Brain-Computer Interfaces for Addiction
Drugs are everywhere — whether it’s opioids, psychostimulants, alcohol, or any kind of addictive drug. Over $700 billion is spent annually in the USA towards addiction and related costs. This remarkable sum reflects the significant impact of addiction on the USA and its foothold in many countries across the planet. However, treatment for addiction remains stagnant and needs to be improved.
First, to improve treatment for addiction, it has to be understood.
What is Addiction?
Addiction is a chronic brain disorder that affects an individual through physical and psychological dependence. Intentional, regular use of addictive substances becomes an addiction when a person can no longer control their actions despite negative consequences.
It’s important to realize drug use does not always lead to addiction. Drug abuse can also take place without addiction following. Abuse can be characterized by excessive and frequent use but is different from addiction because the user is able to separate from the substance for long periods of time. Importantly, someone who abuses an addictive substance (but is not addicted) maintains more control over their everyday lives.
Regardless of the type of addictive substance, they all relate to the release of dopamine in the brain and influence its structure.
Almost all addictive substances activate a system in the brain called the “Reward” system that is primarily controlled by the neurotransmitter dopamine.
Understanding Dopamine — The Reward System
The reward pathway is also called the mesolimbic pathway, runs from the Ventral Tegmental Area (VTA) to the Nucleus Accumbens (NAc). The Mesolimbic pathway is one of four major dopaminergic pathways which also include the Nigrostriatal, Tuberoinfundibular, and Mesocortical pathways.
Contrary to popular belief, dopamine is not just about pleasure. Dopamine is involved in memory, movement, learning, and reward. Dopamine has also been implicated with different neurological disorders like Parkinson’s Disease which is caused by the depletion of dopaminergic neurons in the substantia nigra.
Dopamine is fundamental to understanding the reward system, emotion, and addiction. Dopamine is a monoamine neurotransmitter which means it is derived from amino acids (the monomer of proteins) — specifically phenylalanine (programmed with codons UUU, and UUC) tyrosine (programmed with codons UAU, and UAC).
Addictive drugs have in common that they target the mesocorticolimbic dopamine pathways. This system projects from the VTA to NAc and the prefrontal cortex (PFC). These substances affect glutamatergic (Producing glutamate — Excitatory) and GABAergic (Producing GABA — Inhibitory) synaptic transmission in these three brain areas. These changes are referred to as “drug-evoked synaptic plasticity” which results in the alteration of neural circuits.
Rewiring the Brain — Synaptic Plasticity
Synapses are the spaces between neurons where neurotransmitters are released from one neuron (presynaptic ) to another (postsynaptic) and can trigger an action potential in the latter allowing for the propagation of a neural signal. Receptors on synapses can be altered depending on the usage of a pathway.
This alteration comes in two forms: Long term potentiation (LTP) and Long term depression (LTD).
Long term potentiation (LTP) — Strengthing of a synapse over time due to high-frequency stimulation.
Long term depression (LTD) — Weakening of a synapse over time due to a lack of stimulation.
Both LTP and LTD connect to Hebbian theory in neuroscience.
“Hebbian theory is a neuroscientific theory claiming that an increase in synaptic efficacy arises from a presynaptic cell’s repeated and persistent stimulation of a postsynaptic cell. It is an attempt to explain synaptic plasticity, the adaptation of brain neurons during the learning process.” — Wikipedia
Synaptic plasticity is fundamental in learning, memory, and has been implicated in addiction.
Specifically, changes have been found in the AMPA and NMDA glutamate ionotropic channels in the PFC, NAc, VTA, and Brainstem. A prominent hypothesis suggests changes to the VTA leads to changes in the NAc and PFC. These changes facilitate many of the hallmark behaviors of addiction.
Specifically, after two weeks of cocaine administration, LTD impairment in the NAc was found (The relevance of drug-evoked synaptic plasticity in the NAc has been linked to multiple studies), and its long-lasting impairment may contribute to the inflexible, compulsive behaviors that are trademarks of addiction.
Personalized treatment based on individual changes in the connections in the brain could increase the effectiveness in rehabilitation and treatment overall. Brain-computer interfaces (BCIs) offer a route to this personalized treatment to help image the brain and facilitate necessary changes.
What are Brain-Computer Interfaces (BCIs)?
BCIs describe a system where the human brain is connected to a machine or program which allows a particular task to be completed. An example is a quadriplegic controlling a robotic arm or move a mouse on a computer just with thoughts.
BCIs collect signals from the brain in order to execute the program. There are Invasive and Non-Invasive BCIs. The former is primarily related to electrocorticography (ECoG). Devices are placed past the skull to increase spatial resolution — pinpointing activity from individual neurons. The latter is related to electroencephalography (EEG). EEG does not require placement of sensors past the skull — instead, they’re just placed on the scalp. EEG recording has better temporal resolution (The amount of time required to interpret new data), but worse spatial resolution compared to ECoG.
Evolutions on these technologies have led to products and treatments like Neural Dust (sensors as small as grains of sand are used to communicate using ultrasound and are used to study/control nerves and muscles), Neuropace (a device that monitors brain waves, detects unusual activity, and responds through electrical stimulation to stop seizures), and Neurable (focuses on the control of objects in virtual reality using EEG data).
The growth in this space can also be applied to addiction and rehabilitation. Studies have shown neurofeedback regimes instituted through EEG data have reduced symptoms of addiction. More personal treatment like this can vastly improve the way addiction is treated. Another potential treatment using BCIs relates to induced plasticity. When this is usually referenced it is in regard to changes in the brain which can be induced as a treatment for stroke.
“Recent developments in Bidirectional Brain-Computer Interfaces (BBCI) not only allow the reading out of neural activity from cortical neurons, but also the delivery of electrical signals. These drive neural dynamics and shape synaptic plasticity, thus opening the possibility of engineering novel neural circuits, with important applications for clinical treatments of spinal cord injuries and stroke.” — PLOS Computational Biology
However, these principles offer the possibility of the re-engineering of neural circuits affected by addiction — ultimately increasing the efficacy of treatment and revolutionizing the field.
