Distinct Patterns of Activity Underlie the Motivation to Be Fair

Post by Shireen Parimoo

What's the science?

Why are people motivated to be fair? People can be fair for prosocial reasons when they value the well-being of others, or for strategic reasons when being unfair might cost them something. In the ultimatum game, which is often used to evaluate fairness, people offer to split a sum of money with a recipient who accepts or rejects the offer. Participants typically offer 40% of the sum, which suggests that they could be acting prosocially by providing a nearly equal split. Conversely, they could be acting strategically to ensure that the recipient does not reject the offer. The ultimatum game activates regions of the brain like the dorsolateral prefrontal cortex (dlPFC) that are involved in strategic processing. Prosocial behavior is thought to be supported by Theory of Mind (ToM), which is the ability to empathize with and understand other people’s mental states. No study has yet to examine the pattern of activity in brain regions belonging to the ToM network while people make fair or unfair decisions. This week in Social Cognitive and Affective Neuroscience, Speer and Boksem used functional magnetic resonance imaging to distinguish between patterns of activity associated with prosocial and strategic motivations in the cognitive control and ToM networks.

How did they do it?

Thirty-one young adults played the ultimatum game (UG) and the dictator game (DG) while undergoing functional magnetic resonance imaging scanning. They had to split €20 and could offer between €0-14 to their opponent. Half of the trials consisted of the UG and the other half of the trials consisted of the DG. Unlike the UG, there is no strategic advantage to offering a fair split in the DG, as opponents cannot reject offers made by participants. To evaluate behavior, the authors calculated the difference between the amount of money that participants offered in the two games. Participants were categorized as selfish players if there was a large difference in their offers between the two games, which suggests that they were acting strategically during the UG by offering more money to their opponent.

The authors examined patterns of activity in the ToM and cognitive control networks during the two games. First, they used Neurosynth (an online database of fMRI studies) to identify brain regions that are often active during ToM and cognitive control tasks, which included the temporoparietal junction (TPJ) and the medial prefrontal cortex (mPFC) in the ToM network and the dlPFC and posterior cingulate cortex (PCC) in the cognitive control network. For each participant, they created a model (a support vector machine classifier) to distinguish between the two games based on the pattern of activity in these networks and in individual brain regions. The classifier was trained on brain activity on a subset of UG and DG trials and then tested with a different set of trials to predict whether the pattern of activity corresponds to the UG or the DG. They correlated classifier performance with behavior to determine how patterns of activity related to participants’ motivations in the two games. Finally, to identify other brain regions that might be differentially activated by the two games, the authors applied the classifier to the whole brain by targeting a small area at a time and then correlated classifier performance with behavior.

What did they find?

In general, people made higher offers to their opponents in the UG than in the DG. There were large individual differences in motivation, as prosocial participants made similar offers between the two games whereas selfish players offered comparatively less money to their opponent in the DG. Classification accuracy in the ToM and cognitive control networks was related to behavior. Distinct patterns of activity in these networks were found to underlie prosocial and strategic motivations, as the classifier was more accurate at distinguishing between the two games when participants were behaving strategically than when they were driven by prosocial motivations.

Patterns of activity in individual regions of the ToM and cognitive control networks also differed between prosocial and selfish players. For example, activity in the left TPJ was more different across the two games in selfish players than in prosocial players. Similarly, classification accuracy in the bilateral dlPFC and PCC was higher when the difference in offers was larger, suggesting that the pattern of activity was more distinct between the two games in selfish than in prosocial players. Finally, classifier performance in other regions like the bilateral TPJ, mPFC, and the left IFG was also related to behavior. These results indicate that prosocial players exhibited similar patterns of activity in the two games because they did not differentially engage in strategic and prosocial reasoning. On the other hand, selfish players engaged regions in the ToM and cognitive control network differently when they were motivated to behave strategically in the UG game, even when their offers do not differ from prosocial individuals.

What's the impact?

This study is the first to demonstrate that distinct patterns of activity in the ToM and cognitive control networks underlie prosocial and strategic motivations. Importantly, these results provide a deeper insight into how people rely on both cognitive control processes and ToM processes like empathy to make fairness decisions. 

Speer and Boksem. Decoding fairness motivations from multivariate brain activity patterns. Social Cognitive and Affective Neuroscience (2020). Access the original scientific publication here.

Hypothetical Experiences Encoded by Fast, Regular Firing of Hippocampal Place Cells

Post by Amanda McFarlan

What's the science?

Whether for planning, imagination or decision-making, the ability to construct a hypothetical scenario is an important cognitive process that is fundamental to the brain. Recent studies have identified place cells in the hippocampus (a brain region known to be important for memory and spatial navigation) as a potential neural substrate for thinking about hypotheticals, as place cell firing has been observed to encode hypothetical spatial paths. However, the mechanisms underlying this activity remain unclear. This week in Cell, Kay, and colleagues investigated the role of hippocampal place cells in encoding hypothetical experiences.

How did they do it?

To study the activity of place cells, the authors trained rats to navigate a maze. By design, the maze was extremely simple: it had a single fork where rats had to choose between left or right. The rats were either placed in the centre arm of the maze where they had to move towards the fork (choice imminent group) or they were placed at the fork immediately (choice passed group). As rats ran in this maze, the authors recorded and analyzed the activity of place cells in the moments before the rats chose either the left or right arm of the maze. By doing so, they could determine whether place cells encoded the unchosen arm, and thus, encoded a hypothetical future scenario. The authors examined place cell activity at three levels: single cells, cell pairs, and at the population level. At the population-level, the authors used a decoding algorithm that summarizes the activity of all the cells (approximately dozens to hundreds of cells) recorded in the experiment.

What did they find?

The authors initially found that pairs of place cells encoding either the left or right arm of the maze fired in an alternating pattern at approximately 8 Hz, suggesting that future scenarios (choosing the left or right arm) could be encoded extremely quickly yet also extremely consistently. The authors further found that place cells were also more likely to fire in an alternating pattern when rats were approaching the maze fork (choice imminent group) compared to when they were moving away from the fork (choice passed group). Next, the authors showed that place cells at the population level encoded left and right arms in alternation at 8 Hz, similarly to what was observed in pairs of place cells. In the second stage of their study, they found that place cell activity encoding hypotheticals occurs systematically at specific phases of an 8 Hz neural rhythm called hippocampal theta, indicating that the hypothetical-encoding activity originates from a specific internal brain process. Overall, these findings indicate that hypothetical future scenarios can be neurally encoded both quickly and regularly (at 8 Hz) and that the underlying neural activity can be observed not only at the population level, but even down to the single-cell level.

What’s the impact?

This is the first study to show that neural firing can encode multiple hypothetical future scenarios both quickly and consistently (8 times a second). The authors also found that such neural firing could be seen at the single-cell, cell-pair, and population levels, and was influenced by both behavioral and anatomical factors. Together, these findings provide insight into the neural basis of how the brain can come up with hypothetical scenarios, an ability that is essential to complex cognition.

Kay et al. Constant Sub-second Cycling between Representations of Possible Futures in the Hippocampus. Cell (2020). Access the original scientific publication here.

Online Mindfulness-Based Cognitive Therapy in Patients with Depression

Post by Stephanie Williams

What's the science?

Many individuals with depression experience residual symptoms after receiving treatment. Some individuals may even experience a relapse after treatment. To combat relapse and to encourage full remission of symptoms, a mindfulness-based cognitive therapy program was designed to teach individuals to regulate their emotions by breaking out of harmful ruminating thought patterns. The program was designed with an online framework in order to bypass the usual barriers to in person-psychological interventions, including in-person travel times,  service costs, and long waiting list times, among others. This week in JAMA Psychiatry, Segal and colleagues assess whether the addition of an online mindfulness-based cognitive therapy program to regular treatment for depression can reduce residual symptoms, decrease relapse, and increase remission.

How did they do it?                             

To assess how well the online cognitive therapy program (“Mindful Mood Balance'') could help reduce depressive symptoms, the authors randomly assigned a large cohort (N=460) of participants with depression to one of two groups and assessed their progress over a 15 month period. The first 3 months of the study consisted of an active intervention phase, and the remaining 12 months were used as a follow-up phase. The treatment for the ‘usual depression care’ group included regular access to psychotropic medication and cognitive therapy sessions. The treatment for the mindfulness group was identical, except for the addition of the online mindfulness cognitive therapy program. To qualify for the study, participants must have experienced one depressive episode, have scored between 5 and 9 on PHQ-9, and have been older than 18. The mindfulness-based online cognitive therapy program was segmented into eight sessions. The core idea of the program was to teach participants how to break out of habitual, dysfunctional cognitive patterns (eg. depression-related rumination). To assess the effect of the program on participants’ moods, the authors administered a standard 9-item questionnaire, the PHQ-9, which is known to track depression severity. The authors assessed 3 primary outcomes of interest using the PHQ-9 results, including 1) the amount of reduction in residual symptom severity 2) the rate of remission (a score of 5 on the PHQ-9 was used as a threshold for remission) and 3) the rate of depressive relapse. The authors also administered a seven-item questionnaire related to generalized anxiety disorder, called GAD-7. They used this survey to assess the reduction in each participant’s anxiety symptoms. 

What did they find?

The authors found that the group that received the additional online mindfulness training showed a significantly greater reduction in symptoms across the entire study period compared to the usual depression care group. When the authors compared the reduction in residual symptoms for the two groups across the 12-month follow-up phase of the study, they found that patients who received the additional online training maintained their initial gains in symptom reduction. The authors also found residual symptoms of individuals who received usual depression care without the online program continued to decrease over the 12-month follow-up phase. When the authors assessed the rate of remission among subjects, they found that individuals in the group who received the additional online module achieved remission of their symptoms at a significantly higher rate (59.4%) compared to the group with standard treatment alone (47.0 %). The individuals in the online program treatment group continued to maintain their low rates of remission across the 12-month follow-up phase, while the standard treatment group showed increased rates of remission across the 12-month follow-up phase. When the authors assessed the relapse rate, they found a lower rate of relapse in the mindfulness program group (13.5%) compared to the group that received usual depression care (23%). Results from the generalized anxiety survey showed that the group receiving the additional online treatment showed a mean decrease in their anxiety scores.  

What's the impact?

The authors show that the addition of a low-cost, accessible online program can significantly attenuate depressive symptoms better than usual depressive care alone. These results will inform the treatment of future patients with depression, and provide encouraging evidence that better symptom reduction and remission can be achieved using additional treatment strategies. 

Segal et al. Outcomes of Online Mindfulness-Based Cognitive Therapy for Patients with Residual Depressive Symptoms. Jama Psychiatry. (2020). Access the original scientific publication here.