1 h 8 min
On the purpose and origin of spontaneous neural activity
Neuroscience, Biophysics, Computational Neuroscience and seminar by Prof. Tim Vogels, IST Austria
Hosted by NYU Swartz
Friday 02:00–03:10 New York (GMT-4)
Recording available
Recording
Abstract
Spontaneous firing, observed in many neurons, is often attributed to ion channel or network level noise. Cortical cells during slow wave sleep exhibit transitions between so called Up and Down states. In this sleep state, with limited sensory stimuli, neurons fire in the Up state. Spontaneous firing is also observed in slices of cholinergic interneurons, cerebellar Purkinje cells and even brainstem inspiratory neurons. In such in vitro preparations, where the functional relevance is long lost, neurons continue to display a rich repertoire of firing properties. It is perplexing that these neurons, instead of saving their energy during information downtime and functional irrelevance, are eager to fire. We propose that spontaneous firing is not a chance event but instead, a vital activity for the well-being of a neuron. We postulate that neurons, in anticipation of synaptic inputs, keep their ATP levels at maximum. As recovery from inputs requires most of the energy resources, neurons are ATP surplus and ADP scarce during synaptic quiescence. With ADP as the rate-limiting step, ATP production stalls in the mitochondria when ADP is low. This leads to toxic Reactive Oxygen Species (ROS) formation, which are known to disrupt many cellular processes. We hypothesize that spontaneous firing occurs at these conditions - as a release valve to spend energy and to restore ATP production, shielding the neuron against ROS. By linking a mitochondrial metabolism model to a conductance-based neuron model, we show that spontaneous firing depends on baseline ATP usage and on ATP-cost-per-spike. From our model, emerges a mitochondrial mediated homeostatic mechanism that provides a recipe for different firing patterns. Our findings, though mostly affecting intracellular dynamics, may have large knock-on effects on the nature of neural coding. Hitherto it has been thought that the neural code is optimised for energy minimisation, but this may be true only when neurons do not experience synaptic quiescence.
Topics
Show 1 more topic
Related seminars
Combining two mechanisms to produce neural firing rate homeostasis
Video · 1 h 7 min · Jun 11, 2021Paul Miller, Brandeis UniversityWhen spontaneous waves meet angiogenesis: a case study from the neonatal retina
Video · 1 h 3 min · Oct 12, 2020Evelyne Sernagor, Newcastle University
More from NYU Swartz
All talksLearning representations of specifics and generalities over time
Apr 12, 2024Anna SchapiroRoles of inhibition in stabilizing and shaping the response of cortical networks
Apr 5, 2024Nicolas BrunelVisual mechanisms for flexible behavior
Jan 26, 2024Marlene CohenNeuronal population interactions between brain areas
Dec 8, 2023Byron Yu
More with Tim Vogels
All their workOn co-dependent excitatory and inhibitory plasticity - with Tim Vogels - #30
Episode · Jul 19, 2025Theoretical Neuroscience PodcastOn neuro-AI on the boat - part 2 of 2 - with Cristina Savin, Tim Vogels, Mikkel Lepperød, Paul Middlebrooks - #20
Episode · Oct 11, 2024Theoretical Neuroscience PodcastDopamine dysregulation in Parkinson's Disease
ePoster · Sep 29, 2024Bernstein Conference 2024Knocking out co-active plasticity rules in neural networks reveals synapse type-specific contributions for learning and memory
ePoster · Sep 29, 2024Bernstein Conference 2024