Mentorship for Transfer Student Success in STEM Research: Mentor Approaches and Reflections.

Mentorship has been widely recognized as an effective means to promote student learning and engagement in undergraduate research experiences. However, little work exists for understanding different mentors' perceived approaches to mentorship, including mentorship of students from backgrounds and educational trajectories not well represented in science, technology, engineering, and mathematics (STEM). Transfer students, in particular, face unique trajectories in their pursuit of research opportunities, yet few studies investigate how mentors describe their approaches to supporting these students. Using semistructured interviews, this study examines how mentors approach mentoring students from diverse backgrounds as research trainees, with an emphasis on transfer students. First, using phenomenography as an analytical approach, we identified four categories describing variations in how mentors reflected upon or accounted for the transfer student identity in their approaches. We find that research mentors vary in their understanding and exposure to the transfer student identity and may have preconceived notions of the transfer student experience. Second, we present vignettes to illustrate how mentors' approaches to the transfer student identity may relate or diverge from their general approaches to mentoring students from different backgrounds and identities. The emerging findings have implications for developing effective mentorship strategies and training mentors to support transfer students.

The next generation of neuroscientists needs to learn how to code, and we need new ways to teach them.

Neuroscience education is at an impasse-we need to teach students coding, but many institutions do not have the resources to do so. Here, I outline three major barriers, as well as solutions, to bringing programming education into our undergraduate and graduate programs.

The Mismatch Between Neuroscience Graduate Training and Professional Skill Sets.

Neuroscience career paths are rapidly changing as the field expands and increasingly overlaps with computational and data-heavy job sectors. With the steady growth in neuroscience trainees and the diversification of jobs for those trainees, it is important to identify the necessary skills in neuroscience career paths and how well graduate training is preparing our students for this ever-changing workforce. Here, we survey hundreds of neuroscience professionals and graduate students to assess their use and valuation of a range of skills, from bench skills to communication and management. We find that almost all neuroscience professionals report strongly needing management and communication skills, but that these were seen as are less important by graduate students. In addition, coding and data analysis skills are widely used in academic and industry research, predict higher salaries, and are more commonly used by male-identifying graduate students. These findings can help trainees assess their own skill sets as well as encourage educational leaders to offer training in skills beyond the bench, helping to catapult trainees into the next stages of their careers.

Extraction of Distinct Neuronal Cell Types from within a Genetically Continuous Population.

Single-cell transcriptomics of neocortical neurons have revealed more than 100 clusters corresponding to putative cell types. For inhibitory and subcortical projection neurons (SCPNs), there is a strong concordance between clusters and anatomical descriptions of cell types. In contrast, cortico-cortical projection neurons (CCPNs) separate into surprisingly few transcriptomic clusters, despite their diverse anatomical projection types. We used projection-dependent single-cell transcriptomic analyses and monosynaptic rabies tracing to compare mouse primary visual cortex CCPNs projecting to different higher visual areas. We find that layer 2/3 CCPNs with different anatomical projections differ systematically in their gene expressions, despite forming only a single genetic cluster. Furthermore, these neurons receive feedback selectively from the same areas to which they project. These findings demonstrate that gene-expression analysis in isolation is insufficient to identify neuron types and have important implications for understanding the functional role of cortical feedback circuits.

Implanting and Recycling Neuropixels Probes for Recordings in Freely Moving Mice.

Recording neural activity in unrestricted animals is necessary to unravel the neural basis of ethological behaviors. Recently, Neuropixels probes have made important strides in improving yield and lowering noise, but have limited use cases in freely moving animals. Although there are a number of studies demonstrating the use of these probes in headfixed mice, there are not established protocols for the use and reuse of them in a freely moving mouse. We therefore designed a novel device (the AMIE) that maximizes the potential value of these powerful probes. Here, we provide the technical drawings for the AMIE and detail its preparation, implantation, and explantation. With our approach, researchers can record hundreds of neurons during freely moving behavior across weeks of experiments, and then recycle valuable probes for future use.

A systematic topographical relationship between mouse lateral posterior thalamic neurons and their visual cortical projection targets.

Higher-order visual thalamus communicates broadly and bi-directionally with primary and extrastriate cortical areas in various mammals. In primates, the pulvinar is a topographically and functionally organized thalamic nucleus that is largely dedicated to visual processing. Still, a more granular connectivity map is needed to understand the role of thalamocortical loops in visually guided behavior. Similarly, the secondary visual thalamic nucleus in mice (the lateral posterior nucleus, LP) has extensive connections with cortex. To resolve the precise connectivity of these circuits, we first mapped mouse visual cortical areas using intrinsic signal optical imaging and then injected fluorescently tagged retrograde tracers (cholera toxin subunit B) into retinotopically-matched locations in various combinations of seven different visual areas. We find that LP neurons representing matched regions in visual space but projecting to different extrastriate areas are found in different topographically organized zones, with few double-labeled cells (~4-6%). In addition, V1 and extrastriate visual areas received input from the ventrolateral part of the laterodorsal nucleus of the thalamus (LDVL). These observations indicate that the thalamus provides topographically organized circuits to each mouse visual area and raise new questions about the contributions from LP and LDVL to cortical activity.

Single-trial neural dynamics are dominated by richly varied movements.

When experts are immersed in a task, do their brains prioritize task-related activity? Most efforts to understand neural activity during well-learned tasks focus on cognitive computations and task-related movements. We wondered whether task-performing animals explore a broader movement landscape and how this impacts neural activity. We characterized movements using video and other sensors and measured neural activity using widefield and two-photon imaging. Cortex-wide activity was dominated by movements, especially uninstructed movements not required for the task. Some uninstructed movements were aligned to trial events. Accounting for them revealed that neurons with similar trial-averaged activity often reflected utterly different combinations of cognitive and movement variables. Other movements occurred idiosyncratically, accounting for trial-by-trial fluctuations that are often considered 'noise'. This held true throughout task-learning and for extracellular Neuropixels recordings that included subcortical areas. Our observations argue that animals execute expert decisions while performing richly varied, uninstructed movements that profoundly shape neural activity.

Chronically implanted Neuropixels probes enable high-yield recordings in freely moving mice.

The advent of high-yield electrophysiology using Neuropixels probes is now enabling researchers to simultaneously record hundreds of neurons with remarkably high signal to noise. However, these probes have not been well-suited to use in freely moving mice. It is critical to study neural activity in unrestricted animals for many reasons, such as leveraging ethological approaches to study neural circuits. We designed and implemented a novel device that allows Neuropixels probes to be customized for chronically implanted experiments in freely moving mice. We demonstrate the ease and utility of this approach in recording hundreds of neurons during an ethological behavior across weeks of experiments. We provide the technical drawings and procedures for other researchers to do the same. Importantly, our approach enables researchers to explant and reuse these valuable probes, a transformative step which has not been established for recordings with any type of chronically-implanted probe.

Decision-making behaviors: weighing ethology, complexity, and sensorimotor compatibility.

Rodent decision-making research aims to uncover the neural circuitry underlying the ability to evaluate alternatives and select appropriate actions. Designing behavioral paradigms that provide a solid foundation to ask questions about decision-making computations and mechanisms is a difficult and often underestimated challenge. Here, we propose three dimensions on which we can consider rodent decision-making tasks: ethological validity, task complexity, and stimulus-response compatibility. We review recent research through this lens, and provide practical guidance for researchers in the decision-making field.

Automated identification of mouse visual areas with intrinsic signal imaging.

Intrinsic signal optical imaging (ISI) is a rapid and noninvasive method for observing brain activity in vivo over a large area of the cortex. Here we describe our protocol for mapping retinotopy to identify mouse visual cortical areas using ISI. First, surgery is performed to attach a head frame to the mouse skull (∼1 h). The next day, intrinsic activity across the visual cortex is recorded during the presentation of a full-field drifting bar in the horizontal and vertical directions (∼2 h). Horizontal and vertical retinotopic maps are generated by analyzing the response of each pixel during the period of the stimulus. Last, an algorithm uses these retinotopic maps to compute the visual field sign and coverage, and automatically construct visual borders without human input. Compared with conventional retinotopic mapping with episodic presentation of adjacent stimuli, a continuous, periodic stimulus is more resistant to biological artifacts. Furthermore, unlike manual hand-drawn approaches, we present a method for automatically segmenting visual areas, even in the small mouse cortex. This relatively simple procedure and accompanying open-source code can be implemented with minimal surgical and computational experience, and is useful to any laboratory wishing to target visual cortical areas in this increasingly valuable model system.

Three Types of Cortical Layer 5 Neurons That Differ in Brain-wide Connectivity and Function.

Cortical layer 5 (L5) pyramidal neurons integrate inputs from many sources and distribute outputs to cortical and subcortical structures. Previous studies demonstrate two L5 pyramid types: cortico-cortical (CC) and cortico-subcortical (CS). We characterize connectivity and function of these cell types in mouse primary visual cortex and reveal a new subtype. Unlike previously described L5 CC and CS neurons, this new subtype does not project to striatum [cortico-cortical, non-striatal (CC-NS)] and has distinct morphology, physiology, and visual responses. Monosynaptic rabies tracing reveals that CC neurons preferentially receive input from higher visual areas, while CS neurons receive more input from structures implicated in top-down modulation of brain states. CS neurons are also more direction-selective and prefer faster stimuli than CC neurons. These differences suggest distinct roles as specialized output channels, with CS neurons integrating information and generating responses more relevant to movement control and CC neurons being more important in visual perception.

Pattern and Component Motion Responses in Mouse Visual Cortical Areas.

Spanning about 9 mm(2) of the posterior cortex surface, the mouse's small but organized visual cortex has recently gained attention for its surprising sophistication and experimental tractability. Though it lacks the highly ordered orientation columns of primates, mouse visual cortex is organized retinotopically and contains at least ten extrastriate areas that likely integrate more complex visual features via dorsal and ventral streams of processing. Extending our understanding of visual perception to the mouse model is justified by the evolving ability to interrogate specific neural circuits using genetic and molecular techniques. In order to probe the functional properties of the putative mouse dorsal stream, we used moving plaids, which demonstrate differences between cells that identify local motion (component cells) and those that integrate global motion of the plaid (pattern cells; Figure 1A;). In primates, there are sparse pattern cell responses in primate V1, but many more in higher-order regions; 25%-30% of cells in MT and 40%-60% in MST are pattern direction selective. We present evidence that mice have small numbers of pattern cells in areas LM and RL, while V1, AL, and AM are largely component-like. Although the proportion of pattern cells is smaller in mouse visual cortex than in primate MT, this study provides evidence that the organization of the mouse visual system shares important similarities to that of primates and opens the possibility of using mice to probe motion computation mechanisms.

Do you feel alright? Attenuated neural processing of aversive interoceptive stimuli in current stimulant users.

Inability to appropriately process afferent interoceptive stimuli may contribute to initiation and/or escalation of substance use. An aversive interoceptive stimulus probed neural processing in problem stimulant users (PSU; n = 19), 18 desisted stimulant users (DSU; n = 18), and healthy comparison subjects (CTL; n = 21). Participants completed a continuous performance task while they anticipated and experienced 40 cm H2 O/L/sec inspiratory breathing loads during fMRI. PSU exhibited lower left dorsolateral prefrontal cortex and inferior frontal gyrus (IFG) activation than DSU and CTL across trials. Greater lifetime drug use due to stimulants was also linked to lower activation in these regions. In addition, PSU displayed lower right IFG and insula activation during breathing load than DSU and CTL. Findings suggest that transition to stimulant use disorders is marked by weakened attentional salience of aversive stimuli.