Implementing and Evaluating a Mentor Training to Improve Support for Early-Career Scholars in Tobacco Regulatory Science.

INTRODUCTION: To implement and evaluate a blended online and in-person training to help mentors of early-career researchers appreciate the complexities of Tobacco Regulatory Science (TRS), refine TRS mentoring skills, and become acquainted with resources for providing effective guidance to TRS mentees. METHODS: TRS mentors engaged in a two-part pilot test of the training program. Authors evaluated both the online and in-person training using retrospective pre-post evaluations, which measure learning at the conclusion of a training program, and post-program focus groups. Twenty learners completed the online training, and 16 learners attended the in-person training module. Nine participants completed evaluations for the online module, and 12 participants completed evaluations for the in-person module. RESULTS: Program assessments revealed that participants found that the training achieved its overall goals. The majority of respondents (87.5%) rated the online portion of the training as valuable. For the in-person training, participants reported statistically significant improvements regarding confidence in: helping mentees to identify skills and training to effectively pursue TRS, assisting mentees in weighing career trajectories, and guiding mentees in conducting research responsive to TRS regulatory priorities. CONCLUSIONS: The novel mentoring program was well received by faculty seeking to strengthen skills for mentoring early-career TRS researchers to navigate the complex landscape of TRS, explore diverse funding opportunities, and discern potential career trajectories. It provided unique content to address issues outside the traditional tobacco research training curriculum and offered specific information on regulatory policies, priorities, and opportunities. IMPLICATIONS: This research documents the deployment and evaluation of a blended online and in-person training program for investigators mentoring early-career researchers working in TRS. Our assessment discovered that participants found the training to be valuable to their overall mentoring objectives. The training comprises a novel curriculum for investigators engaged in mentoring early-career researchers in a unique field, thus filling a deficit in the published literature by presenting a curriculum that has been customized to the unique needs of TRS mentors.

Latent Factors and Dynamics in Motor Cortex and Their Application to Brain-Machine Interfaces.

In the 1960s, Evarts first recorded the activity of single neurons in motor cortex of behaving monkeys (Evarts, 1968). In the 50 years since, great effort has been devoted to understanding how single neuron activity relates to movement. Yet these single neurons exist within a vast network, the nature of which has been largely inaccessible. With advances in recording technologies, algorithms, and computational power, the ability to study these networks is increasing exponentially. Recent experimental results suggest that the dynamical properties of these networks are critical to movement planning and execution. Here we discuss this dynamical systems perspective and how it is reshaping our understanding of the motor cortices. Following an overview of key studies in motor cortex, we discuss techniques to uncover the "latent factors" underlying observed neural population activity. Finally, we discuss efforts to use these factors to improve the performance of brain-machine interfaces, promising to make these findings broadly relevant to neuroengineering as well as systems neuroscience.

Memory Retrieval Has a Dynamic Influence on the Maintenance Mechanisms That Are Sensitive to ζ-Inhibitory Peptide (ZIP).

In neuroscientists' attempts to understand the long-term storage of memory, topics of particular importance and interest are the cellular and system mechanisms of maintenance (e.g., those sensitive to ζ-inhibitory peptide, ZIP) and those induced by memory retrieval (i.e., reconsolidation). Much is known about each of these processes in isolation, but less is known concerning how they interact. It is known that ZIP sensitivity and memory retrieval share at least some molecular targets (e.g., recycling α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid, AMPA, receptors to the plasma membrane); conversely, the fact that sensitivity to ZIP emerges only after consolidation ends suggests that consolidation (and by extension reconsolidation) and maintenance might be mutually exclusive processes, the onset of one canceling the other. Here, we use conditioned taste aversion (CTA) in rats, a cortically dependent learning paradigm, to test this hypothesis. First, we demonstrate that ZIP infusions into gustatory cortex begin interfering with CTA memory 43-45 h after memory acquisition-after consolidation ends. Next, we show that a retrieval trial administered after this time point interrupts the ability of ZIP to induce amnesia and that ZIP's ability to induce amnesia is reengaged only 45 h after retrieval. This pattern of results suggests that memory retrieval and ZIP-sensitive maintenance mechanisms are mutually exclusive and that the progression from one to the other are similar after acquisition and retrieval. They also reveal concrete differences between ZIP-sensitive mechanisms induced by acquisition and retrieval: the latency with which ZIP-sensitive mechanisms are expressed differ for the two processes. SIGNIFICANCE STATEMENT: Memory retrieval and the molecular mechanisms that are sensitive to ζ-inhibitory peptide (ZIP) are the few manipulations that have been shown to effect memory maintenance. Although much is known about their effect on maintenance separately, it is unknown how they interact. Here, we describe a model for the interaction between memory retrieval and ZIP-sensitive mechanisms, showing that retrieval trials briefly (i.e., for 45 h) interrupt these mechanisms. ZIP sensitivity emerges across a similar time window after memory acquisition and retrieval; the maintenance mechanisms that follow acquisition and retrieval differ, however, in the latency with which the impact of ZIP is expressed.

Identifying Interpretable Latent Factors with Sparse Component Analysis.

In many neural populations, the computationally relevant signals are posited to be a set of 'latent factors' - signals shared across many individual neurons. Understanding the relationship between neural activity and behavior requires the identification of factors that reflect distinct computational roles. Methods for identifying such factors typically require supervision, which can be suboptimal if one is unsure how (or whether) factors can be grouped into distinct, meaningful sets. Here, we introduce Sparse Component Analysis (SCA), an unsupervised method that identifies interpretable latent factors. SCA seeks factors that are sparse in time and occupy orthogonal dimensions. With these simple constraints, SCA facilitates surprisingly clear parcellations of neural activity across a range of behaviors. We applied SCA to motor cortex activity from reaching and cycling monkeys, single-trial imaging data from C. elegans, and activity from a multitask artificial network. SCA consistently identified sets of factors that were useful in describing network computations.

Motor cortex activity across movement speeds is predicted by network-level strategies for generating muscle activity.

Learned movements can be skillfully performed at different paces. What neural strategies produce this flexibility? Can they be predicted and understood by network modeling? We trained monkeys to perform a cycling task at different speeds, and trained artificial recurrent networks to generate the empirical muscle-activity patterns. Network solutions reflected the principle that smooth well-behaved dynamics require low trajectory tangling. Network solutions had a consistent form, which yielded quantitative and qualitative predictions. To evaluate predictions, we analyzed motor cortex activity recorded during the same task. Responses supported the hypothesis that the dominant neural signals reflect not muscle activity, but network-level strategies for generating muscle activity. Single-neuron responses were better accounted for by network activity than by muscle activity. Similarly, neural population trajectories shared their organization not with muscle trajectories, but with network solutions. Thus, cortical activity could be understood based on the need to generate muscle activity via dynamics that allow smooth, robust control over movement speed.

Neural Trajectories in the Supplementary Motor Area and Motor Cortex Exhibit Distinct Geometries, Compatible with Different Classes of Computation.

The supplementary motor area (SMA) is believed to contribute to higher order aspects of motor control. We considered a key higher order role: tracking progress throughout an action. We propose that doing so requires population activity to display low "trajectory divergence": situations with different future motor outputs should be distinct, even when present motor output is identical. We examined neural activity in SMA and primary motor cortex (M1) as monkeys cycled various distances through a virtual environment. SMA exhibited multiple response features that were absent in M1. At the single-neuron level, these included ramping firing rates and cycle-specific responses. At the population level, they included a helical population-trajectory geometry with shifts in the occupied subspace as movement unfolded. These diverse features all served to reduce trajectory divergence, which was much lower in SMA versus M1. Analogous population-trajectory geometry, also with low divergence, naturally arose in networks trained to internally guide multi-cycle movement.

Motor Cortex Embeds Muscle-like Commands in an Untangled Population Response.

Primate motor cortex projects to spinal interneurons and motoneurons, suggesting that motor cortex activity may be dominated by muscle-like commands. Observations during reaching lend support to this view, but evidence remains ambiguous and much debated. To provide a different perspective, we employed a novel behavioral paradigm that facilitates comparison between time-evolving neural and muscle activity. We found that single motor cortex neurons displayed many muscle-like properties, but the structure of population activity was not muscle-like. Unlike muscle activity, neural activity was structured to avoid "tangling": moments where similar activity patterns led to dissimilar future patterns. Avoidance of tangling was present across tasks and species. Network models revealed a potential reason for this consistent feature: low tangling confers noise robustness. Finally, we were able to predict motor cortex activity from muscle activity by leveraging the hypothesis that muscle-like commands are embedded in additional structure that yields low tangling.

Mentoring for Success in Tobacco Regulatory Science: A Qualitative Study.

OBJECTIVES: Our study explores the experiences of early career and senior scientists regarding mentorship and career trajectories in tobacco regulatory science (TRS). METHODS: We conducted 22 phone interviews with early career and senior tobacco regulatory scientists from July 2015 to January 2016. All interviews were conducted using a structured interview guide and analyzed using a thematic approach by 2 independent coders. RESULTS: TRS presents specific opportunities and challenges to scientists due to its focused goal of informing tobacco regulation. An understanding of US Food and Drug Administration (FDA) research priorities and how science can inform tobacco regulation are essential for effective mentorship in TRS. Careers in TRS can be pursued in various academic and non-academic professional roles; both offer the distinct ability to conduct science that impacts public policy. Early career and senior scientists identified the importance and challenge of providing broad training across the diverse disciplines of TRS. CONCLUSIONS: Effective mentorship in TRS requires that mentors possess an in-depth understanding of the scientific, regulatory, and legislative processes inherent to tobacco regulatory policy-making. A training program for mentors specific to TRS has the potential to meet diverse professional needs of mentors and mentees aiming to impact tobacco policy.