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1

A framework for analysis of mice behavior in Pytho

100%
Leski S.
Acta Neurobiologiae Experimentalis
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2014
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tom 74
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nr 3
An abundance of behavioral data can be obtained with the IntelliCage system. Basic analysis of the data can be performed with a tool provided with the system, however more advanced analyses have to be performed manually. One of disadvantages of manual analysis is its extreme unefficiency since it requires significant effort. Another disadvantage is that it is vulnerable to human errors. The analysis process can be easily automated with a programmable workflow. In this approach a researcher focuses his (or her) effort to design the workflow and let the computer do the work in which it performs better (in aspect of speed, precision and robustness) than a human. Once the workflow has been defined it is possible to reproduce the analysis on data acquired from other application of the experimental protocol facilitating reproducible research. A possibility of convenient access to data is crucial for programming a workflow. To facilitate it we are developing a Python framework which allows for easy loading of recorded data as well as accessing it in an intuitive manner. With the framework we develop a methodology for advanced analysis of these data. Developed analysis methods are being included into the framework providing its users with a powerful tool for their scientific work.
2

Quantitative analysis of shapes of dendritic spines

100%
Leski S.
Acta Neurobiologiae Experimentalis
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2015
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tom 75
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nr Supl.
Dendritic spines are targets of excitatory synaptic inputs. The morphology of a spine is linked to its function. For example, a mature dendritic spine resembles a mushroom, with a wide spine head connected to the dendrite by much thinner neck. Several studies link dimensions of that mushroom to the functioning of the synapse, for example it has been shown that the amplitude of uncaging potential at the soma correlates with spine head volume and negatively correlates with spine neck length. To study the shapes of dendritic spines quantitatively we have developed a set of computational methods for analysis of microscopy images of individual spines. The first method allows for semi-automatic classification of spine shapes in a dataset. First, spine shapes are grouped in an unsupervised way (that is, without assuming any a priori structure of the dataset) using a clustering algorithm. Then the groups can be manually segragated according to criteria set by the researcher. The second method has been designed to automatically measure dimensions of heads and necks of spines in large datasets. The idea is to first represent the shape of a spine as a sum of  building blocks: an ellipsoid for the spine head, a cylinder for the spine neck, and possibly a cone for the part of the spine closest to the dendrite. Then widths and lengths of heads and necks can be defined based on dimensions of the fitted blocks. As an example we show the results of application of these methods to a large collection of dendritic spine shapes – several thousands of individual spines – obtained from confocal microscopy images.
3

Source reconstructin methods in analysis of multielectrode recordings

100%
Leski S.
Acta Neurobiologiae Experimentalis
|
2011
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tom 71
|
nr S
Local field potentials (LFP), the low-frequency part of the extracellular electric potentials, reflect dynamics of the brain at the population level. Because of technological advances it is now feasible to record LFP at tens of locations simultaneously. The interpretation of these signals is complicated by the fact that the electric signals propagate in the tissue, and the signal recorded at each position may have contributions from neurons located more than a millimeter away. Therefore it is useful to estimate and analyze the current source density (CSD), the volume density of transmembrane currents which generate the observed LFP. In the past few years new methods for CSD estimation has been developed, such as the inverse CSD, based on the inversion of the forward-modeling scheme, or the kernel CSD, which employs kernel techniques used in machine learning. I will review these methods and the available software tools.
4

Linking extracellular electric potential in the brain to neural activity - a review of source localization and component identification methods

100%
Leski S.
Acta Neurobiologiae Experimentalis
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2015
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tom 75
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nr 2
Due to technological advances in electrophysiology, there is renewed interest in the analysis of local field potentials recorded at many sites simultaneously. In this paper the main problems related to the analysis of LFP are presented, and recent developments in the data analysis methods are reviewed. The focus of the paper is on reconstruction of current source density from extracellular recordings and on decomposition of neural activity into meaningful components.
5

Morphological changes of CA1 and CA3 pyramidal neurons in rat hippocampal slice cultures following TTYH1 overexpression

51%
Gorniak-Walas M., Kaliszewska A., Leski S., Lukasiuk K.
Acta Neurobiologiae Experimentalis
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2017
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tom 77
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nr Suppl.1
INTRODUCTION: Tweety homolog1 (Ttyh1) is a presumed volume-regulated Cl-channel. It has been proposed to participate in the regulation of neuronal morphology. AIM(S): We aimed to examine dendritic arborization and spine morphology of pyramidal neurons following TTYH1 overexpression in organotypic hippocampal cultures. METHOD(S): Rat organotypic cultures were co-transfected with TTYH1‑GFP‑Synapsin and RFP‑β‑actin constructs, using biolistic transfection (Gene-Gun, BioRad). Neuronal reconstructions of CA1 and CA3 pyramidal cells were obtained with confocal microscopy and Neuromantic software. Morphometric assessments of individual neurons were performed with Sholl method. L-measure software was used to extract more complex quantitative measurements from neuronal reconstructions. Changes in spine morphology and density on CA1 and CA3 neurons were studied with SpineMagick software. RESULTS: Sholl method did not reveal signifficant differences in dendritic arborization of neurons overexpressing TTYH1 compared to control neurons. L-measure revealed that CA3 neurons overexpressing TTYH1 showed increased average branch length in the seventh branch order of apical dendrites (P<0.05) and increased number of branches in the third branch order of basal dendrites (P<0.01). CA1 pyramidal neurons overexpressing TTYH1 showed reduced average branch length in the third (P<0.05) and fourth (P<0.001) branch orders of basal dendrites. TTYH1 overexpression led to increased number of stubby spines on CA1 neurons (apical proximal and distal dendrites: P<0.01; basal dendrites: P<0.05) and CA3 neurons (apical proximal dendrites: P<0.01). Decrease in the number of long spines on CA1 neurons (apical proximal and distal dendrites: P<0.01) and CA3 neurons was confirmed (apical proximal dendrites: P<0.05). CONCLUSIONS: The influence of TTYH1 overexpression on dendritic complexity and spines morphology suggests that TTYH1 protein may be involved in neuronal plasticity. FINANCIAL SUPPORT: This research was supported by Polish National Science Centre Grant 2011/03/B/ NZ4/00302.
6

Dissecting activity of individual cell populations with kernel current source density method and independent components analysis

51%
Wojcik D. K., Potworowski J., Glabska H., Leski S.
Acta Neurobiologiae Experimentalis
|
2012
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tom 72
|
nr 2
Local field potentials (LFP), the low-frequency part of extracellular electric potential, reflect dendritic processing of synaptic inputs to neuronal populations. Today one can easily record simultaneous potentials from multiple contacts. Due to the nature of electric field each electrode may record activity of sources millimeters away which leads to significant correlations between signals and complicates their analysis. Whenever possible it is convenient to estimate the current source density (CSD), the volume density of net transmembrane currents, which generate the LFP. CSD directly reflects the local neural activity and CSD analysis is often used to analyze LFP. We present here a general, nonparametric method for CSD estimation based on kernel techniques, which can take into account known anatomy or physiology of the studied structure. Using data from a simulated large scale model of thalamo-cortical column we also show how CSD analysis combined with independent component analysis (ICA) can reveal information on activity of individual cell populations. Research supported by grants 5428/B/P01/2010/39, POIG.02.03.00- 00-003/09, POIG.02.03.00-00-018/08.
7

Highly replicable, fully automated measures of perseverative behaviors in Intellicage system

51%
Puscian A., Leski S., Romanowska A., Knapska E.
Acta Neurobiologiae Experimentalis
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2013
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tom 73
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nr Suppl.1
Perseveration, defined as resistance to change in routine and repetitive behaviors, is one of the core symptoms of Autism Spectrum Disorders. It was proposed that an inability to break habits, experienced by autistic people, corresponds, in animal models, to impaired performance in the learning tasks that assess ability to change a response strategy to obtain reinforcement. However, the results of conventional behavioral tests can be confounded by anxiety related to handling and social isolation. In order to avoid such effects and to analyze phenotypes of subjects in an efficient manner, we developed a battery of automated tests aimed at appraising behavioral flexibility in mice. The tests were performed in the IntelliCage (IC), a computer-controlled system, which can be used for long-term monitoring of group-housed animals. These tests allow for measuring of exploration patterns, pace and progress of appetitive and reversal learning. To standardize and evaluate the relevant IC tests, we compared valproate treated and control animals from two inbred strains of mice, C57BL/6 and BALB/c. We show that tested mice differ significantly in most of the examined parameters. The obtained results are highly replicable between tested cohorts of subjects, thereby allowing us to infer, that the reported battery of automated behavioral and cognitive tests is a valuable tool in verifying suitability of mouse models of ASD symptoms.
8

Integration of multiple-whisker stimulation in rat barrel cortex

51%
Kaminski J., Kublik F., Leski S., Wrobel A.
Acta Neurobiologiae Experimentalis
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2009
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tom 69
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nr 3
The vibrissal system of rodents has become one of the dominant models for investigating the mechanisms of sensory information processing. However, the mechanisms underlying integration of multiple whisker input is not well understood. To address this question, we recorded local fi eld potentials (LFP) from the barrel cortex in of anaesthetised rat. Recording points were distributed on the 4 × 22 grid covering two neighbouring cortical columns and septa between them. Potentials evoked (EP) by defl ection of single whiskers and sets of three whiskers (within arc and/or row) were analysed by two dimensional current source density method (2D CSD). The multiple whisker response was compared to linear predictor, defi ned as a sum of corresponding single whiskers responses. CSD performed on the data revealed signifi cant differences between linear prediction and multiple whisker defl ection. Multiple input responses had lower amplitudes as compared to linear prediction condition. The earliest differences were observed in infra- and supragranular layer approximately 8 ms after stimulation. Differences in granular layer appeared 10 ms after stimulation. Our data suggest that supra- and infra granular layers are involved in initial phase of the integration of multiple whisker inputs.
9

Translational regulation of matrix metalloproteinase 9 mRNA at the synapse

45%
Dziiembowska M., Milek J., Jasinska M., Leski S., Kaczmarek L.
Acta Neurobiologiae Experimentalis
|
2015
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tom 75
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nr Supl.
BACKGROUND AND AIMS: Matrix metalloproteinase 9 (MMP-9) is locally translated in dendrites in response to synaptic stimulation. Its enzymatic activity at the synapse is involved in the reorganization of spine architecture and was shown to regulate spine morphology in Fragile X syndrome (FXS) which is caused by the loss of mental retardation protein (FMRP). Application of MMP-9 on neurons in culture induces formation of filopodia-like immature dendritic spines that resembles these in FXS. Furthermore, inhibiting MMP-9 activity by application of minocycline, the tetracycline analogue, to Fmr1 KO mice can rescue the abnormal spine phenotype both in vivo and in cultured neurons. Deregulation of local protein synthesis at the synapse contributes to spine dysmorphogenesis and synaptic dysfunction in patients with the Fragile X Syndrome. RESULTS: Here we show that MMP-9 mRNA is a specific target of FMRP and that FMRP regulates its transport and translation at the synapse. In the absence of FMRP MMP-9 mRNA translation is increased and this causes an excess of active MMP-9 protein at synapses leading to the abnormal spine morphology. Moreover our results indicate that synaptic translation of MMP-9 can be regulated by microRNAs. CONCLUSIONS: Our data support a model in which synaptic MMP-9 mRNA is translationally regulated by FMRP and microRNAs. We propose that the regulation of synaptic MMP-9 mRNA translation can contribute to the aberrant spine morphology observed in patients with FXS.
10

Really reproducible behavioural paper

45%
Dzik J. M., Puscian A., Harda Z., Radwanska K., Leski S.
Acta Neurobiologiae Experimentalis
|
2017
|
tom 77
|
nr Suppl.1
INTRODUCTION: The reproducibility of behavioural tests has been improved by the introduction of a number of automated experimental systems. One of such systems is IntelliCage™, which allows for sophisticated experimental designs. Despite the improved reproducibility of experiments, reported results may be rendered irreproducible due to errors introduced by manual data analysis and not standardized reporting of analysis methods. The efficiency of manual analysis is also an issue. AIM(S): Our aim was to facilitate development of automated workflows for reproducible analysis of data yielded by the IntelliCage™ system. METHOD(S): We developed an open source Python library (PyMICE – RRID:nlx_158570) providing IntelliCage™ data as collection of data structures. We have described the library and presented some examples of its use in a paper. According to the literate programming paradigm, the paper was composed of Python and LaTeX snippets. Pweave tool has been used to weave the paper. RESULTS: All analyses contained in our paper “PyMICE – a Python library for analysis of IntelliCage data” (accepted by Behavior Research Methods) are fully reproducible. The source code of the paper (https://github.com/Neuroinflab/PyMICE_SM) does not contain any plots. Instead, they may be easily reproduced by the reader. Also, the correctness of performed analyses may be easily verified. CONCLUSIONS: We propose PyMICE as a common platform for implementing and sharing automated analysis workflows for IntelliCage™ data. The library is a user-friendly tool for analysis of behavioural data in an automated workflow. Such workflow is an unambiguous, formal specification of the performed analysis. The analysis itself may be easily reproduced by simply reapplying the workflow to the same data. Such workflow may be used to perform exactly the same analysis for multiple datasets, e.g. when the same protocol is applied to multiple groups of animals. This is a very common case, as most of experiments have at least one experimental and one control group. FINANCIAL SUPPORT: JD, KR and SŁ supported by a Symfonia NCN grant UMO-2013/08/W/NZ4/00691. AP supported by a grant from Switzerland through the Swiss Contribution to the enlarged European Union (PSPB-210/2010 to Ewelina Knapska and Hans-Peter Lipp). KR and ZH supported by an FNP grant POMOST/2011-4/7 to KR.
11

Separating dynamics of different cell populations from multielectrode signals

45%
Wojcik D., Potworowski J., Glabska H., Majka P., Leski S.
Acta Neurobiologiae Experimentalis
|
2011
|
tom 71
|
nr S
Local field potentials (LFP), low-frequency part of extracellular electric potentials, seem to reflect dendritic processing of incoming activity to neural populations. Long-range nature of electric field leads to correlations even between remote recordings showing sources from millimeters away which complicates analysis of LFP. To get more insight it is convenient whenever possible to look for current sources of the potentials or to decompose the signals into meaningful components using statistical techniques. In Łęski and coauthors (2010) we have combined inverse current source density method with independent component analysis (ICA) to decompose 140 recordings in rat forebrain obtaining physiologically meaningful components across a group of seven animals. To find out what can be really observed with such an approach experimentally we simulated local field potentials generated in a single cortical column in a model of 3560 cells with non-trivial morphologies. Having both the current source density (CSD) and LFP generated by twelve cortical populations included we compared it with independent components obtained in the decomposition of data generated by the whole network. We assumed a set of potential measurements on a regular grid, low-pass filtered it temporally under 500 Hz, reconstructed the sources using kernel current source density and performed the ICA. We found that the recorded evoked activity was dominated by two populations of pyramidal neurons, which were well separated by ICA. Other populations could not be clearly distinguished in the simulated potentials nor in the ICA. Supported by grants POIG.02.03.00-00-003/09, POIG.02.03.00-00-018/08.
12

Reciprocal inhibition and slow calcium decay in recurrent thalamic interneurons explain changes in spontaneous firing of thalamic relay cells after cortical inactivation

45%
Rogala J., Waleszczyk W. J., Leski S., Wrobel A., Wojcik D. K.
Acta Neurobiologiae Experimentalis
|
2012
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tom 72
|
nr 2
Most of recent studies of the role of cortical feedback in thalamocortical loop focused on its effect on thalamo-cortical relay (TCR) cells of the dorsal lateral geniculate nucleus (LGN). In a previous, physiological study we showed in cat visual system that cessation of cortical input decreased spontaneous activity of TCR cells and increased spontaneous firing of recurrent inhibitory interneurons located in the perigeniculate neucleus (PGN). To identify underlying mechanisms we studied several networks of point neurons with varied membrane properties, synaptic weights and axonal delays in NEURON simulator. We considered six network topologies. All models were robust against changes of axonal delays except for the delay between LGN feed-forward (f-f) interneuron and TCR cell. The best representation of physiological results gave models including reciprocally connected PGN cells driven by the cortex assuming slow decay of intracellular calcium. This indicates that thalamic reticular nucleus plays an essential role in the cortical influence over thalamo-cortical relay cells while the thalamic f-f interneurons are not essential in this process. The models revealed also that dependence of the PGN activity on the rate of calcium removal can be one of the key factors determining TCR response to diminished cortical input.
13

A computational model of learning, decision making and basic interactions of mice in IntelliCage

45%
Kowalski J. M., Kiryk A., Kaczmarek L., Wojcik D. K., Leski S.
Acta Neurobiologiae Experimentalis
|
2013
|
tom 73
|
nr 4
14

Simulations of local field potentials and current source density analysis in slices with realistic conductivity distribution

39%
Wojcik D. K., Ness T. B., Chintaluri H. C., Potworowski J., Gabska H., Leski S., Einevoll G. T.
Acta Neurobiologiae Experimentalis
|
2013
|
tom 73
|
nr Suppl.1
To test methods of local field potential (LFP) analysis we need realistic ground truth data which demands plausible models of neural activity and of physical properties of the setup, tissue, and the electrodes. To interpret the recordings we often reconstruct the Current Source Density (CSD) from the LFP. In this work we study the effect of realistic conductivity profiles and the slice geometry on (1) computation of LFP generated by cell populations embedded in slice, as would be measured on multi-electrode array (MEA), and (2) current source density (CSD) reconstruction in the slice from such potentials. We show that the method of images approximates solution through finite elements well while being much more efficient computationally. Inclusion of slice properties with homogeneous and uniform conductivity in the slice noticeably modifies the observed activity (LFP) but inhomogeneity and anisotropy do not further change the profile and amplitude of the LFP. Supported with grants: IP2011 030971, N N303 542839, FP7-PEOPLE-2010-ITN 264872, POIG.02.03.00-00-018/08, POIG.02.03.00-00-003/09.
15

Chronic fluotexine treatment disrupts apetitively motivated learning and central amygdala structural plasticity

39%
Puscian A., Leski S., Winiarski M., Charzewski L., Nikolaev E., Dziembowska M., Knapska E.
Acta Neurobiologiae Experimentalis
|
2015
|
tom 75
|
nr Supl.
AIMS: Fluoxetine, a selective serotonine reuptake inhibitor, is commonly used to treat psychiatric disorders. Available data show that fluoxetine has limited side effects and, more importantly, may improve patient’s cognitive abilities. However, little is known about the mechanisms by which fluoxetine affects learning, especially appetitively motivated one. Thus, in the present project we investigated the effects of a long-term fluoxetine treatment on appetitively motivated discrimination learning. METHODS: We used fully automated behavioral assessment of discrimination learning in group-housed subjects, DI-staining for determining changes in morphology of dendritic spines and gel zymography for measurement of activity of MMP-9 (matrix metaloproteinase 9, an enzyme involved in synaptic plasticity). RESULTS: We showed that above-described learning is severely impaired in mice subjected to the long-term fluoxetine treatment. Since we have previously shown that such learning depends on MMP-9 activity in the central amygdala (CeA), we examined MMP-9 activity in the CeA of the fluoxetine treated mice. We found decreased MMP-9 level. Further, we tested fluoxetine influence on dendritic spine morphology in the CeA and observed that behavioral performance of the control wild type mice was highly correlated with a size and of mature, mushroom-shaped dendritic spines. No such correlation was found in MMP-9 knock out mice. Applied treatment abolished this correlation in wild type mice and did not reinstated it to a significant level in MMP-9 knock outs. CONCLUSIONS: Obtained results show that chronic fluoxetine treatment impairs appetitive discrimination learning in healthy controls, decreases MMP-9 activity and disrupts correlation between subjects’ performance in appetitive learning and structural synaptic plasticity in the CeA. The data shed light on dendritic spines’ dependent learning mechanisms, that may be disarrayed in the CeA by commonly applied fluoxetine treatment in patients.
16

PyEcoHAB: a Python library for analysis of rodent behavioral data recorded with Eco-HAB

39%
Jedrzejewska-Szmek J., Maka J., Leski S., Winiarski M., Wojcik D. K., Knapska E.
Acta Neurobiologiae Experimentalis
|
2019
|
tom 79
|
nr Suppl.1
INTRODUCTION: How can we make mouse studies more reproducible? The obvious answer is the standardization of experimental conditions, minimization of human interference, automation of behavioral tests and data analysis, and introduction of data analysis pipelines to automate the process. Eco‑HAB, a system for automated measurement of social preference and in-cohort sociability in mice, provides a solution for the first two issues. Eco‑HAB closely follows murine ethology, providing a 4‑compartment apparatus with narrow tunnels, and minimizes contact between the experimenter and tested animals. Introduction of pyEcoHAB, a Python library for analysis of EcoHAB murine behavioral data. AIM(S): pyEcoHAB, a Python package, has been developed to automate and facilitate data analysis. METHOD(S): Combining data access and initial interpretation, pyEcoHAB removes the need to do this manually, and allows the researcher to build data analysis pipelines and automation of behavioral tests facilitating data interpretation. pyEcoHAB provides an object‑oriented application programming interface (API) and a data abstraction layer. Auxiliary utilities supporting development of analysis workflows are integrated with pyEcoHAB, including data validation and workflow configuration tools. Moreover, pyEcoHAB provides methods for assessment of mice social behavior, such as approach to social odor, total time spent by each pair of mice together in each compartment (in-cohort sociability), number of times each mouse follows other mice in narrow tunnels (following), and also, the number of times each mouse pushes other mice out of a narrow tunnel. The latter behaviorissimilarto tube dominance tests and is an example of how traditional behavioral tests can be automated. CONCLUSIONS: pyEcoHAB is a computational framework facilitating automatic analysis of behavioral data from EcoHAB system. FINANCIAL SUPPORT: This work was supported by the Polish National Science Centre grant 2017/27/B/ NZ4/02025.
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