the opposite of attention is epilepsy:
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The Opposite of Attention is Epilepsy:. Six ways of thinking about attention and why you should. Everyone Knows What Attention Is. - PowerPoint PPT PresentationTRANSCRIPT
The Opposite of Attention is Epilepsy:Six ways of thinking about attention and why you should
Everyone Knows What Attention Is“Everyone knows what attention
is. It is the taking possession by the mind in clear and vivid form, of one out of what seem several simultaneously possible objects or trains of thought...It implies withdrawal from some things in order to deal effectively with others…”
William James
Everyone Knows What Attention IsJames’ definition is a good start
toward operationalizing attention
What we would call “selective attention”
As distinct from “arousal” “alerting” “cognitive effort”
Everyone Knows What Attention IsThe goal of this talk:
Give you some conceptual handholds to start thinking about attention
Tell you my (and my lab’s) line of thinking about attention
Everyone Knows What Attention IsPreview:
1. Attention solves the philosophical problem of a unitary consciousness
2. Attention solves a metabolic and thermal engineering problem
3. Attention solves a signal-to-noise problem by filtering noise
4. Attention solves a signal-to-noise problem by boosting signal gain
5. Attention solves a problem of ambiguity6. Attention solves a network complexity
problem
Everyone Knows What Attention IsNotice that none of these ideas
are exclusive of any others
They are all compatible ways to conceptualize the same phenomenon
Attention Solves a Philosophical Problem
Unitary Consciousness◦We are each one conscious self◦Attention is the phenomenological
manifestation of this constraint◦You only get one “train of thought”◦Maybe attention is “epiphenomenal”
If you are a “neurophilosopher”, this is why you should think about attention.
Attention Solves an Engineering ProblemWaste heat is both an applied
and theoretical characteristic of computation
The human brain is metabolically demanding
The cortex is a thermal engineering nightmare
If you design microprocessors, this is why you should think about attention.
Attention Solves a Signal-to-Noise Problem by Filtering “Noise”
“capacity limit” or “sensory bottleneck” notion first proposed by Donald Broadbent in the 60’s
“leaky filter” notion proposed by Anne Treismann in the 70’s
Attention Solves a Signal-to-Noise Problem by Filtering “Noise”
Evidence: Selective attention acts as a gate to awareness
Simons & Levin
If you do cognitive psychology (or neurophilosophy), this is why you should think about attention.
Attention Solves a Signal-to-Noise Problem by Filtering “Noise”What are the neural correlates of
such “gating”?
Attention Solves a Signal-to-Noise Problem by Filtering Noise Chelazzi et al. Evidence: Selective attention suppresses neurons
representing task-irrelevant features or objects
◦ Note that search array always contains a “good” stimulus for the recorded cell – but that might not be the target
Intracranial Recordings of Attentional SelectionInitial response
of cells is “classical”
Intracranial Recordings of Attentional SelectionInitial response
of cells is “classical”
Response during delay maintains a representation of the target feature
Intracranial Recordings of Attentional SelectionInitial response
of cells is “classical”
Response during delay represents the target feature
Initial response to search array is “classical”
Intracranial Recordings of Attentional Selection About 200 ms
after array onset, response of cell begins to depend on attention
◦ Response becomes more vigorous if cell is tuned to features of the target (i.e. the selected stimulus)
◦ Response becomes suppressed if cell is tuned to a non-target distractor
If you do electrophysiology: This is why you should think about attention!(note this effect is absent in anesthetized animals)
Attention Solves a Signal-to-Noise Problem by Boosting Signal Gain
Evidence: responses are faster and more accurate (memory !) for attended relative to unattended events
If you’re a cognitive psychologist, this is why you should think about attention (and probably you already do).
Attention Solves a Signal-to-Noise Problem by Boosting Signal GainEvidence: Event-Related Potentials are
enhanced for attended relative to unattended stimuli
If you do electrophysiology, this is why you should think about attention.
Attention Solves an Ambiguity ProblemSensory Input Ambiguity
Cell “tuned” to red. Should it fire?
Area V4 Receptive field = ~4 deg visual angle
Attention Solves an Ambiguity ProblemSensory Input Ambiguity
Cell “tuned” to red. Should it fire?
Area V4 Receptive field = ~4 deg visual angle
If you do computational neuroscience,This is why you should think about attention.
Attention Solves an Ambiguity ProblemResponse Mapping Ambiguity
(e.g. Stroop Task)
Cell “tuned” to line orientation. Should it affect your response?
Area V4 Receptive field = ~4 deg visual angle
If you do computational neuroscience,This is why you should think about attention.
B L U E
Attention Solves an Ambiguity ProblemReward mapping ambiguity
Cell “tuned” to red. Should it be associated with reward?
Area V4 Receptive field = ~4 deg visual angle
If you do computational neuroscience,This is why you should think about attention.
Attention Solves a Network Complexity ProblemThe brain is a massively
interconnected network - each neuron makes ~ 1000 connections
Gordon Kindlmann & Andrew AlexanderUniversity of Wisconsin Van Essen, Andersen & Felleman (1992)
Attention Solves a Network Complexity ProblemOn the time scale of behaviour,
the network is anatomically hard-wired
Fast functional reconfiguration
Attention Solves a Network Complexity ProblemPoint to the red horizontal line
Attention Solves a Network Complexity ProblemPoint to the red horizontal line
Visual stimulus drives visual neurons
Black Brain Box Motor plan is executed
Attention Solves a Network Complexity ProblemPoint to the red horizontal line
Visual stimulus drives visual neurons
Black Brain Box Motor plan is executed
Attention Solves a Network Complexity ProblemPoint to the red horizontal lineNotice the mapping is selective:
Attention Solves a Network Complexity Problem
Point to the red horizontal lineNotice the mapping is selective:
Attention Solves a Network Complexity Problem
Now point to the green vertical line
Notice the mapping is easily reconfigured
Attention Solves a Network Complexity Problem
Attention Solves a Network Complexity Problem Thus sensory neurons
are in some sense omnipotent
each one’s contribution to cognitive and motor networks is not determined by anatomical connectivity
it is determined dynamically by some control system
Attention Solves a Network Complexity Problem Notice this is an extension
of the “binding problem”
Cells representing features of the same objects must contribute to a “reconstituted” whole object representation
These cells must be “bound” to all the other cells mediating the current cognitive or motor behaviour
If you study the “connectome”, this is why you should think about attention.
Attention Solves a Network Complexity ProblemThe brain is a massively
interconnected network - each neuron makes ~ 1000 connections
Attention Solves a Network Complexity ProblemThe brain is a massively
interconnected network - each neuron makes ~ 1000 connections
X 1000
Attention Solves a Network Complexity ProblemThe brain is a massively
interconnected network - each neuron makes ~ 1000 connections
X 1000
X 1000
Attention Solves a Network Complexity ProblemThe brain is a massively
interconnected network - each neuron makes ~ 1000 connections
X 1000
X 1000
X 1000
X 1000
X 1000
Attention Solves a Network Complexity ProblemCrude AnalogyBy 4 synapses the tree comprises
more than 10 Billion cells!
Attention prevents runaway connectivity:◦Clearly the brain must have a system
by which information is routed appropriately through the network
Attention Solves a Network Complexity ProblemWhat does runaway connectivity look
like?Here’s a hint: the “feed forward”
sweep of signal following a visual event is relatively unconstrained by attention
Red = earliest response at this latencyYellow = has already responded
Lamme (2000)
By ~115 ms post-stimulus, much of the cortex has responded to the visual event
Attention Solves a Network Complexity ProblemWhat would be the consequence
if attention did not select cell assemblies?
Neural Gridlock? Maybe not the right concept.
Attention Solves a Network Complexity ProblemThe brain is a system of coupled
oscillatorsDriving such systems can trigger
unexpected synchronization
Attention Solves a Network Complexity ProblemClassic Example of spontaneous
synchronization
Attention Solves a Network Complexity Problem
See a fabulous TED talk about synchronization by Steven Strogatz at:
www.ted.com/talks/steven_strogatz_on_sync.html
Attention Solves a Network Complexity Problem Do brains exhibit
runaway global synchronization?
Yes, this is characteristic of certain kinds of epileptic seizures.
3 Hz “Spike and Wave” EEG pattern during absence seizure
Attention Solves a Network Complexity Problem OK so how might a brain solve this problem? How
might the attention system facilitate a dominant cell assembly and suppress others?
“Neuronal communication through neuronal coherence”
- Pascal Fries, TINS (2005)
Attention Solves a Network Complexity ProblemIndividual oscillators coupled to a
central oscillator
Attention Solves a Network Complexity ProblemRole of the “central oscillator” has been
called the “dominant network”
Communication-through-coherence suggests that oscillations within cell assemblies become phase locked
One set of such assemblies achieves global dominance by having their individual phases nudged into coherence
ThanksTo my lab past, present and
future:◦ Greg Christie◦ Andrew Butcher◦ Jarrod Dowdall◦ Karla Ponjavic◦ Scott Oberg◦ Dillon Hambrook◦ Amanda McMullen◦ Sheena McInnes◦ Aja Mason