M1-2 internship : Discovering Structure in Connectomes Using Latent Space Kernel Embedding

Masters PhD @Pasteur Institute posted 1 week ago

Job Description

Project Description:

The field of connectomics has advanced significantly, allowing us to map synaptic connectivity of neural circuits at cellular resolution using electron microscopy. This internship project aims to develop and apply a novel class of models for analysing connectomic data, focusing on uncovering continuous hidden structures within these neural networks.

Objectives:

  1. Model Development: Extend traditional latent space models to analyse connectomic data, focusing on continuous latent variables representing neural tuning properties and connectivity functions.
  2. Data Analysis: Apply the developed models to synthetic connectomes and real-world datasets, such as the mouse retinal connectome, to uncover underlying structures.
  3. Validation: Assess the model’s performance in recovering known neural connectivity patterns and evaluate its scalability and flexibility in handling both directed and undirected graphs.

Methodology:

  • Construct latent space graph models to estimate the probability of neural connections based on positions in a low-dimensional latent space.
  • To fit the models, utilize advanced optimization techniques, such as quasi-Newton methods and stochastic gradient descent.
  • Validate the approach by recovering classical connection topologies, such as ring attractors and synfire chains, from connectivity matrices.

Expected Outcomes:

  • A robust model capable of revealing hidden structures in neural connectivity data.
  • Insights into the organisational principles of neural circuits, contributing to our understanding of neural computation.
  • Potential applications in neuroscience research, aiding in the interpretation of complex connectomic datasets.

Requirements:

  • Strong background in statistical modeling, machine learning, or related fields.
  • Proficiency in programming, particularly with Python.
  • Familiarity with neural data analysis and connectomics is a plus.

Duration:

  • The internship is expected to last for 6 months

Application:

Interested candidates should submit their CV, a cover letter, and any relevant academic transcripts to  dbc-epi-recrutement at pasteur dot fr

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