Biology subjects

Schleimer, J.-H.

Publications and source records attributed to Schleimer, J.-H..

8 recordsLinked to original sources

bioRxiv2025

Robustness through variability: ion channel isoform diversity safeguards neuronal excitability

Neural circuits are composed of different neuron types that exhibit distinctly different computational properties resulting from the sets of ion channels expressed. Profound insight exists into how neural computations arise from the precise regulation of ion channels (Armstrong et al., 1998; Lai, Jan, 2006; Nusser et al., 2012), how degenerate channel properties support similar computations (Marder, Prinz, 2002; Marder, Goaillard, 2006), and how channelopathies affect brain function (Kullmann, 2010). However, it remains elusive why neurons express many more channels, and isoforms thereof, than required to tune their specific excitabilities. Here, we employ an experiment-theory approach pairing electrophysiology with Drosophila genetics, and mathematical modelling to show that the variance in membrane properties that results from ion channel diversity promotes the robustness of neuron-type specific functions. Specifically, we show that the robustness of flight motoneuron coding properties to internal and external perturbations is significantly enhanced by the diversity of calcium channel splice isoforms expressed. Importantly, increased excitability robustness to perturbations of outward currents or temperature does not require adjustments in calcium channel mean properties. Instead, increases of the variance of calcium channel gating properties that result from channel isoform diversity broaden the dynamic input range the neuron can compute without reaching depolarization block. This broadens our concept of the functional consequences of the tremendous variety and diversity of ion channels expressed in brains. One Sentence SummaryThe variance of calcium channel gating properties is increased by channel isoform diversity and aids neuronal coding and excitability robustness.

neuroscience↗

bioRxiv2025

Integrate-and-fire neurons with potassium dynamics that capture switches in neuronal excitability class and firing regime

In conductance-based models, spiking-induced ion concentration fluctuations can alter the excitability of single neurons. In particular, in class I models, variations in potassium concentration can induce qualitative changes in the dynamics through a codimension-2 bifurcation known as the saddle-node-loop (SNL). Investigating the implications of such effects at the level of neuronal networks will require computationally efficient single neuron models that still capture ion concentration dynamics realistically. To this end, we propose a method to derive a phenomenological model capturing the coupled extracellular potassium and voltage dynamics of a given class I conductance-based model. Rather than fitting voltage traces, we calibrate a canonical reduced model to the two-parameter bifurcation structure of the target model, with input current and a physiological parameter as coordinates. This preserves the location and type of dynamical transitions as the physiological parameter varies, allowing a single reduced model to capture neuronal dynamics across qualitatively different regimes. The resulting model is an extension of the quadratic integrate-and-fire model, in which extracellular potassium accumulation alters voltage dynamics by increasing the reset voltage. We apply our systematic reduction procedure to the Wang-Buzsaki model. Its phenomenological version exhibits quantitatively comparable dynamics and replicates the reshaping of the phase-response curve associated with the transition from SNIC to HOM spikes at elevated potassium. To illustrate the derived model's applicability, we perform a preliminary investigation of how changes in potassium concentration influence synchronization in networks.

neuroscience↗

bioRxiv2025

Dynamically rich states in balanced networks induced by single-neuron dynamics

Network states with rich dynamics and highly variable firing rates of individual neurons are prominent in experimental observations and thought to benefit complex information processing and learning. Such states have been proposed to arise from properties of network coupling, like a strong connectivity or slow synaptic dynamics. Here, we identify an alternative mechanism based on weak synaptic coupling and intrinsic cellular dynamics. We show that a switch in the cellular excitability class of action-potential generation (via a switch in the underlying mathematical bifurcation), further amplified by recurrent interactions, results in super-Poissonian spiking variability in random balanced networks. Information encoding is shifted to higher frequency bands and collective chaos in the network is enhanced when intrinsic cellular dynamics follow a saddle homoclinic orbit (HOM) bifurcation. The robust effect links the biophysics of individual neurons to collective dynamics of large random networks, highlighting the relevance of single-cell dynamics for computation in physiological and artificial networks.

neuroscience↗

bioRxiv2024

The electrogenicity of the Na+/K+-ATPase poses challenges for computation in highly active spiking cells

1The evolution of the Na+/K+-ATPase laid the foundation for ion homeostasis and electrical signalling. While not required for restoration of ionic gradients, the electrogenicity of the pump (resulting from its 3:2 stoichiometry) is useful to prevent runaway activity. As we show here, electrogenicity could also come with disadvantageous side effects: (1) an activity-dependent shift in a cells baseline firing and (2) interference with computation, disturbing network entrainment when inputs change strongly. We exemplify these generic effects in a mathematical model of the weakly electric fish electrocyte, which spikes at hundreds of Hz and is exposed to abrupt rate changes when producing behaviorally-relevant communication signals. We discuss biophysical strategies that may allow cells to mitigate the consequences of electrogenicity at additional metabolic cost and postulate an interesting role for a voltage-dependence of the Na+/K+-ATPase. Our work shows that the pumps electrogenicity can open an additional axis of vulnerability that may play a role in brain disease.

neuroscience↗

bioRxiv2023

Slow rhythmic activity from an interplay of voltage and extracellular concentration dynamics: a minimal biophysical mechanism for neuronal bursting

Slow brain rhythms, for example during slow-wave sleep or pathological conditions like seizures and spreading depolarization, can be accompanied by synchronized oscillations in extracellular potassium concentration. Slow brain rhythms typically have longer periods than tonic action-potential firing. They are assumed to arise from network-level mechanisms, involving synaptic interactions and delays, or from intrinsically bursting neurons equipped with ion channels of slow dynamics. Here, we demonstrate that both mechanisms are not necessarily required and that slow rhythms can also be generated from an interplay of fast neuronal voltage dynamics and changes in extracellular ionic concentrations alone in any neuron with type excitability. The coupling of fast-spiking neuron dynamics and a slow extracellular potassium transient is regulated by the Na+/K+-ATPase. We use bifurcation analysis and the slow-fast method to reveal that this coupling suffices to generate a hysteresis loop organized around a bistable region that emerges from a saddle-node loop bifurcation - a common feature of type excitable neurons. Moreover, the Na+/K+-ATPase not only plays a key role in burst generation by shearing the bifurcation diagram but also modulates tonic spiking and depolarization block by its density and pump rate. These dynamics of bursting, tonic spiking and depolarization block, accompanied by the fluctuation of extracellular potassium, are likely to be relevant for pathological conditions. We suggest that these dynamics can result from any disturbance in extracellular potassium regulation, such as glial malfunction or hypoxia. The identification of a minimal mechanistic requirement for producing these dynamics adds to a better understanding of pathologies in brain rhythms may direct attention to alternative pharmacological targets for therapy. Author SummaryThe brain can produce slow rhythms, such as those observed during sleep or epilepsy. These rhythms are much slower than the neuronal electrical signals, and their origins are still under debate. Mechanisms discussed so far are based on the connection delays in neural networks or on neuronal ion channels with particularly slow kinetics. We show that neurons with specific spiking dynamics - allowing them to fire at arbitrarily low frequencies (type neurons) - can produce slow rhythmic patterns without requiring synaptic connectivity or special ion channels. In these cells, slow rhythmic activity arises from the interplay of slow changes in extracellular potassium concentration and the cells voltage dynamics, mediated by the Na+/K+-ATPase pump. The latter, found in all neurons, regulates the concentrations of sodium and potassium ions across the cell membrane. The core mechanism is not idiosyncratic, rather mathematical analysis shows under which conditions slow rhythmic activity can arise generically from the pump-based coupling in a broad class of neurons. We demonstrate that the pump is relevant for the creation of different firing patterns, which can be associated with various diseases. A better understanding these complex dynamics is important for the development of more effective treatments for concentration-dependent pathologies.

neuroscience↗

bioRxiv2022

Insect asynchronous flight requires neural circuit de-synchronization by electrical synapses

Despite profound mechanistic insight into motor pattern generation, for asynchronous insect flight - the most prevalent form of flight employed by >600.000 species - architecture and function of the underlying central pattern generating (CPG) neural network remain elusive. Combining electro- and optophysiology, Drosophila genetics, and mathematical modelling, we uncover a miniaturized circuit solution of motoneurons interconnected by electrical synapses that, contrary to doctrine, serve to de-synchronize network activity. This minimal gap-junctional motoneuron network suffices to translate unpatterned premotor input into stereotyped firing sequences which are conserved across species and generate stable wingbeat power. Mechanistically, network de-synchronization requires weak electrical coupling in conjunction with specific postsynaptic excitability dynamics, revealing an unexpected, generic feature in the control of neural circuit dynamics by electrical synapses. One Sentence SummaryElectrical synapses de-synchronize neural network firing to enable stable wingbeat power during insect flight.

neuroscience↗

bioRxiv2021

A dynamic clamp protocol to artificially modify cell capacitance

AO_SCPLOWBSTRACTC_SCPLOWDynamics of excitable cells and networks depend on the membrane time constant, set by membrane resistance and capacitance. Whereas pharmacological and genetic manipulations of ionic conductances are routine in electrophysiology, experimental control over capacitance remains a challenge. Here, we present capacitance clamp, an approach that allows to mimic a modified capacitance in biological neurons via an unconventional application of the dynamic clamp technique. We first demonstrate the feasibility to quantitatively modulate capacitance in a mathematical neuron model and then confirm the functionality of capacitance clamp in in vitro experiments in granule cells of rodent dentate gyrus with up to threefold virtual capacitance changes. Clamping of capacitance thus constitutes a novel technique to probe and decipher mechanisms of neuronal signaling in ways that were so far inaccessible to experimental electrophysiology.

neuroscience↗

bioRxiv2020

Activity-mediated accumulation of potassium induces a switch in firing pattern and neuronal excitability type

During normal neuronal activity, ionic concentration gradients across a neurons membrane are often assumed to be stable. Prolonged spiking activity, however, can reduce transmembrane gradients and affect voltage dynamics. Based on mathematical modeling, we investigated the impact of neuronal activity on ionic concentrations and, consequently, the dynamics of action potential generation. We find that intense spiking activity on the order of a second suffices to induce changes in ionic reversal potentials and to consistently induce a switch from a regular to an intermittent firing mode. This transition is caused by a qualitative alteration in the systems voltage dynamics, mathematically corresponding to a co-dimension-two bifurcation from a saddle-node on invariant cycle (SNIC) to a homoclinic orbit bifurcation (HOM). Our electrophysiological recordings in mouse cortical pyramidal neurons confirm the changes in action potential dynamics predicted by the models: (i) activity-dependent increases in intracellular sodium concentration directly reduce action potential amplitudes, an effect typically attributed solely to sodium channel inactivation; (ii) extracellular potassium accumulation switches action potential generation from tonic firing to intermittently interrupted output. Thus, individual neurons may respond very differently to the same input stimuli, depending on their recent patterns of activity and/or the current brain-state. Author summaryIonic concentrations in the brain are not constant. We show that during intense neuronal activity, they can change on the order of seconds and even switch neuronal spiking patterns under identical stimulation from a regular firing mode to an intermittently interrupted one. Triggered by an accumulation of extracellular potassium, such a transition is caused by a specific, qualitative change in of the neuronal voltage dynamics - a so-called bifurcation - which affects crucial features of action-potential generation and bears consequences for how information is encoded and how neurons behave together in the network. Also, changes in intracellular sodium can induce measurable effects, like a shrinkage of spike amplitude that occurs independently of the fast amplitude-effects attributed to sodium channel inactivation. Taken together, our results demonstrate that a neuron can respond very differently to the same stimulus, depending on its previous activity or the current brain state. This finding may be particularly relevant when other regulatory mechanisms of ionic homeostasis are challenged, for example, during pathological states of glial impairment or oxygen deprivation. Finally, Categorization of cortical neurons as intrinsically bursting or regular spiking may be biased by the ionic concentrations at the time of the observation, highlighting the non-static nature of neuronal dynamics.

neuroscience↗