[visionlist] Postdoc position - Neurobiology of reading and dyselxia

[Jason Yeatman]

*Postdoc Position in the Yeatman Lab – Neurobiology of Reading and Dyslexia*

*University of Washington, Institute for Learning & Brain Sciences*



The Yeatman Lab has an opening for a postdoc with exceptional computational
skills and an interest in the neurobiological underpinnings of learning to
read. The lab combines diffusion MRI, functional MRI, MEG and behavioral
measurements to model how changes in brain structure relate to changes in
cortical computation and behavior. Much of the current work in the lab uses
intensive educational intervention programs as a means to study plasticity
and learning. Our goal is to understand how education shapes brain
development and explore the utility of neuroimaging as a tool to predict
learning differences (e.g., in children with dyslexia). The lab is a highly
collaborative environment that tackles scientific questions with relevance
for education. More information on the Brain Development & Education Lab
can be found on our website: http://BrainAndEducation.com

This postdoc position would focus on one of three potential projects:

*1)     **Plasticity in the reading circuitry. *Much of our recent work has
used intensive reading intervention programs to understand how education
shapes brain development. This work is highly interdisciplinary and
collaborative, as we are designing, organizing and delivering tightly
controlled educational interventions, while collecting longitudinal MRI,
MEG and behavioral data. We have multiple intervention studies in
preparation, all of which focus on reading, but span different age ranges
(including pre-reading 5-year-olds and school-aged children with dyslexia)
and employ a variety of neuroimaging (MEG and MRI) and behavioral measures
(psychophysics and normative assessments). This project would involve
working with a team to design experiments probing the neurobiological
underpinnings of learning and develop predictive models to characterize
differences in learning outcomes. Related work: Huber et al., 2018. Rapid
and widespread white matter plasticity during an intensive reading
intervention. *Nature Communications*. *Link <https://rdcu.be/UFXd>*

*2)     **A Big Data approach to understanding the neurobiological
underpinnings of reading disabilities.* With the emergence of public
datasets containing tens of thousands of subjects (e.g., ABCD, Healthy
Brain Network, Human Connectome Project, etc.) there are new opportunities
to apply computational approaches to understanding the multivariate
relationship between white matter development and reading skills. Beyond
identifying correlations between a single behavioral measure and diffusion
properties in a single white matter tract, we would like to progress
towards a model characterizing how the interrelated developmental
trajectories of the brain’s many white matter connections relate to
different components of academic development (e.g., reading, math,
executive function). This project would involve working with large,
publicly available datasets, and developing/applying new statistical
approaches to relate measures of brain anatomy to cognitive skills. Related
work: Yeatman et al., 2018. A browser-based tool for visualization and
analysis of diffusion MRI data. *Nature Communications. **Link
<https://www.nature.com/articles/s41467-018-03297-7>*

*3)     **The neural computations of skilled reading.* The visual word form
area is a region of high-level visual cortex that selectively responds to
written words and develops as children gain proficiency with reading. It is
also at the heart of neurobiological differences found in children with
dyslexia. We are working towards developing a computational model
characterizing the VWFA as a function of bottom-up, stimulus-driven
computations and interactions with the other interconnected regions of the
reading circuitry.  This project would involve conducting fMRI and
diffusion MRI experiments aimed to elucidate the computations performed by
the VWFA, its connectivity with other regions of the reading circuitry, and
how it differs in children with dyslexia. Related work: Kay & Yeatman,
2017. Bottom-up and top-down computations in word- and face-selective
cortex. *Elife*. *Link <https://elifesciences.org/articles/22341>*



Applicants should: (1) have strong computational skills and proficiency
programming in MATLAB or Python; (2) experience conducting psychophysics,
fMRI, diffusion MRI, or MEG experiments/analysis, (3) working in a
fast-paced collaborative environment, (4) strong writing and communication
skills.



Start date: January – November, 2019.



To apply, please send:

1)     A curriculum vitae

2)     Contact information for three references

3)     A two-paragraph letter (less than 1 page) describing: (1) a finding
from you PhD (or previous postdoc) research that you are excited about and
(2) a project you would like to tackle in the lab.



Jason Yeatman (jyeatman at uw.edu)

Assistant Professor

Institute for Learning & Brain Science

University of Washington

Portage Bay Building

Seattle, WA
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://visionscience.com/pipermail/visionlist_visionscience.com/attachments/20181219/4748e60c/attachment-0001.html>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: Yeatman Lab-PostdocPosition-2019.pdf
Type: application/pdf
Size: 104359 bytes
Desc: not available
URL: <http://visionscience.com/pipermail/visionlist_visionscience.com/attachments/20181219/4748e60c/attachment-0001.pdf>