Biology subjects

Gidon, A.

Publications and source records attributed to Gidon, A..

6 recordsLinked to original sources

bioRxiv2026

Dendrite Control Theory: A Unifying Framework Bridging Neuronal Morphology And Dendritic Voltage Behavior

Control theory and dendritic computation have revolutionized their respective fields, yet they rarely converge. Here, we use control theory as a framework to reveal how dendritic morphology and synaptic input organization constrain structural resilience and energy cost. Treating diverse dendritic trees as connected network nodes, we demonstrate that the degree of structural symmetry dictates easy- versus hard-to-access control states. Notably, control inputs restricted solely to peripheral terminal branches are mathematically sufficient to govern the voltage states of the entire dendrite and soma, granting striking resilience against input loss elsewhere. Conversely, limiting input dimensionality amplifies voltage fluctuations and metabolic costs. These findings expose fundamental biophysical trade-offs between wiring cost, functional flexibility, robustness, and energy efficiency, suggesting interneurons generally exhibit higher resilience while excitatory neurons feature superior controllability. We introduce 'Dendrite Control Theory' as a rigorous engineering framework linking neuronal morphology directly to computation and robustness, offering a new neuroscience research paradigm.

neuroscience↗

bioRxiv2024

High-speed three-dimensional random access scanning with SPARCLS

High-speed volumetric imaging is crucial for observing fast and distributed processes such as neuronal activity. Multiphoton microscopy helps to mitigate scattering effects inside tissue, but the standard raster scanning approach limits achievable volume rates. Random-access scanning can lead to a considerable speed-up by sampling only pre-selected locations, but existing techniques based on acousto-optic deflectors are still limited to a point rate of up to [~]50 kHz. This limits the number of parallel targets at the high acquisition rates necessary, for example, in voltage imaging or imaging of fast synaptic events. Here we introduce SPARCLS, a method for 3D random-access scanning at up to 340 kHz point rate using a single 1D phase modulator. We show the potential of this method by imaging synaptic events with fluorescent glutamate sensors in mammalian organotypic slices as well as in zebrafish larvae.

neuroscience↗

bioRxiv2022

Pyruvate supports RET-dependent mitochondrial ROS production necessary to control Mycobacterium avium infection in human primary macrophages

Macrophages deploy a variety of antimicrobial programs to contain mycobacterial infection. Upon activation, they undergo extensive metabolic reprogramming to meet an increase in energy demand, but also to support immune effector functions such as secretion of cytokines and antimicrobial activities. Here, we report that mitochondrial import of pyruvate is linked to production of mitochondrial ROS and control of Mycobacterium avium infection in human primary macrophages. Using chemical inhibition, targeted mass spectrometry and single cell image analysis, we show that macrophages infected with M. avium switched to aerobic glycolysis without any major imbalances in the tricarboxylic acid cycle or changes in the energy charge. Instead, we found that pyruvate import contributed to hyperpolarization of mitochondria in infected cells and increased production of mitochondrial reactive oxygen species by the complex I via reverse electron transport, which reduced the macrophage burden of M. avium. While mycobacterial infections are extremely difficult to treat and notoriously resistant to antibiotics, this work stresses out that compounds specifically inducing mitochondrial reactive oxygen species could present themself as valuable adjunct treatments.

immunology↗

bioRxiv2021

Biological complexity facilitates tuning of the neuronal parameter space

The electrical and computational properties of neurons in our brains are determined by a rich repertoire of membrane-spanning ion channels and elaborate dendritic trees. However, the precise reason for this inherent complexity remains unknown. Here, we generated large stochastic populations of biophysically realistic hippocampal granule cell models comparing those with all 15 ion channels to their reduced but functional counterparts containing only 5 ion channels. Strikingly, valid parameter combinations in the full models were more frequent and more stable in the face of perturbations to channel expression levels. Scaling up the numbers of ion channels artificially in the reduced models recovered these advantages confirming the key contribution of the actual number of ion channel types. We conclude that the diversity of ion channels gives a neuron greater flexibility and robustness to achieve target excitability. Significance statementOver the course of billions of years, evolution has led to a wide variety of biological systems. The emergence of the more complex among these seems surprising in the light of the high demands of searching for viable solutions in a correspondingly high-dimensional parameter space. In realistic neuron models with their inherently complex ion channel composition, we find a surprisingly large number of viable solutions when selecting parameters randomly. This effect is strongly reduced in models with fewer ion channel types but is recovered when inserting additional artificial ion channels. Because concepts from probability theory provide a plausible explanation for this improved distribution of valid model parameters, we propose that this may generalise to evolutionary selection in other complex biological systems. In briefStudying ion channel diversity in neuronal models we show how robust biological systems may evolve not despite but because of their complexity. HighlightsO_LI15 channel model of hippocampal granule cells (GCs) reduces to 5 ion channels without loss of spiking behaviour. C_LIO_LIBut knocking out ion channels can be compensated only in the full model. C_LIO_LIRandom sampling leads to ~ 6% solutions in full but only ~ 1% in reduced model. C_LIO_LILaw of large numbers generalises our observations to other complex biological systems. C_LI

neuroscience↗

bioRxiv2021

Burst coding despite unimodal interval distributions

The burst coding hypothesis posits that the occurrence of sudden high-frequency patterns of action potentials constitutes a salient syllable of the neural code. Many neurons, however, do not produce clearly demarcated bursts, an observation invoked to rule out the pervasiveness of this coding scheme across brain areas and cell types. Here we ask how identifiable spike-timing patterns have to be to preserve potent transmission of information. Should we expect that neurons avoid ambiguous patterns that are neither clearly bursts nor isolated spikes? We addressed these questions using information theory and computational simulations. By quantifying how information transmission depends on firing statistics, we found that the information transmitted is not strongly influenced by the presence of clearly demarcated modes in the interspike interval distribution, a feature often used to identify the presence of burst coding. Instead, we found that neurons having unimodal interval distributions were still able to ascribe different meanings to bursts and isolated spikes. In this regime, information transmission depends on properties of the synapses as well as the length and relative frequency of bursts. Furthermore, we found that common metrics used to quantify burstiness were also unable to predict the degree with which bursts could be used to carry information. Our results provide guiding principles for the implementation of coding strategies based on spike-timing patterns, and show that even unimodal firing statistics can be consistent with a bivariate neural code.

neuroscience↗

bioRxiv2020

Mitochondrial dysfunction in skeletal muscle of fukutin deficient mice is resistant to exercise- and AICAR-induced rescue

Disruptions in the dystrophin-glycoprotein complex (DGC) are clearly the primary basis underlying various forms of muscular dystrophies and dystroglycanopathies, but the cellular consequences of DGC disruption are still being investigated. Mitochondrial abnormalities are becoming an apparent consequence and contributor to dystrophy disease pathology. Herein, we demonstrate that muscle-specific deletion of the fukutin gene [Myf5/fktn-KO mice (KO)], a model of secondary dystroglycanopathy, results in ~30% lower muscle strength (P<0.001) and 16% lower mitochondrial function (P=0.002) compared to healthy littermate controls (LM). We also observed ~80% lower PGC-1 signaling (P=0.004), a primary transcription factor for mitochondrial biogenesis, in KO mice that likely contributes to the mitochondrial defects. PGC-1 is post-translationally regulated via phosphorylation by AMPK. Treatment with the AMPK agonist AICAR (5-aminoimidazole-4-carboxamide ribonucleotide) failed to rescue mitochondrial deficits in KO mice (P=0.458) but did have beneficial (~30% greater) effects on recovery of muscle contractility following injury in both LM and KO mice compared to saline treatment (P=0.006). The beneficial effects of AMPK stimulation via AICAR on muscle function may be partially explained by AMPKs other role of regulating skeletal muscle autophagy, a cellular process critical for clearance of damaged and/or dysfunctional organelles. Two primary conclusions can be drawn from this data, 1) fukutin deletion produces intrinsic muscular metabolic defects that likely contribute to dystroglycanopathy disease pathology, and 2) AICAR treatment accelerates recovery of muscle function following injury suggesting AMPK signaling as a possible target for therapeutic strategies.

physiology↗