Addiction (Short) Notes

Addiction – short notes

Example questions:

1. what may be the importance of synaptic plasticity in the brain’s response to addictive drugs?

2. To what extent can we understand drug addiction by exploring the function and plasticity of the mesostriatal dopamine axis?

Drug addiction

• Addiction is a disease when drug-seeking becomes compulsive despite negative consequences

  • E.g. helath risk, physical detriment, inability to sustain normal social interactions, job

• Alcohol, tobacco and illicit drug use ranked among the top 10 leading risk factors for disease worldwide (1990) (WHO)

• Availability and consumption of tobacco, alcohol and illicit drugs are increasing worldwide due to changing social, environmental and economic conditions

Drug addiction: pharmacology, physiology, environment and learning?

(n.b. not mutually exclusive)

• Acute pharmacological (“physical”) effects

• Rewards… reinforcement

• Tolerance and escalation

• Withdrawal

• Dysregulation of hedonic processes

• Learning – synaptic adaptations

• Increased incentive/desirability/wanting

• Drug-associated environmental cues

• Cue-induced drug-seeking

• Cue-drug interactions

• Drug-seeking habits

• Diminished executive control

• Impaired decision making

• Compulsion

THESE ALL LEAD TO COMPULSIVE DRUG-TAKING = ADDICTION

A disease of pathological reinforcement learning and compulsive behaviour

Animal models:

• Intracranial self-stimulation (ICSS) Olds and Miller (1953) – rats will work for ICSS of mesolimbic pathways – the stimulus is reinforcing. Rats will press a lever at a rate of several thousand times per hour for DAYS to obtain stimulation at the expense food until starvation (compulsive behaviour)

• Drug self-administration pressing of lever results in drug administration into discrete brain region via indwelling cannula (into VTA). Drug has reinforcing properties if lever pressing increases, or animal will work for reward. this pattern of behaviour resembles compulsive or addictive behaviour in humans.

Circuits that may be involved in addiction

• Drug effects on reinforcement, actions-outcome learning, stimulus-response habits in NAcb and dorsal striatum – pathological learning of maladaptive behaviour

• Memory? – processing of conditioned reinforcement by basolateral amygdala and context by hippocampus

• Drug craving/drive – orbital and anterior cingulate cortex, and temporal love including amygdala

• “executive control” of decisions about goal-directed actions – PFC-striatum (contingencies, outcomes, value and subjective states including craving)

• serial interactions via nigrostriatonigral spirals

Transition from PREFRONTAL control to STRITAL control of drug-seeking behaviour

• over-representation of dopamine-modulated processes?

  • May depend on neuroplasticity in cortical and striatal structures that is induced by chronic administration of drugs

• PFC: disrupted function of the PFC leads to a syndrome of impaired response inhibition and salience attribution (iRISA) in addiction

Addictive drugs have a common outcome: increased mesostriatal dopamine

Classically, in ventral striatum (NAc) BUT not the whole story

disinhibition, excitation and/or direct modulation of DA availability

Diverse neurobiological targets of addictive drugs

1. drugs that activate GPCRs (Opioids, cannabinoids)

2. drugs that bind to ionotropic receptors (nicotine, alcohol, benzodiazepines)

3. drugs that bind to transporters of biogenic amines (cocaine, amphetamine, ecstasy)

Not all psychoactive or abused drugs are addictive

e.g. ketamine, LSD

the ability to INCREASE DOPAMINE may be a defining characteristic of addictive drugs

Can we understand drug addiction if we understand what dopamine neurons do?

• Mesostriatal dopamine neurons signal reward prediction error during learning

Discrimination learning task: initially monkey does not know which is rewarded stimulus (lever presses)

Action potentials in VTA/SN:

• Neuron activity increases briefly after reward stimulus

• Neuron activity is briefly inhibited after un-rewarded stimulus (error)

• As monkey learns which is rewarded stimulus, both excitatory and inhibitory responses disappear

• Rewardd prediction error – a teaching signal during learning?

From Hollerman and Schultz 1998 – Dopamine neurons report an error in the temporal prediction of reward during learning

Dopamine neurons in the SN and VTA are believed to be involved in reward-dependent learning – activated by rewards and because they are activated more strongly by unpredicted than predicted rewards they may play a role in learning. In this experiment, dopamine neurons were activated by rewards during early trials, when errors were frequent and rewards unpredictable, but activation was progressively reduced as performance was consolidate and rewards became more predictable

• Mesostriatal dopamine neurons signal reward prediction after learning

Recordings in VTA/SN:

Dopamine neurons are activated by unexpected rewards (R) (primary, or novel reinforcers) and by reward predicting cues (CS) but not rewards (R) after learning

• Reward-prediction error

• Reward predictions or cues

Alert or update striatum

NOT “pleasure” or “reward”

What dopamine neurons do NOT do

Dopamine neurons do NOT necessarily encode the PLEASURE of the reward itself

• Dopamine is not necessary or sufficient for “liking”; rather “wanting”

  • E.g. experimentally, liking expressions for sweet tastes in rats are not modified by stimulation or suppression/lesion of mesolimbic DA systems

• Pleasurable aspects of reward are encoded by other brain nuclei e.g. orbitofrontal cortex

Tsai et al – “Phasic firing in dopaminergic neurons is sufficient for behavioural conditioning”

• DA neurons controlled selectively through targeting expression of light-activated channelrhodopsin-2 carried by a Cre-inducible AAV by injection in to TH-Cre transgenic mice

• Abstract: Natural rewards and drugs of abuse can alter dopamine signaling, and ventral tegmental area (VTA) dopaminergic neurons are known to fire action potentials tonically or phasically...

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