Coordinating brain-distributed network activities in memory resistant to extinction.

Certain memories resist extinction to continue invigorating maladaptive actions. The robustness of these memories could depend on their widely distributed implementation across populations of neurons in multiple brain regions. However, how dispersed neuronal activities are collectively organized to underpin a persistent memory-guided behavior remains unknown. To investigate this, we simultaneously monitored the prefrontal cortex, nucleus accumbens, amygdala, hippocampus, and ventral tegmental area (VTA) of the mouse brain from initial recall to post-extinction renewal of a memory involving cocaine experience. We uncover a higher-order pattern of short-lived beta-frequency (15-25 Hz) activities that are transiently coordinated across these networks during memory retrieval. The output of a divergent pathway from upstream VTA glutamatergic neurons, paced by a slower (4-Hz) oscillation, actuates this multi-network beta-band coactivation; its closed-loop phase-informed suppression prevents renewal of cocaine-biased behavior. Binding brain-distributed neural activities in this temporally structured manner may constitute an organizational principle of robust memory expression.

Finding the right candidate: Developing hiring guidelines for screening applicants for clinical research coordinator positions.

Impact: The success of any clinical research team is dependent on hiring individuals with the experience and skill set needed for a specific research project. Strategies to improve the ability of human resource (HR) recruiters to screen and advance qualified candidates for a project will result in improved initiation and execution of the project. Objective/Goals: HR recruiters play a critical role in matching research applicants to the posted job descriptions and presenting a list of top candidates to the PI/hiring manager for interview and hiring consideration. Methods/Study Population: Creating guidelines to screen for applicant qualification based on resumes when clinical research positions have multiple levels of expertise required is a complex process of discovery, moving from subjective rationale for rating individual resumes to a more structured less biased evaluation process. To improve the hiring process of the research workforce, we successfully developed guidelines for categorizing research coordinator applications by level from beginner to advanced. Results/Anticipated Results: Through guideline development, we provide a framework to reduce bias and improve the matching of applicant resumes to job levels for improved selection of top candidates to advance for interviewing. Improved applicant to job matching offers an advantage to reduce hiring time, anticipate training needs, and shorten the timeline to active project engagement. These guidelines can form the basis for initial screening and ultimately matching individual qualities to project-specific needs.

Training in experimental design and statistics is essential: Response to Jordan.

This Formal Comment responds to Jordan et al., and stresses that if scientific findings are to be robust, training in experimental design and statistics is critical to ensure that research questions, design considerations, and analyses are aligned.

What exactly is 'N' in cell culture and animal experiments?

Biologists determine experimental effects by perturbing biological entities or units. When done appropriately, independent replication of the entity-intervention pair contributes to the sample size (N) and forms the basis of statistical inference. If the wrong entity-intervention pair is chosen, an experiment cannot address the question of interest. We surveyed a random sample of published animal experiments from 2011 to 2016 where interventions were applied to parents and effects examined in the offspring, as regulatory authorities provide clear guidelines on replication with such designs. We found that only 22% of studies (95% CI = 17%-29%) replicated the correct entity-intervention pair and thus made valid statistical inferences. Nearly half of the studies (46%, 95% CI = 38%-53%) had pseudoreplication while 32% (95% CI = 26%-39%) provided insufficient information to make a judgement. Pseudoreplication artificially inflates the sample size, and thus the evidence for a scientific claim, resulting in false positives. We argue that distinguishing between biological units, experimental units, and observational units clarifies where replication should occur, describe the criteria for genuine replication, and provide concrete examples of in vitro, ex vivo, and in vivo experimental designs.