Hi, I am a computational cognitive neuroscientist in training. As of Fall 2020, I am a graduate student in the Hellen Wills Neuroscience Institute at UC Berkeley. Here you can find all my recent work. 

 

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Education

August, 2020 - Present

University of California at Berkeley

Graduate Student in the Hellen Wills Neuroscience Institute 

June, 2018

University of New Hampshire

BS (Honors) in Neuroscience and Behavior

Minor in Philosophy

 

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Research Labs

May, 2021 - Present

Graduate Student Researcher - Cognac Lab

I am interested in the computations that the cerebellum performs during cognitive tasks. I have been studying this using a data driven approach to map representations of cognitive information across the cerebellar cortex as compared to the cerebral cortex. I do this by collecting large amounts of fMRI data during a naturalistic language task and building voxelwise encoding models inspired by computational linguistics and NLP. {link}

June, 2018 - August, 2020

Research Assistant - Huth Lab

During my time in the Huth lab, I was responsible for all fMRI data collection and preprocessing. Additionally, I led various projects including studying language processing in early blind individuals and studying the contribution of the cerebellum to language processing. {link}

January, 2017 - June, 2018

Undergraduate Research Assistant - Charntikov Lab

In this lab I assisted on a series of projects using operant conditioning to study addiction in a rat model.

September, 2014 - June, 2018

Undergraduate Research Assistant - Stine Lab

In this lab I used psychophysical techniques to study motion induced blindness.

 

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Awards & Fellowships

October, 2017

Research Presentation Grant

Presentation grant awarded by UNH to present at the 33rd annual meeting for the International Society for Psychophysics in Japan.

May, 2017

Summer Undergraduate Research Fellowship

Research fellowship to cover 10 weeks of research experience in the Stine Lab.

September, 2014-2018

Dean's Scholarship

 

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Skills

  • Python, MatLab, & Swift programming

  • Keras, Pytorch, & TensorFlow

  • fMRI data collection and analysis

  • Psychophysical techniques

 

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Preprints & Papers

Tang, J., LeBel, A., Huth, A. G. (2021). Cortical 

      representations of concrete and abstract concepts in 

      language combine visual and linguistic representations.

      {link}

LeBel, A., Jain, S., Huth, A. G. (2021). Voxelwise 

      encoding models show that cerebellar language 

      representations are highly conceptual. {link}

Jain, S.,  Vo, V., Mahto, S., LeBel, A., Turek, J.S., Huth, 

       A.G. (2020). Interpretable multi-scale models for                 prediciting fMRI responses to continuous natural

       speech. Advances in Neural Information Processing            Systems 34 {NeurIPS}. {link}

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Conferences & Abstracts

Jain, S., LeBel, A. & Huth, A. G. Uncovering

    compositional semantics in fMRI language encoding

    with transformers. From Neuroscience to Artificially

    Intelligent Systems (NAISyS), CSHL 2020.

 

Jain, S., LeBel, A. & Huth, A. G. Natural language 

    encoding models for fMRI reveal distinct patterns of 

    semantic integration across cortex. Society for the

    Neurobiology of Language (SNL) 2020.

LeBel, A., Jain, S., Huth, A. (October, 2019) Voxelwise          encoding models of the cerebellum during                             natural speech processing presented at the Society for         Neuroscience 2019.

 

Xu, L., LeBel, A., Huth, A. (October, 2019) Sparse                  experimental design for encoding models presented by         LX at Society for Neuroscience 2019.

 

Jain, S., LeBel, A., Huth, A. (October, 2019) Improving          language encoding for fMRI with transformers                     presented by SJ at Society for Neuroscience 2019. 

 

Tang, J.,  LeBel, A., Huth, A. (October, 2019) Visually            grounded language encodig models for fMRI

    highlight the influence of sensory experience on

    semantic representations presented by JT at Society for       Neuroscience 2019.

 

Griffith, I. M., LeBel, A., Jain, S., Huth, A., Liberty, L.S.        (October, 2019) Phonological feature and pitch                     classification with a branched convolutional neural               network presented by IMG at Society for 

    Neuroscience 2019.

 

LeBel, A. & Stine, W. (2017) Reducing Between Subject        Variation in Motion-Induced Blindness Using the

    Method of Constant Stimuli presented at the 33rd

    Annual Meeting of the International Society for

    Psychophysics in Fukuoka, Japan.