Brain Machine Interfaces for Motor Control - Unither Nanomedical ...

boorishadamantAI and Robotics

Oct 29, 2013 (3 years and 7 months ago)

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http://nrg.mbi.ufl.edu

http://nrg.mbi.ufl.edu

Symbiotic Brain
-
Machine
Interfaces

Justin C. Sanchez, Ph.D.


Assistant Professor

Neuroprosthetics Research Group (NRG)

University of Florida

http://nrg.mbi.ufl.edu


jcs77@ufl.edu


http://nrg.mbi.ufl.edu

Enabling Neurotechnologies

for Overcoming
Paralysis


Develop direct neural
interfaces to bypass
injury. Communicate
and control (closed
-
loop, real
-
time) directly
via the interface.


Leuthardt

http://nrg.mbi.ufl.edu

Vision for BMI in Daily Life

Lebedev

http://nrg.mbi.ufl.edu

What are the Building Blocks?

Signal Sensing

Amplification

Pre
-
Processing

Telemetry

Interpret Neural
Activity

Control

Scheme

Feedback

Closed Loop BMI

Provide neurophysiologic basis and engineering theory for a fully implantable neural

Interface for restoring communication and control

http://nrg.mbi.ufl.edu

BMI lessons learned

Relationship between user
and BMI is inherently
lopsided. Users are
intelligent and can use
dynamic brain organization
and specialization while
BMIs are passive devices
that enact commands

I/O models have difficulty
contending with new
environments without
retraining

Laboratory BMIs need to be
better prepared for ADL


http://nrg.mbi.ufl.edu

Translating Thoughts into
Action: The Neural Code

Stimulus

Neural

System

Neural Response

Stimulus

Neural Response

Coding

Given

To determine

Decoding

To determine

Given

http://nrg.mbi.ufl.edu

Vision for Next Generation Brain
-
Machine
Interaction


Intelligent behavior arises from
the actions of an individual
seeking to maximize received
reward in a complex and
changing world.


Perception
-
Action Cycle:
Adaptive, continuous process
of using sensory information to
guide a series of goal
-
directed
actions.

Behavior

Consequences

Antecedents

http://nrg.mbi.ufl.edu

Co
-
Adaptive BMIs using Reinforcement
Learning

http://nrg.mbi.ufl.edu

Prerequesites for Symbiosis

http://nrg.mbi.ufl.edu

Co
-
Adaptive BMI involves TWO intelligent
agents involved in a continuous dialogue!!!

ROBOT

actions

rewards

brain states

RAT’S BRAIN

environment

RAT’S BRAIN

COMPUTER AGENT

http://nrg.mbi.ufl.edu


Decoding using
Reinforcement Learning



Rather than knowledge of the kinematic hand trajectory
only a performance score is supplied. The score could
represent reward or penalty, but does not directly provide
information about how to correct for the error.


Reward based learning
-

try to choose strategy to maximize
rewards.




RL originated from optimal control theory in Markov
Decision Processes.

http://nrg.mbi.ufl.edu

Experimental Co
-
Adaptive BMI Paradigm

Incorrect

Target

Correct

Target

Starting

Position

Match LEDs

Grid
-
space

Match LEDs

Rat’s Perspective

Water Reward

Map workspace
to grid

Rat

Robot Arm

Left Lever

Right Lever

27 discrete actions


26 movements


1 stationary


http://nrg.mbi.ufl.edu

Agent
-

Value function estimation

http://nrg.mbi.ufl.edu

Evidence for Symbiosis

Valuation
Change in
Computer
Agent

Brain
Reorganization

Overall
Performance

http://nrg.mbi.ufl.edu

Key Concepts for the Future


Fully implantable interfaces are only half of
the story.


Sharing of goals enables brain
-
computer
dialogue and symbiosis


Need for intelligent decoders that assist and
co
-
adapt with the user.


http://nrg.mbi.ufl.edu

History of Man
-
Machine
Interaction


“Implanting tiny machines
into the nerves of the heart
would make us less human”


Today, over half a million
pacemakers are implanted
annually!


We are at the frontier for
integrating machines with
the nervous system to
restore and enhance
function.


Nicolelis

http://nrg.mbi.ufl.edu

Tremendous team effort!

Jack
DiGiovanna
-

BME

Babak
Mahmoudi
-

BME

This work is supported by NSF project No. CNS
-
0540304

Jose
Principe
-

ECE

Jose Fortes
-

ECE

http://nrg.mbi.ufl.edu

Please visit the lab website for publications
and additional information.

Neuroprosthetics Research Group


http://nrg.mbi.ufl.edu