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Cognition, Brain and Consciousness: An Introduction to Cognitive Neuroscience
Edited by Bernard J. Baars and Nicole M. Gage
2007 Academic Press
Chapter 3 Neurons and Their Connections
“There is no more important quest in the whole of science probably than the attempt to understand those
very particular events in evolution by which brains worked out that special trick that enabled them to add to
the scheme of things: color, sound, pain, pleasure, and all the facets of mental experience.”
Roger Sperry, 1976
Cognition, Brain and Consciousness: An Introduction to Cognitive Neuroscience
Edited by Bernard J. Baars and Nicole M. Gage
2007 Academic Press
Chapter Outline
1.0 Introduction
2.0 Working assumptions
3.0 Arrays and maps
4.0 How neural arrays adapt and learn
5.0 Coordinating neural nets
6.0 Summary
Cognition, Brain and Consciousness: An Introduction to Cognitive Neuroscience
Edited by Bernard J. Baars and Nicole M. Gage
2007 Academic Press
1.0 Introduction
Real and idealized neurons
A single bipolar neuron
Cortical neurons may have 10,000
dendrites (input fibers) and 1 or more
axons (output fibers)
An idealized neuron
A simplified neuron with dendrites
shown on top and axon at the bottom
Cognition, Brain and Consciousness: An Introduction to Cognitive Neuroscience
Edited by Bernard J. Baars and Nicole M. Gage
2007 Academic Press
1.0 Introduction
Excitation and inhibition
Neurons are connected through synapses
which can be excitatory or inhibitory
The probability that the next neuron will fire
a spike will be increased if it an excitatory
connection or decreased if it is an inhibitory
connection
Cognition, Brain and Consciousness: An Introduction to Cognitive Neuroscience
Edited by Bernard J. Baars and Nicole M. Gage
2007 Academic Press
1.0 Introduction
Neural computation
Simplified -- idealized -- neurons are used
in artificial neural nets (ANN) to model
many brain functions.
ANNs are artificial but they have provided
understanding of ways neural computation
might work in the brain.
Cognition, Brain and Consciousness: An Introduction to Cognitive Neuroscience
Edited by Bernard J. Baars and Nicole M. Gage
2007 Academic Press
2.0 Working Assumptions
Starting simple: receptors, pathways, and circuits
Six working assumptions:
1.
2.
3.
4.
5.
6.
Neurons work using an integrate-and-fire action
Connections are either excitatory or inhibitory
Idealized neurons are used in artificial neural nets to model brain function
Neurons typically form two-way pathways, providing the basis for reentrant connectivity
The nervous system is formed into arrays or maps of neurons
Hebbian cell assemblies underlie the change from transient to stable,
lasting connections
Cognition, Brain and Consciousness: An Introduction to Cognitive Neuroscience
Edited by Bernard J. Baars and Nicole M. Gage
2007 Academic Press
3.0 Arrays and Maps
Maps flow into other maps: The nervous system often uses layers of neurons in
giant arrays.
Cognition, Brain and Consciousness: An Introduction to Cognitive Neuroscience
Edited by Bernard J. Baars and Nicole M. Gage
2007 Academic Press
3.0 Arrays and Maps
Neuronal arrays usually have two-way connections
Cognition, Brain and Consciousness: An Introduction to Cognitive Neuroscience
Edited by Bernard J. Baars and Nicole M. Gage
2007 Academic Press
3.0 Arrays and Maps
Sensory and motor systems work together
Cognition, Brain and Consciousness: An Introduction to Cognitive Neuroscience
Edited by Bernard J. Baars and Nicole M. Gage
2007 Academic Press
3.0 Arrays and Maps
Temporal codes: spiking patterns and brain rhythms
Neurons have different spiking
codes. These two electrode
traces show the voltage of
simulated neurons with differing
spiking codes
Cognition, Brain and Consciousness: An Introduction to Cognitive Neuroscience
Edited by Bernard J. Baars and Nicole M. Gage
2007 Academic Press
3.0 Arrays and Maps
Choice-points in the flow of information
Ambiguous figures such as the face-vase illusion (a) and Necker cube (b) pose
points at which the brain must make a decision or choice about how to perceive
and interpret sensory input.
Cognition, Brain and Consciousness: An Introduction to Cognitive Neuroscience
Edited by Bernard J. Baars and Nicole M. Gage
2007 Academic Press
4.0 How Neural Arrays Adapt and Learn
Hebbian learning: ‘Neurons that fire together, wire together’
Donald Hebb was one of the most influential theorists
for cognitive science and neuroscience. He clarified the
notion of the cell assembly and proposed the bestknown learning rule for neural networks
Cognition, Brain and Consciousness: An Introduction to Cognitive Neuroscience
Edited by Bernard J. Baars and Nicole M. Gage
2007 Academic Press
4.0 How Neural Arrays Adapt and Learn
Neural Darwinism: survival of the fittest cells and synapses
An example of Neural Darwinism in learning: stages of encoding a neural
activation pattern until dynamic synaptic activity allows permanent connections to
be strengthened, allow memories to be stored
Cognition, Brain and Consciousness: An Introduction to Cognitive Neuroscience
Edited by Bernard J. Baars and Nicole M. Gage
2007 Academic Press
4.0 How Neural Arrays Adapt and Learn
Symbolic processing and neural nets
A network which represents a large set of
propositions such as ‘a robin is a bird’
and ‘a rose has petals’.
Cognition, Brain and Consciousness: An Introduction to Cognitive Neuroscience
Edited by Bernard J. Baars and Nicole M. Gage
2007 Academic Press
5.0 Coordinating Neural Nets
An activation map of visual areas
active while a subject is watching a
movie. Note the correlation of neural
activity in the left hemisphere (top of
figure,marked with ‘l’) and the right
hemisphere, (bottom of figure, marked
with ‘r’) across differing visual areas
such as V3 and V4.
Cognition, Brain and Consciousness: An Introduction to Cognitive Neuroscience
Edited by Bernard J. Baars and Nicole M. Gage
2007 Academic Press
6.0 Summary
A basic question in cognitive neuroscience is
how nerve cells combine to perform complex
cognitive functions such as perception,
memory, and action. While neurons form the
basic building block of cognition, we are still
unfolding how they work both as individual
cells and in synchrony in large scale arrays.
Some working assumptions about how
neurons work -- such as the integrate-andfire neuron, two-way pathways, cell
assemblies and artificial neural nets -- have
allowed scientists to begin to model the
complex and dynamic activity in the brain
that underlies human cognition.