Teaching
Our teaching covers various aspects of the neurosciences and is part of the MSc Neuroscience program at the University of Freiburg and of the curriculum of the Bachelor and Master of Science Biology offered by the Faculty of Biology.
Search for current lectures in HISinOne.
Current Master thesis projects, Bachelor thesis projects and Research projects
Decoding 2D mouse trajectory from one-photon calcium imaging (Bachelor thesis project/ Master thesis project / research project)
Previous studies have shown that one can predict the running trajectory of a mouse during free foraging of a two-dimensional arena with the help of the Support Vector Regression decoder, trained on the population of calcium transients of cells recorded during the behavioral experiment. The results indicate that the place cells (cells with a high firing rate in a specific location, yielding a high value of mutual information between the Calcium signal and the running trajectory) and non-place cells contribute equally to the decoder; decoding error depends solely on the number of transients the model is trained on.
The project aims to investigate the stability of cell population code capitalizing on reliable tracking of the cells across multiple days. We will test how the decoder, trained on the population of trackable cells on a certain day, would predict the trajectory on the next day using the same population of cells.
Students are expected to have basic Python skills, as well as an eagerness for biology and data analysis.
Contact: vladislav.ivantaev@bcf.uni-freiburg.de
Comparing Burst Sequences in Artificial Neural Network with Real Data from Mouse PFC (Bachelor thesis project / Master thesis project / research project)
Aim: Detecting burst sequences in artificial neural network and compare it with real data recorded from mouse prefrontal cortex (PFC).
The objective of this project is to verify the findings obtained through burst sequence analysis of calcium traces recorded from the prefrontal cortex (PFC) by comparing them with sequences generated by an artificial neural network (ANN). We conducted calcium trace recordings from the mouse PFC, capturing data before, during, and after the learning of a task. Our analysis using burst sequence analysis revealed significant alterations in sequence rates and patterns across different behavioral conditions throughout the learning process.
To further validate our approach, we aim to evaluate our methodology on data generated by an ANN. Consequently, the primary goal of this project is to develop a model, preferably a recurrent neural network, capable of emulating the neural activity in the PFC. Subsequently, we will implement the developed pipeline for sequence analysis to detect and quantify the pattern of bursts generated by the ANN model. Ultimately, the outcomes of this research will enhance our comprehension of the neural mechanisms underlying sequence generation in the PFC.
Contact: hamed.shabani@bcf.uni-freiburg.de
Closed-loop components of hippocampal place field activity
(Bachelor thesis project / Master thesis project / Research project)
We will test recent state-of-the-art dimensional reduction method on the product space of hippocampal firing rates and behavioral tracking data from freely behaving rats. This analysis approach will elucidate the behavioral correlates of hippocampal network activity beyond spatial tuning of single cells. Students are expected to have basic programming skills in python and an interest in modern data science approaches.