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2015 TDLC Boot Camp Application


* = required fields (N/A if needed)

* First Name:
* Last Name :
* Gender (for
accommodations)


* Institution:
* Research Area / Discipline:
Academic Title:

* Advisor’s/Mentor’s Name:

MAILING ADDRESS --
Street:

* City: * State: * Zip:
Home Phone:
* Cell Phone:
* Email Address:

Statement:
(Please provide a statement explaining why you are interested in participating in the TDLC Boot Camp.)

* Research Background:

(Please provide a summary of your research background.)

* Recommender's Name:
* Recommender's
Email Address:

Proposed Project: (This box can be left blank)
Each Boot Camp participant will engage in a weeklong research project. The projects are typically
designed by the Boot Camp instructors,but we would like to give our applicants the opportunity to
propose a project within the scope of something that can be reasonably executed in the allotted time, and
something preferably outside of your comfort zone.


Proposed Topics:

Listed below the form are the lectures, labs, and evening tutorials from the 2009 Boot Camp.
These topics will once again form the framework of the 2015 Boot Camp, but we would like to give our
applicants the opportunity to propose additional topics, whether for a training day or an evening tutorial,
that will be taken into consideration as we finalize the training curriculum.

 





Lectures and Labs


Interacting Memory Systems

Lectures: The Multiple Memory Systems of the Brain; Theories of the Spacing Effect; Perpetual plasticity and the dentate gyrus

Labs: Spacing effects; Comparative Neuroanatomy

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Social Interaction

Lectures: Collecting and analyzing data for understanding the development of triadic attention
Methods for facial expression analysis: ELAN, CERT and FACS; An Optimal Control Approach to Affect-sensitive Automated Teaching

Labs: Collection and representation of multimodal features of human behavior.Using CERT, ELAN and other labeling tools and discursis to analyze video data

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Sensorimotor

Lectures: Perception and Psychophysics; Towards methods for robotic systems capable of human-level dexterity in manipulation and locomotion; Optimal control of movement in animals and robots

Labs: Robotics Systems, Signals, and Hardware; Movement and memory in a virtual radial maze

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Modeling and Analysis

Lectures: Neural Network Models; Bayesian models; Diffusion Models of decision making and reaction time

Labs: Matlab neural net demo; Discursis

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Perceptual Expertise

Lectures: The Time Scale of Perceptual Expertise; Becoming an Expert, One Day at a Time; Expertise, Millisecond by Millisecond; What is perceptual expertise, anyway?

Labs: Photoshop exercises in morphing and holistic perception


Evening Tutorial Subjects

Linear Algebra; Matlab; Python file and R file; Transcranial Magnetic Stimulation (TMS); Eye Tracker Tutorial