Research Spotlights: January 2021

Brainwave activity connects experiences and expectations during memory recall

A certain frequency of brainwave activity may help us set expectations by comparing our current experience to previous memories of similar experiences. Intramural research conducted by NINDS on patients with epilepsy found that feedforward brain signals, which convey ‘bottom-up’ sensory information to more evolved brain regions (in this case, the neocortex and the medial temporal lobe), can establish a connection with a single visual experience.

Prior research has shown that predictive coding is used by the brain to process common sensory information, such as the sight of green grass or sounds of common bird chirps in our environment. Predictive coding assumes that the prediction of sensory input after exposure to new stimuli involves higher-order neural circuits sending feedback to lower-order neural circuits within the neocortex of the brain. This in turn predicts that the brain uses more energy, or neural activity, to process new information than for old information. This study sought to determine whether the brain used similar predictive coding during the recall of contextual memories by creating an internal model of the world in order to predict future environmental input. Specifically, this study focused on recollection of episodic memory, a type of long-term memory that involves conscious recollection of previous experiences along with the context of time, place, and emotions.

Fourteen participants (seven males, 40.9 ± 12 years) with drug-resistant epilepsy that had been previously implanted with grids of electrodes to diagnose and treat their seizures were included in this study. Patients were asked to memorize a set of four natural scenes on a computer screen, such as a brown bicycle leaning upright on a kickstand in front of a green bush. A few seconds later, a new set of four images were shown; some the same as before, some modified such as a color change or additional object. When asked whether they recognized the scene or noticed a change in the scene, patients successfully recognized 88% of the repeated scenes, 68% of the scenes that were missing something, and 65% of the scenes with a new addition. 82% of the additions and 70% of removals were successfully located in the scene. Interestingly, participants eyes’ frequently fixated on new scene additions (83% of the time) but rarely fixated on areas in which an object was removed (34% of the time).

When researchers looked at the electrical recordings of participants’ brains, they found that brainwave activity differed between when patients successfully remembered a scene that had been previously shown and when they spotted a change to the scene. Both cases prompted a rise of high-frequency brainwaves in the visual processing brain center (occipital cortex) immediately followed by brain activity in the memory brain center (medial temporal lobe). This same brainwave pattern was repeated when the participant saw the scene again, whether the new scene was identical to the earlier scene or slightly modified. However, when patients recognized a change to a scene, the same feedforward brain activity between the occipital and temporal lobe was stronger, indicative of a prediction error signal, and was accompanied by a lower frequency wave. This suggests that our expectations of visual experience are controlled by a feedback loop between the visual cortex and medial temporal lobe, which is amplified when our new experience does not match our expectations. In addition, this lower frequency wave may be responsible for updating our memories.

This data demonstrates how episodic memories can establish expectations based on previous experiences in order to compare to future experiences. In fact, these predictions can be developed after a single exposure to a visual stimulus, suggesting that every experience that we encode into memory may be setting our expectations and predictions for our future actions. As a result, these findings inform future research that will allow us to better understand how the brain portrays reality under healthy and disease conditions.

Haque RU, Inati SK, Levey AI, Zaghloul KA 2020. Feedforward prediction error signals during episodic memory retrieval. Nature Communication. doi: 10.1038/s41467-020-19828-0

A home-court advantage – the importance of circadian rhythms and performance

Basketball fans are acutely aware of the power of home-court advantage, however the specific reasons behind this advantage are unclear. Researchers supported by grants from the NHLBI and the Oregon Institute of Occupational Health Sciences at Oregon Health and Science University leveraged the unique disruptions caused by the COVID-19 pandemic to further investigate this phenomenon.

The specific reasons for the home-court advantage phenomenon have been difficult to study due to multiple variables pertaining to game situations and environment, as well as the effects of travel, which are all occurring at the same time. Due to the COVID-19 pandemic, the National Basketball Association (NBA) paused its season after approximately 64 games in March of 2020 and then resumed games approximately five months later with the top 22 teams isolated together (the “bubble”) to play eight games each to end the regular season. This change in the schedule, that eliminated travel by teams, provided a natural experiment where the researchers could assess the impact of travel and home-court advantage, especially the potential effects of disruptions of the internal body clock from jet-lag due to rapidly crossing time zones, as well as potentially poor sleep for the traveling teams. When traveling across the country into different time zones, the mismatch between the new time zone and a person’s home time zone has a physiological effect in a specific area of the brain called the suprachiasmatic nucleus, also referred to as the master circadian clock. When performing activities that require precision, such as in sports, even slight disruptions in the master circadian clock could negatively affect performance.

The researchers used this unique opportunity to compare the performance of teams during travel before the COVID-19 pandemic with the performance of those same teams that were isolated together for several weeks at Disney World in Orlando, Florida. They retrospectively examined the 22 NBA teams invited to the regular season restart bubble and compared their winning and athletic performance among three playing scenarios: (1) games played at home before the COVID-19 shutdown (649 games total), (2) games played when traveling between zero and three time zones before the COVID-19 shutdown (715 games total), and (3) games played after all teams lived and played in the same location “bubble” for their final eight regular season games (176 games total). Game locations, team results, and statistics were obtained from the website,, where data are published by the official statistics provider of the NBA. The average age of the 22 teams that partook in the bubble was 25.6 years.

Using data collected prior to the COVID-19 pandemic, the researchers found that there were significant differences in performance among teams that traveled within their time zone as compared to those that traveled across time zones. Teams traveling across time zones had a lower winning percentage, shooting accuracy, and turnover percentage. Any traveling reduced the away teams’ offensive rebounding and increased the number of points scored by the home team, regardless of whether the game was played in their own time zone or three time zones away. This may be due to better sleep quality for players that were sleeping in their homes, which are more familiar to them, as compared to sleeping in a hotel. The decline in performance was most notable in the teams that were traveling from the east coast to the west coast.

When players started living and playing in the “bubble” with no travel nor home-court advantage, winning percentage, shooting accuracy, and rebounding were more similar to performance seen when playing with a home-court advantage. These results indicate that home-court advantage in professional basketball may be linked with the away team’s impaired shooting accuracy (less precision) and rebounding, which may be separately influenced by either circadian disruption or the general travel effects, since there were differential effects observed when teams travel within or across multiple time zones.

In summary, this study suggests that even small misalignments between the internal body clock and a new time zone can impact accuracy and impair performance. In this natural experiment the results indicated the home-court advantages may be a result of the away team’s reduced shooting accuracy when traveling multiple time zones and rebounding when traveling in general. These results have implications not only for professional basketball and other competitive sports but also for any activity that requires accuracy and precision performance.

McHill AW, Chinoy ED. 2020. Utilizing the National Basketball Association’s COVID-19 restart “bubble” to uncover the impact of travel and circadian disruption on athletic performance. Sci Rep 10, 21827.

Children gain weight when new convenience stores open nearby

Determinants of obesity have been examined at many levels, but policies and interventions typically target individual factors in order to improve community health. However, evidence on community level factors such as food environments influence on weight is more limited. This study funded by NICHHD, NHLBI, and the Robert Wood Johnson Foundation, aims to understand the relationship between changes in food store availability and changes in weight status using prospective cohort design by investigating availability of different types of small retail outlets selling food, such as convenience stores and grocery stores, and impact on children’s weight in low income minority communities.

In this study, two low income cohorts of children (n=449, male= 53.2%, non-Hispanic Black= 48.3%) ages three to fifteen years old living in New Jersey cities of Camden, New Brunswick, Newark, and Trenton were studied. The New Jersey Child Health Study was designed using a natural experiment framework to investigate changes in the environment over a two to five-year period. Survey data were collected in the four cities between 2009 and 2017. Demographic data on children’s and other household members’ heights and weights, behaviors, and perceptions of community environment were collected using computer aided telephone interviews in English and Spanish.

A longitudinal home address database was used to identify and track the change in location of the children’s home address during the study, and all addresses were subsequently geocoded. The food environment around a child’s home was calculated for each month between the two timepoints using the home address and the data on community food environment. The predictor variable was constructed using geocoded addresses of all residencies. Origin-destination matrix, numbers of food outlets up to a one mile-buffer in the child’s residence, and number of months between time points were used to conduct the analysis. Differences in average monthly counts between the two timepoints were taken to determine change in food environment over time. Proportional-odds cumulative logit regression models were used to assess distance and length of food environment exposure variables.

At timepoint one, 25% of children were classified as obese based on zBMI measurements (measure of relative body mass index adjusted for child age and sex), calculated using parent-reported height and weight. Weight change was measured between the two timepoints using three weight change categories. zBMI did not change in 41.2% of children, decreased in 33.6% of children, and increased in 25.2% of children.

In addition, food outlets were categorized based on previous literature as supermarkets, small grocery stores, convenience stores, pharmacies, full-service restaurants, or limited service restaurants. This study found that if a convenience store was added within 24 months after the first time point, the child had 11.7% higher odds of having a higher zBMI (P=0.007). This relationship was statistically significant (P < 0.05) when convenience stores were examined within a one-mile radius (where confidence intervals are smaller due to a higher prevalence of change) for all time periods of exposure, and the pattern was consistent across models representing other distance/length of exposure combinations. Statistically significant evidence suggest children were less likely to have increases in zBMI scores with exposure to small grocery stores compared to other types of food outlets.

Increased exposure to convenience stores was associated with less healthy weight changes (higher zBMI) in children over time and provides evidence of the link between unhealthy outcomes and closer distance to convenience stores. Children’s exposure to nearby small grocery stores, which contained healthier food, over time observed less increase in zBMI change. The findings provide evidence for improving the food environment by increasing access to food outlets like small grocery stores in low income communities which may impact childhood obesity in communities with unhealthy food environments. This may inform food environment policies needed to address childhood obesity in low income communities in other areas of the United States.

Ohri-Vachaspati P, Acciai F, Lloyd K, Tulloch D, DeWeese RS, DeLia D, Todd M, Yedidia MJ. Evidence That Changes in Community Food Environments Lead to Changes in Children’s Weight: Results from a Longitudinal Prospective Cohort Study. J Acad Nutr Diet.