Master Theses

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  1. Brain states
    • Topic: Analysis of electrophysiological data collected from anaesthetized mice with multi-electrode surface arrays.
    • Target: Determination and classification of brain states from multi-unit activity signals in healthy and pathological subjects; determination and classification of waves propagation patterns, link with the brain state and the level of anaesthesia.
    • The candidate should:
      • be interested in cortical activity during sleep;
      • be interested in statistics and statistical analysis of experimental data;
      • know/be willing to learn MATLAB and Python.
  2. Optical imaging
    • Topic: Analysis of electrophysiological data collected from anesthetized mice with optical imaging techniques (wide-field and two-photon microscopy).
    • Target: Study of waves propagation patterns,  propagation speed, excitability, multi-areal connectivity; comparison with electrodes data.
    • The candidate should:
      • be interested in cortical activity during sleep;
      • be interested in statistics and statistical analysis of experimental data;
      • know/be willing to learn MATLAB and Python.
  3. Behaving monkeys
    • Topic: Analysis of electrophysiological data collected with Utah arrays from behaving monkey performing transitive inference task.
    • Target: Study of multi-areal connectivity and activation patterns; measurement of sleep-related learning performance.
    • The candidate should:
      • be interested in cortical activity during tasks;
      • be interested in spiking and in neural encoding/decoding;
      • be interested in statistics and statistical analysis of experimental data;
      • know/be willing to learn MATLAB, Python and spike sorting software.
  4. SWAP (Slow Wave Analysis Pipeline)
    • Topic: Development and improvement of the analysis pipeline, test on experimental and simulated data.
    • Target: Focus on reliability, robustness, reconfigurability, portability, parallelisation, open source.
    • The candidate should:
      • be interested in programming, code optimization, parallelization;
      • be interested in computer science and algorithms;
      • know/be willing to learn MATLAB, Python + any other programming languages/tools useful for improving performance.

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Ph.D Theses & Research Fellowships