Principles Underlying the Construction of Brain- Based Devices Jeff Krichmar The Neurosciences...
Transcript of Principles Underlying the Construction of Brain- Based Devices Jeff Krichmar The Neurosciences...
Principles Underlying the Construction of
Brain-Based DevicesJeff Krichmar
The Neurosciences InstituteSan Diego, California, USA
test behavior in real worldcompare withempirical data
developtheory
create simulation
Construction of an Intelligent Machine
Following the Brain Based Model
Design should be constrained by these principles: Active sensing and autonomous movement in the
environment. Organize the signals from the environment into
categories without a priori knowledge or instruction. Incorporate a simulated brain with detailed neural
dynamics and neuroanatomy. Engage in a behavioral task and adaptation of
behavior when an important environmental event occurs.
Allow comparisons with experimental data acquired from animal systems.
Active Sensing and Autonomous Movement in
the Environment Darwin VII-VIII
1999 - 2002Darwin IX-X
2003 - presentDarwin IV-VI1992 - 1998
BrainWorks2004 - present
Organize the Signals from the Environment into Categories
without A Priori Knowledge or Instruction
Fabre-Thorpe, Phil. Trans. R. Soc. Lond. B (2003) 358, 1215–1223
Seth et al, Cerebral Cortex, November 2004, V 14 N 11
Incorporate A Simulated Brain With Detailed Neural
Dynamics And Neuroanatomy
voltage independent
inhibitoryplastic
value dependent
voltage dependent
Incorporate A Simulated Brain With Detailed Neural
Dynamics And Neuroanatomy
Cortex
ECin
ECout
ECinFB
ECoutFB
DG
DGFB
CA3
CA3FB
CA3FF
CA1
CA1FB
CA1FF
S MHDG
V1Color
Camera
V1Width
V2/4Color
V2/4Width
ODOMETRY
HD
IT Pr ATN MHDG
HIPPOCAMPUS
SR+
IRPlatform
IRWall
R-
MOTOR
BF
Engage in a Behavioral Task And Adapt Behavior When An
Important Environmental Event Occurs
Engage in a Behavioral Task And Adapt Behavior When An
Important Environmental Event Occurs
Allow Comparisons with Experimental Data Acquired
from Animal Systems
Allow Comparisons with Experimental Data Acquired
from Animal Systems
ECout
ECinDGCA3
CA1
Incorporate A Simulated Brain With Detailed Neural
Dynamics And Neuroanatomy
reflex response= error signal
predictiveinput
“Preflex”
reflex
Incorporate A Simulated Brain With Detailed Neural
Dynamics And Neuroanatomy
inhibitory
climbing fibererror signal
excitatory
Camera
IRTurn
IRVelocity
MotorVelocity
MotorTurn
Pre-Cerebellar Nuclei
Motion Area (MT)
Purkinje Cells Turn
Deep Cerebellar Nuclei
Turn
InferiorOliveTurn
Purkinje Cells Velocity
Deep Cerebellar Nuclei
Velocity
InferiorOlive
Velocity
LTD LTD
LTP
Reflex
Errorsignal
Errorsignal
Reflex“Preflex” “Preflex”
Engage in a Behavioral Task and Adapt Behavior when an
Important Environmental Event Occurs
Un-Trained Trained
Allow Comparisons with Experimental Data Acquired from
Animal Systems
Weight Matrices (initially, all weights were equal) Pre-Cerebellar-NucleiPurkinje Cells for velocity
White = maximum Black = minimum
More widespread LTD for sharper courses results in lower velocity
LTD
Pre-Cerebellar Nuclei
Purkinje Cells Velocity
LTD
Development of Intelligent Machines that follow Neurobiological and
Cognitive Principles in their Construction
JasonFleischer
JeffMcKinstry
DonHutson
BotondSzatmary
AnilSeth
JimSnook
JeffKrichmar
BrianCox
AlishaLawson
ThomasAllen
Donatello
Darwin VDarwin X BrainWorks
Segway B
Build A Brain Team
Construction of an Intelligent Machine
Following the Brain Based Model
Design should be constrained by these principles: Active sensing and autonomous movement in the
environment. Organizing the signals from the environment into
categories without a priori knowledge or instruction. Incorporating a simulated brain with detailed neural
dynamics and neuroanatomy. Engaging in a behavioral task and adaptation of
behavior when an important environmental event occurs.
Allowing comparisons with experimental data acquired from animal systems.