Degeneracy in epilepsy: multiple routes to hyperexcitable brain circuits and their repair

Stöber, Tristan M.; Batulin, Danylo; Triesch, Jochen; Narayanan, Rishikesh; Jedlicka, Paul

doi:10.1038/s42003-023-04823-0

Cited by 22 publications

(12 citation statements)

References 301 publications

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“…We compared our results with the experimental data of Šišková et al (2014), which showed a firing mode change from single spikes to bursting observed in APP/PS1 cells. Our results are largely in line with the concept of degeneracy (Edelman & Gally, 2001;Tononi et al, 1999), according to which similar physiological but also similar pathological states such as neural hyperexcitability can emerge from multiple distinct mechanisms (Kamaleddin, 2022;Medlock et al, 2022;Neymotin et al, 2016;O'Leary, 2018;Ratté & Prescott, 2016;Stöber et al, 2022).…”

Section: Introductionsupporting

confidence: 87%

“…Rich et al, 2022) and homeostasis. However, the homeostatic compensation might only be possible for a limited range of parameters or fail due to the complex interactions in the high-dimensional parameter space of the extrinsic and intrinsic neuronal mechanisms (O'Leary, 2018;Stöber et al, 2022;Yang et al, 2022). Even though the high-dimensional parameter space might offer more possible solutions for firing rate homeostasis (Schneider et al, 2021), these solutions might be difficult to find due to the necessary adjustment of several ion channels and/or extrinsic parameters for multiple properties at the same time (Yang et al, 2022; but see also Jedlicka et al, 2022).…”

Section: Limitations and Applicabilitymentioning

confidence: 99%

“…Paradoxically, in systems displaying multi-causality and degeneracy, repairing a single target mechanism may not be enough for restoring their normal excitability (Kamaleddin, 2022;Stöber et al, 2022). Compensatory effects and adaptations (O'Leary, 2018) and their variability in different individuals (Medlock et al, 2022;Onasch & Gjorgjieva, 2020;Sakurai et al, 2014) can sometimes impede mono-causal therapeutic options targeting a single mechanism (Ratté & Prescott, 2016;Ratté et al, 2014).…”

Section: Multiple Configurations Of Pathomechanisms Leading To Ad-rel...mentioning

confidence: 99%

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Modelling the contributions to hyperexcitability in a mouse model of Alzheimer's disease

Mittag

Mediavilla

Remy

et al. 2023

The Journal of Physiology

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Neuronal hyperexcitability is a pathological characteristic of Alzheimer's disease (AD). Three main mechanisms have been proposed to explain it: (i) dendritic degeneration leading to increased input resistance, (ii) ion channel changes leading to enhanced intrinsic excitability, and (iii) synaptic changes leading to excitation–inhibition (E/I) imbalance. However, the relative contribution of these mechanisms is not fully understood. Therefore, we performed biophysically realistic multi‐compartmental modelling of neuronal excitability in reconstructed CA1 pyramidal neurons from wild‐type and APP/PS1 mice, a well‐established animal model of AD. We show that, for synaptic activation, the excitability‐promoting effects of dendritic degeneration are cancelled out by decreased excitation due to synaptic loss. We find an interesting balance between excitability regulation and an enhanced degeneration in the basal dendrites of APP/PS1 cells, potentially leading to increased excitation by the apical but decreased excitation by the basal Schaffer collateral pathway. Furthermore, our simulations reveal three pathomechanistic scenarios that can account for the experimentally observed increase in firing and bursting of CA1 pyramidal neurons in APP/PS1 mice: scenario 1: enhanced E/I ratio; scenario 2: alteration of intrinsic ion channels (IAHP down‐regulated; INap, INa and ICaT up‐regulated) in addition to enhanced E/I ratio; and scenario 3: increased excitatory burst input. Our work supports the hypothesis that pathological network and ion channel changes are major contributors to neuronal hyperexcitability in AD. Overall, our results are in line with the concept of multi‐causality according to which multiple different disruptions are separately sufficient but no single particular disruption is necessary for neuronal hyperexcitability. Key points This work presents simulations of synaptically driven responses in pyramidal cells (PCs) with Alzheimer's disease (AD)‐related dendritic degeneration. Dendritic degeneration alone alters PC responses to layer‐specific input but additional pathomechanistic scenarios are required to explain neuronal hyperexcitability in AD as follows. Possible scenario 1: AD‐related increased excitatory input together with decreased inhibitory input (E/I imbalance) can lead to hyperexcitability in PCs. Possible scenario 2: changes in E/I balance combined with altered ion channel properties can account for hyperexcitability in AD. Possible scenario 3: burst hyperactivity of the surrounding network can explain hyperexcitability of PCs during AD.

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Section: Introductionsupporting

confidence: 87%

Section: Limitations and Applicabilitymentioning

confidence: 99%

Section: Multiple Configurations Of Pathomechanisms Leading To Ad-rel...mentioning

confidence: 99%

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Modelling the contributions to hyperexcitability in a mouse model of Alzheimer's disease

Mittag

Mediavilla

Remy

et al. 2023

The Journal of Physiology

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“…We found that LPG was not necessary to maintain coordination among gastric mill neurons and there was little difference in the timing relationships in the absence of LPG. Given the variability of the Gly 1 -SIFamide gastric mill rhythm, our analysis might not have been sensitive enough to detect changes in coordination in the absence of LPG, or there might be degeneracy such that other synapses contribute the same function as the LPG neurons (80, 81). However, when other chemical synapses among gastric mill neurons were blocked with picrotoxin, LPG fully coordinated the activity of the other gastric mill network neurons, but with different timing relationships.…”

Section: Discussionmentioning

confidence: 99%

“…Degeneracy also includes neuromodulatory actions, in which distinct modulators converge on the same ionic current to stabilize neuron bursting activity (5, 94–96). Furthermore, degeneracy of ion channels or synapses contributes to different mechanisms for the same motor pattern under different modulatory states (60, 61, 81). In the Gly 1 -SIFamide modulatory state, partial synaptic degeneracy among LG, IC, LPG, and DG neurons may be important for enabling the gastric mill network to carry out multiple coordination patterns.…”

Section: Discussionmentioning

confidence: 99%

Switching Neuron Contributions to Second Network Activity

Fahoum,

Blitz

2023

Preprint

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Network flexibility is important for adaptable behaviors. This includes neuronal switching, where neurons alter their network participation, including changing from single-to dual-network activity. Understanding the implications of neuronal switching requires determining how a switching neuron interacts with each of its networks. Here, we tested 1) whether “home” and second networks, operating via divergent rhythm generation mechanisms, regulate a switching neuron, and 2) if a switching neuron, recruited via modulation of intrinsic properties, contributes to rhythm or pattern generation in a new network. Small, well-characterized feeding-related networks (pyloric, ∼1 Hz; gastric mill, ∼0.1 Hz) and identified modulatory inputs make the isolated crab (Cancer borealis) stomatogastric nervous system (STNS) a useful model to study neuronal switching. In particular, the neuropeptide Gly1-SIFamide switches the lateral posterior gastric (LPG) neuron (2 copies) from pyloric-only to dual-frequency pyloric/gastric mill (fast/slow) activity via modulation of LPG intrinsic properties. Using current injections to manipulate neuronal activity, we found that gastric mill, but not pyloric, network neurons regulated the intrinsically generated LPG slow bursting. Conversely, selective elimination of LPG from both networks using photoinactivation revealed that LPG regulated gastric mill neuron firing frequencies but was not necessary for gastric mill rhythm generation or coordination. However, LPG alone was sufficient to produce a distinct pattern of network coordination. Thus, modulated intrinsic properties underlying dual-network participation may constrain which networks can regulate switching neuron activity. Further, recruitment via intrinsic properties may occur in modulatory states where it is important for the switching neuron to actively contribute to network output.New and NoteworthyWe used small, well-characterized networks to investigate interactions between rhythmic networks and neurons that switch their network participation. For a neuron switching into dual-network activity, only the second network regulated its activity in that network. Additionally, the switching neuron was sufficient but not necessary to coordinate second network neurons, and regulated their activity levels. Thus, regulation of switching neurons may be selective, and a switching neuron is not necessarily simply a follower in additional networks.

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The enigmatic HCN channels: A cellular neurophysiology perspective

Mishra,

Narayanan

2023

Proteins

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What physiological role does a slow hyperpolarization‐activated ion channel with mixed cation selectivity play in the fast world of neuronal action potentials that are driven by depolarization? That puzzling question has piqued the curiosity of physiology enthusiasts about the hyperpolarization‐activated cyclic nucleotide‐gated (HCN) channels, which are widely expressed across the body and especially in neurons. In this review, we emphasize the need to assess HCN channels from the perspective of how they respond to time‐varying signals, while also accounting for their interactions with other co‐expressing channels and receptors. First, we illustrate how the unique structural and functional characteristics of HCN channels allow them to mediate a slow negative feedback loop in the neurons that they express in. We present the several physiological implications of this negative feedback loop to neuronal response characteristics including neuronal gain, voltage sag and rebound, temporal summation, membrane potential resonance, inductive phase lead, spike triggered average, and coincidence detection. Next, we argue that the overall impact of HCN channels on neuronal physiology critically relies on their interactions with other co‐expressing channels and receptors. Interactions with other channels allow HCN channels to mediate intrinsic oscillations, earning them the “pacemaker channel” moniker, and to regulate spike frequency adaptation, plateau potentials, neurotransmitter release from presynaptic terminals, and spike initiation at the axonal initial segment. We also explore the impact of spatially non‐homogeneous subcellular distributions of HCN channels in different neuronal subtypes and their interactions with other channels and receptors. Finally, we discuss how plasticity in HCN channels is widely prevalent and can mediate different encoding, homeostatic, and neuroprotective functions in a neuron. In summary, we argue that HCN channels form an important class of channels that mediate a diversity of neuronal functions owing to their unique gating kinetics that made them a puzzle in the first place.

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Degeneracy in epilepsy: multiple routes to hyperexcitable brain circuits and their repair

Cited by 22 publications

References 301 publications

Modelling the contributions to hyperexcitability in a mouse model of Alzheimer's disease

Modelling the contributions to hyperexcitability in a mouse model of Alzheimer's disease

Switching Neuron Contributions to Second Network Activity

The enigmatic HCN channels: A cellular neurophysiology perspective

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