José L. Contreras-Vidal, Ph.D.
Associate Professor
Behavioral, Neuroimaging and Computational Neuroscience Research Group
Research Foci
Research Opportunities: Undergraduate
Research Opportunities: Graduate
Research Opportunities: Postdoctoral
Decoding Human Action and Cognition:
We integrate non-invasive measurements of human motion and electrical activity and associated changes in blood hemoglobin concentrations produced by the brain and recorded from sensors placed on the scalp, for the purpose of using these signals to uncover the brain's computational rules and instructions underlying all human action and cognition. A novel computational framework that builds on the language of actions (Human Action Language or HAL) guides our research design, adaptive signal processing, and biomedical applications. Our research uses interdisciplinary, multi-level, and integrated approaches as illustrated below:
(1) We are developing non-invasive, multi-modality, wireless devices that can serve to monitor and interface with movement and brain activity;
(2) We use sophisticated data mining and machine learning algorithms to decode a Human Action Language (HAL) by harnessing activity patterns that can distinguish among actions and thoughts by deciphering or reading out brain activity (brain grammars) and movement (action grammars)
(3) We focus on two fundamental abilities central to adaptive human functioning: the ability to deploy actions strategically in service of goals, and the ability to infer the goals or actions of one's social partners: Specifically, we are developing non-invasive smart prosthetics for hand reaching and grasping that allow for co-adaptation of the brain and the decoding algorithms. We are also investigating the role of a neural network of the brain, namely, the mirror neuron system, thought to be involved in action understanding and imitation.
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Movement disorders:
We use behavioral, neuroimaging and computational neuroscience methods to study the neural mechanisms and computational principles underlying adaptive sensory-motor control in humans. Specifically, we study how the macro and microstructure of movement is altered by transient or permanent changes in the human brain due to environmental change, development, aging or disease, as compared to the young, mature, healthy population. An important goal of our research is to understand how the brain reorganizes during across the life span and how it changes in response to novel environments. In this regard, we are studying how multiple internal models of the interaction between our body and the environment (e.g., during learning to use a new tool) are formed, and how these models are affected by disease (e.g., developmental coordination disorder, cerebellar dysfunction and Parkinson's disease). We are also interested in developing novel intervention procedures to restore or enhance cognitive-motor behavior in patients with neurological disorders.
Bio-robotics and large-scale computational modeling:
Investigations aimed at determining the computational principles of adaptive sensory-motor control are two-fold: first, modeling the connectivity and neurophysiology of the brain allows us to integrate a large amount of biological data related to behavior and to provide a mechanistic account for movement invariances. Second, neural modeling allows us to examine in detail intervention procedures or predictions that can be tested experimentally. Importantly, top-down information provided by behavioral tasks is used to constrain the mathematical description of neural networks based on neuroscience data. Thus, the behavioral research is closely related to the computational neuroscience methods fostering the transfer of biological principles to robotics, bio-engineering and medicine.
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Research Opportunities: Undergraduate
Students receive credit or a note in their transcript through
the Undergraduate
Research Assistant Program (URAP), get paid interships
through the Summer
Research Program, or the Howard
Hughes Medical Fellowship Program
Typical Research Projects for Undergraduate Students
(summer, semester, or academic year):
How the brain learns visuo-motor transformations
for movement:
In visually guided arm movements, a perceived target direction
needs to be mapped into motor commands that drive the arm
in the intended spatial direction. This so-called visuo-motor
map needs to be updated continuously based on growth, environmental
changes, or aging. This line of research will explore the
effects of development, aging, brain disease or changes in
the environment on visuo-motor learning. Typical paradigms
would include changes in the relationship between hand movements
and the visual feedback of cursor movement on a computer screen.
Both normal and neurological populations (e.g., Parkinson's
disease) are studied.
Simulation of neural networks for movement control:
Several models for spinal cord, subcortical structures and
cortical brains areas involved in adaptive sensory-motor control
have been developed. Mathematical models that simulate the
behavioral operating characteristics of human and animal movement
have also been put forward. These models need to be tested,
refined or disposed. Engineering methods and/or control theory
can be used to evaluate these models.
Instrumentation and measurement:
Physiological, bio-mechanical or bio-potential variables need
to be measured using specialized sensors and circuits. Students
can participate in the development/refinement of new sensor
technology/circuits for measurement of variables in sensory-motor
research (e.g., grasping force, brain activity, or muscular
activity).
Research Opportunities: Graduate
Several lines of research within Behavioral and Computational
Motor Neurosciences, Complex Systems, Non-stationary Pattern
Recognition and Analysis, or Bio-robotics are available for
research work towards a Master’s or Ph.D. degree.
Cognitive-Motor Behavior in Parkinson’s Disease:
We use Parkinson’s disease as a window to study the
functions of motor, cognitive, and limbic networks of the
basal ganglia-thalamo-cortical circuits. Opportunities exist
for research in the learning, selection, planning, initiation,
and execution of actions using behavioral and/or computational
paradigms. Tools include EEG, MEG, Independent Component Analysis.
Disordered Motor Activity in Dystonia:
This line of research aims to understand the source of dystonia,
a disease characterized by disordered muscular, subcortical,
and cortical activity that results in muscular co-contraction
and overflow of EMG activity, slowness, prolonged muscle contractions,
abnormal posture of the affected body part(s), movement variability
and uncontrolled/involuntary movements. Opportunities for
research at the spinal cord, basal ganglia, or cortical levels
are available. Behavioral and/or computational paradigms can
be utilized to gain insight about the mechanisms underlying
dystonia.
Bio-robotics:
Students with a strong background in engineering and/or neuroscience
and who wish to undergo advanced training in the applied neuroscience/computational
neuroscience areas have opportunites for research/development
in the application of neural network theories/models to robotics.
Our project ``Systems Neuroscience and Engineering Research
for Antropomorphic Grasping and Handling ‘’ aims
to develop the next generation of artificial limbs/hands for
use in prosthetic devices, assembling lines, and robotic research
in general. In contrast to traditional robotic systems, our
work mimics both the bio-mechanical atttributes of the arm/hand
system and the neural network control algorithms that we believe
the brain uses to learn and control prehensile tasks.
Non-stationary Pattern Recognition and Analysis:
Biological data, including neurophysiological recordings,
sequence data, and behavioral data, may be characterized as
non-stationary spatio-temporal patterns of activity that need
to be analyzed, clustered, matched, filled-in, and correlated
with other brain or behavioral variables. Recent neural networks
for self-organizing pattern recognition provide useful tools
to aid in this task.
Research Opportunities: Postgraduate
Several opportunities for postdoctoral research exist within the Cognitive-Motor Behavior Laboratory in the Behavioral and Computational Motor Neuroscience Group.
Deadline: April 5, August 5, December 5, annually.
2 year support. Up to $40,000 per year.
Deadline: Sept. 1, annually.
3 year support. Up to $50,000 per year.
Deadline: Feb. 26, annually.
Deadline: December 30, annually.
