Cognitive Neuroscience
and Embodied Intelligence
Memory and Learning
Based on book Cognition, Brain and Consciousness ed. Bernard J. Baars
courses taught by Prof. Randall O'Reilly, University of Colorado, and
Prof. Włodzisław Duch, Uniwersytet Mikołaja Kopernika
and http://wikipedia.org/
http://grey.colorado.edu/CompCogNeuro/index.php/CECN_CU_Boulder_OReilly
http://grey.colorado.edu/CompCogNeuro/index.php/Main_Page
Janusz A. Starzyk
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Introduction
 Learning is the
process by which we
acquire knowledge
about the world.
 Learning involves
memory to store
representations that
reflect experience,
behavior and values.
 Human memory has surprising limitations and impressive
capacities.
 Brain evolved around tasks of survival, thus it is well prepared to
deal with ill-defined problems and challenges in real world.
 Its ability to remember academic information is quite recent and
not as well developed in terms of storage capacities.
 Humans are exceptionally flexible in learning new skills.
 It is amazing that practically the same brain was serving humans to live in
the stone age and was able to learn the skills needed in the age of
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computers and Internet.
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Memory
 Memory is the process by
which that knowledge of
the world is encoded,
stored, and later
retrieved. (Kandel 2000)
 Memory storage involve
synaptic changes in
cortex.
 Correlated activities
between neurons leads to
strengthening connections
between them.
 Temporary cell activities
maintain immediate
memories.
 Medial temporal lobes
(MTL) are important for
building memories.
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General remarks
Memory is any persistent effect of experience.
Memory is seemingly uniform, but in reality it is very differentiated:
spatial, visual, aural, recognition, declarative, semantic, procedural,
explicit, implicit …
Here we test mechanisms, so the primary division is:
 Synaptic memory (physical changes in synapses), long-term and
requiring activation to have some influence on functioning.
 Dynamic memory, active, temporary activations, affects current
functioning.
 Long-term priming, based on synaptic memory, yielding to fast
modification – semantic and procedural memory are the result of
slow processes.
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 Short-term priming, based on active memory.
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General remarks
Memory Types
STM
LTM
Working memory
Short term memory
Long term memory
Nondeclarative
Declarative
Facts
Events
Parietal cortex
Prefrontal cortex
Limbic system
Manual
skills
Conditioning
Emotional
Nuclei
Priming
Motor
Cerebellum
Neocortex
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Memory
 MTL (perirhinal cortex)
include two hippocampi
and olfactory area.
 MTL interacts with the
higher level visual area:
inferior temporal lobe (IT)
 Close to MTL is auditory
cortex and amygdala
responsible for emotions
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Memory
 Thus MTL (perirhinal cortex)
integrates multiple brain inputs.
 It is a “hub of hubs”.
 Hippocampus combines
cognitive information from
neocortex with emotional
information from limbic areas
and bids this information into
memory that codes consciously
experienced events.
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Memory
 MTL helps to store and retrieve episodic memories.
 When visual cortex is activated by an image of the coffee cup it
activates memory traces through MTL.
 These include semantic associations of the coffee cup such as coffee
beans or the coffee aroma.
 Visual features like cup handle are also activated.
 This may activate episodic memory of yesterday’s coffee with a friend8
in cafeteria and traces of conversation.
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Memory
 Sensory input goes to working memory (WM).
 Working memory temporarily retains small amounts of
information; only 4-7 items can be held in immediate WM.
 WM interacts with cognitive processes to perform explicit learning
and retrieval as well as implicit learning.
 Explicit learning involves semantic memory (facts), episodic
memory (episodes) and perceptual memory (learning music, art).
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Implicit memory (fear, habits, biases, goals)
Memory
 Explicit memory is first acquired
through association areas of
the cerebral cortex, namely
prefrontal, limbic and parietooccipital-temporal.
 Then, the information is
transferred to parahippocampal
cortex, entorhinal cortex
dentate gyrus, hippocampus,
subiculum and back to
entorhinal cortex.
 Damage to parahippocampal and entorhinal cortices produces greater
deficits in memory storage for object recognition than does hippocampal
damage.
 Right hippocampal damage produces greater deficits in memory for
spatial representation, whereas left hippocampal damage produces
greater deficits in memory for words, objects or people.
 In either case, the deficits are in formation of new, long-term memory;
old memories are spared.
www.unmc.edu/physiology/Mann/mann19.html
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Memory
The relative positions of parts of the limbic system
involved in learning and memory. (Kandel, 2000
Principles of Neural Science. )
 Current thought is that the hippocampal system does the initial steps in
long-term memory storage–different parts being more important for
different kinds of memory.
 The results of hippocampal machinations–presumably memories–are
transferred to the association cortex for storage.
www.unmc.edu/physiology/Mann/mann19.html
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Memory
 Implicit memory
contains procedural,
emotional and motor
skills.
 Implicit memory is
often tested using
priming where subjects
receive subconscious
perceptual or
conceptual
information.
 Perceptual memory refers to sensorimotor habits (skills) largely
unconscious involving basal ganglia.
 Imagine riding a bike and you start falling to the right – WHAT TO DO?
 Conscious answer is to lean to the left (many cyclists say this)
 However when they ride a bike they instead turn their handlebar in the
direction of the fall, expressing unconscious procedural knowledge.
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Amnesia
 Clive Wearing suffered a viral infection
that destroyed hippocampi and some
frontal lobe areas.
 He retained his skills as musician, but he
did not remember the most recent past.
 Some of his short term memory was
preserved so he could converse, and be
aware of the present.
 However he could not remember events
from the recent past.
 For instance he would talk to his wife and
few minutes later he forgot she was
there.
 He couldn't register episodic or semantic
memory.
 Ne couldn't recall episodic memory.
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Amnesia
 The most important patient in cognitive neuroscience is known as HM.
 His medial temporal lobes were surgically removed by a surgeon who
was unaware about their importance for memories.
 HM cannot not remember any events in his life after the surgery.
 He even cannot recognize his face due to changes over the years.
 He also suffers from retrograde amnesia and does not remember events
from years immediately before surgery.
 His other cognitive functions are intact: he can reason, solve problems
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and carry normal conversation.
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Amnesia
 HM represents amnesia in its pure form.
 In general amnesia is any loss of episodic
memory with otherwise normal cognitive
functions.
 The causes include infections, stroke, tumor,
drugs, oxygen depravation, epilepsy,
degenerative disease (like Alzheimer) or be
of psychogenic nature.
 Amnesia results from damage to MTL
including hippocampi and causes:
 Impaired memory but preserved perception,
cognition, intelligence, and action.
 Impaired long term but not working memory
– Amnesic people can perform normally on standard tests of intelligence
– They can play chess, solve crossword puzzles, comprehend instructions, and
reason logically
 Impaired recent but not remote memories (anterograde amnesia).
 Impaired explicit but not implicit memory
– Learning, retention, and retrieval of memory without awareness is normal.
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Amnesia
 Implicit and procedural memories are not
damaged in amnesia.
 Perceptual priming involve sensory cortex
 Conceptual priming include word
association.
 Patients with amnesia perform well on
perceptual and conceptual priming tasks
 Patients with Alzheimer disease perform well
on perceptual but not on conceptual priming
tasks
 Procedural memory depends on perceptual-motor regions like basal ganglia.
 HM patient was able to learn and retain some motor tasks even he did not remember
learning them.
 Patients with impaired basal ganglia due to Parkinson’s or Huntington’s disease show not
improvement after practicing sensorimotor tasks.
 In serial time reaction (STR) tasks subjects are requested to retrace a series of dots
on a computer screen
 Amnesic patients do well on implicit STR task but poorly on explicit tasks.
 Patients with basal ganglia disorders like Parkinson’s disease do poorly on both tasks
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3 regions
PC – rear parietal cortex and motor
cortex; distributed representations,
spatial memory, long-term priming,
associations, deductions, schemes.
FC – prefrontal cortex, isolated
representations, disruption control,
working memory.
HC – hippocampus formation, episodic
memory, spatial memory, declarative memory, sparse representations,
good image separation.
Slow learning, statistically relevant relationships => procedural and
semantic memory, cortical; fast => episodic, HC.
Retaining active information and simultaneously accepting new
information, eg. multiplying in your head 12*6, requires FC.
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Slow/rapid learning
A neurons learns situational
probability, correlations between
the desired activity and input
signals; optimal value of 0.7 is
reached rapidly only with a small
learning constant of 0.005
Every experience is a small fragment of uncertain, potentially useful
knowledge about the world => stability of one's image of the world requires
slow learning, integration leads to forgetting individual events.
Relevant new information is learned after a single exposure.
Lesions in the formation of the hippocampus cause subsequent amnesia.
The neuromodulation system reaches a compromise of stability/plasticity.
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Complementary learning systems
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Active memory and priming
Distributed overlapping representations in the PC
can efficiently record information about the world, but
this is not very precise and blurs with the passage of
time.
FC – prefrontal cortex, stores isolated
representations; increases memory stability.
The effects of priming are evident in people with a
damaged hippocampus, cortical priming in the PC is
possible.
We will differentiate many forms of priming:
 length (short-term, long-term),
 type of information (visual, lexical),
 similarity (repetition, semantic).
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Priming
Standard: completing roots, after reading a list of words we get a root
and must add the ending, eg.
rea--If reaction was on the list earlier, then it is usually chosen.
The interval of time can be about an hour, so active memory can't be
responsible for this.
Homophones: read, reed.
Completion: "It was found that the ...eel is on the ...", in which the last
word is "orange, wagon, shoe, table” is heard as:
"peel is on the orange",
"wheel is on the wagon",
"heel is on the shoe"
"meal is on the table".
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Priming model
Project wt_priming.proj, Chapter 9 from
(http://grey.colorado.edu/CompCogNeuro/index.php/CECN1_Wt_Priming)
View Events: the first 3 have the same input images, but different output images, in
total 13 pairs x 2 outputs = 26 combinations, IA - IB
Attention: we're not yet learning the AB-AC lists, just the effect of learning.
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Exploring the model
View TrainLog and evaluation of
the result:
similarity of the output image,
summarized as a yellow line, the
name of the most similar event,
measured by sm_nm = binary
errors in the names of the closest
events, part of the result not very
similar to the given: A  B.
In blue both_err = 1 only if this isn't one of the two acceptable output
images.
Noise helps to break through impasses but it also causes a small lack of
stabilisation of already-learned images.
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Further tests
Test_logs: first we will check if there are some tendencies, and then if we
can teach a network to change preference after the presentation of IA
and then IB.
wt_update=Test, Test does one epoch, check Trial1_TextLog:
ev_nm is either IA, or IB, and sm_nm is either 0 or 1, randomly.
In Epoch1_TextLog we can see that there is always one of the two
results, in sum 13/26, or half the time: there is no tendency.
We check whether one exposure changes anything.
wt_update => On_Line, learning after every event,
Run Test, the frequency increases significantly to 18 and then 25 times.
Conclusions: just error reduction gives mixed outputs A and B, a network
without kWTA won't learn this task.
The parietal cortex can be responsible for long-term priming.
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AB-AC Learning
People are able to learn two lists, word pairs A-B, and then A-C, eg.
window-mind
bike-trash
....
and then:
window-train
bike-cloud
without greater interference, doing well on tests for AB and AC.
Networks with only error correction forget catastrophically!
Interference results from using the same elements and weights to learn
different associations.
It's necessary to use different units, or to learn with context.
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AB-AC Model
Project ab_ac_interference.proj
(http://grey.colorado.edu/CompCogNeuro/index.php/CECN1_ABAC_List_Learning)
View Events_AB, Events_AC,
Output: either A, or C, the context differentiates.
Replication of catastrophic learning:
View: Train_graph_log, red = errors, yellow = tests for AB.
The test shows that after learning AC, the network forgets AB, many
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units
in
the
hidden
layer
take
part
in
the
learning
of
both
lists.
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AB-AC Model
hid_kwta 12=>4 to decrease the number of active elements.
The test, but without changes.
Increase the variance of initial values.
wt_var 0.25=>0.4
Stronger influence of context
fm_context 1=>1.5
Hebbian learning hebb 0.01=>0.05
Decrease the rate of learning lrate => 0.1, Batch
Nothing here clearly helps but the catastrophes are less likely...
Two systems of learning are clearly necessary, a fast one and a
slow one – cortex and hippocampus.
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How memories are made?
 Traditional thinking of memory as a permanent record Memories Are Made Of This
of past events that can be played back, examined
and retrieved is false.
 Memories of past events are in fact rarely accurate.
 Two people experiencing the same event may have
different memories of it.
 The process view, considers memory as a result of a
dynamic process, a reconstruction of the past
influenced by present, anticipation of future events
and other cognitive processes.
 We forgot most of what happened within minutes or
hours and what remains is distorted by our
knowledge and biases.
 Try to reconstruct what you did two weeks ago with as
much detail and exact order as you can.
 Most of us will try to search for cues to figure out the
sequence of events.
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– Did I go shopping and which stores I visited?
– What merchandise did I look at?
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How memories are made?
 You may confuse what happened two weeks ago
with what happened some other time.
 Patients with disorder called confabulation make up
false memories without intention of lying or
awareness that they are not true.
 Memories influence how other memories are
formed and retrieved.
 They influence our thoughts and actions, and are
influenced by them.
 Stimulation of temporal lobe sometimes results in flood of conscious
memories. One patient during brain stimulation experienced memory of:
 At four electrodes location 1-2 and 9-10 re-experiencing Flinstone cartoons
from childhood
 At locations 8-9 and 13-14 hearing the rock band Pink Floyd.
 At locations 9-10 a baseball announcer.
 At locations 7-8 and 12-13 a female voice singing.
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How memories are made?
 What happens in the nervous system to
produce habituation?
 If the siphon of the animal (Aplysia
californica ) is stimulated mechanically
the animal withdraws the gill,
presumably for protection.
 That action is known to occur because
the stimulus activates receptors in the
siphon, which activates, directly or
indirectly through an interneuron, the
motoneuron that withdraws the gill.
 This is a simple reflex circuit.
 With repeated activation, the
stimulus leads to a decrease in the
number of dopamine-containing
vesicles that release their contents
onto the motor neuron.
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From
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www.unmc.edu/physiology/Mann/mann19.html
How memories are made?
Autobiographical memories evoked by temporal lobe stimulation
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How memories are made?
 Possible explanation for this electrically stimulated recall of memories
involves temporal lobe in neocortex.
 If some neurons are activated in neocortex, this evokes an overlapping
pattern of neural activation in hippocampal system (MTL).
 The flow of information form neocortex to MTL causes hippocampal
system to resonate with the original memory traces, to produce the
original episodic experience in neocortex.
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How memories are made?
 Most synapses in cortex are
excitatory using
neurotransmitter glutamate.
 A large minority are
inhibitory using
neurotransmitters like
GABA (gamma amino
butyric acid).
 These two processes are
called long term
potentiation (LTP) and long
term depression (LTD).
 LTP has been observed in
hippocampus using single
cell recording.
A schematic of a single cell recording in hippocampus
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Hippocampus
Anatomy and connections of the
structures of the hippocampal
formation: signals reach from uniand multimodal association areas
through the Entorminal Cortex
(EC).
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More anatomy
Hippocampus = king of the cortex
Bidirectional connections with the
entorhinal cortex:
olfactory bulb,
cingulate cortex,
superior temporal gyrus (STG),
insula,
orbitofrontal cortex.
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More anatomy
Sporadic activation
Representations in CA3 and CA1
are focused on specific
stimuli, while in the
subiculum and the entorhinal
cortex they are strongly
distributed.
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Hippocampal formation
Model contains structures:
dentate gyrus (DG),
areas CA1 and CA3,
entorhinal cortex (EC).
Pct Act = % of activation.
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How memories are made?
 Many millions of neurons and billions of synapses are
involved in LTP or LTD.
 Based on evidence from EEG, ERP, and fMRI we can
suppose that formation of long term memories involves:
 Episodic input is presented via neocortex.
 It is integrated for memory purpose in the MTL (medial
temporal lobes) involving hippocampi and related
structures and perhaps thalamus and surrounding regions.
 Consolidation: MTL and related regions bind and integrate
a number of neocortical regions in the process that
transforms temporary synaptic connections into longer
lasting memory traces in both MTL and neocortex.
 The main mechanism used is LTP and LTD.
 Normal sleep is important to form long-lasting memory
traces.
 More permanent memories require protein synthesis –
such as growth of dendritic spikes on the top of axons
and dendrites.
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How memories are made?
 The steps of learning, binding, consolidation and remembering.




When a new event is learned cortex activates MTL
Cortex and MTL resonate to establish the memory traces in a binding step
In consolidation the resonance continues without external support
Upon presentation of the original event's cue, MTL and cortex resonate to
recall the stored memories.
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How memories are made?
 Reconsolidation turns active
neuronal connections into
lasting ones.
 We have two kinds of
reconsolidations: cellular
and system reconsolidation.
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How memories are made?
 Rapid consolidation occurs within minutes to hours from learning event.
 It correlates with morphological changes in synapses.
 If the stimulus is intense or repeated then gene transcription and protein
formation lead to long lasting changes including creation of new
synapses to form long lasting memory.
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How memories are made?
 Nadel and Moskovitch concluded
that contrary to the standard
consolidation model, MTL is needed
to represent even old episodic
memories for as long as these
memories exist.
 MTL neurons act as pointers to
neocortical neurons that represent
the experience.
 Neocortex, on the other hand, is
sufficient to represent repeated
experiences with words, objects,
people and environment.
 MTL may help in initial formation of
these neocortical traces, but once
formed they can exist on their own.
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Varieties of Memories
 Declarative memory
can be divided into
episodic and semantic
memory.
 Episodic memory have
specific source in time,
space and events.
 It allows us to go
back in time and
relieve the
experience.
 Semantic memory
involve facts about the
world, ourselves and
other knowledge.
 We know which city
is a capital of France
or where are the
great pyramids.
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Varieties of Memories

Episodic memories:
1.
Have reference to
oneself
Are organized around
specific time period
Are remembered
consciously such that
we can relive them
Are susceptible to
forgetting
Are context dependent
w.r.t. time, place,
relationships etc.
2.
3.
4.
5.
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Varieties of Memories

Semantic memories:
1.
Have reference to
shared knowledge
Are not organized
around specific time
period
Give a feeling of
knowing rather than
recollection of a
specific event.
Are less susceptible to
forgetting than events.
Are relatively context
independent.
2.
3.
4.
5.
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Varieties of Memories


In a study subjects were
asked to tell if they
remember the item or
“know” the item.
The act of remembering
(episodes) resulted in
higher brain activation
than the “feeling of
knowing” (semantic)
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Varieties of Memories

Episodic memories may
turn into semantic
memories over time




Initially memories are
episodic and context
dependent
Over time, episodic
memories are
transformed into semantic
memories
MTL is important for
recovering episodic
memories, which are
linked by specific
autobiographical context
Episodic memories in Fig. show a man cooking on a barbecue, giving
flowers to a lady, painting a picture and playing golf.

A semantic network above combines all these specific episodes into a
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simplified
knowledge
of
a
man
who
BBQs,
loves,
paints,
and
plays
golf.
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Varieties of Memories

Learning is often thought
to require consciousness
and paying attention.

It certainly helps to learn
by being aware of it
It is a basic learning
strategy for humans.


However there are some
evidence for learning
without consciousness
especially with emotional
stimuli.
Fig. from: http://universe-review.ca/R10-16-ANS.htm

The terms explicit and implicit memories are used in context of
remembering.

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Explicit (declarative) memory requires conscious awareness
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Varieties of Memories




Prefrontal cortex (PFC) is critical for
working memory
Lesions of PFC impaired performance
in delayed response tasks.
Fuster (1971) experimented with
monkeys – they were trained to
remember a color for a short period of
time and then point to a correct color
when presented with two choices.
Through implanted electrodes he
observed sustained neurons activities
over the delay period in the area of
dorsolateral (DL) PFC
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Varieties of Memories






Prefrontal cortex (PFC) serves to support the mental work
performed on stored information rather than as a site of storage
itself.
Its primary function is to modulate activity in other cortical areas
where the items in memory are stored.
PFC enhances the relevant information in the memory and inhibits
irrelevant information.
When the information is relevant to a specific item in the memory,
then ventral part of PFC is involved
When the information regards the relations between many items,
then dorsal part of PFC is involved.
Anterior (frontal) regions of PFC are involved with coordination and
monitoring activities among different PFC regions to implement
higher order functions such as planning.
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Varieties of Memories



Combined brain regions work
together for visual working
memory.
Hippocampus may encode new
memories, while MTL may
combine them with pother
modalities and IT is involved in
high level visual object
representation.
DL-PFC and anterior PFC is
involved in short term
maintenance of relations
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Varieties of Memories
Clive Wearing knows that
something is wrong as he
always lives in present
time.
He has a metacognitive
concept of his own
cognitive functions.
A person may recall an
episode using semantic
cue and vice versa.

For effective retrieval the retrieved information must overlap with
learned and encoded one – the person must have a goal to retrieve it.

MTL is mostly involved in retrieving episodic memory.

Poor frontal function impairs tests on the source of memory and
temporal order.

Semantic memory both learning and retrieval depend more on the52left
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Varieties of Memories









Other kinds of memory may involve other brain structures.
The amygdala mediates fear conditioning.
The cerebellum and basal ganglia are needed for habits and skills,
and subconscious conditioning.
The thalamus is information hub constantly trading signals with
cortex.
Perceptual and motor learning involve the dynamic organization of
cortical maps.
Brain surgery can alter body maps – this is related to brain
plasticity.
Life is a development process of learning, adaptation and memory
formation.
New neurons are being born throughout the lifetime starting from
stem cells.
The ongoing placement of the neurons involves dynamic learning
and adaptation process.
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Varieties of Memories
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Overview of multiple learning systems in the brain
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Separation and conjunction of images
The hippocampus rapidly associates
various representations of the cortex.
Creates episodic memory
Completes activations recreated
from the memory and separates them
into clearly distinct meanings
Sparse encoding eases the
separation of meanings
CA1 separates by conjunction of images
(representations)
It's also able to recreate the original
activation from the EC by reversible
connections
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Model of the hippocampus
Project hip.proj
(http://grey.colorado.edu/CompCogNeuro/index.php/CECN1
_Hippocampus)
Input signals enter through the entorhinal
cortex (EC_in), to the dentate gyrus
DG and the CA3 area,
DG also influences CA3, where received
signals can be completed through
associations.
CA3 has strong internal connections. CA1
has more distributed sparse
representations => EC_out.
EC: 144 el = 4*36; 1 of 4 active.
DG: 625 el, CA3: 240 el
CA1: 384 el = 12 col * 32 el
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Exploration of the hippocampal model
Learning of AB – AC associations without interference.
Autoassociations: EC_in = EC_out, reversible transformations.
BuildNet, View_Train_Trial_Log will show the statistics.
The input includes information about the input and output images and
the list.
StepTrain: units chosen in the previous step have white outlines.
Partial overlapping of images in EC_in, DG, CA3, CA1.
Training epoch: 10 list elements + 3 test sets: AB, AC, new
View Test_Logs => text and graph log
train_updt = no_updt to the test log,
Run will do 3 epochs, the results are in Text_log, 70% remembered from
the AB list and 100% from the AC list.
Set test_uodt = no_updt, the network will more rapidly finish 3
training/test epochs.
Test analysis: test_updt = Cycle_updt, Clear Trial1_1_Text_log
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StepTest, we see only A + context, we see how the image completes.
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Further exploration
Targ in Network shows what image was learned, act  targ
In TextLog,
stim_er_on = proportion of units erroneously activated in EC_out,
stim_er_off = erroneously not activated in EC_out.
In Trial_1_GraphLog we can see these two
numbers after every test, for known images
they're small, correct memories,
for new ones they're large, but on ~0,5 and off
~0.8, the network rarely fails.
To move to list AC we turn off Test_updt = Trial_updt (or no_updt)
and StepTest until in text_log, epc_ctrl changes to 1. These are events
for list AC: the network does not recognize them (rmbr=0) because it
hasn't learned them yet.
Train_Epcs=5, train_env=Train_AC,
Run and check results.
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Summary
The hippocampal model can rapidly, sequentially learn associations
AB – AC without excessive interference. For this it was sufficient to
use the Hebbian contrast rule, CPCA and the correct architecture.
Interference results from using the same units, in CA3 it arrives at
separation of identical images (representations) learned in another
context.
Separation of images doesn't allow associations, inferences based on
similarity, efficient encoding of multidimensional information.
The conjunction of images happens in CA1.
This suggests a complementary role of the hippocampus,
supplementing the slow learning mechanisms of the cortex.
The hippocampus can remember episodes helping in spatial
orientation, create conjunctive representations connecting different
stimuli together quicker than the cortex.
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Memory
Memory is not uniform
1.
Weights (long-term, require activation) vs activations (short-term,
already activated, can influence processing)
2.
Based on weights


3.
The cortex has initial states but suffers from catastrophic influences.
The hippocampus can learn fast without influences, using sparse
distributed representations of images
Based on activation


The cortex shows initial states but
isn't good for short-term memory
4.
Cooperation of activation and memory based on weights
5.
Video
1.
2.
short-term memory in chimpanzees -30 sec
Comparison with students– 30 sec
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Active short-term memory
Short-term priming: attention and influence on reaction speed.
Besides the duration, memory content and effects resulting from similarity are like
long-term priming.
Project act_priming.proj. (http://grey.colorado.edu/CompCogNeuro/index.php/CECN1_Act_Priming)
Completing roots or homophony, but without learning, only the influence of the
remains after the last activation.
The network has learned series IA-IB.
The test has a series of images and results A and B, we show it A upon output,
the network responds A; now we show the image for B but only phase is turned
on – (lack of learning), the network's result is sometimes A, sometimes B.
LoadNet, View TestLogs,Test
The correlations of previous results A and B depend on the speed of fading of
activation; check efekt act_decay 1 => 0, tendency to leaving a.
Analyze the influence on results in test_log.
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Active maintenance
Project act_maint.proj (http://grey.colorado.edu/CompCogNeuro/index.php/CECN1_Active_Maintenance):
active maintenance of information in working memory despite
interference, quickly accessible, doesn't require synaptic changes.
Recurrence is necessary, an attractor network with a large pool of
attraction, resistant to noise.
Video – remembering with delay – 30 sec
The processes of analysing environmental data don't require such networks,
because they are steered by incoming information.
Activation should diverse, enabling associations and inferences, while we
have external signals this will suffice, eg. if we note on paper the results of
intermediate operations.
With a lack of external activations, we have to rely on actively maintained
representations in working memory, which has serious limits (famous
Miller's 72, and even 42 for complex objects).
First a model without attractors, which requires external signals, then
distributed representations, but shallow attractors, not very resistant to
noise; in the end deep but localised attractors, which disable associations.
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Maintenance model
Project act_maint.proj.
3 objects, 3 elements (features)
r.wt, View Grid_log, Run: if there is an input activation is maintained, but
after removal it disperses (the network blurred...).
Check influence wt_mean =0.5, wt_var = 0.1, 0.25, 0.4
Net_Type Higher_order: we add combinations of feature pairs.
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Defaults, Run, add noise_var=0.01, the network forgets...
Isolated representations
Default to return to initial parameters.
network = IsolatedNet
Lack of connections between hidden units, but
there is recurrence, activation doesn't fade.
Noise = 0.01 doesn't interfere, but with 0.02
sometimes gets ruined.
Is it worth learning to focus in spite of noise?
Different task: does stimulus S(t) = S(t+2)?
Parameters: input_data = MaintUpdateEnv,
network Isolated, noise 0.01
Init, Run: there are two inputs, Input 1 and 2,
wt_scale 1=>2, changes the strength of local connections.
The network can be switched from fast actualization to long-lasting
maintenance.
How to do this automatically?
Dopamine and dynamic regulation of reward in the PFC.
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Working memory
The prefrontal cortex plays the central role in
maintaining active working memory and has desired
properties: isolated self-activating attractor networks
with extensive pools.
Neuroanatomy, PFC connections and microcolumns =>
specialized area for active memory.




A. PR – spatial.
B. PR - spatial, self-ordered tasks.
C. PR - spatial, object and verbal, self-ordered tasks and analytical
thinking.
D. PR - objects, analytical thinking.
Typical experiments require delayed choice and show the differences
between PC, IT, which have only temporary stimulus representations,
and PFC, which maintains them longer.
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Role of dopamine
Blocking of dopamine
has a negative
influence on working
memory, and aiding it
has a positive
influence.
TD – temporal
Difference in RL
Dopamine (DA) arrives
from the VTA (ventral
tegmental area).
DA strengthens
internal activations,
regulating access to
working memory.
VTA displays such
increased activity.
Basal ganglia can also regulate PFC activity.
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Basal Ganglia
Pathways: thalamus- basal ganglia - cortex.
Red lines – inhibition, mostly
GABA.
Blue lines: excitation, mostly
glutamine.
Black lines: dopamine, mostly
inhibition.
Malfunctions in these pathways
lead to Parkinson, Huntington and
other diseases.
GP – Globus Pallidus
Putamen; Substantia Nigra
Subthalamic nucleus
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Working memory
Project pfc_maint_updt.proj (http://grey.colorado.edu/CompCogNeuro/index.php/CECN1_PFC_Maint_Updt)
Dynamic "gate” AC
added to the network
with recurrence and
learning based on
temporal differences
(TD).
Inputs: A, B, C, D
Ignore, Store, Recall
decides what to do with
them
PFC is working memory, AC = adaptive critic is a reward system
(dopamine) controlling information renewal in the PFC, hidden layer
represents the parietal cortex, hidden 2 maps to the output (frontal
cortex). AC learns to predict the next reward, modulating the strength of
internal PFC connections.
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PFC Model
r.wt: one-to-one connections between input, hidden layers and the PFC.
AC has connections with the hidden layer and the PFC, but reverse
connections AC => PFC serve only to modulate.
Act, Step: we observe phases – and +, at first the activation of PFC and
AC is zero, there are two + steps, first to change PFC weights, and then
to set the correct signal propagation.
When signal R appears (reminders), the network will not act correctly at
first, the reward in AC is 0.
At first the network doesn't know what's going on, learning only on Store,
Ignore hidden layer 2, but sometimes noise in the PFC will cause the
correct result and reward to appear.
View Epoch_log, observe the change in weight of unit AC, r.wt
Weights of S => AC should increase and error will decrease, the yellow
line is the number of incorrect predictions of AC.
View, Grid_log, Clear, act, Step. Store introduces data to the PFC, but
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Ignore doesn't. After Recall, PFC is zeroed.
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PFC Model
Figures EpochOutputData:
cnt_err (black): number of errors per
epoch (100 epochs), mostly errors in
Recall.
S_da (red): average amount of
dopamine for Store, initially
decreasing (PV/LV gives initially a lot
of dopamine for all inputs), increasing
when system starts to work correctly
and number of errors goes down.
I_da (blue): amount of dopamine for
Ignore, decreases to 0, no reward.
R_da (zielona): amount of dopamine
in Recall, large fluctuations, shows
difference with expectations.
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A- not B
Interactions between active and synaptic memory - weights have already
changed but active memory is in a different state: what wins?
These interactions are visible in the developing brains of children ~ 8
months (Piaget 1954), experiments done also on animals.
A toy (food) is hidden in box A and after a short delay the child (animal)
can remove it from there. After several repetitions in A, the toy is hidden in
box B; the children keep looking in A.
Active memory doesn't work in children
as efficiently as synaptic memory,
lesions in the area of the prefrontal
cortex cause similar effects in adult
and infant rhesus monkeys.
Children make fewer errors looking in
the direction of the place where the toy
was hidden, than reaching for it. There
are many interesting variants of this
type of experiment and explanations
on different levels.
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Project A- not B
Decision-making process model: we know that information about place
and objects is divided, so this information is given on input: place A, B, C,
toy T1 or T2 and cover C1 or C2.
Synaptic memory is realized with the help of standard CPCA Hebbian
learning, and active memory as bi-directional connections between
network representations in the hidden layer.
Output layers: decisions about the direction of looking and reaching.
The direction of looking is always activated
during each experience, reaching is
activated less often, only after moving the
whole set-up toward the child, so these
connections will rely on weaker learning.
Initial tendency: agreement of looking and
reaching on A (weight 0.7). All inputs
connected with hidden neurons, weight 0.3.
Project a_not_b.proj.
(http://grey.colorado.edu/CompCogNeuro/index.php/CECN1_A_Not_B)
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Experiment 1
rect_ws =0.3 decides on the strength of
recurrent activations in the hidden layer
(working memory), changing this parameter
simulates a child's development.
View Events: 3 types of events, initial showing
4x, then A 2x, then B 1 x. An event has 4
temporal segments:
1) start, pretrial – boxes covered;
2) presentation, toy hidden in A;
3) expectation – toy in A;
4) choice – possible reaching.
Only visible elements are active.
View: Grid_log, Run performs the entire
experiment, turns off display.
ViewPre shows on Grid_log, A is activated
ViewA shows A tests, after learning.
ViewB shows B tests: the network makes an error.
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Further experiments
Activation in the hidden layer flows toward the representation associated
from A.
rect_ws 0.3 => 0.75 for a mature child.
Run, ViewB
Although synaptic memory didn't change, more efficient working memory
enables the undertaking of correct action.
Try for rect_ws = 0.47 i 0.50
What happens? There is no activity – hesitation?
The results depend on the length of the delay, with a shorter delay there
are fewer errors.
Delay 3=>1
Do tests for rect_ws = 0.47 i 0.50
What happens with a very young child?
rect_ws = 0.15, delay = 3;
Weak recurrence, weak learning for A.
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Other types of memory
The traditional approach to memory assumes functional, cognitive,
monolithic, canonical representations in memory.
From modeling, it turns out that there are many systems interacting with
each other which are responsible for memory, with different
characteristics, variable representations and types of information.
Recognition memory: was an element of the list seen earlier?
A "recognition" signal is enough, remembering is not necessary.
A hippocampus model is also useful here, it allows for remembering, but
this is too much – in recognition memory the central role seems to be
played by the area of the perirhinal cortex.
Cued recall - completion of missing information.
Free recall – effects of placement on the list (best at the beginning and
the end), as well as grouping (chunking) of information.
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Learning categories
Categorization in psychology - many theories. Classic experiments:
Shepard et al. (1961), Nosofsky et al. (1994).
Problems with an increasing degree of complexity, division into
categories C1, C2, 3 binary properties: color (black/white), size
(small/large), shape (,).
Type I: one property defines the category.
Type II: two properties, XOR, np. Cat A: (black,large) or (white,small),
any shape.
Type III-V: one property + increasingly more exceptions.
Type VI: lack of rules, enumeration
Difficulties and speeds of learning: Type I < II < III ~ IV ~ V < VI
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Canonical dynamic
What happens in the brain while learning category definitions based on
examples? Complex neurodynamics <=> the simplest dynamics
(canonical). For all logical rules, we can write corresponding equations.
For type II problems, or XOR:
1 2
2
2 2
V  x, y, z   3 xyz   x  y  z 
4
V
x
 3 yz   x 2  y 2  z 2  x
x
V
y
 3 xz   x 2  y 2  z 2  y
y
V
z
 3 xy   x 2  y 2  z 2  z
z
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Feature
area
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Against majority
List: diseases C or R, symptoms PC, PR, I
Disease C is associated with symptoms (PC, I),
disease R with (PR, I); C happens 3 times more often
than R. (PC, I) => C, PC => C, I => C.
Predictions „against majority” (Medin, Edelson 1988).
Although PC + I + PR => C (60%),
PC + PR => R (60%)
Neurodynamic attractor pools?
PDF in areas {C, R, I, PC, PR}.
Psychological interpretation (Kruschke
1996): PR has meaning even though this is
a differentiating symptom, although PC is
more common. Activation PR + PC more
often leads to result R although the
gradient
in direction R is greater.
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Learning
Point of view
Neurodynamics
Psychology
I+PC is more common =>
stronger synaptic connections,
larger and deeper attractor
basins.
Symptoms I, PC are typical for C
since they happen more often.
To avoid attractors around I+PC
leading to C, a deeper and more
localized attractor around I+PR is
created.
For rare disease R, symptom I is
not distinct, so attention focuses
on PR associated with R.
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Testing
Point of view
Neurodynamics
Psychology
Activating only I leads to C since
more examples of I+PC create a
larger shared attractor basin than
I+PR.
I => C, in accordance with
expectations, more frequent
stimuli I+PC are recalled more
often.
Activation by I+PC+PR leads
frequently to C, because I+PC
puts the system in the middle of
the large C basin and even for PR
gradients still lead to C.
I+PC+PR => C because all
symptoms are present and C is
more frequent (base rates again).
Activation by PR+PC leads more
PC+PR => R because R is distinct
frequently to R because the
symptom, although PC is more
attractor basin for R is deeper, and common.
the gradient at (PR,PC) leads to R.
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Summary

Knowledge formed in memory is
 built, dynamic, continuous, appearing





Behavior and inhibition of knowledge are the result of
dynamic information processing rather than interaction
structures set at the top.
Recognition is based on the ability to differentiate
earlier-learned activations from new, unknown
activations.
The hippocampus ensures high-quality recognition
with a high threshold guaranteeing association of
earlier-learned activations.
Priming contributes to slow building of inviariant
representations
Two learning mechanisms
 Based on connection weights
 Based on neuron activation
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Summary







The cortex helps recognition by priming
The cortex leads to unstimulated associations
The cortex is responsible for working memory
cooperating with the hippocampus
Sequences of grouped representations are stored in
long-term memory
Memory based on activation requires combining
quick-actualizing with stable representations
The hippocampus uses sparse distributed
representations for fast learning without mixing ideas
Priming memory can be long-term (based on weights)
or short-term (based on activation)
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