Carmen C. Canavier

Pacemaking neurons, often found in mammalian nervous systems, integrate their inputs differently than quiescent neurons. Rhythmic single-spike pacemaking that is robust to noise can be achieved with a slow process that enforces a “resting potential” at each point along a ramp-like interspike interval (ISI) coupled with a fast restorative component. To demonstrate this phenomenon, we modeled previously identified distinct subpopulations of midbrain dopamine neurons that differed in projection target and in the regularity of their pacemaking. In the model of the more regularly-firing subpopulation projecting to the dorsomedial striatum, K _V 4 current was recruited by a deep after-hyperpolarizing potential (AHP) mediated by the SK channel. In the model of the less regularly-firing subpopulation projecting to the medial shell of the nucleus accumbens, the AHP was too shallow to recruit the K _V 4 current. In the more regularly firing population, the trajectory in the phase space of membrane potential and slow inactivation of K _V 4 was confined to move slowly through a narrow channel during the ramp-like portion of the ISI. Noisy perturbations from this channel were quickly damped by fast activation of K _V 4. In contrast, the smaller AHP in the model of the subpopulation projecting to the medial shell of the nucleus accumbens failed to recruit Kv4-mediated current, therefore the narrow channel was never entered, greatly decreasing the regularity in the presence of noise. This mechanism may be broadly applicable to single-spike pacemakers and explains how slow pacemaking with small net currents can be robust to fluctuations in single channel openings. Author Summary: Pacemaking cells spike at regular intervals without the need for external input. There are numerous examples of pacemaking cells in the nervous system. We show that a process with slow dynamics relative to the individual spikes can make regular pacemaking robust to the noise that is always present in biological systems.

Dopamine neurons projecting to distinct brain regions have unique biophysical properties, which are thought to reflect functional specialization. One of these defining properties is the duration of hyperpolarization-induced firing pauses, or rebound delays, which are longer in atypical dopamine neurons targeting ventromedial striatal areas like the nucleus accumbens core. Differences in rebound delay are determined by Kv4 channel-mediated A-type currents, but the mechanisms underlying these differences and their functional implications are not well understood. We hypothesized that KChIP4a, a unique Kv4 β-subunit splice variant, determines rebound delay duration in atypical dopamine neurons. To test this, we generated a transgenic mouse line with dopamine neuron-selective removal of KChIP4a. We found that KChIP4a deletion shortened rebound delays in core-projecting atypical dopamine neurons by changing A-type current kinetics, without affecting conventional dopamine neurons. This indicates that KChIP4a acts as a selective biophysical amplifier of hyperpolarizing inhibition in core-projecting dopamine neurons, and computational modeling suggests that this effect is robust across a wide range of in vivo-like conditions for excitation/inhibition balance. Since firing pauses in core-projecting dopamine neurons are thought to drive learning from reward omission, or negative prediction errors, we tested the effect of KChIP4a deletion on different types of behavior in male and female mice. We found that removal of KChIP4a from dopamine neurons selectively accelerated learning from negative prediction errors, without affecting learning from positive prediction errors or other behavioral variables. Together, our results suggest that KChIP4a fine-tunes subthreshold excitability in projection-defined dopamine neuron populations to regulate specific types of learning.

Previously, electrophysiological differences between subpopulations of midbrain dopamine (DA) neurons were identified based on projection targets, including distinct responses to hyperpolarization and in the regularity of pacemaking. Here we explored single-compartment models of three subpopulations of DA neurons, projecting to medial shell of the nucleus accumbens (VTA-mNAcc), dorsomedial striatum (SNc-DMS) or dorsolateral striatum (SNc-DLS). We reduced the dimensionality to a phase plane consisting of membrane potential and one slow variable, either total slow potassium conductance or Kv4 channel inactivation. Nullclines are curves on which the rate of change of each variable is zero, given the value of the other variable. The voltage nullclines had three branches: upper spiking, unstable middle, and lower quiescent branch. Recruitment of Kv4 channels by the more prominent after-hyperpolarizing potential (AHP) in the DA-DMS and DA-DLS models channels stabilized pacemaking by creating a restorative moving fixed point along the quiescent branch. The slow inactivation of KV4 channels dominated and regularized the dynamics during the interspike interval; a dominant slow process may be a general mechanisn for stable regular pacemaking in a frequency range between 1-10 Hz. In contrast, the smaller AHP in VTA-mNAcc models prevented recruitment of this Kv4-mediated moving fixed point, which increased the sensitivity to synaptic inputs. On rebound from hyperpolarization the ability to produce robust ramps reverses between the DA neurons: now VTA-mNAcc projecting DA models fully recruited Kv4 channels and produced stable ramp-like pauses, whereas SNc-DLS projecting cells recruited significant regenerative inward CaV3 channels that overwhelmed Kv4 channels and produced ‘rebound’ bursts. Author Summary: Midbraim dopamine (DA) neurons in the mammalian midbrain are linked to motivation, control of voluntary movement initiation, and reward-based learning. Their dysfunction is implicated in major disorders like Parkinson’s disease, schizophrenia or substance use disorders. Firing patters like bursts or pauses in most DA subpopulations are thought to signal better or worse than expected outcomes. Here we use dynamic systems analysis to capture how functional diversity of DA neurons of their intrinsic properties results in differences of synaptic input integration leading to the generation of burst and pause patterns of electrical activity.

Gamma oscillations (40–140 Hz) play a fundamental role in neural coordination and cognitive functions in the medial entorhinal cortex (mEC). While previous studies suggest that pyramidal–interneuron network gamma (PING) and interneuron network gamma (ING) mechanisms contribute to these oscillations, the precise role of inhibitory circuits remains unclear. Using optogenetic stimulation and whole-cell electrophysiology in acute mouse brain slices, we examined synaptic input and spike timing in neurons across layer II/III mEC. We found that fast-spiking interneurons exhibited robust gamma-frequency firing, while excitatory neurons engaged in gamma cycle skipping. Stellate and pyramidal cells received minimal recurrent excitation, whereas fast-spiking interneurons received strong excitatory input. Both excitatory neurons and fast-spiking interneurons received gamma-frequency inhibition, emphasizing the role of recurrent inhibition in gamma rhythms. Gamma activity was reduced but persisted after AMPA/kainate receptor blockade, indicating that interneurons can sustain oscillations via an ING mechanism. Selective activation of PV+ interneurons confirmed their ability to sustain fast gamma inhibition autonomously. To further assess the interplay of excitation and inhibition, we developed computational network models constrained by our experimental data. Simulations revealed that weak excitatory input to interneurons supports fast ING-dominated rhythms (∼100–140 Hz) while strengthening excitatory drive induces a transition to slower PING-dominated oscillations (60–100 Hz), although this regime shift was not observed consistently after AMPA/kainate receptor block. These findings highlight the dominant role of inhibitory circuits in sustaining gamma rhythms, demonstrate how excitation strength tunes the oscillatory regime, and refine models of entorhinal gamma oscillations critical for spatial memory processing.

Dopamine (DA) midbrain neurons are involved in a wide array of key brain functions including movement control and reward-based learning. They are also critical for major brain disorders such as Parkinson’s disease or schizophrenia. DA neurons projecting to distinct striatal territories are diverse with regard to their molecular makeup and cellular physiology, which are likely to contribute to the observed differences in temporal DA dynamics. Among these regions, the dorsolateral striatum (DLS) displays the fastest DA dynamics, which might control the moment-to-moment vigor and variability of voluntary movements. However, the underlying mechanisms for these DLS-specific fast DA fluctuations are unresolved. Here, we show that DLS-projecting DA neurons in the substantia nigra (SN) possess a unique biophysical profile allowing immediate 10-fold accelerations in discharge frequency via rebound bursting. By using a combination of in vitro patch-clamp recordings in projection-defined DA SN subpopulations from adult male mice and developing matching projection-specific computational models, we demonstrate that a strong interaction of Ca _v 3 and SK channels specific for DLS-projecting Aldh1a1–positive DA SN (DLS-DA) neurons controls the gain of fast rebound bursting, while K _v 4 and HCN channels mediate timing of rebound excitability. In addition, GIRK channels activated by D2 and GABA _B receptors prevent rebound bursting in these DLS-DA neurons. Furthermore, our in vivo patch-clamp recordings and matching in vivo computational models provide evidence that these unique rebound properties might be preserved in the intact brain, where they might endow specific computational properties well suited for the generation of fast DA dynamics present in DLS.

Gamma oscillations (40–140 Hz) play a fundamental role in neural coordination, facilitating communication and cognitive functions in the medial entorhinal cortex (mEC). While previous studies suggest that pyramidal-interneuron network gamma (PING) and interneuron network gamma (ING) mechanisms contribute to these oscillations, the precise role of inhibitory circuits remains unclear. Using optogenetic stimulation and whole-cell electrophysiology in acute mouse brain slices, we examined synaptic input and spike timing in neurons across layer II/III mEC. We found that fast-spiking interneurons exhibited robust gamma-frequency firing, while excitatory neurons engaged in gamma cycle skipping. Stellate and pyramidal cells received minimal recurrent excitation, whereas fast-spiking interneurons received strong excitatory input. Both excitatory neurons and fast-spiking interneurons received gamma frequency inhibition, emphasizing the role of recurrent inhibition in gamma rhythm generation. Notably, gamma activity was reduced, but persisted after AMPA/kainate receptor blockade, indicating that interneurons can sustain gamma oscillations independently through an ING mechanism. Selective activation of PV+ interneurons confirmed their ability to sustain fast gamma inhibition autonomously. To further assess the interplay of excitation and inhibition, we developed computational network models constrained by our experimental data. Simulations revealed that weak excitatory input to interneurons supports fast ING-dominated rhythms (∼100–140 Hz), while strengthening excitatory drive induces a transition to slower PING-dominated oscillations (60–100 Hz). These findings highlight the dominant role of inhibitory circuits in sustaining gamma rhythms, demonstrate how excitation strength tunes the oscillatory regime, and refine models of entorhinal gamma oscillations critical for spatial memory processing. Significance Statement: Gamma oscillations in the medial entorhinal cortex (mEC) are essential for spatial navigation and memory, yet the mechanisms underlying their generation remain unresolved. Combining optogenetics, whole-cell electrophysiology, and computational modeling, we show that fast-spiking interneurons can autonomously sustain gamma rhythms via interneuron network gamma (ING). Blocking excitatory input reduced, but did not abolish gamma-frequency inhibition, and selective activation of PV+ interneurons confirmed their capacity to generate fast gamma independently. Modeling revealed that excitatory strength tunes the oscillatory regime, with weak excitation favoring fast ING and stronger excitation inducing slower pyramidal-interneuron network gamma (PING). These findings refine entorhinal gamma models and suggest a hybrid mechanism for switching between faster and slower gamma critical for spatial computation.

A mean field theory for synchrony in neural networks in which neurons are generally above threshold in the mean-driven regime is developed to extend and complement mean field theory previously developed by others for neurons that are generally below threshold in the fluctuation-driven regime. This work extends phase response curve theory as applied to high-frequency oscillations in networks with synaptic inputs that are not short with respect to the network period.

A mean field method for pulse-coupled oscillators with delays used a self-connected oscillator to represent a synchronous cluster of N-1 oscillators and a single oscillator assumed to be perturbed from the cluster. A periodic train of biexponential conductance input was divided into a tonic and a phasic component representing the mean field input. A single cycle of the phasic conductance from the cluster was applied to the single oscillator embedded in the tonic component at different phases to measure the change in the cycle length which the perturbation was initiated, that is, the first order phase response curve (PRC), and the second order PRC in the following cycle. A homogeneous network of 100 biophysically calibrated inhibitory interneurons with either shunting or hyperpolarizing inhibition tested the predictive power of the method. A self-consistency criterion predicted the oscillation frequency of the network from the PRCs as a function of the synaptic delay. The major determinant of the stability of synchrony was the sign of the slope of the first order PRC of the single oscillator in response to an input from the self-connected cluster at a phase corresponding to the delay value. For most short delays, first order PRCs correctly predicted the frequency and stability of simulated network activity. However, considering the second order PRC improved the frequency prediction and resolved an incorrect prediction of stability of global synchrony at delays close to the free running period of single neurons in which a discontinuity in the PRC precluded existence of 1:1 self-locking.

Persistent activity in excitatory pyramidal cells (PYRs) is a putative mechanism for maintaining memory traces during working memory. We have recently demonstrated persistent interruption of firing in fast-spiking parvalbumin-expressing interneurons (PV-INs), a phenomenon that could serve as a substrate for persistent activity in PYRs through disinhibition lasting hundreds of milliseconds. Here, we find that hippocampal CA1 PV-INs exhibit type 2 excitability, like striatal and neocortical PV-INs. Modeling and mathematical analysis showed that the slowly inactivating potassium current K_V1 contributes to type 2 excitability, enables the multiple firing regimes observed experimentally in PV-INs, and provides a mechanism for robust persistent interruption of firing. Using a fast/slow separation of times scales approach with the K_V1 inactivation variable as a bifurcation parameter shows that the initial inhibitory stimulus stops repetitive firing by moving the membrane potential trajectory onto a coexisting stable fixed point corresponding to a nonspiking quiescent state. As K_V1 inactivation decays, the trajectory follows the branch of stable fixed points until it crosses a subcritical Hopf bifurcation (HB) and then spirals out into repetitive firing. In a model describing entorhinal cortical PV-INs without K_V1, interruption of firing could be achieved by taking advantage of the bistability inherent in type 2 excitability based on a subcritical HB, but the interruption was not robust to noise. Persistent interruption of firing is therefore broadly applicable to PV-INs in different brain regions but is only made robust to noise in the presence of a slow variable, K_V1 inactivation.