Biology subjects

Pettersen, K. H.

Publications and source records attributed to Pettersen, K. H..

3 recordsLinked to original sources

bioRxiv2021

Validating a computational framework for ionicelectrodiffusion with cortical spreading depression as a case study

Cortical spreading depression (CSD) is a wave of pronounced depolarization of brain tissue accompanied by substantial shifts in ionic concentrations and cellular swelling. Here, we validate a computational framework for modelling electrical potentials, ionic movement, and cellular swelling in brain tissue during CSD. We consider different model variations representing wild type or knock-out/knock-down mice and systematically compare the numerical results with reports from a selection of experimental studies. We find that the data for several CSD hallmarks obtained computationally, including wave propagation speed, direct current shift duration, peak in extracellular K+ concentration as well as a pronounced shrinkage of extracellular space, are well in line with what has previously been observed experimentally. Further, we assess how key model parameters including cellular diffusivity, structural ratios, membrane water and/or K+ permeabilities affect the set of CSD characteristics. Significance StatementMovement of ions and molecules in and between cellular compartments is fundamental for brain function. Cortical spreading depression (CSD) is associated with dramatic failure of brain ion homeostasis. Better understanding the sequence of events in CSD could thus provide new insight into physiological processes in the brain. Despite extensive experimental research over the last decades, even basic questions related to mechanisms underlying CSD remain unanswered. Computational modelling can play an important role going forward, since simulation studies can address hypotheses that are difficult to target experimentally. Here, we assess the physiological validity of a novel mathematical framework for detailed modelling of brain electrodiffusion and osmosis - and provide a platform for in silico studies of CSD and other cerebral electro-mechanical phenomena.

neuroscience↗

bioRxiv2020

RippleNet: A Recurrent Neural Network for Sharp Wave Ripple (SPW-R) Detection

Hippocampal sharp wave ripples (SPW-R) have been identified as key bio-markers of important brain functions such as memory consolidation and decision making. SPW-R detection typically relies on hand-crafted feature extraction, and laborious manual curation is often required. In this multidisciplinary study, we propose a novel, self-improving artificial intelligence (AI) method in the form of deep Recurrent Neural Networks (RNN) with Long Short-Term memory (LSTM) layers that can learn features of SPW-R events from raw, labeled input data. The algorithm is trained using supervised learning on hand-curated data sets with SPW-R events. The input to the algorithm is the local field potential (LFP), the low-frequency part of extracellularly recorded electric potentials from the CA1 region of the hippocampus. The output prediction can be interpreted as the time-varying probability of SPW-R events for the duration of the input. A simple thresholding applied to the output probabilities is found to identify times of events with high precision. The reference implementation of the algorithm, named RippleNet, is open source, freely available, and implemented using a common open-source framework for neural networks (tensorflow.keras) and can be easily incorporated into existing data analysis workflows for processing experimental data.

neuroscience↗

bioRxiv2019

Ca2+ signaling in astrocytes is sleep-wake state specific and modulates sleep

Astrocytic Ca2+ signaling has been intensively studied in health and disease but remains uncharacterized in sleep. Here, we employed a novel activity-based algorithm to assess astrocytic Ca2+ signals in the barrel cortex of awake and naturally sleeping mice while monitoring neuronal Ca2+ activity, brain rhythms and behavior. We discovered that Ca2+ signaling in astrocytes exhibits distinct features across the sleep-wake cycle and is reduced in sleep compared to wakefulness. Moreover, an increase in astrocytic Ca2+ signaling precedes transitions from slow-wave sleep to wakefulness, with a peak upon awakening exceeding the levels during whisking and locomotion. Genetic ablation of a key astrocytic Ca2+ signaling pathway resulted in fragmentation of slow-wave sleep, yet increased the frequency of sleep spindles. Our findings suggest a role for astrocytic Ca2+ signaling in modulating sleep.

neuroscience↗