What makes you happy?
For me: The sun, the ocean, cute animals, musicals, and all things Wicked.
But, how do you know you are happy? Glinda asks this of Elphaba at the beginning of “Defying Gravity” in the 2024 movie soundtrack by Cynthia Erivo and Ariana Grande. Listening to this song produces goosebumps, smiles, and a “strange exhilaration,” just like in “What is this Feeling” (Cynthia Erivo and Ariana Grande or Idina Menzel and Kristen Chenoweth)!
Unfortunately, most of us don’t have a set of pipes (stolen or otherwise, thank you, Scuttle from Little Mermaid) to belt out our feelings through song, and we have to rely on other measures to identify them.
Neuroscientists (wizards with a little more power than the Wizard in Wicked) have focused quite a bit of research on mapping the neural underpinnings of the reward pathway, which encompasses areas such as the medial prefrontal cortex, orbitofrontal cortex, ventral striatum, and basolateral amygdala via cortico-striatal-limbic projections (see the figures in this paper to visualize the areas of interest and not the ChatGPT version presented below).
Research with rats and humans has indicated that the timing of a reward and the amount of a reward is processed within this network and may translate to various psychiatric conditions with impaired systems, such as anhedonia or addictions.
This pathway has been targeted in humans in an effort to predict dysregulation through observable measures that are less invasive than single-cell recordings or neuroimaging. One promising line of research for a physiological biobehavioral marker is monitoring the oscillations of specific waves (e.g., theta and beta waves).
Brain wave activity can be distinguished into five types in humans: Gamma, Beta, Alpha, Theta, and Delta. Each wave type is linked to a particular behavioral state, with many of those states conserved across other animal species. In humans, Beta waves, ranging between 12-35 HZ, indicate an active, externally attentive state, while Theta waves, ranging between 4-8 HZ, indicate a more relaxed state.
In research with rodents and humans using electrophysiological recordings of brain wave activity patterns along the cortico-striatal-limbic, changes in activity patterns are related to reward expectations. For example, Theta wave oscillations appear to be linked to cognitive-control processes while beta wave oscillations change specifically to reward feedback, like the rat receiving a big payout of pellets and then receiving a smaller payout the next time, or in my case, listening to Ariana Grande sing Popular versus the theater-goers singing along during the movie.
Koloski, Hulyalker, Barnes, Mishra, and Ramanathan (all pictured below except Hulyalker) investigated whether or not a physiological biomarker could be linked to reward processing by Long-Evans rats in a recent study published by the Psychonomic Society’s Cognitive, Affective, and Behavioral Neuroscience.
Before Elphaba is Galinda-fied
For this study, the rats went through several rounds of training to familiarize themselves with the task before measuring electrophysiological responses. First, the researchers conditioned the rats to respond to the presence of a stimulus (LED light) to receive the reward. When the light was on at one of the ports (NP2, NP3, NP4 in the image below), the water reward was available. In the next training phase, the rats learned that they started in NP3 and could receive an immediate water reward in either NP2 or NP4.
Following the initial training, the researchers introduced the temporal discounting task training in which the rats learned that a small reward would be delivered after a short delay (500ms) if they chose NP2 or a larger reward would be delivered after a longer delay (delays varied across sessions) if they chose NP4. The rats were given visual and sound cues to know which choice was currently available so they could learn the difference between the two types of rewards. All water rewards were received through NP3 once the rat made a choice. The figure above (A) provides the conditions in which rewards were given and the protocol used for each trial.
Elphaba Gets Her “Smart” Hat
Once an animal demonstrated a preference for the larger, delayed reward (.5), it received additional training on other delay durations (1, 2, 5, 10, or 20s) to ensure it had learned the temporal discounting task. Animals that passed this training phase also moved on to the testing phase, in which an electrode was implanted to measure brain wave activity during experimental conditions.
As seen in the figure above, B, delays up to 5 sec were associated with reliable preferences for the large reward overall, with 10s and 20s delays showing a preference for 50% and 25%, respectively, of the choices made by the animals as a group. At these longer delays, many of the rats shifted to the smaller magnitude rewards. However, individual differences between the rats did emerge, with some rats showing clear preferences across all time delays (the first 3 lines).
To assess the physiological biomarker of beta wave activity, the rats had electrodes placed at 12 different locations. The expectation was that beta wave activity (15-30 Hz) would have more power for a large reward (30 microliters) than a small reward (10 microliters) when the delay was the same (.5 seconds).
Using measurements made from the lateral orbitofrontal cortex, the results supported this prediction, as seen in panel A in the figure below. The yellow colors on the left panel (large reward) indicated greater power than the blue colors on the right panel (small reward).
This difference in power was significant only for beta wave activity and not for any other wave type, as seen by the difference between the teal bars in Panel B in the figure above. Finally, as the reward was delayed more, the power of the beta wave activity decreased for the larger magnitude reward, while the beta wave power for a small magnitude reward remained stable or slightly increased across delays, as seen in Panel C in the figure below. No differences emerged across the different electrode sites, as Panel D illustrates above.
Timing Matters as “No One Mourns the Wicked”
Like Elphaba, who harnessed her power once she found the path to right the wrongs of Oz, the researchers also found evidence for additional brain areas involved in selecting the large reward trials. Specifically, the researchers found increased power for beta wave activity in a more extended network, including the prefrontal cortex, orbitofrontal cortex, and the ventral striatum. However, the longer the delay, the less active these areas became, as indicated by the greater number of yellow pixels on panel A with the shortest delay (0.5 s delay) and decreasing number of yellow pixels across panel B with a 10s delay and panel C with a 20s delay.
Image from Figure 3A of Koloski et al. (2024) showing the changes in power in beta wave activity across delay of delivery as evidence of an extended network. The x- and y-axis show the 12 different electrode sites.
The electrophysiological findings were also validated with a computational model tested by the researchers and a pilot study involving electrical stimulation of specific electrodes using a beta frequency (20 Hz), which biased the tested rats to choose a larger, delayed reward.
“Defying Gravity” (from 2003 Broadway recording by Idina Menzel and Kristen Chenoweth)
Studies like these incrementally increase our mechanistic understanding of the brain’s role in reward processing. When convergence between human-based outcomes and rodent-model outcomes is achieved, as it is with this line of research, we inch one step closer to understanding the mechanisms behind reward processing. These small steps (small rewards) will hopefully lead to larger rewards of learning how to reset brain regions involved in neuropsychiatric disorders like depression or addictions.
In the meantime, keep those immediate small rewards in mind for those times you need a little more motivation and keep those delayed larger rewards for significant advancements. In the meantime, enjoy “Dancing Through Life” as your reward for reading this post.
Featured Psychonomic Society paper
Koloski, M. F., Hulyalkar, S., Barnes, S. A., Mishra, J., & Ramanathan, D. S. (2024). Cortico-striatal beta oscillations as a reward-related signal. Cognitive, Affective, & Behavioral Neuroscience, 24(5), 839-859. https://doi.org/10.3758/s13415-024-01208-6
