A5027042571- Neural dynamics and brain function
- Neuroscience and Neural Engineering
- EEG and Brain-Computer Interfaces
- Functional Brain Connectivity Studies
- Advanced Memory and Neural Computing
- Photoreceptor and optogenetics research
- Neural Networks and Applications
- Proteoglycans and glycosaminoglycans research
- Neuroscience and Neuropharmacology Research
- Animal Vocal Communication and Behavior
- Cell Image Analysis Techniques
- Advanced MRI Techniques and Applications
- Bioinformatics and Genomic Networks
- Receptor Mechanisms and Signaling
- Magnetic Field Sensors Techniques
- Plant and Biological Electrophysiology Studies
- Planarian Biology and Electrostimulation
- Optical Imaging and Spectroscopy Techniques
- 3D Printing in Biomedical Research
- Marine animal studies overview
- NMR spectroscopy and applications
- Bat Biology and Ecology Studies
- Ion channel regulation and function
- Power Transformer Diagnostics and Insulation
- stochastic dynamics and bifurcation
Norwegian University of Life Sciences
2015-2024
University of Life Sciences in Lublin
2024
University of Oslo
2019-2023
University of California, San Diego
2018
Identification of the cellular players and molecular messengers that communicate neuronal activity to vasculature driving cerebral hemodynamics is important for (1) basic understanding cerebrovascular regulation (2) interpretation functional Magnetic Resonance Imaging (fMRI) signals. Using a combination optogenetic stimulation 2-photon imaging in mice, we demonstrate selective activation cortical excitation inhibition elicits distinct vascular responses identify vasoconstrictive mechanism as...
Recordings of extracellular electrical, and later also magnetic, brain signals have been the dominant technique for measuring activity decades. The interpretation such is however nontrivial, as measured result from both local distant neuronal activity. In volume-conductor theory potentials can be calculated a distance-weighted sum contributions transmembrane currents neurons. Given same currents, to magnetic field recorded inside outside computed. This allows development computational tools...
Microelectrode arrays (MEAs), substrate-integrated planar of up to thousands closely spaced metal electrode contacts, have long been used record neuronal activity in vitro brain slices with high spatial and temporal resolution. However, the analysis MEA potentials has generally mainly qualitative. Here we use a biophysical forward-modelling formalism based on finite element method (FEM) establish quantitatively accurate links between neural slice recorded set-up. Then develop simpler...
The local field potential (LFP), the low-frequency part of extracellular potentials recorded in neural tissue, is often used for probing circuit activity. Interpreting LFP signal difficult, however. While cortical thought mainly to reflect synaptic inputs onto pyramidal neurons, little known about role various subthreshold active conductances shaping LFP. By means biophysical modelling we obtain a comprehensive qualitative understanding how generated by single neuron depends on type and...
Brain research investigating electrical activity within neural tissue is producing an increasing amount of physiological data including local field potentials (LFPs) obtained via extracellular in vivo and vitro recordings. In order to correctly interpret such electrophysiological data, it vital adequately understand the properties itself. An ongoing controversy neuroscience whether frequency-dependent effects bias LFP recordings affect proper interpretation signal. On macroscopic scales with...
Electroencephalography (EEG) and magnetoencephalography (MEG) are among the most important techniques for non-invasively studying cognition disease in human brain. These signals known to originate from cortical neural activity, typically described terms of current dipoles. While link between dipoles EEG/MEG is relatively well understood, surprisingly little about different kinds activity themselves. Detailed biophysical modeling has played an role exploring origin intracranial electric...
New, silicon-based multielectrodes comprising hundreds or more electrode contacts offer the possibility to record spike trains from thousands of neurons simultaneously. This potential cannot be realized unless accurate, reliable automated methods for sorting are developed, in turn requiring benchmarking data sets with known ground-truth times. We here present a general simulation tool computing evaluation spike-sorting algorithms entitled ViSAPy (Virtual Spiking Activity Python). The is...
Neural circuits typically consist of many different types neurons, and one faces a challenge in disentangling their individual contributions measured neural activity. Classification cells into inhibitory excitatory neurons localization on the basis extracellular recordings are frequently employed procedures. Current approaches, however, need lot human intervention, which makes them slow, biased, unreliable. In light recent advances deep learning techniques exploiting availability neuron...
To understand the neural basis of behavior, it is essential to sensitively and accurately measure activity at single neuron spike resolution. Extracellular electrophysiology delivers this, but has biases in neurons detects imperfectly resolves their action potentials. minimize these limitations, we developed a silicon probe with much smaller denser recording sites than previous designs, called Neuropixels Ultra (
In cortex, the local field potential (LFP) is thought to mainly stem from correlated synaptic input populations of geometrically aligned neurons. Computer models single cortical pyramidal neurons showed that subthreshold voltage-dependent membrane conductances can also shape LFP signal, in particular hyperpolarization-activated cation current (<i>I</i><sub>h</sub>; h-type). This ion channel prominent various types neurons, typically showing an increasing density gradient along apical...
The electroencephalogram (EEG) is a major tool for non-invasively studying brain function and dysfunction. Comparing experimentally recorded EEGs with neural network models important to better interpret in terms of mechanisms. Most current use networks simple point neurons. They capture properties cortical dynamics, are numerically or analytically tractable. However, neurons cannot generate an EEG, as EEG generation requires spatially separated transmembrane currents. Here, we explored how...
The EEG signal is generated by electrical brain cell activity, often described in terms of current dipoles. By applying forward models we can compute the contribution from such dipoles to potential recorded electrodes. Forward are key both for generating understanding and intuition about neural origin signals as well inverse modeling, i.e., estimation underlying dipole sources signals. Different varying complexity biological detail used field. One analytical model \emph{four-sphere model}...
Objective. Mechanistic modeling of neurons is an essential component computational neuroscience that enables scientists to simulate, explain, and explore neural activity. The conventional approach simulation extracellular recordings first computes transmembrane currents using the cable equation then sums their contribution model potential. This two-step relies on assumption space infinite homogeneous conductive medium, while measurements are performed probes. main purpose this paper assess...
The perineuronal nets (PNNs) are sugar coated protein structures that encapsulate certain neurons in the brain, such as parvalbumin positive (PV) inhibitory neurons. As PNNs theorized to act a barrier ion transport, they may effectively increase membrane charge-separation distance, thereby affecting capacitance. Tewari et al. (2018) found degradation of induced 25%-50% capacitance [Formula: see text] and reduction firing rates PV-cells. In current work, we explore how changes affects rate...
Abstract Neural activity at the population level is commonly studied experimentally through measurements of electric brain signals like local field potentials (LFPs), or electroencephalography (EEG) signals. To allow for comparison between observed and simulated neural it therefore important that simulations can accurately predict these Simulations often rely on point-neuron network models firing-rate models. While simplified representations are computationally efficient, they lack explicit...
Temporal analysis of sound is fundamental to auditory processing throughout the animal kingdom. Echolocating bats are powerful models for investigating underlying mechanisms temporal processing, as they show microsecond precision in discriminating timing acoustic events. However, neural basis discrimination has eluded researchers decades. Combining extracellular recordings midbrain inferior colliculus (IC) and mathematical modeling, we that registering stimulus events emerges from...
Genome-wide association studies have implicated many ion channels in schizophrenia pathophysiology. Although the functions of these are relatively well characterized by single-cell studies, contributions common variation to neurophysiological biomarkers and symptoms remain elusive. Here, using computational modeling, we show that a biomarker schizophrenia, namely, an increase delta-oscillation power, may be direct consequence altered expression or kinetics voltage-gated calcium transporters....
Simulations of neural activity at different levels detail are ubiquitous in modern neurosciences, aiding the interpretation experimental data and underlying mechanisms level cells circuits. Extracellular measurements brain signals reflecting transmembrane currents throughout tissue remain commonplace. The lower frequencies (≲ 300Hz) measured generally stem from synaptic driven by recurrent interactions among populations computational models should also incorporate accurate predictions such...
Most modeling in systems neuroscience has been descriptive where neural representations such as 'receptive fields', have found by statistically correlating activity to sensory input. In the traditional physics approach modelling, hypotheses are represented mechanistic models based on underlying building blocks of system, and candidate validated comparing with experiments. Until now validation cortical network comparison neuronal spikes, from high-frequency part extracellular electrical...
Abstract Three-dimensional cell technologies as pre-clinical models are emerging tools for mimicking the structural and functional complexity of nervous system. The accurate exploration phenotypes in engineered 3D neuronal cultures, however, demands morphological, molecular especially measurements. Particularly crucial is measurement electrical activity individual neurons with millisecond resolution. Current techniques rely on customized electrophysiological recording set-ups, characterized...