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.github/profile/README.md

Abuzar Mahmood

Exploring the Neural Symphony of Taste

Hi! I'm Abuzar. I'm a Computational Neuroscience Postdoctoral Fellow at Brandeis University studying the role of brain-region interactions in sensory processing. My journey in neuroscience began with a fascination for how the brain processes sensory information. I studied Physics at the University of Missouri and received my PhD in Neuroscience from Brandeis University. In my dissertation, I investigated how brain regions coordinate to process taste and demonstrated that these regions likely behave as a joint attractor network—a discovery that opened new avenues for understanding neural dynamics.

One of my most exciting research moments came when I first visualized the synchronized activity patterns between the gustatory cortex and amygdala. It was like watching a neural symphony unfold, with each region playing its unique part in the taste experience. This moment crystallized my passion for understanding the brain's complex networks.

Research Interests

Broadly, I'm interested in the mechanisms underlying the dynamics of processing and neural activity in the brain. This falls under the domain of studying the brain as a dynamical system, and studying the dynamics of interactions in the brain.

Current Work

My current work aims to further elucidate neural interactions by investigating the timeseries of influence between the gustatory cortex, basolateral amygdala, and gustatory thalamus, as well as studying the critical role of feedback projections from cortex to amygdala and thalamus.

Featured Projects

  • blech_clust: Core contributor and maintainer of this Python/R-based spike sorting and analysis pipeline for electrophysiology data recorded using Intan RHD2132 chips
  • teachables: Educational Jupyter notebooks for neuroscience and data analysis
  • neuRecommend: Classifier for semi-automated spike-sorting and channel recommendation
  • pytau: Library to streamline batch-fitting of Bayesian changepoint models to neural population spiking data
  • ocr_database: Streamlit app to upload and search documents using optical character recognition
  • blech_github_bot: A Python bot that monitors GitHub repositories and automatically responds to issues using OpenAI's GPT-4

Connect With Me

Explore More

Investigating dynamics of sensory processing using electrophysiology and statistical modelling

Pinned Loading

  1. teachables teachables Public

    Jupyter Notebook 1

  2. neuRecommend neuRecommend Public

    Classifier for semi-automated spike-sorting and channel recommendation

    Jupyter Notebook 2

  3. katzlabbrandeis/blech_clust katzlabbrandeis/blech_clust Public

    Forked from narendramukherjee/blech_clust

    A comprehensive Python and R-based toolkit for clustering and sorting electrophysiology data recorded using Intan RHD2132 chips. Originally developed for cortical multi-electrode recordings in the …

    Python 9 5

  4. pytau pytau Public

    Library to streamline batch-fitting of Bayesian changepoint models to neural population spiking data

    Jupyter Notebook 1 2

  5. ocr_database ocr_database Public

    Streamlit app to upload and search documents using optical character recognition

    Python 1 1

  6. blech_github_bot blech_github_bot Public

    A Python bot that monitors GitHub repositories and automatically responds to issues using OpenAI's GPT-4 through Autogen. The bot analyzes issues, suggests relevant files and code changes, and prov…

    Python 2 1