Introduction
Like a digital computer, the brain generates output from input. Food generates hunger, nighttime generates sleep, a normal day generates whatever you do on a normal day. Like a computer, the brain can also be reprogrammed - learn - to produce new input-output patterns. Much of what we do in life is 'organic' programming: with little or no scientific knowledge of or direct access to the learning brain we nevertheless try, intuitively and by trial-and-error, to change its input-output patterns for the better. We exert effort, try to overcome our limits, drink coffee or alcohol to change our states of mind, and expose ourselves to new situations in the hope that new experiences and behaviours will be established. For some, the process is effective; their brains tolerate stress and learn well. For others, the process is hostile, slow and marred by self-sabotage and pathology. What if organic programming, when it fails, could be enhanced by direct, electronic, digital programming of the learning brain?
In recent years, monoamine neuroscience has provided us with the principles by which the brain learns and behaves (Doya 2002, Schultz 2008). In essence, dopamine regulates learning, motivation and attention (Schultz 2008, Cools & Robbins 2004), and serotonin modulates mood and creativity (Clarke et al 2005, Lechin et al 2006, Jans et al 2007). What's more, by electrically stimulating the neurons that produce these neurotransmitters, researchers have long been able to regulate monoamine concentrations (Garris et al 1997, Fiorino et al 1993, Bean & Roth 1991) and generate specific behaviors in laboratory animals. Importantly, by making rewarding brain stimulation (stimulation of the dopamine system) conditional on specific behavioural output, rats can been trained to perform heavy exercise and learn new skills (Burgess et al 1991 , Garner et al 1991 , Talwar et al 2002, Hermer-Vasquez et al 2005).
To enable the same direct control of monoamine neurotransmission in human brains we need to apply deep brain stimulation surgery and technology, or await mature deep magnetic brain stimulation. We also need to prepare for significant ethical and philosophical challenges. In this section however, we focus on how electronic programming of human monoamine signaling might be developed once those challenges have been met.
Functions refer to functionally distinct ranges of monoamine modulation. For example, rewarding brain stimulation refers to strong, brief stimulation of the dopamine system, which releases the >100 nM dopamine required to activate D1 receptors necessary for learning; whereas tonic dopamine regulation refers to relatively weak but constant stimulation of the dopamine system, which may raise baseline dopamine concentrations, thus enhancing signal-to-noise ratios and attention (Cools & Robbins 2004). Dopaminergics and serotonergics map the quantitative relation between monoamine concentrations and brain-states.
Programs refer to behavioral sequences that are be learnt and maintained by repeatedly associating specific behaviors with rewarding brain stimulation and other functions. In this way, rats have been trained to run on treadmills (Burgess et al 1991), lift weights (Garner et al 1991) and learn new skills (Talwar et al 2002, Hermer-Vasquez et al 2005). Presumably the same procedure could be applied to persons and used to motivate beneficial but difficult behaviors such as physical exercise, learning or basic research.
Finally, defense mechanisms are security measures that will most likely have to be put in place to prevent abuse, over-use and degeneration of natural self-discipline in heavy iPlant users. Defense mechanisms include strict access control to the implant hardware and software by the manufacturer and/or medical team, as well as a minimum number of hours of non-iPlant-aided effort to balance the number of hours spent running iPlant programs.
Functions
Tonic dopamine regulation
Baseline dopamine concentration ('dopamine tone') in the frontal cortex and elsewhere determines our level of attention, is lowered in attention deficit disorder, and is elevated by stimulants such as Ritalin and coffee (Schultz 2008, Cools & Robbins 2004 ). The function of tonic dopamine regulation by iPlants could be to tailor a person's level of attention to the task at hand. Once through clinical trials this function could be of use not only to those suffering from clinically recognized attention-deficit disorders, but to anyone who experiences regular problems with lacks attention and wishes to optimize his/her dopamine tone. Moreover, the ability to regulate and adjust stimulation strength over time might offer advantages compared to pharmacological stimulants (e.g. the ability to turn stimulation off at night and prevent insomnia).
Rewarding brain stimulation (RBS)
Discrete pulses of dopamine are released when we experience important events, particularly unexpected rewards (Schultz 2008). They motivate us to remember and repeat the behaviour that led up to the experience. iPlant-induced pulses of dopamine are referred to as RBS. Their function would be to provide a person with motivation for behaviors he or she would otherwise find too difficult to perform or remember. Defense mechanisms must be applied to prevent abuse of RBS.
Tonic serotonin regulation
Serotonin tone strongly influences our mood, stress levels and ability to think creatively. It is lowered in depression, anxiety and forced social subordination, and is increased by antidepressants such as Prozac and Citalopram (Cools & Robbins 2004 , Clarke et al 2005, Lechin et al 2006). The function of tonic serotonin regulation by iPlants could be to prevent stress, promote hippocampal neurogenesis, psychological well-being, social behaviours and creativity. Once through clinical trials, the function might be of use not only to those suffering from severe affective disorders but to anyone wishing to optimize his/her serotonin tone for hippocampal growth, psychological well-being, creativity and stress-tolerance.
Discrete pulses of serotonin
Discrete bursts of serotonin release occur naturally in the brain, but unlike dopamine bursts their function is still not known. Further information about such bursts may be gained by using an iPlant to record what kind of situations bring them about.
Dopaminergics
In recent years it has become possible to assign exact numerical values to the dopamine release that accompanies specific rewards and states of attention. Microdialysis probes and other biosensors associate rewards, particularly unexpected rewards and rewarding brain stimulation, with sharp increases in dopamine concentrations in the prefrontal cortex and basal ganglia in many animals (Schultz 2008). States of high or low attention have similarly been associated with high or low concentrations of dopamine in the prefrontal cortex (Cools & Robbins 2004). These numerical relations are here referred to as dopaminergics. Dopaminergics describe the relation between dopaminergic events (e.g. a salient object in the environment, the activation of a deep brain stimulation electrode, the discovery of a solution to a problem), dopamine release (e.g. 20nM increase in prefrontal cortex as evidenced by a microdialysis probe) and brain/mental states (e.g. attention, motivation, learning, memory, motor output). Dopaminergics and should thus serve as a foundation for iPlant programming using dopamine and it may be helpful to think of dopaminergics as assembly code for the learning brain.
Programs
Exercise programs
Physical exercise can be motivated by repeatedly delivering rewarding brain stimulation (RBS) whenever an animal runs on a treadmill (Burgess et al 1991) or lifts a weight (Garner et al 1991). iPlant-driven exercise programs would apply the same principle to humans, for example by delivering RBS whenever the user pulls a stroke on a rowing machine or when pressure-sensitive shoe hit the ground during running (see top image). Every exercise program must have a strict time-limit agreed on in collaboration with a physician.
Learning programs
Learning is often difficult and requires the ability to inhibit distraction, boredom and frustration for the sake of distant, often abstract goals. A failure to do so is particularly evident in people suffering from disorders of learning and attention. Learning programs could ensure optimal levels of attention for learning (by tonic dopamine regulation) and deliver RBS a whenever the user provides correct answers to questions posed by computer tutorial designed to teach skills such as new languages. Strict time-limits would prevent over-use. Note that learning programs have been successfully developed for rats (Talwar et al 2002, Hermer-Vasquez et al 2005).
Research programs
Progress in science depends on experiments and data analysis, both of which proceed according to 'protocols'. Often, following such protocols quickly becomes easy, monotonous work, even for a scientifically inexperienced person, but nevertheless require a degree of dexterity, nonlinear thinking, noise filtering and contextual knowledge that computers cannot provide. Human workers must thus be hired, which makes funding the rate-limiting factor in the fight against urgent global problems like cancer, HIV, age-related diseases and global warming. In iPlant-driven research, iPlant users would volunteer time to become highly motivated, via a combination of RBS and other functions, to engage in scientific research according to well-defined protocols.
Clinical programs
Reprogramming of maladaptive behaviours such as substance abuse and phobia. Further debate needed.
Defence mechanisms
It seems likely that no one person would be able to avoid devastating addiction if given full control over a deep brain stimulation implant regulating strongly rewarding/dopaminergic regions of his or her brain (see Portenoy 1968 for a case of compulsive self-stimulation). Like rats do in that situation, a person would probably self-stimulate to the exclusion of any other behaviour and to the point of complete exhaustion. To prevent such short-circuiting and allow rewarding brain stimulation to be tied to and motivate useful behaviours, iPlant users will have to accept certain restrictions and preconditions. Such security measures are here referred to as defense mechanisms.
Defense mechanisms will have to include restrictions on users' freedom to adjust implant-properties such as strength, frequency and duration of stimulation. Defense mechanisms should also include prudent practices that prevent degeneration of natural self-discipline: the cortex must be allowed to activate dopaminergic midbrain neurons in a healthy, natural way even when those neurons could more easily be activated by an iPlant. In other words, iPlant users must not become too dependant on their iPlant for motivation, or their own self-discipline may disintegrate. A minimum amount of time of non-iPlant-aided effort for every hour of iPlant-aided behaviour may be required.
Comments
Write New Comment ▼
Write New Comment
Sorry! This knol's owner(s) have blocked you from editing, making suggestions, or commenting here.