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Introduction to Neurobiology
Yonatan Loewenstein
[email protected]
Introduction to Neurobiology
• Introduction to computational neuroscience:
Applications in the study of learning, memory and
decision making
Delayed match-to-sample task
Delayed match-to-sample task
Delayed match-to-sample task
Delayed match-to-sample task
16 sec
0.2 sec
0.2 sec
time
Activity of a single neuron in the temporal cortex
Miyashita (1988)
Activity of a single neuron in the temporal cortex
The visual system
“photoreceptors”
“ganglion cells”
“LGN”
“V1”
“temporal ctx”
F-I curve of single neurons
Berger, EPFL, unpublished
Neurons and synapses
Nelson, Brandeis
Characteristic time of
neurons and synapses is
typically ~1-100 msec
“photoreceptors”
“ganglion cells”
“LGN”
“V1”
“temporal ctx”
“photoreceptors”
“ganglion cells”
“LGN”
“V1”
“temporal ctx”
“photoreceptors”
“ganglion cells”
“LGN”
“V1”
“temporal ctx”
“photoreceptors”
“ganglion cells”
“LGN”
“V1”
“temporal ctx”
“photoreceptors”
“ganglion cells”
“LGN”
“V1”
“temporal ctx”
“photoreceptors”
“ganglion cells”
“LGN”
“V1”
“temporal ctx”
“photoreceptors”
“ganglion cells”
“LGN”
“V1”
“temporal ctx”
“photoreceptors”
“ganglion cells”
“LGN”
“V1”
“temporal ctx”
“photoreceptors”
“ganglion cells”
“LGN”
“V1”
“temporal ctx”
“photoreceptors”
“ganglion cells”
“LGN”
“V1”
“temporal ctx”
“photoreceptors”
“ganglion cells”
“LGN”
“V1”
“temporal ctx”
“photoreceptors”
“ganglion cells”
“LGN”
“V1”
“temporal ctx”
“photoreceptors”
“ganglion cells”
“LGN”
“V1”
“temporal ctx”
“photoreceptors”
“ganglion cells”
“LGN”
“V1”
“temporal ctx”
“photoreceptors”
“ganglion cells”
“LGN”
“V1”
“temporal ctx”
“photoreceptors”
“ganglion cells”
“LGN”
“V1”
“temporal ctx”
“photoreceptors”
“ganglion cells”
“LGN”
“V1”
“temporal ctx”
“photoreceptors”
“ganglion cells”
“LGN”
“V1”
“temporal ctx”
“photoreceptors”
“ganglion cells”
“LGN”
“V1”
“temporal ctx”
Activity of a single neuron in the temporal cortex
Activity of a single neuron in the temporal cortex
Questions:
• How can we explain activity that persists
for 16 sec after the disappearance of the
external stimulus
• Why some images and not others?
“photoreceptors”
“ganglion cells”
“LGN”
“V1”
“temporal ctx”
“photoreceptors”
“ganglion cells”
“LGN”
“V1”
“temporal ctx”
most inputs to cortical neurons are recurrent, coming from the
same cortical region
• How can we explain activity that persists
for 16 sec after the disappearance of the
external stimulus
• The recurrent connections in the cortex
enable persistent activity in time scales that
are much longer than the time-scale of
neurons and synapses
• Why some images and not others?
Activity of a single neuron in the cortex
one of the learned
stimuli
new
stimulus
Neurons and synapses
Nelson, Brandeis
Synapses are plastic
• What rules underlie changes in synaptic
efficacies?
Coincidence-based plasticity
Coincidence-based plasticity
Coincidence-based plasticity
Coincidence-based plasticity
Coincidence-based plasticity
Coincidence-based plasticity
Coincidence-based plasticity
Hebbian plasticity
“When an axon of cell A is near enough to
excite cell B and repeatedly or persistently
takes part in firing it, some growth process
or metabolic change takes place in one or
both cells such that A's efficiency, as one
of the cells firing B, is increased”
Donald Hebb, 1949
“Neurons that fire together wire together”
A cortical network
A cortical network
A cortical network
A cortical network
A cortical network
A cortical network
Hebbian plasticity
A cortical network
Network can sustain
activity even in the
absence of input
Specificity of sustained activity
Specificity of sustained activity
Specificity of sustained activity
Specificity of sustained activity
Specificity of sustained activity
Activity of a single neuron in the cortex
one of the learned
stimuli
new
stimulus
Difference in response can be explained as resulting
from Hebbian plasticity creating strong recurrent
connections
A model of associative memory
A model of associative memory
A model of associative memory
A model of associative memory
A model of associative memory
‘Biological’ memories
• Memories are stored in the efficacies of
synapses in the brain
• Recalled memories are represented in the
pattern of activity of neuron
new
stimulus
Learned
stimulus
Miyashita (1988)
Is Hebbian plasticity, mediated by NMDA
synapses, important for associative
memory?
Henry Gustav Molaison (1926 – 2008)
Associative memory in the CA3
region of the hippocampus
• Ample evidence for the involvement of the
hippocampus in associative memory
Neurons in area CA3 of the hippocampus
form a recurrent network in which each
neuron receives ~10,000 collateral inputs
(2% of the network)
• Synapses between
strengthened
cells
are
easily
Requirement for Hippocampal CA3 NMDA
Receptors in Associative Memory Recall
Nakazawa et al., Science (2002)
Morris water maze test
day 13
day 14
Conclusion: Hippocampal CA3 NMDA receptors are required for
associative memory recall
Can we store several patterns in this
framework?
A model of associative memory
A model of associative memory
A model of associative memory
A model of associative memory
A model of associative memory
A model of associative memory
A model of associative memory
A model of associative memory
A model of associative memory
A model of associative memory
A model of associative memory
A model of associative memory
Question:
If neurons A and B are grouped by a
memory pattern and neurons B and C
are grouped by another memory pattern,
will neuron C be activated as a result of
the activation of neuron A?
• What is the memory capacity
of the network?
‘Biological’ memories
• Associative: recall is based on content
rather than on the address
• A transient cue induces a sustained recall
• Robust to minor failures of the hardware
• Distributed
• Fast dynamics relative to the intrinsic timescale of the neuron  parallel computing