The Neuroscience of Contextualized Goals

At every moment there is something a person/animal is trying to do (a goal) and a reason they are trying to do it (a context for that goal). In the Affect Management Framework (AMF; Haynes-LaMotte, 2025), contextualized goals are constantly shifting in the brain, informed by the senses of the world and the body (vision, hearing, touch, taste, smell, interoception, and proprioception) as well as the semantic factors of meaningfulness, certainty, and agency.

Because our affect is attached to our goals, what contextualized goals we take on and how and when we choose to pursue or relinquish across similar situations can be described as different affect management policies.

You can find an overview of the AMF here. In this post, I hope to introduce some research speaking to the neuropsychological basis for contextualized goals:

Intrinsic Brain Activity

Our contextualized goals are always updating as part of ongoing experience, and can be thought of as a feature of the intrinsic brain activity that is always engaged, regardless of what someone is currently doing (Sadaghiani & Kleinschmidt, 2013). In fact, a considerable amount of the body’s energy (about 20% in an adult human) goes to meeting the metabolic costs of momentary brain activity, with the vast amount of this coming from intrinsic activity that is always present, even when unconscious (e.g., while asleep, under anesthesia; Raichle, 2015a). In terms of the hierarchical Bayesian estimation central to Predictive Processing and Active Inference, Sadaghiani and Kleinschmidt (2013) describe that “these intrinsic activity fluctuations reflect the dynamic nature of the underlying internal model. This model does not remain locked in a stationary mode but stays malleable by continuously exploring hypotheses regarding future experience and action” (p. 382).

What Determines What is Prediction and What is Error?

Along these lines, it is worth considering what factors determine whether something constitutes prediction and or prediction error at a given moment within the Predictive Processing perspective. For example, pain is often considered interoceptive prediction error in the model (Kiverstein, Kirchhoff, & Thacker, 2022), but while this generally seems true, it does not account for the existence of self-harm and disordered eating behaviors that use pain and hunger signals as an interoceptive evaluation of the goals they support (Armey, Crowther, & Miller, 2011; Hooley & Franklin, 2018; Kay et al., 2020; Swerdlow, Pearlstein, Sandel, Mauss, & Johnson, 2020).

I would argue that it makes sense for the two consciously describable factors that determine the prediction/error designation to be one’s (1) goals and (2) expectations (in fact, expectations are most often the framework used for intuiting what would be considered prediction error). Goals represent the momentary outcome that the individual is seeking within the context of their environment, and expectations represent a sense of what the likely consequences of an action or situation will be. In the most abstract sense, goals emphasize the side of the individual while expectations emphasize the side of the outside context. However, both are highly interconnected with one another, in that it does not make much sense to have a goal without a context.

While goals emphasize the role of the individual, they are, of course, highly contextual and thus reflect something about the environment at all times. This idea has roots in the field of Ecological Psychology, which was spearheaded by James Gibson and emphasizes the role that the environment plays in animal behavior by shaping its goals (Withagen, 2022).

Gibson created the term affordances to describe the opportunities for meaningful action that the environment allows. These affordances are “affectively charged” (Hesp et al., 2021) which help guide behavior by either treating objects or situations as threats (i.e., avoiding them) or as inviting affordances (i.e., approaching them). In this way, animals are constantly affectively engaged with their environments (Withagen, 2022) and this affect represents in animals and even more basic life forms “a capacity to be sensitive to what matters to them” (Columbetti, 2017).

Source: Drawing by Adam Haynes-LaMotte

Brain Networks Supporting Contextualized Goals

More support for the AMF emphasis on contextualized goals comes from neuroscience research on the nature of intrinsic activity in the brain, and the different modes the brain is cycling between as part of this ongoing activity. For example, Dosenbach, Raichle, and Gordon (2025) describe an action-mode network (AMN) in the brain evolutionarily refined to handle “engage[ment] with the environment through goal-directed behavior” (p. 159), and that this network is integrated with a somato-cognitive action network (SCAN; Gordon et al., 2023) heavily involved in moving the body and implementing allostasis within it.

The default-mode network (DMN; Raichle, 2015b) is involved in generating novel goals and concepts in the brain (Barrett, 2017; Binder, Desai, Graves, & Conant, 2009; Spunt, Falk, & Lieberman, 2010), and is sometimes negatively correlated with AMN activity (i.e., when the task is purely focused in the outside environment), but is most often positively correlated with AMN activity, such as when conceptual knowledge is involved in the task (Binder et al., 1999; Buckner, 2012; Raichle, 2015b).

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The Salience Network (SN) in the brain helps navigate the balance between AMN and DMN activity (Dosenbach et al., 2025), and the SN itself overlaps greatly with the part of the brain that processes interoceptive information from the body (i.e., the anterior insula; Katsumi et al., 2022; Molnar-Szakacs & Uddin, 2022).

Overall, this paints a picture of the neuroscientific mechanisms underpinning how the contextualized goals of the brain are shaped to help manage affect across its different sources:

The AMN is involved in maintaining a goal and closely tracking progress toward it (Dosenbach et al., 2025), where progress towards the goal is correlated with positive momentary affect (Asutay & Vjästfäll, 2021; Voodla et al., 2024).

The DMN is involved in conceptual categorization and spontaneous goal creation (Barrett, 2017; Binder et al., 2009; Spunt et al., 2010), which both have consequences for affect that depend on the context (e.g., Gross et al., 2024; Wen et al., 2022). The DMN may also be responsible for the anticipatory nature of affect management, based on its role in counterfactual thinking (Barrett, 2017; Raichle, 2015b).

The SN helps determine what goals to switch to as the focus for one’s momentary attention, informed on the one side by interoceptive information (i.e., anterior insula; Molnar-Szakacs & Uddin, 2022) and informed on the other by concepts, meaning-making, and goal-pursuit (i.e., DMN, Language Network, AMN; Barrett, 2017; Dosenbach et al., 2025; Hertrich, Dietrich, & Ackermann, 2020).

Notably, the anterior insula, where interoception is processed in the brain, is a major component of the SN itself (Molnar-Szakacs & Uddin, 2022), which would explain the special role that interoception seems to play in affect (MacCormack & Lindquist, 2019).