Towards a functional neuroanatomy of pleasure and happiness

Abstract

The pursuit of happiness is a preoccupation for many people. Yet only the pursuit can be promised, not happiness itself. Can science help? We focus on the most tractable ingredient, hedonia or positive affect. A step toward happiness might be gained by improving the pleasures and positive moods in daily life. The neuroscience of pleasure and reward provides relevant insights, and we discuss how specific hedonic mechanisms might relate to happiness or the lack thereof. Although the neuroscience of happiness is still in its infancy, further advances might be made through mapping overlap between brain networks of hedonic pleasure with others, such as the brain's default network, potentially involved in the other happiness ingredient, eudaimonia or life meaning and engagement.

Fig 1. Measuring reward and hedonia

Reward and pleasure are multifaceted psychological concepts. Major processes within reward (first column) consist of motivation or wanting (white), learning (blue), and – most relevant to happiness – pleasure liking or affect (light blue). Each of these contains explicit (top rows, light yellow) and implicit (bottom rows, yellow) psychological components (second column) that constantly interact and require careful scientific experimentation to tease apart. Explicit processes are consciously experienced (e.g. explicit pleasure and happiness, desire, or expectation), whereas implicit psychological processes are potentially unconscious in the sense that they can operate at a level not always directly accessible to conscious experience (implicit incentive salience, habits and ‘liking’ reactions), and must be further translated by other mechanisms into subjective feelings. Measurements or behavioral procedures that are especially sensitive markers of the each of the processes are listed (third column). Examples of some of the brain regions and neurotransmitters are listed (fourth column), as well as specific examples of measurements (fifth column), such as an example of how highest subjective life satisfaction does not lead to the highest salaries (top) . Another example shows the incentive-sensitization model of addiction and how ‘wanting’ to take drugs may grow over time independently of ‘liking’ and ‘learning’ drug pleasure as an individual becomes an addict (bottom).

Fig 2. Hedonic brain circuitry

The schematic figure shows the brain regions for causing and coding fundamental pleasure in rodents and humans. (a) Facial ‘liking’ and ‘disliking’ expressions elicited by sweet and bitter taste are similar in rodents and human infants. (b, d) Pleasure causation has been identified in rodents as arising from interlinked subcortical hedonic hotspots, such as in nucleus accumbens and ventral ‘pallidum, where neural activation may increase ‘liking’ expressions to sweetness. Similar pleasure coding and incentive salience networks have also been identified in humans. (c) The so-called ‘pleasure’ electrodes in rodents and humans are unlikely to have elicited true pleasure but perhaps only incentive salience or ‘wanting’. (d) The cortical localization of pleasure coding may reach an apex in various regions of the orbitofrontal cortex, which differentiate subjective pleasantness from valence processing of aspects the same stimulus, such as a pleasant food.

Fig 3. The brain' s default network and eudaimonic – hedonic interaction

(a - c) The brain's default network , has been linked to self awareness, remembering the past and prospecting the future . Some components overlap with pleasure networks, including midline structures such as the orbitofrontal, medial prefrontal and cingulate cortices. We wonder whether happiness might include a role for the default network, or for related neural circuits that contribute to computing relations between self and others, in evaluating eudaimonic meaning and interacting with hedonic circuits of positive affect. Examples show (d) key regions of the default network such as the anterior cingulate and orbitofrontal cortices that have a high density of opiate receptors , (e) have been linked to depression , and (f) its surgical treatment . (g) Subregional localization of function may be indicated by connectivity analyses of cingulate cortex and related structures, (h) important in pleasure-related monitoring, learning and memory , (i) as well as self-knowledge, person perception and other cognitive functions . (j) The default network may change over early life in children and pre-term babies , , (k) in pathological states including depression and vegetative states, (l) and after lesions to its medial orbitofrontal and subgenual cingulate cortices that disrupt reality monitoring and create spontaneous confabulations.