Biology subjects

Ermentrout, G. B.

Publications and source records attributed to Ermentrout, G. B..

5 recordsLinked to original sources

bioRxiv2026

Differential Vulnerability of Stimulus-Locked and Persistent Gamma Oscillations: Implications in Schizophrenia

Working memory depends on gamma oscillations generated across sensory and prefrontal cortices. In sensory cortices such as primary visual cortex (V1), stimulus-locked gamma oscillations encode stimulus information, while in prefrontal cortex (PFC), persistent gamma oscillations maintain this information after the stimulus is removed. In schizophrenia (SZ), gamma power is reduced in both V1 and PFC, consistent with deficits in sensory encoding and working memory maintenance in the illness. These two regimes of gamma oscillations arise from a canonical microcircuit involving pyramidal neurons (PNs) and parvalbumin-expressing interneurons (PVIs). Yet, whether stimulus-locked and persistent gamma oscillations are similarly or differentially vulnerable to synaptic alterations within this circuit in SZ remains unknown. To investigate this question, we used a mean-field model of the PN-PVI circuit generating either stimulus-locked or persistent gamma oscillations. We then assessed the effects of three synaptic alterations found in SZ: lower excitatory drive to PVIs (E[->]I), lower inhibitory drive to PNs (I[->]E), and greater variability in E[->]I synaptic strength. Each alteration produced larger gamma power deficits in the persistent regime than in the stimulus-locked regime. When applied together, these alterations interacted synergistically to reduce gamma power in both regimes, with the persistent regime exhibiting a more pronounced deficit. Among the three parameters, E[->]I synaptic strength was the strongest contributor to the synergistic loss of gamma power. Two-dimensional bifurcation analyses further revealed that this differential vulnerability arises from a narrower margin of oscillatory stability in the persistent regime, where the parameter values producing maximum gamma power sit closer to the Hopf bifurcation boundary. Together, these findings identify the persistent regime as intrinsically more fragile than the stimulus-locked regime, with the implications for understanding regional patterns of synaptic pathology and cortical gamma oscillations with distinct dynamics in SZ. Author summaryWorking memory depends on stimulus-locked gamma oscillations in sensory cortices such as primary visual cortex (V1) for encoding stimulus information, and persistent gamma oscillations in prefrontal cortex (PFC) for maintaining this information after stimulus offset. In schizophrenia (SZ), gamma power is reduced in both V1 and PFC, and postmortem human brain studies suggest that the underlying synaptic alterations are more severe in V1 than in PFC. Our computational modeling results suggest that this regional pattern arises because persistent gamma oscillations are intrinsically more fragile than stimulus-locked gamma oscillations, so that smaller synaptic alterations are sufficient to disrupt gamma oscillations in PFC while larger alterations are required to produce comparable disruption in V1. Together, these findings give rise to a differential vulnerability model of cortical gamma oscillations in SZ, linking the regional patterns of synaptic pathology to the deficits in gamma oscillations observed across sensory and prefrontal cortices in the illness.

neuroscience↗

bioRxiv2026

Reconciling contradictory models of subthalamic nucleus contributions to basal ganglia beta oscillations

Recent computational studies of Parkinsons disease have yielded contradictory findings regarding the role of the subthalamic nucleus (STN) in pathological beta oscillations, with some models implicating STN as essential for beta generation and others suggesting that STN suppresses oscillations. This work addresses these discrepancies by systematically investigating how the specific features of the integrate-and-fire neurons used in these models influence simulated basal ganglia network dynamics. Using both rate models and spiking network simulations incorporating coupled subthalamopallidal and pallidostriatal circuits, we demonstrate that the choice between leaky integrate-and-fire (LIF) and quadratic integrate-and-fire (QIF) models to represent STN neurons fundamentally impacts the phase relationship between STN and external globus pallidus prototypical (Proto) neuron populations. QIF STN neurons establish in-phase coupling with Proto neurons, which enhances beta oscillation amplitude, while LIF STN neurons develop anti-phase relationships, which suppresses beta power. Through intervention experiments and parameter sweeps across physiologically relevant firing rates, we show that these phase-related effects persist robustly across network conditions, and we mathematically establish conditions under which these results are guaranteed to hold. Our findings reveal that the fundamental mathematical structure underlying spike generation, rather than other biophysical details, determines whether the subthalamopallidal loop acts as a beta amplifier or suppressor. This mechanistic insight reconciles contradictory findings in the literature, demonstrates that seemingly minor modeling choices can have profound consequences for understanding disease mechanisms and therapeutic targets, and offers predictions for determining which model framework reflects the biological reality. Author summarySubstantial work has explored the mechanisms underlying enhanced beta oscillations in the basal ganglia, motivated by their potential relevance to parkinsonian conditions and associated treatments. Often inferences about these mechanisms are based on simulations and reasoning that focus on features of network connectivity. We show that in fact the specific dynamical properties of the neurons in these circuits can strongly influence their emergent dynamics, with completely opposing effects arising in a given network structure depending on which neuron model is used, and we explain the factors underlying this divergence. Based on these factors, the determination of a small set of neuron properties in future biological experiments will lead to predictions about the mechanisms that can generate beta oscillations in the parkinsonian basal ganglia.

neuroscience↗

bioRxiv2022

Mechanisms regulating the frequency of inhibition-based gamma oscillations in primate prefrontal and parietal cortices

In primates, the dorsolateral prefrontal (DLPFC) and posterior parietal (PPC) cortices are critical nodes in the network mediating cognitive functions including attention and working memory. Notably, during working memory tasks, gamma oscillations, usually prominent in layer 3 (L3), are induced in both DLPFC and PPC but exhibit higher frequency in DLPFC. These oscillation frequency differences might be crucial for working memory function, but the mechanisms producing different oscillation frequencies in monkey DLPFC and PPC remain poorly understood. To investigate the basis of the DLPFC-PPC differences in oscillation frequency we studied GABAAR-mediated inhibition, which plays a crucial role in gamma oscillation production, in L3 pyramidal neurons (L3 PNs) from the rhesus monkey DLPFC or PPC. Recordings of GABAAR-mediated synaptic currents from L3 PNs, while suggesting a contribution to network synchronization in both areas, revealed no DLPFC-PPC differences in the strength or kinetics of GABAAR-mediated inhibition. Likewise, the expression of GABAAR genes in L3 PNs did not differ between regions. In the absence of differences in inhibition, DLPFC L3 PNs showed greater dendritic spine density and higher expression of AMPAR and NMDAR subunit genes relative to PPC L3 PNs, suggesting that the excitatory synaptic drive onto L3 PNs could be stronger in the DLPFC. Simulations in computational models of the cortical microcircuit showed that, with constant synaptic inhibition, increasing the strength of recurrent excitatory synaptic drive increased the network oscillation frequency. Hence, the DLPFC-PPC differences in gamma oscillation frequency could depend on stronger recurrent excitation in the DLPFC relative to PPC. Significance statementGamma oscillations may contribute to the neural substrate of working memory and exhibit a higher frequency in the prefrontal (DLPFC) than parietal (PPC) areas of primate cortex. To investigate the basis of these oscillation frequency differences which may be crucial for working memory encoding, we studied GABAAR-mediated inhibition on L3 pyramidal neurons (L3 PNs) from rhesus monkey DLPFC or PPC. Our data revealed no DLPFC-PPC differences in GABAAR-mediated inhibition but showed greater dendritic spine density in DLPFC L3 PNs, suggesting stronger excitatory synaptic drive. Simulations in computational network models showed that stronger recurrent excitatory synaptic drive increased the network oscillation frequency, suggesting that the higher oscillation frequency could depend on stronger recurrent excitation in the DLPFC relative to PPC.

neuroscience↗

bioRxiv2020

Kcns3 Deficiency Disrupts Parvalbumin Neuron Physiology in Mouse Prefrontal Cortex: Implications for the pathophysiology of schizophrenia

The unique fast spiking (FS) phenotype of cortical parvalbumin-positive (PV) neurons depends on multiple subtypes of voltage-gated potassium channels (Kv). PV neurons selectively express Kcns3, the gene encoding Kv9.3 subunits, suggesting that Kcns3 expression is critical for the FS phenotype. KCNS3 expression is lower in PV neurons in schizophrenia, but the effects of this alteration are unclear, because Kv9.3 subunit function is poorly understood. We therefore assessed the role of Kv9.3 subunits in PV neuron function by combining gene expression analyses, computational modeling, and electrophysiology in acute slices from the cortex of Kcns3-deficient mice Kcns3 mRNA levels were ~50% lower in cortical PV neurons from Kcns3-deficient relative to wildtype mice. While silent per se, Kv9.3 subunits are believed to amplify the Kv2.1 current in Kv2.1-Kv9.3 channel complexes. Hence, to assess the consequences of reducing Kv9.3 levels, we simulated the effects of decreasing the Kv2.1-mediated current in a computational model. The FS cell model with reduced Kv2.1 produced spike trains with irregular inter-spike intervals, or stuttering, and greater Na+ channel inactivation, possibly due to a smaller afterhyperpolarization. As in the computational model, PV basket cells (PVBCs) from Kcns3-deficient mice displayed spike trains with strong stuttering, which depressed PVBC firing, and smaller afterhyperpolarization. Moreover, Kcns3 deficiency impaired the recruitment of PVBCs by stimuli mimicking synaptic input during cortical UP states, which elicited bursts of spikes at gamma frequency. Our data suggest that Kv9.3 subunits are critical for PVBC physiology, and that KCNS3 deficiency in schizophrenia may impair the substrate of gamma oscillations. Significance statementIn the neocortex, Kcns3, the gene encoding voltage-dependent potassium (Kv) channel subunits Kv9.3, is selectively expressed by parvalbumin-positive (PV) neurons. Moreover, KCNS3 expression is decreased in PV neurons in schizophrenia. Kv 9.3 subunits are believed to amplify the current mediated by Kv2.1 subunits, however Kv9.3 function has not been investigated in PV cells. Here, simulations in a computational model and electrophysiological experiments with Kcns3-deficient mice revealed that Kcns3 deficiency disrupts repetitive firing in cortical PV neurons, possibly enhancing Na+ channel inactivation, and particularly with stimuli eliciting firing at gamma frequency band (30-80Hz). Our results suggest that Kv9.3 subunits are essential for PV neuron electrophysiology and that KCNS3 deficiency likely contributes to PV neuron dysfunction and gamma oscillation impairments in schizophrenia.

neuroscience↗

bioRxiv2020

Direction-selective motion discrimination by traveling waves in visual cortex

The majority of neurons in primary visual cortex respond selectively to bars of light that have a specific orientation and move in a specific direction. The spatial and temporal responses of such neurons are non-separable. How neurons accomplish that computational feat without resort to explicit time delays is unknown. We propose a novel neural mechanism whereby visual cortex computes non-separable responses by generating endogenous traveling waves of neural activity that resonate with the space-time signature of the visual stimulus. The spatiotemporal characteristics of the response are defined by the local topology of excitatory and inhibitory lateral connections in the cortex. We simulated the interaction between endogenous traveling waves and the visual stimulus using spatially distributed populations of excitatory and inhibitory neurons with Wilson-Cowan dynamics and inhibitory-surround coupling. Our model reliably detected visual gratings that moved with a given speed and direction provided that we incorporated neural competition to suppress false motion signals in the opposite direction. The findings suggest that endogenous traveling waves in visual cortex can impart direction-selectivity on neural responses without resort to explicit time delays. They also suggest a functional role for motion opponency in eliminating false motion signals. Author summaryIt is well established that the so-called simple cells of the primary visual cortex respond preferentially to oriented bars of light that move across the visual field with a particular speed and direction. The spatiotemporal responses of such neurons are said to be non-separable because they cannot be constructed from independent spatial and temporal neural mechanisms. Contemporary theories of how neurons compute non-separable responses typically rely on finely tuned transmission delays between signals from disparate regions of the visual field. However the existence of such delays is controversial. We propose an alternative neural mechanism for computing non-separable responses that does not require transmission delays. It instead relies on the predisposition of the cortical tissue to spontaneously generate spatiotemporal waves of neural activity that travel with a particular speed and direction. We propose that the endogenous wave activity resonates with the visual stimulus to elicit direction-selective neural responses to visual motion. We demonstrate the principle in computer models and show that competition between opposing neurons robustly enhances their ability to discriminate between visual gratings that move in opposite directions.

neuroscience↗