The authors critique the vague use of “high-level” motivation constructs as explanatory variables in various sections of the psychological literature and propose that the “black box” of mechanistic explanation should be opened. We fully concur that in many theories on motivation, processes are underspecified or ignored. At the same time, though, research on the underlying processes in motivation has been steadily going on for more than half a century in various corners of the field. While we acknowledge that there are literatures that utilize motivation constructs for various purposes other than explanatory (e.g., to predict behavior), we highlight here three (of many) very different lines of research (including our own) that have unpacked the black box to identify various degrees of “mechanism.”

First, in focusing heavily on drive theory, the author completely overlooked incentive theory (Bindra, Reference Bindra1974; Bolles, Reference Bolles1972; Toates, Reference Toates1986), which replaced drive theory as the dominant motivation theory in the 1970s/1980s, as well as the work that spawned from it. According to this theory, needs or motives do not directly affect behavior, but rather change the incentive value of behavioral opportunities and stimuli in the environment. Thus, needs or motives – in combination with deprivation – modulate the value of behavioral goals in the situation at hand, while these in turn energize and give direction to behavior (Custers & Aarts, Reference Custers and Aarts2010). Put differently, Custers and Aarts (Reference Custers and Aarts2005) have argued that the causal starting point of behavior can best be understood to be the environmental cues that activate mental representations of goals, with their effects on the direction of behavior and the effort invested in it being moderated by their subjective value at the time of activation. This subjective value is determined by abstract motivational constructs such as needs and situational variables such as deprivation or discrepancy relative to the goal state. Importantly, goal representations are not magical, and are subject to mechanisms applied to all mental representations such as accessibility and its dynamics (Eitam & Higgins, Reference Eitam and Higgins2014). This literature therefore provides specific mechanistic paths by which high-level motivation constructs do not cause, but rather moderate the effects of the environment on behavior (see Berridge & Robinson, Reference Berridge and Robinson1998, for a popular neural implementation of the incentive value theory).

Second, self-regulatory systems theory is the product of a three decades-long research program that details both “chronic” and transient (situational) changes in the balance of motivational orientations (Higgins & Cornwell, Reference Higgins and Cornwell2016). This research program has shown a myriad of effects from a shifting focus from a “prevention” state – minimizing a negative (“−1”) discrepancy between one's current state and a baseline state (“0”) – versus a “promotion” state – maximizing a positive discrepancy (“ + 1”) between one's current state and a baseline state (“0”). While differing in the level of explanation from our previous example, this research program has been anything but a black box by showing how such motivational orientations are affected by parenting (Manian, Papadakis, Strauman, & Essex, Reference Manian, Papadakis, Strauman and Essex2006) and how they influence basic processes such as judgment and decision making (Förster, Higgins, & Bianco, Reference Förster, Higgins and Bianco2003; Higgins & Cornwell, Reference Higgins and Cornwell2016).

Our third and final example is the work on reinforcement from sensorimotor predictability (Eitam, Kennedy, & Higgins, Reference Eitam, Kennedy and Higgins2013), which can be easily cast as an attempt to open the “black box” of the abstract need for autonomy and control. What this body of work shows is that sensorimotor prediction, which is considered part of the brain's mechanism to execute planned or volitional movement, also serves as a reinforcement signal for “effective” motor plans. More specifically, motor programs that are associated with more successful predictions are reinforced above and beyond their utility or association with tangible rewards. This has shown to occur in healthy adults (Hemed, Bakbani-Elkayam, Teodorescu, Yona, & Eitam, Reference Hemed, Bakbani-Elkayam, Teodorescu, Yona and Eitam2020) as well as in clinically depressed individuals (Bakbani-Elkayam, Dolev-Amit, Hemed, Zilcha-Mano, & Eitam, Reference Bakbani-Elkayam, Dolev-Amit, Hemed, Zilcha-Mano and Eitam2024), and more recently in a mouse model. This process is another example that hardly fits the author's depiction of motivational concepts as “initiating behavior,” as it reflects a subtle interplay between environmental input and a computational process, together, creating a direction of behavior.

Thus, such efforts to explain how high-level motivation constructs affect behavior have been going on for quite a while, admittedly with varying degrees of success. Given the above, we suggest that any effort to advance a general framework of motivation would benefit tremendously from the more local work that has already been done to unpack the relevant black boxes. Such work may provide the necessary glue to connect abstract motivation constructs to the lower computation level, at which behavior is controlled by rewards.