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1. Interneuronal network model of theta-nested fast oscillations predicts differential effects of heterogeneity, gap junctions and short term depression for hyperpolarizing versus shunting inhibition

   https://doi.org/10.1371/journal.pcbi.1010094  

   Via, Guillem ; Baravalle, Roman ; Fernandez, Fernando R. ; White, John A. ; Canavier, Carmen C. ( December 2022 , PLOS Computational Biology)

   Rubin, Jonathan (Ed.)

   Theta and gamma oscillations in the hippocampus have been hypothesized to play a role in the encoding and retrieval of memories. Recently, it was shown that an intrinsic fast gamma mechanism in medial entorhinal cortex can be recruited by optogenetic stimulation at theta frequencies, which can persist with fast excitatory synaptic transmission blocked, suggesting a contribution of interneuronal network gamma (ING). We calibrated the passive and active properties of a 100-neuron model network to capture the range of passive properties and frequency/current relationships of experimentally recorded PV+ neurons in the medial entorhinal cortex (mEC). The strength and probabilities of chemical and electrical synapses were also calibrated using paired recordings, as were the kinetics and short-term depression (STD) of the chemical synapses. Gap junctions that contribute a noticeable fraction of the input resistance were required for synchrony with hyperpolarizing inhibition; these networks exhibited theta-nested high frequency oscillations similar to the putative ING observed experimentally in the optogenetically-driven PV-ChR2 mice. With STD included in the model, the network desynchronized at frequencies above ~200 Hz, so for sufficiently strong drive, fast oscillations were only observed before the peak of the theta. Because hyperpolarizing synapses provide a synchronizing drive that contributes to robustness in the presence of heterogeneity, synchronization decreases as the hyperpolarizing inhibition becomes weaker. In contrast, networks with shunting inhibition required non-physiological levels of gap junctions to synchronize using conduction delays within the measured range. 

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2. Mechanisms regulating the properties of inhibition-based gamma oscillations in primate prefrontal and parietal cortices

   https://doi.org/10.1093/cercor/bhad077  

   Gonzalez-Burgos, Guillermo ; Miyamae, Takeaki ; Reddy, Nita ; Dawkins, Sidney ; Chen, Chloe ; Hill, Avyi ; Enwright, John ; Ermentrout, Bard ; Lewis, David A. ( March 2023 , Cerebral Cortex)

   In primates, the dorsolateral prefrontal (DLPFC) and posterior parietal (PPC) cortices are key nodes in the working memory network. The working memory-related gamma oscillations induced in these areas, predominantly in layer 3, exhibit higher frequency in DLPFC. Although these regional differences in oscillation frequency are likely essential for information transfer between DLPFC and PPC, the mechanisms underlying these differences remain poorly understood. We investigated, in rhesus monkey, the DLPFC and PPC layer 3 pyramidal neuron (L3PN) properties that might regulate oscillation frequency and assessed the effects of these properties simulating oscillations in computational models. We found that GABAAR-mediated synaptic inhibition synchronizes L3PNs in both areas, but analysis of GABAAR mRNA levels and inhibitory synaptic currents suggested similar mechanisms of inhibition-mediated synchrony in DLPFC and PPC. Basal dendrite spine density and AMPAR/NMDAR mRNA levels were higher in DLPFC L3PNs, whereas excitatory synaptic currents were similar between areas. Therefore, synaptically evoked excitation might be stronger in DLPFC L3PNs due to a greater quantity of synapses in basal dendrites, a main target of recurrent excitation. Simulations in computational networks showed that oscillation frequency and power increased with increasing recurrent excitation, suggesting a mechanism by which the DLPFC–PPC differences in oscillation properties are generated.

    

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3. Functional control of oscillator networks

   https://doi.org/10.1038/s41467-022-31733-2  

   Menara, Tommaso ; Baggio, Giacomo ; Bassett, Dani ; Pasqualetti, Fabio ( August 2022 , Nature Communications)

   Oscillatory activity is ubiquitous in natural and engineered network systems. The interaction scheme underlying interdependent oscillatory components governs the emergence of network-wide patterns of synchrony that regulate and enable complex functions. Yet, understanding, and ultimately harnessing, the structure-function relationship in oscillator networks remains an outstanding challenge of modern science. Here, we address this challenge by presenting a principled method to prescribe exact and robust functional configurations from local network interactions through optimal tuning of the oscillators’ parameters. To quantify the behavioral synchrony between coupled oscillators, we introduce the notion offunctional pattern, which encodes the pairwise relationships between the oscillators’ phases. Our procedure is computationally efficient and provably correct, accounts for constrained interaction types, and allows to concurrently assign multiple desired functional patterns. Further, we derive algebraic and graph-theoretic conditions to guarantee the feasibility and stability of target functional patterns. These conditions provide an interpretable mapping between the structural constraints and their functional implications in oscillator networks. As a proof of concept, we apply the proposed method to replicate empirically recorded functional relationships from cortical oscillations in a human brain, and to redistribute the active power flow in different models of electrical grids.

    

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4. Phasic cholinergic signaling promotes emergence of local gamma rhythms in excitatory–inhibitory networks

   https://doi.org/10.1111/ejn.14744  

   Lu, Yiqing ; Sarter, Martin ; Zochowski, Michal ; Booth, Victoria ( May 2020 , European Journal of Neuroscience)

   Recent experimental results have shown that the detection of cues in behavioral attention tasks relies on transient increases of acetylcholine (ACh) release in frontal cortex and cholinergically driven oscillatory activity in the gamma frequency band (Howe et al. Journal of Neuroscience, 2017, 37, 3215). The cue‐induced gamma rhythmic activity requires stimulation of M1 muscarinic receptors. Using biophysical computational modeling, we show that a network of excitatory (E) and inhibitory (I) neurons that initially displays asynchronous firing can generate transient gamma oscillatory activity in response to simulated brief pulses of ACh. ACh effects are simulated as transient modulation of the conductance of an M‐type K⁺current which is blocked by activation of muscarinic receptors and has significant effects on neuronal excitability. The ACh‐induced effects on the M current conductance,g_Ks, change network dynamics to promote the emergence of network gamma rhythmicity through a Pyramidal‐Interneuronal Network Gamma mechanism. Depending on connectivity strengths between and among E and I cells, gamma activity decays with the simulatedg_Kstransient modulation or is sustained in the network after theg_Kstransient has completely dissipated. We investigated the sensitivity of the emergent gamma activity to synaptic strengths, external noise and simulated levels ofg_Ksmodulation. To address recent experimental findings that cholinergic signaling is likely spatially focused and dynamic, we show that localizedg_Ksmodulation can induce transient changes of cellular excitability in local subnetworks, subsequently causing population‐specific gamma oscillations. These results highlight dynamical mechanisms underlying localization of ACh‐driven responses and suggest that spatially localized, cholinergically induced gamma may contribute to selectivity in the processing of competing external stimuli, as occurs in attentional tasks.

    

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5. Inhibition-based relaxation oscillations emerge in resonator networks

   https://doi.org/10.1051/mmnp/2019019  

   Bel, Andrea ; Torresi, Ana ; Rotstein, Horacio G. ; Korobeinikov, A. ; Lázaro, J. T. ; Mortell, M.P. ; Sobolev, V.A. ( January 2019 , Mathematical Modelling of Natural Phenomena)

   We investigate the mechanisms responsible for the generation of oscillations in mutually inhibitory cells of non-oscillatory neurons and the transitions from non-relaxation (sinusoidal-like) oscillations to relaxation oscillations. We use a minimal model consisting of a 2D linear resonator, a 1D linear cell and graded synaptic inhibition described by a piecewise linear sigmoidal function. Individually, resonators exhibit a peak in their response to oscillatory inputs at a preferred (resonant) frequency, but they do not show intrinsic (damped) oscillations in response to constant perturbations. We show that network oscillations emerge in this model for appropriate balance of the model parameters, particularly the connectivity strength and the steepness of the connectivity function. For fixed values of the latter, there is a transition from sinusoidal-like to relaxation oscillations as the connectivity strength increases. Similarly, for fixed connectivity strength values, increasing the connectivity steepness also leads to relaxation oscillations. Interestingly, relaxation oscillations are not observed when the 2D linear node is a damped oscillator. We discuss the role of the intrinsic properties of the participating nodes by focusing on the effect that the resonator’s resonant frequency has on the network frequency and amplitude. 

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