A tried-and-true method to help recovering addicts avoid relapse is to avoid the people, places, and things connected with their addiciton.  Now the world’s top neruroscientists are shedding light on the scientific reasons why this is so critically important. Drug abuse causes the brain to forge enduring associations between a drug and the environment where it is purchased and used that are so strong they might as well be set in stone.  It is this mental stamp that makes up the biggest part of the clenched fist of addiction.

Hitoshi Morikawa is a neurobiologist at the University of Texas at Austin who says, “There’s a growing consensus in the addiction field that addiction is a learning and memory disorder. We learn behavior associated with these drugs too well.” His new research was recently published in the Journal Of Neurobiology and it shows how alcohol has a dangerous tendency to form reward-based associations.  Mice given a 7-day binge of booze were far more likely to remember the environment in which they later received cocaine.  It is this important discovery which could very well explain why certain environments can push a sober individual over the cliff in no time at all.  Here’s an excerpt from the Scientific American article:

Addictive drugs cause dopamine neurons, which synthesize and store the neurotransmitter dopamine, to release it, signaling to other brain areas to take note of the context surrounding the drug—the better to replicate the experience in the future. “We can think of those neurons that release dopamine as ‘teachers’ that tell other brain areas, the ‘students,’ to learn the associations surrounding rewards such as food, sex and addictive drugs,” Morikawa explains. In essence, alcohol and other addictive drugs help the “teachers” teach better. Morikawa emphasizes that the study does not show that alcohol improves “conscious” forms of learning and memory—a fact that could be corroborated by many a college freshman. Indeed, alcohol use is known to cause both acute and lasting damage to cognitive function. The type of learning that alcohol and other addictive drugs may promote is best described as “subconscious” reward-based conditioning, much like the classic example of Pavlov’s dog. Just as the dog learns to associate the sound of a bell with food (a reward), a person may similarly associate a particular street corner in his hometown with cocaine use. After much repetition the dog salivates at the sound of a bell, and a cocaine addict craves a hit when he returns to the old hangout. The new insight from Morikawa’s work is that alcoholics may be more vulnerable to reward-based conditioning—meaning they would learn new cravings sooner.

Previous research on mice by Morikawa’s team proved how repeated amphetamine use has a very similar positive effect on reward-based conditioning.  Just like other addictive drugs such as opiates and nicotine, the sinister common element is increased dopamine levels.  So what is it about addiction that locks in these memories so strongly?  All forms of learning and memory cause the synapses between neurons to be strengthened in a particular manner in a process called Long Term Potentiation (LTP) which is affected by the flow of calcium ions into and out of the neurons.  Morikawa has shown that repeated dopamine surges significantly boost the chances of LTP occurring in the brain’s reward centers.

Larry Zweifel, a pharmacologist at the University of Washington in Seattle who was not involved in Morikawa’s work, is fascinated by these results showing how drug and alcohol abuse can change the brain by “strengthening the capacity of neurons in the reward circuit to be strengthened, in effect setting up a positive feedback loop to drive persistent drug seeking.” The end goal now is to figure out a way of erasing these “trigger memories” without erasing the good ones.  Morikama is excited about this direction saying, “I believe it is an attainable goal.” You can read the full story including detailed accounts of the Pavlovian mouse study at Scientific American.

Source: Scientific American

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