Biology subjects

Ron, S.

Publications and source records attributed to Ron, S..

4 recordsLinked to original sources

bioRxiv2024

Effective excitability captures network dynamics across development and phenotypes

Neuronal cultures in vitro are a versatile system for studying the fundamental properties of individual neurons and neuronal networks. Recently, this approach has gained attention as a precision medicine tool. Mature neuronal cultures in vitro exhibit synchronized collective dynamics called network bursting. If analyzed appropriately, this activity could offer insights into the networks properties, such as its composition, topology, and developmental and pathological processes. A promising method for investigating the collective dynamics of neuronal networks is to map them onto simplified dynamical systems. This approach allows the study of dynamical regimes and the characteristics of the parameters that lead to data-consistent activity. We designed a simple biophysically inspired dynamical system and used Bayesian inference to fit it to a large number of recordings of in vitro population activity. Even with a small number of parameters, the model showed strong inter-parameter dependencies leading to invariant bursting dynamics for many parameter combinations. We further validated this observation in our analytical solution. We found that in vitro bursting can be well characterized by each of three dynamical regimes: oscillatory, bistable, and excitable. The probability of finding a data-consistent match in a particular regime changes with network composition and development. The more informative way to describe the in vitro network bursting is the effective excitability, which we analytically show to be related to the parameter-invariance of the models dynamics. We establish that the effective excitability can be estimated directly from the experimentally recorded data. Finally, we demonstrate that effective excitability reliably detects the differences between cultures of cortical, hippocampal, and human pluripotent stem cell-derived neurons, allowing us to map their developmental trajectories. Our results open a new avenue for the model-based description of in vitro network phenotypes emerging across different experimental conditions.

neuroscience↗

bioRxiv2024

Small animal brain surgery with neither a brain atlas nor a stereotaxic frame

Stereotaxic surgery is a cornerstone in brain research for the precise positioning of electrodes and probes, but its application is limited to species with available brain atlases and tailored stereotaxic frames. Addressing this limitation, we introduce an alternative technique for small animal brain surgery that requires neither an aligned brain atlas nor a standard stereotaxic frame. This method requires a high-contrast MRI scan of a specimen and access to a microCT scanner. The process involves attaching miniature markers to the skull, followed by CT scanning of the head. Subsequently, MRI and CT images are co-registered using standard image processing software and the targets for recordings in the brain are marked in the MRI image. During surgery, the animals head is stabilized in any convenient orientation, and the probes 3D position and angle are tracked using a multi-camera system. We have developed a software that utilizes the on-skull markers as fiducial points to align the CT/MRI 3D model with the surgical positioning system, and in turn instructs the surgeon how to move the probe to reach the targets within the brain. Our technique allows the execution of insertion tracks connecting two points in the brain. We successfully applied this method for neuropixels probe positioning in owls, quails, and mice, demonstrating its versatility and its potential to open new avenues for research in non-standard and novel animal models.

neuroscience↗

bioRxiv2024

Ribonanza: deep learning of RNA structure through dual crowdsourcing

Prediction of RNA structure from sequence remains an unsolved problem, and progress has been slowed by a paucity of experimental data. Here, we present Ribonanza, a dataset of chemical mapping measurements on two million diverse RNA sequences collected through Eterna and other crowdsourced initiatives. Ribonanza measurements enabled solicitation, training, and prospective evaluation of diverse deep neural networks through a Kaggle challenge, followed by distillation into a single, self-contained model called RibonanzaNet. When fine tuned on auxiliary datasets, RibonanzaNet achieves state-of-the-art performance in modeling experimental sequence dropout, RNA hydrolytic degradation, and RNA secondary structure, with implications for modeling RNA tertiary structure.

biophysics↗

bioRxiv2020

Head-Direction Coding in the Hippocampal Formation of Birds

Birds strongly rely on spatial memory and navigation. Therefore, it is of utmost interest to reveal how space is represented in the avian brain. Here we used tetrodes to record neurons from the hippocampal formation of Japanese quails - a ground-dwelling species - while the quails roamed a 1x1-meter arena (>2,100 neurons from 23 birds). Whereas spatially-modulated cells (place-cells, border-cells, etc.) were generally not encountered, the firing-rate of 12% of the neurons was unimodally and significantly modulated by the head-azimuth - i.e. these were head-direction cells (HD cells). Typically, HD cells were maximally active at one preferred-direction and minimally at the opposite null-direction, with preferred-directions spanning all 360{degrees}. The HD tuning was relatively broad (mean width [~]130{degrees}), independent of the animals position and speed, and was stable during the recording-session. Similarly to findings in rodents, the HD tuning usually rotated with the rotation of a salient visual cue in the arena. These findings support the existence of an allocentric head-direction representation in the quail hippocampal formation, and provide the first demonstration of head-direction cells in birds.

neuroscience↗