Dopamine-dependent oscillations in frontal cortex index "start-gun" signal in interval timing.

作者: Tadeusz W. Kononowicz

DOI: 10.3389/FNHUM.2015.00331

关键词:

摘要: Although perceiving the passage of time is a basic building block cognitive processes and behavior such as expecting relevant events to happen, neural underpinnings interval timing are not well-understood yet (van Wassenhove, 2009; Allman Meck, 2012; Merchant et al., 2013). From neurobiological point view, it has been established that dopamine impacts (e.g., 1986, 1996; 2012). However, link between pharmacological manipulations their impact on neurophysiological signals rarely investigated. The leading neurobiologically plausible model considers both components Striatal Beat Frequency (SBF) (Mattel 2004; Buhusi 2005; van Rijn 2014). SBF relies neuromodulatory dynamics thalamo-cortico-striatal loops. currently most interactions in assumed be unidirectional, Mattel Meck (2004) also acknowledged possibility feedback from cortex neurons VTA well striatal substantia nigra pars compacta. These potential mechanisms unaddressed model. implementation would allow for more accurate description clock speed memory updating trial basis (W. personal communication, May 15, 2015). Nevertheless, assumes coded by coincidental activation spiny with cortical oscillators (CO). Numerical implementations utilizes phase, or amplitude, CO envisioned oscillate at various frequencies giving rise different amplitude patterns over illustrated Figure ​Figure1.1. Hence, given specific pattern can encoded neurons. Crucially, that, onset to-be-timed interval, phases reset burst dopaminergic input ventral tegmental area (VTA, 2004). Further, contends initial dopamine-triggered phase-resetting plays role “start-gun” initiates timing. This signal forces whole set start same allowing coincidence detection read state CO, code particular duration multiple trials. Importantly, phase-reset interval—that is, proportion phase—the larger phase synchronization oscillatory power ongoing oscillations (Canavier, 2015), reduces variability representation (see ​Figure1;1; Ng 2011). Within this framework precise should associated an increase accuracy. Note accuracy seen peak latency response distribution, kurtosis distribution. According distribution accounted features modulated frequency range whereas (Oprisan Buhusi, As width shows consistency estimated number What referred here terms Therefore, affected reset. covariation precision represented modulation synchrony any population tested directly.

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