induced Stochastic Neural Firing at a Saddle-Node Bifurcation

Individual aortic baroreceptors are sensitive to different ranges of blood pressures

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