Download PPT

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project

Document related concepts

Artificial consciousness wikipedia , lookup

Functionalism (philosophy of mind) wikipedia , lookup

Bioecological model wikipedia , lookup

George Armitage Miller wikipedia , lookup

William Clancey wikipedia , lookup

Executive functions wikipedia , lookup

Holonomic brain theory wikipedia , lookup

Anomalous monism wikipedia , lookup

Neuropsychopharmacology wikipedia , lookup

Attention wikipedia , lookup

Time perception wikipedia , lookup

Dual process theory wikipedia , lookup

Neurophilosophy wikipedia , lookup

Cognitive interview wikipedia , lookup

Neuroesthetics wikipedia , lookup

Visual selective attention in dementia wikipedia , lookup

Neural correlates of consciousness wikipedia , lookup

Introspection illusion wikipedia , lookup

Neuroeconomics wikipedia , lookup

Cognitive flexibility wikipedia , lookup

Cognitive semantics wikipedia , lookup

Neural modeling fields wikipedia , lookup

Convolutional neural network wikipedia , lookup

Eliminative materialism wikipedia , lookup

Mental image wikipedia , lookup

Nervous system network models wikipedia , lookup

Background music wikipedia , lookup

Cognitive neuroscience wikipedia , lookup

Cognitive psychology wikipedia , lookup

Stephen Grossberg wikipedia , lookup

Cognitive development wikipedia , lookup

Embodied cognitive science wikipedia , lookup

Recurrent neural network wikipedia , lookup

Neo-Piagetian theories of cognitive development wikipedia , lookup

Cognitive model wikipedia , lookup

Mental chronometry wikipedia , lookup

Transcript
Some YouTube movies:
The Neocognitron Part I:
http://www.youtube.com/watch?v=Qil4kmvm2Sw
The Neocognitron Part II:
http://www.youtube.com/watch?v=oVYCjL54qoY
Automatic license plate recognition:
http://www.youtube.com/watch?v=3GJWvsUIiyk
Evolution of neural network robotic controllers:
http://www.youtube.com/watch?v=lmPJeKRs8gE
December 1, 2009
Introduction to Cognitive Science
Lecture 22: Neural Models of Mental Processes
1
Review of Neural Network Facts
• In biological systems, neurons of similar
functionality are usually organized in separate
areas (or layers).
• Often, there is a hierarchy of interconnected layers
with the lowest layer receiving sensory input and
neurons in higher layers computing more complex
functions.
• For example, neurons in macaque visual cortex
have been identified that are activated only when
there is a face (monkey, human, or drawing) in the
macaque’s visual field.
December 1, 2009
Introduction to Cognitive Science
Lecture 22: Neural Models of Mental Processes
2
“Data Flow Diagram”
of Visual Areas in
Macaque Brain
Blue:
motion perception
pathway
Green:
object recognition
pathway
December 1, 2009
Introduction to Cognitive Science
Lecture 22: Neural Models of Mental Processes
3
Receptive Fields in Hierarchical Neural Networks
neuron A
December 1, 2009
receptive field of A
Introduction to Cognitive Science
Lecture 22: Neural Models of Mental Processes
4
Receptive Fields in Hierarchical Neural Networks
neuron A
in top layer
December 1, 2009
receptive field of A in input layer
Introduction to Cognitive Science
Lecture 22: Neural Models of Mental Processes
5
Visual Attention
The attentional cueing task introduced by Michael
Posner gives insight into the dynamics of visual
attention.
Subjects are instructed to fixate on the central cross.
One of the two boxes flashes to capture the subject’s
attention (an automatic, involuntary response).
After some a short delay (stimulus onset asynchrony SOA) an asterisk appears in one of the boxes.
The subject has to report as quickly as possible in
which box the asterisk appeared.
December 1, 2009
Introduction to Cognitive Science
Lecture 22: Neural Models of Mental Processes
6
The Posner Attention Task
x
December 1, 2009
Introduction to Cognitive Science
Lecture 22: Neural Models of Mental Processes
7
The Posner Attention Task
x
December 1, 2009
Introduction to Cognitive Science
Lecture 22: Neural Models of Mental Processes
8
The Posner Attention Task
x
December 1, 2009
Introduction to Cognitive Science
Lecture 22: Neural Models of Mental Processes
9
The Posner Attention Task
*
December 1, 2009
x
Introduction to Cognitive Science
Lecture 22: Neural Models of Mental Processes
10
The Posner Attention Task
x
December 1, 2009
Introduction to Cognitive Science
Lecture 22: Neural Models of Mental Processes
11
The Posner Attention Task
For short SOAs (< 200 ms), subjects respond faster if
flash and asterisk appear on the same side.
 Cueing of attention to relevant location allows
faster response.
For longer SOAs, subjects respond more slowly if
flash and asterisk appear on the same side.
 Inhibition-of-Return mechanism makes attention
less likely to remain on the side of the flash until the
asterisk appears.
December 1, 2009
Introduction to Cognitive Science
Lecture 22: Neural Models of Mental Processes
12
The Fröhlich Effect
The Fröhlich effect is a localization error that occurs
when observers are asked to indicate the initial
position of a fast moving stimulus.
Compared to the actual starting location, the
perceived starting location is shifted in the direction of
motion.
This perceptual illusion was named after Friedrich
Fröhlich, a German physiologist who discovered the
phenomenon more than 80 years ago.
December 1, 2009
Introduction to Cognitive Science
Lecture 22: Neural Models of Mental Processes
13
The Fröhlich Effect
Today the most widely accepted explanation of this
effect is given by the “Asynchronous Updating Model”
(Scharlau & Neumann, 2003).
This model states that the stimulus onset triggers an
attention shift towards its location.
During the shift the stimulus changes its location, and
because the conscious perception depends on the
stimulus being attended, a later position is consciously
perceived as being the first position.
December 1, 2009
Introduction to Cognitive Science
Lecture 22: Neural Models of Mental Processes
14
The Fröhlich Effect
We tried to build a quantitative, neural model of the
relevant parts of the visual system to explain this
effect.
This model includes a vision hierarchy (simple
features and small receptive fields in lower layers,
complex features and large receptive fields in higher
layers).
In this hierarchy, processing of visual input is done in
bottom-up direction, and attentional modulation
(selective enhancement of processing) works in a topdown fashion.
December 1, 2009
Introduction to Cognitive Science
Lecture 22: Neural Models of Mental Processes
15
The Fröhlich Effect Model
December 1, 2009
Introduction to Cognitive Science
Lecture 22: Neural Models of Mental Processes
16
The Fröhlich Effect - Results
December 1, 2009
Introduction to Cognitive Science
Lecture 22: Neural Models of Mental Processes
17
The Fröhlich Effect - Results
December 1, 2009
Introduction to Cognitive Science
Lecture 22: Neural Models of Mental Processes
18
The Fröhlich Effect - Results
December 1, 2009
Introduction to Cognitive Science
Lecture 22: Neural Models of Mental Processes
19