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Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist / science writer
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Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist

Jul 08, 2020

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Page 1: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

Addiction, Brain Change, and Gambling: Deep Learning, not Disease

Marc Lewis

Radboud University Nijmegen

Independent journalist / science writer

Page 2: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

Models of Addiction

• Disease model

• Choice model

• Social construction of addiction

• Traumatic early history

• Developmental-learning model

Page 3: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

Addiction defined as a brain disease

• NIDA (National Institute on Drug Abuse):

“Addiction is defined as a chronic, relapsing brain disease that is characterized by compulsive drug seeking and use, despite harmful consequences.”

“Brain-imaging studies from drug-addicted individuals show physical changes in areas of the brain that are critical for judgment, decision-making, learning and memory, and behavior control.”

Page 4: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

Striatum:

Nucleus accumbens

Dorsolateral

prefrontal cortex

Midbrain The Bridge of the Ship

The Motivational Engine

Dopamine Pump

Page 5: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

From Connolly, Bell, Foxe, & Garavan. PLOS ONE, vol. 8, 2013.

Looks suspiciously like brain disease…?

Use it or Lose it?!?

Page 6: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

But what if it’s not a disease?

Page 7: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

Reinterpreting the neural data…

• If brains change with learning and development, then brain change doesn’t necessarily mean brain disease

• But how do brains change with development?

Page 8: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

Changes in cortical density from age 4 through age 20 (from averaged MRI data)

Page 9: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

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Development =

Synaptic growth + synaptic pruning

• Synaptic growth flexibility, novelty, increasing range of knowledge and skills

• Synaptic pruning consolidation, efficiency, habit formation

Page 10: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

If this thinning is viewed as synaptic pruning….

…then we should not be surprised by further synaptic alteration!

Page 11: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

Since pruning makes the brain more efficient…

• …the addict’s brain learns to aim behaviour toward (expected) rewards – i.e., tuning the brain to the goodies

• I think it’s exactly the same for gamblers

• So, addiction (including gambling) is highly efficient

– striatal tuning

– gradual shift from impulsive (ventral striatum) to COMpulsive (dorsal striatum) tuning

• This “efficient” reward-seeking tries to counteract three kids of loss

– short-term loss

– long-term “blunting”

– longer-term isolation, shame, and despair

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Page 12: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

1. Strong attraction repetition deep learning deliberate mood regulation

2. Getting trapped by “now appeal”

3. Ego fatigue: the loss of self-control

So why is it so hard to stop?

Page 13: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

1. The classic feedback cycle in addiction

Craving Drug imagery

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Page 14: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

Cycle of brain activation

Planning: To do or Not

to do

Midbrain

Action

Imagining

Perception

Trigger

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DO IT!

Page 15: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

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….ongoing modification of networks

Page 16: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

Shift of activation from ventral to dorsal striatum

Midbrain

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DO IT!

Page 17: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

2. Now Appeal

Page 18: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

Dopamine focuses attention on the

immediate goal….

craving

The circuitry of desire

Page 19: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

…dopamine is tuned to the cake.

Why is that man

going after the cake?

Craving delay discounting = “now appeal”

Because it

seems worth more

than imagined

future happiness

Page 20: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

The grip of the immediate goal …outweighs the imagined future!

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Page 21: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

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Page 22: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

3. Ego fatigue

Page 23: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

Hungry?

Page 24: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

Cues, cues, cues

Page 25: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

Cues, cues, cues

Page 26: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

Gambling…

• …looks similar to substance addiction in the brain and in real life

Page 27: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

From Brewer & Potenza (2008). The neurobiology and genetics of impulse control

disorders: Relationships to drug addictions, Biochemical Pharmacology, vol 75.

Page 28: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

But gambling may be particularly insidious

Page 29: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

• Reward-predicting stimuli dopamine rush

• Reward prediction error dopamine tuning

• Reward uncertainty ? ?? ??? ????

Dopamine has three jobs

Page 30: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

The three faces of dopamine

From Schultz, 2007. Trends in Neuroscience.

Page 31: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

Reward prediction --

-- reward prediction error

But what goes on here?!

Page 32: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

The lure of uncertainty

“One of the main underlying factors to the phenomenon of loss-chasing may relate to the importance of reward uncertainty….. In PG, accumbens DA is maximal during a gambling task when the probability of winning and losing money is identical—a 50% chance for a two-outcome event representing maximal uncertainty…”

Anselme et al., 2013. What motivates gambling behavior?

Insight into dopamine's role. Frontiers in Behavioral Neuroscience

Page 33: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

Snakes and shocks study

Designed to track “irreducible uncertainty” ….surrounding 50% level.

De Berker et al. (2015). Nature Communications 7.

Page 34: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

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Excitement/stress peaks with uncertainty

“Irreducible uncertainty best predicted subjective stress responses.”

Page 35: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

“The pathological gambling (PG) group shows a significant (p < .002) quadratic

Relationship between [dopamine uptake in striatum] and probability of selecting

advantageous decks (P(IGT)). The healthy control group shows no significant

quadratic interaction.”

Linnet et al. (2012) Psychiatry Research: Neuroimaging. 204, 55–60.

Iowa Gambling Task: variability and dopamine

Page 36: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

In sum: brain change with addiction

PFC = judgment

Midbrain = dopamine

36

Now

Appeal

Ego

fatigu

e

and gambling

Page 37: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

The disease model of addiction isn’t just wrong…

It’s also harmful!

Page 38: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

Why the disease model fails addicts

• The disease model calls for medical treatment

• “Medicalization” makes addicts into patients

• Patients don’t feel they have the power to change their goals

• Because they’re not formulating those goals

(somebody else is…)

Page 39: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

Empowerment is an antidote to ego fatigue

But how do we encourage it?

Page 40: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

What happens when you give the wheel to your teenage kid?

Utilize addicts’ desire for other goals

Page 41: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

Stretching one’s sense of time into the future is an antidote to now appeal

But how do we help addicts & gamblers

connect with their past and their future?

Page 42: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

Help them see their life as a narrative …embedded in a past

…and stretching into a desired future

Page 43: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

Ainslie’s

Intertemporal dialogue

Perhaps they can start a dialogue with a future self

Page 44: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

But addicts have a hard time seeing their future self as anyone but an addict….

And addicts aren’t

trustworthy!

Page 45: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

Striatum

Dorsolateral

prefrontal cortex

The Bridge of the Ship

The Motivational Engine

Reconnect…

…empowerment to a sense of personal time

Page 46: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

How do you change the brain?

• Frontal lobotomy

• Meditation

• Psychotherapy

• Development itself

• NOT believing you have a chronic disease

• Not by taking drugs (e.g., opiate substitutes, sedatives, antagonists)

• Not by repeating familiar slogans

• Not by continuing to do what you’ve been doing

But by…

Page 47: Addiction, Brain Change, and Gambling: Deep …...Addiction, Brain Change, and Gambling: Deep Learning, not Disease Marc Lewis Radboud University Nijmegen Independent journalist /

Notes for update for Australia • The flow experience is considered the most addictive of all states: see

https://www.youtube.com/watch?v=y1MHyyWsMeE at 20:00 for discussion, esp idea of hypofrontality…suppressing the dlPFC…we like turning it off

• Also see Maia’s talk about dopamine and the hedonic treadmill phenomenon – very relevant! – The Influence

• Notes from Monday night:

– Amazing flatness of affect whether just won or just lost…almost nil

– When I hovered a bit, I was asked to go away several times. Looks like shame…or else just wanting to be in your own world

– Idea of two types: those who just oscillate vs those who go down hard and wipe themselves out

– Anger (e.g. at the dealer) even if you’re a winner (1000 ahead at roulette) after a few losses…. 4:00 on George Paddy Power recording, also 9:13 for a failed attempt at imagining a different future; on George William recording, ; 8:25 Don’t’ talk to me, let me be, also 10:30 for a glimpse of Just Say No uselessness