Prediction in Brain

Prediction in Human
Presented by: Rezvan Kianifar
January 2009
Syllabus
Prediction Levels
senasorimotor level
cognitive level
Related brain regions at cognitive level
Characteristics which emerge by prediction
Discussion
Motor prediction
biological systems need to be able to predict the sensory
consequences of their actions to be capable of rapid,
robust, and adaptive behavior.
Control Strategies:
direct
directly maps sensations to actions, without meaningful
intermediate steps and, in particular, without any
attempts to explicitly model the movement system or task.
indirect
explicitly employs multiple information-processing steps to
build the control policy, and in particular it employs internal
models.
What is internal model?
Internal models are neural substrates that model
input/output relationships and their inverses of
kinematic and dynamic processes of the motor
system and the environment
Why seek for internal model?
Helmholtz observation
Holst and Sperry
Other studies
1950s(efferent
copy)
Motor Prediction Influences
State estimation
Sensory confirmation and cancellation
Context estimation
State estimation
Sensory confirmation and cancellation
Context estimation
Mental practice, imitation and social
cognition
Forward model is used to predict the sensory outcome of an action,
without actually performing the action.
In perception of action we could usemultiple forward models to
make multiple predictions and, based on the correspondence
between these predictions and the observed behaviour, we could
infer which of our controllers would be used to generate the
observed action
.
in social interaction, a forward social model could be used to
predict the reactions of others to our actions.
How to investigate prediction in cognitive
level?
Cognitive Tests
FMRI-Functional Magnetic Resonance
Imaging
Related brain regions in cognitive level of
prediction
DLPFC- DorsoLateral PreFrontal Cortex
OFC- OrbitoFrontal Cortex
ACC- Anterior Cingulated Cortex
DLPFC-
DorsoLateral PreFrontal Cortex
DLPFC- DorsoLateral PreFrontal Cortex is known
as a neural substrate for working memory in which
a model of environment could exist
OFC- OrbitoFrontal Cortex
OFC provides an updated representation of value
through interactions with other brain areas, such
as the amygdale, which can affect adaptive
behavior
ACC- Anterior Cingulated Cortex
ACC detects the state of conflict and drives control
processes to resolve the internal conflict. Because of its
anatomical position which receives information from limbic
and prefrontal regions as well as having direct access to the
motor system, it seems to play a key role in monitoring the
outcomes of voluntary choices under uncertainty when the
environment is changing.
Midbrain regions
OFC have connections with the amygdala and ventral
striatum, both of which have been involved in anticipating
the contingencies between environmental stimuli, actions and
rewards.
The serial flow of information between the amygdala and
ACC is essential for guiding efficient decision making
relations
Characteristics which emerge by prediction
Prediction:
capability of predicting
future properties
Anticipation:
mechanisms that use
predictions to improve
other mechanisms including
learning and behavior
predictive capabilities
(1) the types of predictions represented,
(2) the quality or accuracy of the predictions,
(3) the time scales of the predictions,
(4) the generality of the predictions,
(5) the capability of incorporating context information and action
decision information for improving predictions,
(6) the focusing and attentional capabilities of prediction
generation,
.
(7) the capability of predicting inner states
Anticipatory capabilities
(I) learning,
(II) attention,
(III) action initiation and control,
(IV) decision making.
Epigenetic Robotic
goal of Epigenetic robotics is to understand, and model, the
role of development in the emergence of increasingly
complex cognitive structures from physical and social
interaction.
It is being driven by two main, somewhat parallel,
motivations:
(a) to understand the brain by constructing embodied
systems the so-called synthetic approach,
(b) to build better systems by learning from human
studies.
Discussion
1- Prediction is a main characteristic of human activity.
2-new modeling approaches should consider prediction aspect
of human behavior (model-based control algorithms such as
MPC or RL are good candidates)
3- neural substrates under brain prediction is not well
understood but it seems it is better to consider a general
framework which covers all prediction levels.
thank you
References
1-Wolpert,D.M. & Flanagan,J.R., “Motor prediction” Current Biology Vol 11 No
18,2001
2-Mehta,B. & Schaal,S. “Forward Models in Visuomotor Control” J
Neurophysiol88: 942–953, 2002;
3-Web,B. “Neural mechanisms for prediction: do insects have forward models?”
Trends in Neurosciences, April 2004.
4-Yoshida,W. & Ishii,S., “Resolution of Uncertainty in Prefrontal Cortex”
Neuron 50, 781–789, 2006.
5- Butz,M.V., “MIND RACES: From Reactive to Anticipatory Cognitive Embodied
Systems”, Cognitive Systems,2005.
6- Sun,R. & Berthouze,L. & Metta,G., “Epigenetic robotics: modelling cognitive
development in robotic systems”, Cognitive Systems Research,2004
7- Polezzi,D. & Lotto,L. & Daum,I. & Sartori,G. & Rumiati,R., “Predicting
outcomes of decisions in the brain”, Behavioural Brain Research 187 (2008)
116–122.
8- Tanaka,S.C. & Samejima,K. & Okada,G. & Ueda,K. & Okamoto,Y. & Yamawaki,S.
& Doya,K., “Brain mechanism of reward prediction under predictable and
unpredictable environmental dynamics” ,Neural Networks 19 (2006)
References
9- Cohen,M.X. & Ranganath,Ch.,“Reinforcement Learning Signals Predict Future
Decisions”,
J.NeuroSci,27(2)371-378,2007371-378,2007.
10- Amemori,K.I. & Sawaguchi,T.,”Contrasting Effects of Reward Expectation
on Sensory and MotorMemories in Primate Prefrontal Neurons”,Cerebral
Cortex,16:1002-1015,2006
11- Coricelli,G. & Dolan,R.J. Sirigu,A., “Brain, emotion and decision making: the
paradigmatic example of regret”, TRENDS in Cognitive Sciences Vol.11
No.6,2007.
12- Brown,J.W. & Braver,T.S., “A computational model of risk, conflict, and
individual difference effects in the anterior cingulate cortex”, Brain
Research-37062. (2007)
13- Walton,M.E. & Croxson,P.L. & Behrens,T.E.J. & Kennerley,S.W. &
Rushworth,M.F.S., “Adaptive decision making and value in the anterior
cingulate cortex”, NeuroImage 36 (2007) T142–T154
14- Floresco,S.B. & Sharifi,S.G., “Amygdala-Prefrontal Cortical Circuitry
Regulates Effort-Based Decision Making”, Cerebral Cortex February
2007;17:251—260