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Sheremet, A.

Publications and source records attributed to Sheremet, A..

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LINEAR ANALYSIS OF HIPPOCAMPAL LFP: SLOW GAMMA VS HIGH THETA

AO_SCPCAPBSTRACTC_SCPCAPLocal field potential (LFP) oscillations are the superposition of excitatory/inhibitory postsynaptic potentials. In the hippocampus, the 20-55 Hz range ( slow gamma) is proposed to support cognition independent of other frequencies. However, this band overlaps with theta harmonics. We aimed to dissociate the generators of slow gamma versus theta harmonics with current source density and different LFP decompositions. Hippocampal theta harmonic and slow gamma generators were not dissociable. Moreover, comparison of wavelet, ensemble empirical-mode (EEMD), and Fourier decompositions produced distinct outcomes with wavelet and EEMD failing to resolve high-order theta harmonics well defined by Fourier analysis. The varying sizes of the time-frequency atoms used by wavelet distributed the higher-order harmonics over a broader range giving the impression of a low frequency burst (\"slow gamma\"). The absence of detectable slow gamma refutes a multiplexed model of cognition in favor of the energy cascade hypothesis in which dependency across oscillatory frequencies exists.

neuroscience

Theta-Gamma Cascades and Running Speed

The local field potentials (LFPs) of the hippocampus are primarily generated by the spatiotemporal accretion of electrical currents via activated synapses. Oscillations in the hippocampal LFP at theta and gamma frequencies are prominent during awake-behavior and have demonstrated several behavioral correlates. In particular, both oscillations have been observed to increase in amplitude and frequency as a function of running velocity. Previous investigations, however, have examined the relationship between velocity and each of these oscillation bands separately. Based on energy cascade models where \"...perturbations of slow frequencies cause a cascade of energy dissipation at all frequency scales\" (Buzsaki 2006), we hypothesized that the cross-frequency interactions between theta and gamma should increase as a function of velocity. We examined these relationships across multiple layers of the CA1 subregion and found a reliable correlation between the power of theta and the power of gamma, indicative of an amplitude-amplitude relationship. Moreover, there was an increase in the coherence between the power of gamma and the phase of theta, demonstrating increased phase-amplitude coupling with velocity. Finally, at higher velocities, phase entrainment between theta and gamma becomes stronger. These results have important implications and provide new insights regarding how theta and gamma are integrated for neuronal circuit dynamics, with coupling strength determined by the excitatory drive within the hippocampus.

neuroscience

Theta-gamma coupling: a nonlinear dynamical model

Cross-frequency coupling in the hippocampus has been hypothesized to support higher-cognition functions. While gamma modulation by theta is widely accepted, evidence of phase-coupling between the two frequency components is so far unconvincing. Our observations show that theta and gamma energy increases with rat speed, while the overall nonlinearity of the LFP trace also increases, suggesting that energy flow is fundamental for hippocampal dynamics. This contradicts current representations based on the Kuramoto phase model. Therefore, we propose a new approach, based on the three-wave equation, a universally-valid nonlinear-physics paradigm that synthesizes the effects of leading order, quadratic nonlinearity. The paradigm identifies bispectral analysis as the natural tool for investigating LFP cross-frequency coupling. Our results confirm the effectiveness of the approach by showing unambiguous coupling between theta and gamma. Bispectra features agree with predictions of the three-wave model, supporting the conclusion that cross-frequency coupling is a manifestation of nonlinear energy transfers.

neuroscience

Mesoscale turbulence in the hippocampus

Wave turbulence provides a powerful stochastic description for nonlinear collective neural activity in the hippocampus. Recent studies that show theta waves propagating across the hippocampus suggest that turbulence is a natural description for collective neural activity. We formulate the fundamental principles of a turbulence model and demonstrate turbulent behavior by analyzing rat hippocampal LFP traces. LFP spectra and bispectra exhibit fundamental turbulent properties: weak nonlinear coupling, energy cascade, and stationary spectra of the Kolmogorov-Zakharov type (power-law). Weak turbulence holds the promise of quantitative physical models of hippocampal dynamics, in the service of understanding the mechanisms of multi-scale integration of brain activity to cognition.

neuroscience