Tomas Barta

tomas.barta@fgu.cas.cz

I am a PhD student jointly at Institute of Physiology CAS (Czech Academy of Sciences, Prague) and INRAE (Versailles). I obtained my BSc in general physics. During my master's studies in mathematical and computational modelling in physics I changed my focus to computational neurosciences and wrote my thesis under the supervision of Lubomir Kostal. Now I continue with my studies jointly in Lubomir Kostal’s lab in Prague and Philippe Lucas’s lab in Versailles. In my research I focus on metabolically efficient information transmission by neurons and on modelling the insect olfactory system.

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ORCID: 0000-0002-0467-3240
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Affiliations and work experience

Doctoral researcher

Institute of Physiology, Czech Academy of Sciences

Institute of Ecology and Enviromental Sciences, INRAE

I work on my PhD jointly in two labs, which means that each year I spend several months (4-5) in the laboratory of Philippe Lucas in Versailles. In the project with Philippe Lucas I focus on studying how insects use olfactory cues to navigate in complex environments. Particularly, we are interested in the signal transdution and adaptation mechanisms of the olfactory receptor neurons. To this end I analyze electrophysiologal recordings from the moth Agrotis ipsilon and use biophysical models to reproduce the activity.

In the second project with Lubomir Kostal we focus on the information metabolic efficiency of neurons and neural networks. We employ Shannon's information theory to evaluate the information transmitted by a single neuron or a group of neurons and use biophysical properties of the neurons to estimate the metabolic cost of the activity. We work mostly with simulated data obtained from Monte Carlo simulations. To perform the simulations we use either custom code in Python and C++ or the Brian2 Python package.

September 2018 - present

Data Scientist

Datatree

I worked part-time as a data scientist at the end of my BSc and during my MSc studies. Datatree uses transactional data to help banks understand their clients and to automate financial advice. My job was to develop algorithms to classify transaction and evaluate risk factors using both heuristic approaches and machine learning. Subsequently I worked on approaches to evaluate the clients' financial health and to provide suggestions on where money can be saved.

I worked mostly with Python and data analysis and scientific packages - Pandas, NumPy, SciPy. For machine learning I used mostly methods implemented in the SciKitLearn package, XGBoost and Shap for result interpretation. I also used Tableau, D3JS and Plotly for advanced visualizations and SQL for database queries.

September 2015 - August 2018

Education

Charles University in Prague & Sorbonne University in Paris

PhD - Computational neuroscience

September 2018 - now

Charles University in Prague

MSc - Mathematical modelling in physics

September 2016 - June 2018

Charles University in Prague

BSc - General physics

September 2012 - June 2016

Publications

Published

T. Barta, L. Kostal. 2021. Regular spiking in high conductance states: The essential role of inhibition. Physical Review E, 103, 022408. https://doi.org/10.1103/PhysRevE.103.022408 | download pdf
T. Barta, L. Kostal. 2019. The effect of inhibition on rate code efficiency indicators. PLoS Computational Biology, 15, e1007545. https://doi.org/10.1371/journal.pcbi.1007545 | download pdf
M. Svanda, M. Sobotka, T. Barta. 2014. Moat flow system around sunspot subsurface layers. The Astrophysical Journal, 790, 2. https://doi.org/10.1088/0004-637x/790/2/135

Preprints

T. Barta, L. Kostal. 2023. Shared input and recurrency in neural networks for metabolically efficient information transmission. bioRxiv, https://doi.org/10.1101/2023.03.13.532471 | download pdf
T. Barta, C. Monsempès, E. Demondion, A. Chatterjee, L. Kostal, P. Lucas. 2022. Stimulus duration encoding occurs early in the moth olfactory pathway. bioRxiv, https://doi.org/10.1101/2022.07.21.501055 | download pdf

Presentations at conferences

T. Barta, L. Kostal. 2022. Excitation-inhibition coupling in recurrent neural networks promotes energy-efficient information transmission. Poster: Bernstein Conference 2022, Berlin.
T. Barta, L. Kostal. 2022. Maximally informative coupling in a balanced excitatory-inhibitory neuronal network. Talk: CNS*2022, Information theory workshop, Melbourne.
T. Barta, L. Kostal. 2022. Spike frequency adaptation mechanism leading to variability quenching in recurrent neural networks. Poster: CNS*2022, Melbourne. abstract online
T. Barta, C. Monsempès, E. Demondion, A. Chatterjee, L. Kostal, P. Lucas. 2022. Stimulus duration encoding by moth olfactory receptor neurons. Poster: FENS Forum 2022, Paris.
T. Barta, L. Kostal. 2021. Information-metabolically optimal E-I balance in a network of heterogeneous neurons. Online poster: Bernstein Conference 2021. abstract online | summary video (3:03)
T. Barta, L. Kostal. 2021. Inhibitory noise decreases membrane potential fluctuations and may lead to increased firing regularity. Online talk: Neural Coding 2021.
T. Barta, L. Kostal. 2021. Inhibitory input may increase firing regularity despite higher synaptic noise. Online poster: CNS*2021. abstract online | summary video (2:27)
T. Barta, L. Kostal. 2021. Precise spike-timing can be achieved by increasing inhibitory input. Flash talk: International Conference on Mathematical Neurosciences.
T. Barta, C. Monsempès, E. Demondion, L. Kostal, P. Lucas. 2021. Triphasic response of the moth olfactory receptor neurons. Online talk: Young Researchers in Life Sciences Conference.
T. Barta, L. Kostal. 2020. Inhibition enhances spike firing regularity. Online poster: Bernstein Conference 2020. abstract online

Grants & Awards

GA UK (Charles University Grant Agency). 2020-2022: Neural coding and metabolic cost of information processing. 22120 EUR
FENS-IBRO/PERC Travel Grant for the FENS Forum 2022. 750 EUR

Teaching & Outreach

Code In Place 2021, Section Leader.

Member of the teaching team for Code In Place, April - May 2021. This online course was offered by Stanford University during the COVID-19 pandemic. The course is a 6-week introduction to Python programming using materials from the first half of Stanford’s CS106A course.

As a volunteer section leader, I prepared and taught a weekly discussion section of small group of students to supplement professors' lectures.

April 2021 - May 2021

Science To Go, Outreach talk.

Science To Go organizes lectures at various places across the Czech Republic to present various topics from the natural sciences to the general public interested in science.

During my talk at their event I introduced basics of neuroscience and why and how we can use mathematics and physics to investigate information transmission by neurons.

May 2019

FYKOS, Event Organizer

Member of the organizing team of correspondence competition in physics for high school students. I was setting physics problems and grading the solutions. During other events organized by FYKOS I presented various mathematical and physical topics to motivated high school students. I was also the main organizer of Physics Brawl, competition for high school students, taking place once a year, organized by FYKOS.

October 2012 - May 2015

Hobbies & Interests

I love going into nature to run, hike, cycle. I can't do a year without going backpacking or bikepacking at least once. Recently I started climbing and I think it will be my new hobby. I like to play chess, board games and video games with friends (I also like to play video games alone). I also enjoy cooking, baking and learning about why and how it works.