Research Spotlights: September 2019

research spotlight

Making long-term memories requires teamwork

Memory is fundamental to human behavior and when impaired, as seen in diseases associated with aging such as Alzheimer’s, can severely impact a person’s daily life and quality of life. Recent research supported by the BRAIN Initiative, NINDS, the American Heart Association, the Della Martin Foundation, and the Burroughs Wellcome Fund sheds light on how long-term memories are made. Previous research has shown that memories are processed and stored by complex neuronal networks across several brain circuits; however, how neurons do this for long-term memories is not well understood. To investigate long-term memory, brain activity was recorded and analyzed of mice performing a location-based memory task to locate a sugar water reward. In initial trials, mice were allowed to explore the arena until they found the reward. During these trials the neural recordings showed single neurons activated when the mouse noticed a symbol on the wall where they received the reward. After several trials, the brain recordings showed an increase in the number of neurons that were synchronously activated as the mice became better at performing the task. To study how memories fade over time, the mice were removed and kept away from the arena for up to 20 days. Despite the time away from the arena, the mice performed the task well, indicating that a strong memory was formed. These memories were still encoded by high numbers of neurons that fired in synchrony. Even though some of the original neurons showed asynchronous activity, the neural activity pattern of the larger group of neurons was still identifiable for that memory task. By using groups of neurons working in synchrony the brain provides redundancy so that memories can be recalled even if some of the original neurons are damaged. One theory regarding memory storage contends that in order to make a memory stronger the connections to individual neurons must be strengthened. However, the results from this study suggest that increasing the number of neurons that encode the same memory is what allows for long-term (stronger) memories. These findings may have implications for aging and diseases that affect memory, suggesting that memory loss may increase in aging due to fewer neurons being used to encode each memory. Potentially, designing treatments that could boost the recruitment of a higher number of neurons to encode memories could help prevent memory loss.

Citation: Gonzalez WG, Zhang H, Harutyunyan A, Lois C. 2019. Persistence of neuronal representations through time and damage in the hippocampus. Science, 365(6455): 821-825.

Double the benefit: Treating posttraumatic stress disorder leads to a decrease in the incidence of type 2 diabetes in veterans

In a recent publication, researchers supported by the NHLBI and the Harry S. Truman Memorial Veterans’ Hospital conducted a retrospective cohort study in veterans with posttraumatic stress disorder (PTSD) to determine if PTSD symptom improvement is associated with changes in type 2 diabetes (T2D) risk. Having PTSD increases a person’s risk for certain chronic health conditions, such as depression, alterations in sleep, and T2D. There is also a high prevalence of obesity, glucose dysregulation, inflammation, metabolic syndrome, and depression among those diagnosed with PTSD versus those without PTSD, which may also contribute to the increased T2D risk. Improving PTSD symptoms has been correlated with improvements in some of these conditions, including depression and general physical health. In this study, the researchers reviewed Veterans Health Affairs medical records from 2008–2015 and randomly selected 5,916 cases (patient ages 18–70) who had two or more visits to PTSD specialty care between 2008–2012 and followed their records through 2015. Patient eligibility was determined by having a PTSD Checklist (PCL) score of 50 or higher at these prior visits. Patients were defined as having a clinically meaningful improvement in PTSD symptoms if their PCL scores were reduced by 20 points or more during a 12-month or as having little or no improvement if their PCL scores were reduced by less than 20 points. A total of 1,598 patients met the eligibility requirements and were included in the study (mean age, 42 years; 1,347 [84 percent] male; 1,060 [66 percent] Caucasian). During the 2- to 6-year follow-up, the incidence of T2D was 49 percent lower for patients that had a clinically meaningful reduction in PTSD (2.6 percent), as opposed to patients that did not (5.9 percent). This difference in T2D risk persisted even after controlling for confounding factors (such as demographic, psychiatric and physical comorbidities, as well as the number of psychotherapy sessions) with these patients being significantly less likely to develop T2D compared with those without a clinically meaningful decrease (hazard ratio, 0.51; 95 percent CI, 0.26–0.98). These results suggest PTSD symptom improvement is associated with a lower risk of T2D. In patients with only PTSD, a clinically meaningful reduction in PTSD was associated with a lower risk for T2D. In patients with PTSD and depression, the improvement in both conditions was associated with a lower risk for T2D. Unexpectedly, the PTSD improvement was not associated with a change in body mass nor in A1C values. Future prospective studies are needed to further understand these association between PTSD, depression, and T2D risk.

Citation: Scherrer JF, Salas J, Norman SB, Schnurr PP, Chard KM, Tuerk P, Schneider FD, van den Berk-Clark C, Cohen BE, Friedman MJ,  Lustman PJ. 2019. Association Between Clinically Meaningful Posttraumatic Stress Disorder Improvement and Risk of Type 2 Diabetes. JAMA Psychiatry. doi:10.1001/jamapsychiatry.2019.2096. [Epub ahead of print]

Your networks influence your social perceptions

Recent research supported by NICHD, Complex Systems Society’s Bridge Fund and GESIS, and the Army Research Office, investigated social perception bias and how a person’s peer networks influence these biases. Social perception bias is an individual’s tendency to assume that others think the same as they do, and to underestimate the size and influence of a minority group. These social perception biases are often attributed to biased cognitive or motivational processes rather than social network structure. However, it has been observed that social perception biases can be related to the structural properties of personal networks, which can greatly influence the information and information sources that are used when forming their social perceptions. This research sought to determine the impact of different network properties on social perception biases such as (1) the level of homophily or how likely are the people in the network to be similar to each other; (2) asymmetry of homophily, or whether homophily is larger in some subgroups than in others; and (3) the relative size of minority and majority groups in a society. The research team used a previously developed network model for a society consisting of majority and minority groups. Based on the position of an individual node within the network, the researchers predicted different perception biases would arise depending on two network properties: the relative sizes of the majority and minority groups, and their level of homophily. In this model, the researchers did not control for individual cognitive processes, so an individual's perception was based solely on their network. The team then develop and administered a survey to 300 participants (Germany, n = 99; South Korea, n = 100; United States, n = 101) to test the model's predictions. Additionally, the researchers examined six empirical networks; a Brazilian network, a Swedish dating network, a Facebook network of a university in the United States, a network extracted from the collaborative programming environment GitHub, a network of scientific collaborations in computer science, and a scientific citation network of the APS. Using a multi-country survey, analytical investigations of a network model, and numerical simulations on real-world networks, the researchers showed that structural properties of personal networks strongly affect perception biases. Additionally, the greatest perception biases emerged when majority and minority groups were very different in size, and when nodes within the same group were highly connected to each other. In these situations, individuals in both groups tended to overestimate their own group and underestimate the other. Other perception biases were demonstrated, such as the tendency for a majority group to overestimate the presence of a minority group when the two groups are more evenly dispersed within the network (heterophily). The model predictions corresponded well with the cross-cultural survey data and with numerical calculations from the six real-world networks. Additionally, the research team was able to identify circumstances under which individuals can reduce their biases by relying on perceptions of their neighbor. This work advances the understanding of the impact of social network structure on social perception biases and provides a quantitative mechanistic description of selective exposure that may play an important role in social perception biases.

Citation: Lee E, Karimi F, Wagner C, Jo H, Strohmaier M, Galesic M. 2019. Homophily and minority-group size explain perception biases in social networks. Nat Hum Behav. doi: 10.1038/s41562-019-0677-4. [Epub ahead of print]