Understanding the Function of Motivation in Addiction and Information Processing

Continuing with the themes from my previous essay discussing motivation and functional autonomy, I will start by expounding upon my claim that this principle is a factor in addiction. Next, my goal is to provide a selective overview of pertinent topics related to reinforcement learning and perception before concluding with neuroscience and psychiatry topics that I will likely continue to investigate in subsequent writings.

To state simply, the principle of functional autonomy espoused by Gordan Allport (1937) is significant in that it demonstrates that not only does a complete set of instincts or inherent drives not exist but, in fact, initial motives for behaviors can be severed and replaced with novel ones that function to maintain motivation to conduct the same behavior. Therefore, there exists an expansive, diverse, and emergent set of potential motives that drive a person’s behavior at a specific point in time.

Since I first was introduced to the concept of functional autonomy years ago while completing my undergraduate degree, the connection between this principle and addiction has remained in my memory primarily due to an illustration my professor provided to explain functional autonomy. While I do not remember the specific class (or professor to give them credit), I recall the general gist of the example because of how directly it corresponded with functional autonomy.

Imagine there is a young person in high school or college who has never smoked a cigarette and is detested by the smell, in addition to being frightened of the health risks. However, they desperately want to socialize with a group of peers and realize that smoking cigarettes is a means to achieve this end. Let us assume this plan is successful, as this hypothetical peer group has only smoking as their shared interest.

At this point, this fictional person likely feels a sense of reward from attaining their goal of a sense of belonging; however, as time passes by, this person’s initial motive of smoking for social inclusion is replaced by the rewarding pleasure of smoking itself. It is here, at this point, that their initial means (smoking cigarettes) to the end (social inclusion) has been transformed into an end in itself. Consequently, this new end goal of feeling satisfaction from smoking is capable of functioning independently of the initial end goal of social inclusion—in fact, it may even be that smoking cigarettes is hindering social inclusion with desired groups, but this person now is driven by a motive that is exerting a more significant influence relative to this other potential desire.

With this hypothetical case study in mind, let us broaden our view to examine how the brain’s general processes function to navigate daily life.

Our brains constantly receive and process information from our external environment via perception and our internal environment via interoception (or internal (Chen et al., 2021). For this paper, I will remain on the surface of these deep topics, but I hope to write about them in further detail in the future.

Throughout our days, these input data are being filtered, sorted, and processed for relevancy, particularly as it relates to the future. Our brains generate models based on past experiences and data from our current sensory inputs to create representational models that account for our current state of being and futuristic thinking. We conduct mental cost-benefit analyses for our future behaviors, taking into consideration the effort and energy required to perform some action or series of actions to obtain a given reward outcome; moreover, our brain seeks to minimize the energetic cost while maximizing the reward of our selected outcome (Peters, McEwen, & Friston, 2017).

These are topics rich in-depth that I hope to return to in the future. Still, this essay will focus on the more surface-level takeaways: Our brains process troves of information, and our values, prior experiences, future goals, and availability of environmental rewards all function to assist in sorting and filtering the stream of raw sensory data. This is by no means an exhaustive account of the cognitive process of perception, reinforcement learning, and decision-making.

However, embedded with this brief overview are core assumptions of human motivation that are applicable and well-documented for the general population; however, an additional inquiry is necessary for individuals who possess serious psychiatric disorders, particularly schizophrenia (though similarities are found in other psychiatric disorders).

For example, central to the mental processes I have highlighted for perception and predictive planning is the ability to create mental representations. Closely related (if not integral) to this process is reward valuation; that is, associating varying degrees of reward value with different reward stimuli, typically relying on past experiences and personal values to facilitate this determination (Der-Avakian et al., 2016).

The ability to formulate goals is indeed so significant that machine learning researchers Richard Sutton and Andrew Barto write in their 2018 book Reinforcement Learning: An Introduction:

“A learning agent must be able to sense the state of its environment to some extent and must be able to take actions that affect the state. The agent also must have a goal or goals relating to the state of the environment…Rewards are basically given directly by the environment, but values must be estimated and re-estimated from the sequences of observations an agent makes over its entire lifetime.” (pp. 5-6)

However, aberrant reward learning, dysregulated goal-directed behaviors as a result of inappropriate attribution, and the inability to accurately discriminate relevant stimuli from those irrelevant are precisely central areas of deficit identified by those researching the mechanisms of schizophrenia. In fact, researchers Der-Avakian et al. reported, “pleasure and valuation have been dissociated in schizophrenia, with patients showing intact capacity to experience pleasure, but deficits in properly representing the value of future rewards” (2016, p. 237).

Additional research findings further elucidate the implications of these findings and provide other intriguing points that extend the scope to incorporate other psychiatric disorders, such as mood and development disorders. The most intriguing aspect for me is discovering the common themes that exist across diagnoses. I believe this indicates overlaps in the underlying mechanisms responsible for the symptomatology of these different categories of disorders.

With this in mind, the theme that has become most apparent as a significant diagnostic challenge is further understanding how goals are constructed, what factors are involved in attributing and experiencing reward values as outcomes of goal-directed behaviors, and how does one’s time orientation affect their creation and implementation of futuristic goals. These are topics that I will seek to (or attempt to) unravel in my subsequent writings.

References

Allport, G. W. (1937). The Functional Autonomy of Motives. The American Journal of Psychology, 50, pp. 141-156.

Barto A.G., & Sutton R.S. (2018). Reinforcement Learning: An introduction (adaptive computation and machine learning series) (2nd ed.). The MIT Press: Cambridge.

Chen W., Schloesser D., Arensdorf A., Horowitz T., Vallejo Y., & Langevin H. (2021). The Emerging Science of Interoception: Sensing, Integrating, Interpreting, and Regulating Signals within the Self. Review Special Issue: The Neuroscience of Interoception. 44(1) 3-16. https://doi.org/10.1016/j.tins.2020.10.007

Der-Avakian A., Barnes S., Markou A., & Pizzagalli D. (2016) Translational assessment of reward and motivational deficits in psychiatric disorders. In: Robbins T.W., Sahakian B.J. (eds) Translational Neuropsychopharmacology. Current Topics in Behavioral Neurosciences. https://doi.org/10.1007/7854_2015_5004

Peters A., McEwen B.S., & Friston K. (2017). Uncertainty and stress: Why it causes diseases and how it is mastered by the brain. Progress in Neurobiology. Volume 156, pp.164-188. https://doi.org/10.1016/j.pneurobio.2017.05.004

Exploring the Nature of Motivation

Motivation is fundamental to understanding why people act in their unique manner; moreover, motivation is closely linked to one’s personality as a whole. However, the depth and nuance of an individual’s motivational system are often overlooked or oversimplified due to the scientific bias toward viewing and understanding human motivation solely in general terms.

Gordan Allport espouses his principle of functional autonomy in his 1937 article, The Functional Autonomy of Motives. I will provide a general overview and selection of key points, quotes, and context from Allport’s article before concluding with a discussion of the role and application functional autonomy has in contemporary thought.

In fact, Allport believed “motivation is always contemporary” (p.144, 1937). This conviction about the nature of motivation is likely one reason he writes so critically of the scientific thought of his time. He stood opposed to the attitude of always seeking to generalize; however, he was still aware of the need for this attitude, in some regards, stating, “Science must generalize” (p. 154). Moreover, he explains how relying on generalizations can result in negative consequences, characterizing that “it is a manifest error to assume that a general principle of motivation must involve the postulation of abstract or general motives” (p.154).

Allport uses these critiques as a way to highlight the gaps present in the scientific foundation of his time, and he proceeds to explain how the principle of functional autonomy is both “general enough to meet the needs of science, but particular enough…for the uniqueness of personal conduct” (p.155).

This claim is likely related to an assumption central to the principle of functional autonomy: life is inherently dynamic. Therefore, the motivation that underpins a person’s behaviors is not a static entity that can be quantified, isolated, and said to be fixed, rather a fluid force that possesses the property of emergence (this concept will be further addressed, subsequently).

Allport uses a variety of everyday examples, among other kinds, to demonstrate that even if there exists an “unchanging set of original urges,” it comprises far less than the “plurality of constantly changing [motivational] systems of a dynamic order” (p.153).

At the core of functional autonomy is the notion that the initial motive driving a given behavior does not necessarily entail that it will be the same motive through which the behavior is maintained. Instead, Allport believes “original motives [can be] entirely lost. What was a means to end has become an end in itself” (p.150).

For instance, selecting one of the many everyday examples Allport provides, there is a description of “a businessman, long since secure economically,” yet this businessman continues to work himself into poor health because of a drive that is different from the original. Allport does not expand much on this example but rather explains how all of these examples illustrate “some new function emerg[ing]” (p. 146).

Not only does Allport put forth the notion of emergent motives, but he also describes these emergent motives as being “independently structured units” that function without dependence “upon the continued activity of the units from which they developed” (pp.146-147).

Allport writes about the maturation process of a seed into a tree, “The life of a tree is continuous with that of its seed, but the seed no longer sustains and nourishes the full-grown tree. Earlier purposes lead into later purposes, and are abandoned in their favor” (p.144).

Although this tree imagery is before Allport introduces functional autonomy, I believe it captures both the sophistication and simplicity possessed in the principle of functional autonomy. It is simple in that the tree could never have emerged into being if not for the seed’s existence, in addition to suitable environmental conditions for growth; consequently, there logically exists a point when the seed ceases to exist as a seed.

For the sake of sanity, I implore you not to become fixated on identifying the transitionary point where this identity change occurs—if you cannot resist, then research Sorites paradox—because the primary point that has practical significance is the notion that we are able to sever connections with even original and necessary causes. For example, the process of a child maturing and cleaving with their parents is analogous to the tree analogy (as well as an example Allport provides).

However, this can be applied in other domains than solely developing functionally autonomous drives after maturing to a particular biological or temporal point; in fact, I think addiction is the most straightforward application of the principle of functional autonomy.

While Allport acknowledges this as a domain where functional autonomy applies, he is brief in discussing the matter, and it does not seem to have received much attention to the present day. Nevertheless, the principle of functional autonomy assists in understanding how someone becomes addicted to a given substance or behavior and how it is maintained.

In future writings, I intend to further explore the potential descriptive and explanatory role the principle of functional autonomy may offer the issue of addiction. Additionally, I hope to incorporate relevant takeaways from further research into the Rescorla–Wagner model that is a contemporary model for understanding associative and reward learning.

References

Allport, G. W. (1937). The Functional Autonomy of Motives. The American Journal of Psychology, 50, pp. 141-156.