A Digital Game for Undergraduate Calculus

This study has two goals: first, to investigate the effectiveness of using a digital game to teach undergraduate-level calculus in improving task immersion, sense of control, calculation skills, and conceptual understanding, and second, to investigate how feedback and visual manipulation can facilitate conceptual understanding of calculus materials. One hundred thirty-two undergraduate students participated in a controlled lab experiment and were randomly assigned to either a game-playing condition, a practice quiz condition, or a no-treatment control condition. The authors collected survey data and behavioral-tracking data recorded by the server during gameplay. The results showed that students who played the digital game reported highest task immersion but not in sense of control. Students in the game condition also performed significantly better in conceptual understanding compared to students who solved a practice quiz and the control group. Gameplay behavioral-tracking data was used to examine the effects of visual manipulation and feedback on conceptual understanding.

The gut microbiota affects the social network of honeybees

The gut microbiota influences animal neurophysiology and behavior but has not previously been documented to affect emergent group-level behaviors. Here we combine gut microbiota manipulation with automated behavioral tracking of honeybee sub-colonies to show that the microbiota increases the rate and specialization of social interactions. Microbiota colonization was associated with higher abundances of one third of metabolites detected in the brain, including several amino acids, and a subset of these metabolites were significant predictors of social interactions. Colonization also affected brain transcriptional processes related to amino acid metabolism and epigenetic modification in a brain region involved in sensory perception. These results demonstrate that the gut microbiota modulates the emergent colony social network of honeybees, likely via changes in chromatin accessibility and amino acid biosynthesis.

Hierarchical organization of rhesus macaque behavior

Primatologists, psychologists and neuroscientists have long hypothesized that primate behavior is highly structured. However, fully delineating that structure has been impossible due to the difficulties of precision behavioral tracking. Here we analyzed a dataset consisting of continuous measures of the 3D position of fifteen body landmarks from two male rhesus macaques (Macaca mulatta) performing three different tasks in a large unrestrained environment over many hours. Using an unsupervised embedding approach on the tracked joints, we identified commonly repeated pose patterns, which we call postures. We found that macaques' behavior is characterized by 49 distinct identifiable postures, lasting an average of 0.6 seconds each. We found evidence that behavior is hierarchically organized, in that transitions between poses tend to occur within larger modules, which correspond to intuitively identifiably actions; these actions are in turn organized hierarchically. Our behavioral decomposition allows us to identify universal (cross-individual and cross-task) and unique (specific to each individual and task) principles of behavior. These results demonstrate the hierarchical nature of primate behavior and provide a method for the automated "ethogramming" of primate behavior.

Assessing the bioactivity of cannabis extracts in larval zebrafish

Background Whole-plant cannabis extracts are consumed by the public for medical and non-medical (“recreational”) purposes but are poorly researched compared to pure cannabinoids. There is emerging evidence that cannabis extracts comprising complex mixtures of cannabinoids may have different biological effects from that of pure cannabinoids. In the current study, we sought to assess the effect of whole-plant cannabis extracts produced from different chemotypes of cannabis on the normal behavior of zebrafish larvae. Methods Three cannabis plant chemotypes were used in this study that contained either high amounts of THC, high amounts of CBD, high but equal amounts of THC and CBD, or low but equal amounts of THC and CBD. Following solvent extraction, liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) was performed for the detection and quantitation of target cannabinoids. Larval zebrafish behavioral models were subsequently used to assess the effect of the four different whole-plant cannabis extracts on the normal larval behavior using the DanioVision behavioral tracking systems and software. To compare, changes in the behavior activity levels for 30 min periods were compared to controls using 2-way ANOVA with multiple comparisons followed by a Bonferroni post hoc test. Results It was found that the whole-plant extracts that contained high levels of THC had similar effects on larval behavior, while the high CBD and low THC:CBD extracts produced distinct effects on normal larval behavior. Exposure of larvae to concentration-matched levels of THC and CBD found in the extracts revealed that a subset of the cannabis extracts tested had similar behavioral profiles to the pure cannabinoids while others did not. Conclusions To our knowledge, this is the first study to test and compare the bioactivity of different whole-plant cannabis extracts in larval zebrafish. This work will provide a framework for future studies of distinct cannabis extracts and will be useful for comparing the bioactivity of extracts from different cannabis chemotypes as well as extracts made through various heating processes. It will also act as the first stage of assessment before testing the extracts against zebrafish models of toxicity and disease.

Invasive Electrophysiology for Circuit Discovery and Study of Comorbid Psychiatric Disorders in Patients With Epilepsy: Challenges, Opportunities, and Novel Technologies

Intracranial electroencephalographic (iEEG) recordings from patients with epilepsy provide distinct opportunities and novel data for the study of co-occurring psychiatric disorders. Comorbid psychiatric disorders are very common in drug-resistant epilepsy and their added complexity warrants careful consideration. In this review, we first discuss psychiatric comorbidities and symptoms in patients with epilepsy. We describe how epilepsy can potentially impact patient presentation and how these factors can be addressed in the experimental designs of studies focused on the electrophysiologic correlates of mood. Second, we review emerging technologies to integrate long-term iEEG recording with dense behavioral tracking in naturalistic environments. Third, we explore questions on how best to address the intersection between epilepsy and psychiatric comorbidities. Advances in ambulatory iEEG and long-term behavioral monitoring technologies will be instrumental in studying the intersection of seizures, epilepsy, psychiatric comorbidities, and their underlying circuitry.