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1

To LFP or to CSD? – That is the question

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Czerwinski M. B., Kowalska M., Chintaluri C. H., Wojcik D. K.
Acta Neurobiologiae Experimentalis
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2017
|
tom 77
|
nr Suppl.1
INTRODUCTION: Current Source Density (CSD) is spatially smoothed transmembrane activity of the neurons. Local Field Potential (LFP) is the electric potential generated by ionic currents in the neural tissue and it is directly related to the CSD. LFP is relatively easily accessible experimentally but due to the long range of electric field, it is difficult to interpret. CSD needs to be calculated but it reflects the local neural activity directly. Since the currents directly reflect neuronal computations, using electric potentials (LFP’s) to infer performed computation may lead to misinterpretations. AIM(S): 1) Discuss challenges arising in multielectrode LFP and CSD analysis, in particular case where direct analysis of LFPs can lead to misinterpretation. 2) Show that the kernel Current Source Density reconstruction method (kCSD) gives a better insight into the underlying phenomena than the observed potentials, and to show the limits and uncertainties yielded by the method. 3) Present the kCSD-python toolbox for CSD analysis. METHOD(S): All of the modeling and computations was done in Python and tested on model data. Potentials were calculated using assumed physical models of tissue. The kCSD library in Python is available at: https://github.com/ Neuroinflab/kCSD‑python. RESULTS: We show examples where the LFP’s can ‘hide’ more complex underlying CSD patterns and how the kCSD can reconstruct those sources, depending on the number and configuration of recording electrodes. CONCLUSIONS: Complex CSD patterns studied at the resolution of few electrodes can be obscured if only direct LFP analysis is used. The kCSD method can help to recover them. The main limiting factors are the number of recording electrodes and their configuration. FINANCIAL SUPPORT: This work was supported by EC-FP7-PEOPLE sponsored NAMASEN Marie-Curie ITN grant 264872, Polish Ministry for Science and Higher Education grant 2948/7.PR/2013/2, Narodowe Centrum Nauki grants 2013/08/W/NZ4/00691 and 2015/17/B/ ST7/04123.
2

New insight into kernel current source density reconstruction

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Kowalska M., Czerwinski M. B., Chintaluri C. H., Wojcik D. K.
Acta Neurobiologiae Experimentalis
|
2017
|
tom 77
|
nr Suppl.1
INTRODUCTION: The low-frequency part of extracellular potential, called the Local Field Potential (LFP), is a useful measure of neural systems activity. However, a direct interpretation of LFP is problematic as it is not a local measure – each electrode may record activity observed millimeters away from source. Estimation of current source density (CSD), the volume density of net transmembrane currents, has become a convenient way to deal with this problem. AIM(S): The aim of the study is to investigate the properties of kCSD method to develop a procedure which will facilitate optimal usage of the presented method in complicated experimental scenarios, for complex measurement setups etc. METHOD(S): In the study we use kCSD method which estimates the sources in a family of allowed CSD distributions of dimensionality larger than the number of measurements. To identify the parameters of the method leading to optimal source estimation, a statistical technique of cross-validation is used. We perform this study using Python programming language with several types of known (model) reference data and different electrodes setups. We employ singular value decomposition (SVD) method to study the internal properties of kCSD reconstruction. RESULTS: To examine the influence of the measurement setup on the reconstruction capability of the kCSD method we performed simulated study. We present error maps of CSD estimation which give us valuable insight into kCSD reconstruction quality. CONCLUSIONS: The quality of CSD estimation significantly depends on the measurement setup. This study enables the researchers to check how much they can trust the obtained kCSD reconstruction for a given setup and specific collection of recordings. FINANCIAL SUPPORT: This work was supported by EC-FP7-PEOPLE sponsored NAMASEN Marie-Curie ITN grant 264872, Polish Ministry for Science and Higher Education grant 2948/7.PR/2013/2, Narodowe Centrum Nauki grants 2013/08/W/NZ4/00691 and 2015/17/B/ST7/04123.
3

DAT1 gene, ADHD, and the development of attentional functions

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Cybulska-Klosowicz A., Kuc K., Bielecki M., Racicka-Pawlukiewicz E., Czerwinski M. B.
Acta Neurobiologiae Experimentalis
|
2019
|
tom 79
|
nr Suppl.1
INTRODUCTION: Neuropharmacological and human clinical studies have suggested that the dopaminergic system of the brain is substantively involved in normal and pathological phenotypes of attention. Dopamine transporter gene (DAT1) was proposed as a candidate gene for Attention‑Deficit/Hyperactivity Disorder (ADHD). AIM(S): To investigate the effect of the DAT1 gene on performance in the several attentional tasks. METHOD(S): ADHD and healthy children and teenagers aged 9 – 16 were evaluated using tests and procedures involving attentional switching, selective and sustained attention (Test of Everyday Attention, TEA-Ch and Sustained Attention to Response Test, SART), and also three attentional networks – alerting, orienting, and executive attention (Attention Network Test, ANT). DAT1 polymorphism analysis was performed by polymerase chain reaction on saliva samples provided by subjects. ADHD children performed significantly worse in comparison to healthy controls in most of the tasks, demonstrating deficits in various attention processes which were persistent within the examined age range. The results showed an effect of improvement in almost all indices of attentional processes with increasing age in both ADHD and control groups. RESULTS: The results revealed a significant main effect of DAT1 genotype for switching, wherein subjects carrying the 9R allele displayed worse performance in comparison to children with 10R/10R and 10R/11R genotypes. A similar effect of genotype was observed for orienting, which was not disturbed in ADHD subjects. No association between ADHD and the DAT1 polymorphism, and no interaction of DAT1 genotype and ADHD diagnosis were found. CONCLUSIONS: DAT1 is associated with attentional switching and orienting. ADHD is associated with deficits in primary functions that are distinct from those associated with the DAT1 gene polymorphism. FINANCIAL SUPPORT: This research was supported by National Science Centre Poland Grants 2011/01/D/ NZ4/04958 and 2015/17/N/HS6/03020.
4

Spatial distribution of light evoked currents in ChR2-transfected rat’s cortex

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Kublik E., Skladowska A., Czerwinski M. B., Pasierski M., Wojcik D. K.
Acta Neurobiologiae Experimentalis
|
2017
|
tom 77
|
nr Suppl.1
INTRODUCTION: Optogenetics allows to stimulate selected neuronal populations with high temporal resolution but the spatio‑temporal extent of resulting effects is not well characterized. AIM(S): Experiment were aimed to evaluate spatial distribution of the potentials and currents evoked by light impulses in the channelrhodopsin-transfected rat cortex. METHOD(S): Rats were injected with viral vector introducing ChR2 into large portion of somatosensory cortex. 2–3 weeks later we performed acute in vivo experiments recording multichannel local field potentials evoked (EP) by a blue light delivered either to the cortical surface (surf-stim) or into the cortex (deep-stim). We analyzed spatio-temporal patterns of EPs and their 2-D current source density (CSD) profiles (kernel CSD method, https://github. com/Neuroinflab/kCSD‑python). RESULTS: Our preliminary results indicated that light evoked potentials consisted of early waves, resulting from opening ChR2 channels, overlapping with later components related to the synaptic spread of activity within cortical network. As expected, largest EPs were recorded close to the fiber tip, in layer 2–3 with surf‑stim and layer 5 with deep-stim. Longer impulses (10 ver 1 ms) evoked around 20% stronger responses. Up to 600–800 µm from a light source EPs sustained ~50% of max amplitude. However, CSD analysis indicated that after surf-stim the early current sink (1–2 ms) was restricted to ~400 µm in layer 2–3. Later, postsynaptic sink developed at 5–8 ms in layer 5. Later components had wider lateral spread across few columns with clear reflection of cortical layering. After intra-cortical light delivery activity seemed to spread within, not across the cortical columns. CONCLUSIONS: For well controlled use of optogenetics it is not enough to ensure light beam of sufficient strength. The localization of the fiber tip can have specific impact on the activity developing within local neuronal network. FINANCIAL SUPPORT: Supported by Polish National Science Centre grant 2013/08/W/NZ4/00691.
5

Kernel current source density revisited

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Chintaluri C., Kowalska M., Czerwinski M. B., Sredniawa W., Jedrzejewska-Szmek J., Dzik J. M., Wojcik D. K.
Acta Neurobiologiae Experimentalis
|
2019
|
tom 79
|
nr Suppl.1
INTRODUCTION: Extracellular recordings reflect transmembrane currents of neural and glial cells and thus have long been the foundation of measurements of neural activity. Recorded potential reflects activity of the underlying neural network and is directly related to the distribution of current sources along the active cells (current source density, CSD). The long‑range of the electric field leads to significant correlations between recordings at distant sites, which complicates the analysis. However, data interpretation can be facilitated by reconstruction of current sources. AIM(S): Facilitate reconstruction of sources of brain activity with open software. METHOD(S): The Kernel Current Source Density method (KCSD) is a general non-parametric framework for CSD estimation based on kernel techniques, which are widely used in machine‑learning. KCSD allows for current source estimation from potentials recorded by arbitrarily distributed electrodes. Overfitting is prevented by constraining complexity of the inferred CSD model. RESULTS: Here, we revisit KCSD to present a new, open-source implementation in the form of a package, which includes new functionality and several additional tools for kCSD analysis and for validation of the results of analysis accompanied by extensive tutorials implemented in Jupyter notebook. Specifically, we have added 1) analysis of spectral properties of the method; 2) error map generation for assessment of reconstruction accuracy; and 3) L‑curve, a method for estimation of optimum reconstruction parameters. The new implementation allows for CSD reconstruction from potentials measured by 1D, 2D, and 3D experimental setups for a) sources distributed in the entire tissue, b) in a slice, or c) in a single cell with known morphology, provided that the potential is generated by that cell. CONCLUSIONS: New Python implementation of kCSD facilitates CSD analysis and allows for estimation of errors. The toolbox and tutorials are available at https:// github.com/Neuroinflab/kCSD‑python.
6

Microelectronic system for low-artifact electrical stimulation and recording of brain activity at up to 512 electrodes

52%
Szypulska M., Wiacek P., Skoczen A., Ahmed I., Futowski T., Jurgielewicz P., Kolodziej K., Czerwinski M. B., Wojcik D. K., Mindur B., Kublik E., Dabrowski W., Hottowy P.
Acta Neurobiologiae Experimentalis
|
2019
|
tom 79
|
nr Suppl.1
INTRODUCTION: We present a novel microelectronic system for in vivo stimulation and recording of neuronal activity. The system is intended for use with multielectrode silicon probes and is based on a dedicated 64‑channel CMOS chip. It can generate complex sequences of microstimulation pulses and simultaneously record (with low artifacts) neuronal responses at up to 512 electrodes. The system is compatible with most silicon probes used in the brain research and can use up to four probes in parallel, providing bidirectional communication with populations of neurons simultaneously in several brain areas. Each channel of the chip includes a recording amplifier and a stimulation circuit. The amplifier has adjustable gain (110‑550x), low cut‑off frequency (1.4‑7 Hz), and anti‑aliasing filter frequency (1.2‑14 kHz). The input‑referred noise is 6.8 µV. Signals from all the channels are digitized at 40 kHz. The stimulation signal is defined independently for each channel with 40 kHz refresh rate. The stimulation artifacts are reduced by temporally disconnecting the amplifiers from electrodes and optimization of the pulse waveform. METHOD(S): The system has been tested in experiments exploring somatosensory thalamo-cortical network in rodents. 2‑3 weeks before surgery, animals received injections of AAV‑hSyn‑ChR2‑EYFP viral vector. In anesthetized animals, multichannel probes were inserted into the barrel cortex and/or sensory thalamus for recording of LFPs and multi-unit responses to microstimulation delivered to various nodes of thalamo‑cortical network. Electrically evoked activity was compared with responses to natural whisker deflection and optical stimulation. RESULTS: The reported system can generate complex patterns of stimulation pulses and record neuronal signals with very low artifacts at up to 512 electrodes, making it a powerful tool for mapping of the functional connections between brain circuits. FINANCIAL SUPPORT: Supported by Polish National Science Centre grant 2013/08/W/NZ4/00691.
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