Membrane Resonance Enables Stable and Robust Gamma Oscillations

Abstract

Neuronal mechanisms underlying beta/gamma oscillations (20–80 Hz) are not completely understood. Here, we show that in vivo beta/gamma oscillations in the cat visual cortex sometimes exhibit remarkably stable frequency even when inputs fluctuate dramatically. Enhanced frequency stability is associated with stronger oscillations measured in individual units and larger power in the local field potential. Simulations of neuronal circuitry demonstrate that membrane properties of inhibitory interneurons strongly determine the characteristics of emergent oscillations. Exploration of networks containing either integrator or resonator inhibitory interneurons revealed that: (i) Resonance, as opposed to integration, promotes robust oscillations with large power and stable frequency via a mechanism called RING (Resonance INduced Gamma); resonance favors synchronization by reducing phase delays between interneurons and imposes bounds on oscillation cycle duration; (ii) Stability of frequency and robustness of the oscillation also depend on the relative timing of excitatory and inhibitory volleys within the oscillation cycle; (iii) RING can reproduce characteristics of both Pyramidal INterneuron Gamma (PING) and INterneuron Gamma (ING), transcending such classifications; (iv) In RING, robust gamma oscillations are promoted by slow but are impaired by fast inputs. Results suggest that interneuronal membrane resonance can be an important ingredient for generation of robust gamma oscillations having stable frequency.

Frequency preference in two-dimensional neural models: a linear analysis of the interaction between resonant and amplifying currents

“…A large number of studies in recent years has focused on subthreshold membrane resonance in neurons, its dependence on ionic currents and its influence on neuronal and network oscillations (Richardson et al 2003; Ledoux and N. 2011; Castro-Alamancos et al 2007; Tohidi and Nadim 2009; Izhikevich et al 2003; Engel et al 2008; Reinker et al 2004; Kispersky et al 2012; Moca et al 2012; Thevenin et al 2011). Subthreshold membrane resonance is primarily described on the basis of a linear RLC circuit where R is equated with the membrane resistance, C with the membrane capacitance and the inductance L , more abstractly, with voltage-gated ionic conductance properties (Erchova et al 2004).…”

“…Recent work suggests that the frequency of the network oscillations may crucially depend on the intrinsic preferred frequencies of the constituent neurons (Lau and Zochowski 2011; Wu et al 2001; Tohidi and Nadim 2009; Ledoux and N. 2011; Moca et al 2012; Sciamanna and Wilson 2011). These preferred frequencies arise in different contexts: the ability of a neuron to generate subthreshold oscillations at a particular frequency, often in response to a DC current input (Dickson and Alonso 1997; Lampl and Yarom 1997; Schmitz et al 1998; Reboreda et al 2003); the tendency of a neuron to produce subthreshold membrane potential resonance, a peak in the impedance amplitude in response to an oscillatory input current at a non-zero (resonant) frequency (Hutcheon and Yarom 2000); or membrane potential oscillations with zero phase lag in response to an oscillatory current input at a specific frequency (zero-phase-frequency).…”

Do gamma oscillations play a role in cerebral cortex?

“…The inhibitory network could generate the rhythm by itself or through periodic excitation arising from the pyramidal cell population (see [20] and references therein for a detailed discussion of cellular mechanisms). Several models have been proposed to explain this phenomenon [22–26]. In most of these models, gamma oscillations are generated due to excitation-inhibition interactions as a consequence of simple network dynamics and time constants associated with excitatory post-synaptic potentials and inhibitory post-synaptic potentials.…”

Two emerging topics regarding long-range physical signaling in neurosystems: Membrane nanotubes and electromagnetic fields

“…For electrodynamic induction (which is, regarding to the near-field condition, analogous to evanescent-wave coupling in optics), a resonance condition must be fulfilled. Interestingly, it is known that brain cells possess resonant properties, i.e., frequency-dependent excitability (Llinás, 1988;Pike et al, 2004;Reinker et al, 2004;Schreiber et al, 2009;Tohidi and Nadim, 2009;Moca et al, 2014) -a property that could play a role for the EM-fieldmediated cell-to-cell coupling. This frequency preference of neurons due to the membrane potential resonance (MPR) is observed in many types of neurons, e.g., interneurons ("resonator interneurons"), thalamocortical neurons and pyramidal neurons (Moca et al, 2014).…”

“…Interestingly, it is known that brain cells possess resonant properties, i.e., frequency-dependent excitability (Llinás, 1988;Pike et al, 2004;Reinker et al, 2004;Schreiber et al, 2009;Tohidi and Nadim, 2009;Moca et al, 2014) -a property that could play a role for the EM-fieldmediated cell-to-cell coupling. This frequency preference of neurons due to the membrane potential resonance (MPR) is observed in many types of neurons, e.g., interneurons ("resonator interneurons"), thalamocortical neurons and pyramidal neurons (Moca et al, 2014). Regarding MPR in the context of electromagnetic-field-mediated cell-to-cell coupling, two additional aspects may be of relevance: (i) Reinker et al (2004) discovered that both, MPR and stochastic resonance (SR) are properties of neurons.…”