the opposite of attention is epilepsy:

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