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1

Brainslices-image sharing for neuroscience

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Kowalski J., Majka P., Puscian A., Wojcik D.
Acta Neurobiologiae Experimentalis
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2015
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tom 75
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nr Supl.
AIM: Images of brain tissue are common outcome of a great number of neuroscience experiments; however, their impact on scientific development is limited since they are usually not published directly. Internet technology facilitates making the images available online, nonetheless, raw image files of good quality are very large and therefore inconvenient to provide and analyze online directly. There is still no convenient way to share annotated images of neuroscientific specimens. To fill that gap we developed BrainSlices software – a user-friendly tool dedicated for that purpose. METHODS: The software is built in the client-server model and consist of a web application at the client side, and server software running on a Linux system. Thanks to this design there is no need for installation and the only thing a BrainSlices user must do is to open a website. This approach also makes BrainSlices a cross-platform tool. Handling of large images is solved with image pyramid technique. RESULTS: We used BrainSlices software to set up an online repository (http://brainslices.org) of annotated high quality images of brain tissue. The repository combines the power of the image pyramid technique with convenience of image upload. Every image can be easily annotated with exhaustive metadata which facilitate search. The user interface of the repository and the provided facilities were developed with typical neuroscience use in mind. Every image receives a unique identifier and a permalink which allows direct access and citing. CONCLUSION: We provide the community with a user friendly tool for multiple image storage, viewing, sharing, and annotation. The tool may be used to store one’s own collection of slice images to share high quality specimen images with collaborators, to share them with the whole community, or to provide the images online as supplementary material for publications.
2

Experience-dependent acquisition of visuomotor behavioral representation in primary visual cortex

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Puscian A., Benisty H., Tang L., Higley M. J.
Acta Neurobiologiae Experimentalis
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2019
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tom 79
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nr Suppl.1
INTRODUCTION: The role of primary sensory cortical areas in perception and behavior remains unclear. Moreover, the functional plasticity of these circuits during task acquisition is largely unknown. AIM(S): Here, we developed a visual learning task in awake, head-fixed mice in which animals learn to associate a small drifting grating stimulus with an aversive air puff to the cornea, driving the establishment of a conditioned blink response. METHOD(S): We previously showed that both task acquisition and performance require intact primary visual cortex (V1). Pairing this approach with 2‑photon calcium imaging of identified neuronal subpopulations in V1, we monitored cellular activity across two weeks of learning. RESULTS: Our results show that the population activity of excitatory neurons in both layer 2/3 and 5 reliably encodes the presence of a sensory stimulus throughout training, but acquires the ability to accurately represent motor output over several days. Analysis of individual neurons demonstrates that cells not encoding behavior significantly lose their visual responses during learning, producing an overall enhancement of the population-level representation. We find similar results for GABAergic interneurons expressing parvalbumin and vasoactive intestinal peptide. However, somatostatin‑expressing interneurons fail to encode behavior at any point in training, suggesting that cell type‑specific mechanisms promote plasticity in V1 circuits associated with learning. CONCLUSIONS: In conclusion, our data suggest that visual experience produces a functional reorganization of both excitatory and inhibitory networks that facilitates efficient performance in visuomotor behavior.
3

Influence of chronic fluoxetine treatment on apetitive learning in matrix metalloproteinase-9 knock-out mice

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Charzewski L., Puscian A., Knapska E.
Acta Neurobiologiae Experimentalis
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2013
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tom 73
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nr Suppl.1
Matrix metalloproteinase-9 (MMP-9) is an extracellular endopeptidase which cleaves extracellular matrix proteins and plays a significant role in synaptic plasticity, learning and memory. Impairment of MMP-9 knock-out mice in appetitively motivated learning has been previously shown. In the present project we investigated whether chronic treatment with fluoxetine, antidepressant drug, which stimulates synaptic plasticity, would affect appetitive learning of MMP-9 knock-out mice. To this end, MMP-9 knock-out and wild type mice were treated with fluoxetine or vehicle for 35 days, and trained in sucrose-water discrimination task in the IntelliCage system. The IntelliCage system allows for long-term monitoring of the behavior of group-housed animals. For five days the mice had to discriminate between bottles (placed on two sides of the same corner of the cage) that contained either sweetened or plain water. The results suggest that chronic fluoxetine treatment improves appetitive learning of MMP-9 knock-out mice.
4

New and “cool” methods in behavioral neuroscience

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Boguszewski P. M., Puscian A., Knapska E.
Acta Neurobiologiae Experimentalis
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2014
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tom 74
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nr 3
Behavioral tests in laboratory rodents play an essential role in basic and applied biomedical research. Development of new animal models for neurological and psychiatric disorders, as well as preclinical phase of drug research require a „proof-of-concept” testing on a system level. Since most of the behavioral procedures are not rigorously standardized, it is difficult to obtain replicable results between laboratories. One of the approaches to solve this problem is designing more ethologically-relevant behavioral tasks, in which behavioral expression is more voluntary and manifold behavioral measures are collected over long periods. Collecting large amounts of data requires automatic control of all stages of a study – experimental cage/system manipulation, data gathering and analysis. Such automated systems offer important advantages. They increase level of standardization that results in more coherent data, save time and manpower, as well as reduce animal numbers required. Automated monitoring, although new and often sophisticated, could be cheap as well. The inspiration comes from growing popularity of amateur robotics, accessibility of 3D printing and progress in electronics. The aim of the lecture is to present new tests and solutions we are developing in Nencki Institute, including RFID tags for social experiments, automatic vocalization classification, video image animals detection and recognition software and even Mindstorm Lego robots.
5

New measures of social interactions for ecoHAB cage

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Maka J., Puscian A., Knapska E., Wojcik D. K.
Acta Neurobiologiae Experimentalis
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2017
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tom 77
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nr Suppl.1
INTRODUCTION: Eco-HAB is an open source system for automated measurements and analysis of social preferences and in-cohort sociability in mice. It requires no contact between a human experimenter and tested animals. In Eco-HAB, group-housed mice live in a spacious, four-compartment, resembling natural burrows. It allows an assessment of the tendency of mice to voluntarily spend time together in ethologically relevant mouse group sizes. Results are obtained faster, with less manpower needed and without confounding factors. AIM(S): The aim of the of this study is to develop measures for the EcoHAB system, which could well describe social relations in a group of mice. We test the proposed measures in experiments with four FX WT and three FX KO groups. We expected that FX KO mice would have disturbed social skills comparing to FX WT. METHOD(S): We developed a dedicated workflow for analysis of social interactions based on analysis of the decision patterns. For each pair of mice, one mouse is a leader, the other is a follower. After the leader changes the room, the follower’s reaction in a 3-second window is analysed. If the follower acts on the leader’s movement and follows it, the pattern is classified as “following”; otherwise it is “evasion”. Lack of follower’s reaction is ignored. The numbers of interactions for each pair and distribution of the patterns were obtained. To characterize the relations between the mice in selected time windows we used binomial model. We also studied changes of these relation in time and their distribution in mice groups. RESULTS: Our study proved that FX KO mice have significantly less interactions within a pair than FX WT. What’s more, FX WT are following each other more often and the character of interaction is more stable. CONCLUSIONS: EcoHAB is a good environment for conducting advanced analysis of mice social interactions. Proposed measures show significant difference between WT and KO group and are a promising tool to study social interactions.
6

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

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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.
7

Really reproducible behavioural paper

88%
Dzik J. M., Puscian A., Harda Z., Radwanska K., Leski S.
Acta Neurobiologiae Experimentalis
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2017
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tom 77
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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.
8

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

76%
Puscian A., Leski S., Winiarski M., Charzewski L., Nikolaev E., Dziembowska M., Knapska E.
Acta Neurobiologiae Experimentalis
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2015
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tom 75
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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.
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