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

Integrating Programming into Neuroscience Courses.

Programming is a useful skill for students, both in neuroscience research and in the broader economy. Many instructors, however, may wonder how and when they should integrate it into their coursework, especially if they themselves have limited computational training. The suggestions offered here aim to help a wide range of educators - even those who have minimal coding experience - who wish to expose their students to the intersection of neuroscience and programming. Throughout, I provide examples of how I have weaved coding into various elements of neuroscience courses, even those without a computational focus. I also discuss the rich landscape of low-cost, accessible programming tools as well as how generative AI can (and should) impact the way that we are teaching programming. Ultimately, the goal is not to insist that all our students learn how to code, but rather to lower barriers and provide exposure and opportunity to any student who wishes to integrate programming into their research or careers

Learning How to Code While Analyzing an Open Access Electrophysiology Dataset.

Conducting neuroscience research increasingly requires proficiency in coding and the ability to manipulate and analyze large datasets. However, these skills are often not included in typical neurobiology courses, partially because they are seen as accessory rather than central, and partially because of the barriers to entry. Therefore, this lesson plan aims to provide an introduction to coding in Python, a free and user-friendly programming language, for instructors and students alike. In this lesson, students edit Python code in the Jupyter Notebook coding environment to interact with cutting-edge electrophysiology data from the Allen Institute for Brain Science. Students can run their own experiments with these data to compare cell types in mice and humans. Along the way, they gain exposure to Python coding and the role of coding in the field of neuroscience

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

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

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

A case study of actual versus desired inclusion of community-derived core concepts into neuroscience courses in different disciplines at a large university

Neuroscience is an inherently interdisciplinary and rapidly evolving field. While many universities have neuroscience or related majors, they are highly heterogeneous, and it is unclear how their content aligns with a recent proposal of what ideas make up the field of neuroscience. It is therefore important to document and assess the alignment of neuroscience curricula with core concepts in the field. Recently, a large effort by some members of the neuroscience education community described eight core concepts for undergraduate neuroscience curricula. In this paper, we focus primarily on courses in biology, cognitive science, and psychology at a large university, surveying the recent and current course instructors of these courses to ask them (1) to what extent these community-derived core concepts are incorporated into their classes and (2) to what extent these concepts should be incorporated into their classes. In addition, we map core concepts onto course syllabi. We found that core concepts are well-represented across disciplines, and identified differences between departments' inclusion of core concepts. We found that instructors cover fewer core concepts than they desire, and that two core concepts, “Evolution” and “Gene-environment interactions”, were less frequently addressed across disciplines. We consider barriers to instructors' ability to align course content with core concepts, both within and across disciplines. In this effort, we provide an example of how departments can evaluate their alignment of major requirements with the neuroscience core concepts

A case study of actual versus desired inclusion of community-derived core concepts into neuroscience courses in different disciplines at a large university

Neuroscience is an inherently interdisciplinary and rapidly evolving field. While many universities have neuroscience or related majors, they are highly heterogeneous, and it is unclear how their content aligns with a recent proposal of what ideas make up the field of neuroscience. It is therefore important to document and assess the alignment of neuroscience curricula with core concepts in the field. Recently, a large effort by some members of the neuroscience education community described eight core concepts for undergraduate neuroscience curricula. In this paper, we focus primarily on courses in biology, cognitive science, and psychology at a large university, surveying the recent and current course instructors of these courses to ask them (1) to what extent these community-derived core concepts are incorporated into their classes and (2) to what extent these concepts should be incorporated into their classes. In addition, we map core concepts onto course syllabi. We found that core concepts are well-represented across disciplines, and identified differences between departments' inclusion of core concepts. We found that instructors cover fewer core concepts than they desire, and that two core concepts, “Evolution” and “Gene-environment interactions”, were less frequently addressed across disciplines. We consider barriers to instructors' ability to align course content with core concepts, both within and across disciplines. In this effort, we provide an example of how departments can evaluate their alignment of major requirements with the neuroscience core concepts

Centering Diversity, Equity, and Inclusion in Graduate Admissions.

Many undergraduate neuroscience trainees aspire to earn a PhD. In recent years the number, demographics, and previous experiences of PhD applicants in neuroscience has changed. This has necessitated both a reconsideration of admissions processes to ensure equity for an increasingly diverse applicant pool as well as renewed efforts to expand access to the training and research experiences required for admission to graduate programs. Here, we describe both facets of graduate school admissions by demystifying the process and providing faculty with tools and resources to help undergraduate students successfully navigate it. We discuss admissions requirements and processes at two graduate institutions, highlighting holistic approaches to evaluating students, the ever-increasing research experience expectations, and the decreasing reliance on the GRE. With a particular focus on improving equity, diversity, inclusion and belonging, we discuss resources for applying to graduate school that are available for students from underrepresented populations, including summer institutes and fellowship programs and intentional relationships with minority serving institutions (MSIs) to foster bi-directional engagement between undergraduate programs at MSIs and graduate institutions. With diverse perspectives as faculty involved in undergraduate education, graduate programs, and post-baccalaureate training programs, we provide recommendations and resources for how to help all trainees - especially those from populations underrepresented in the STEM workforce - succeed in the current graduate education admissions landscape

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

Neuromatch Academy: Teaching Computational Neuroscience with Global Accessibility

Neuromatch Academy (NMA) designed and ran a fully online 3-week Computational Neuroscience Summer School for 1757 students with 191 teaching assistants (TAs) working in virtual inverted (or flipped) classrooms and on small group projects. Fourteen languages, active community management, and low cost allowed for an unprecedented level of inclusivity and universal accessibility