The New Blueprints: Undergraduate Neuroscience Education in the Twenty-First Century.

The Faculty for Undergraduate Neuroscience (FUN) has mounted many summer workshops since its first in 1995 held at Davidson College. An important outcome of the 1995 workshop was the development of four "blueprints" to help guide institutions in developing and maintaining undergraduate programs in neuroscience. Since then, at approximately ten-year intervals, participants at the FUN workshops have revisited and amended the Blueprints to better reflect best practices in undergraduate neuroscience education, including adding a fifth blueprint in 2005. In 2017, participants at the FUN workshop held at Dominican University again conducted a review of the blueprints and amended each of the five. A significant change resulting from the 2017 discussions was revision of the neuroscience minor blueprint to reflect the evolution of this program type across institutions.

Using a Pop-Science Book to Teach Introductory Neuroscience: Advantages for Science Majors and Non-Science Majors Alike.

The traditional approach to teaching neuroscience often involves presenting a topic like one might present a "murder mystery"; evidence is presented serially until the final answer is revealed. Although this approach mirrors the scientific discovery process, it is not always effective at engaging students, particularly those who are less familiar with the scientific concepts being presented as evidence. By the time the answer arrives, students may be too overwhelmed to absorb it. One way to combat this is to reverse the order of presentation. By starting with the final condition and working backwards through the underlying neuroscientific concepts, students have a relatable framework in which to couch the scientific detail necessary to understand neural phenomena. It was with this approach in mind that the course, "Fundamental Neuroscience: Understanding Ourselves" was designed. Taught for the past seven years at the University of Minnesota, the course uses the best-selling book The Brain That Changes Itself by Norman Doidge in lieu of a traditional textbook. Each chapter focuses on a case study of a particular neuropsychological problem or, in some cases, the work of a particular neuroscientist. This material is then used as a launching point to delve deeper into the neurobiological mechanisms underlying the particular disorder. In our experience, the result is that students from a wide variety of academic backgrounds are able to engage with the material throughout the entire lesson and apply their new knowledge broadly across the discipline of Neuroscience. This article aims to provide an in-depth presentation of the course, including potential challenges of working with a pop-science text. Further, we extend our discussion to a newly-developed companion course using non-traditional texts and how these courses fit into a Neuroscience minor.

Infraslow dynamic patterns in human cortical networks track a spectrum of external to internal attention.

Early efforts to understand the human cerebral cortex focused on localization of function, assigning functional roles to specific brain regions. More recent evidence depicts the cortex as a dynamic system, organized into flexible networks with patterns of spatiotemporal activity corresponding to attentional demands. In functional MRI (fMRI), dynamic analysis of such spatiotemporal patterns is highly promising for providing non-invasive biomarkers of neurodegenerative diseases and neural disorders. However, there is no established neurotypical spectrum to interpret the burgeoning literature of dynamic functional connectivity from fMRI across attentional states. In the present study, we apply dynamic analysis of network-scale spatiotemporal patterns in a range of fMRI datasets across numerous tasks including a left-right moving dot task, visual working memory tasks, congruence tasks, multiple resting state datasets, mindfulness meditators, and subjects watching TV. We find that cortical networks show shifts in dynamic functional connectivity across a spectrum that tracks the level of external to internal attention demanded by these tasks. Dynamics of networks often grouped into a single task positive network show divergent responses along this axis of attention, consistent with evidence that definitions of a single task positive network are misleading. Additionally, somatosensory and visual networks exhibit strong phase shifting along this spectrum of attention. Results were robust on a group and individual level, further establishing network dynamics as a potential individual biomarker. To our knowledge, this represents the first study of its kind to generate a spectrum of dynamic network relationships across such an axis of attention.

Reconfiguration of brain-wide neural activity after early life adversity.

Early life adversity (ELA) predisposes individuals to both physical and mental disorders lifelong. How ELA affects brain function leading to this vulnerability is under intense investigation. Research has begun to shed light on ELA effects on localized brain regions within defined circuits. However, investigations into brain-wide neural activity that includes multiple localized regions, determines relationships of activity between regions and identifies shifts of activity in response to experiential conditions is necessary. Here, we performed longitudinal manganese-enhanced magnetic resonance imaging (MEMRI) to image the brain in normally reared or ELA-exposed adults. Images were captured in the freely moving home cage condition, and short- and long-term after naturalistic threat. Images were analyzed with new computational methods, including automated segmentation and fractional activation or difference volumes. We found that neural activity was increased after ELA compared to normal rearing in multiple brain regions, some of which are involved in defensive and/or reward circuitry. Widely distributed patterns of neural activity, "brain states", and their dynamics after threat were altered with ELA. Upon acute threat, ELA-mice retained heightened neural activity within many of these regions, and new hyperactive responses emerged in monoaminergic centers of the mid- and hindbrain. Nine days after acute threat, heightened neural activity remained within locus coeruleus and increased within posterior amygdala, ventral hippocampus, and dorso- and ventromedial hypothalamus, while reduced activity emerged within medial prefrontal cortical regions (prelimbic, infralimbic, anterior cingulate). These results reveal that functional imbalances arise between multiple brain-systems which are dependent upon context and cumulative experiences after ELA.

Quantitative skills in undergraduate neuroscience education in the age of big data.

For over a half-Century, the mathematics requirement for graduation at most undergraduate colleges and universities has been one year of calculus and a semester of statistics. Many universities and colleges offer a neuroscience major that may or may not add additional mathematics, statistics, or data science requirements. Today in the age of Big Data and Systems Neuroscience, many students are ill-equipped for the future without the tools of computational competency that are necessary to tackle the large data sets generated by contemporary neuroscience research. Required courses in statistics still focus on parametric statistics based on the normal distribution and do not provide the computational tools required to analyze big data sets. Undergraduates in STEM fields including neuroscience need to enroll in the Data Science courses that are required in the social sciences (e.g., economics, political science and psychology). Contemporary systems neuroscience is routinely done by interdisciplinary research teams of statisticians, engineers, and physical scientists. Emerging "NeuroX-omics" such as connectomics have emerged along with genomics, proteomics, and transcriptomics, all of which deploy systems analysis techniques based on mathematical graph theory. Connectomics is the 21st Century's functional neuroanatomy. Whole brain connectome research appears almost monthly in the Drosphila, zebra fish, and mouse literature, and human brain connectomics is not far behind. The techniques for connectomics rely on the tools of data science. Undergraduate neuroscience students are already squeezed for credit hours given the high-prescribed science curriculum for biology majors and premedical students, in addition to required courses in social sciences and humanities. However, additional training in mathematics, statistics, computer science, and/or data science is urgently needed for undergraduate neuroscience majors just to understand the contemporary research literature. Undoubtedly, the faculty who teach neuroscience courses are acutely aware of the problem and most of them freely acknowledge the importance of quantitative analytical skills for their students. However, some faculty members may feel that their own math and statistics knowledge or other analytical skills have atrophied beyond recall or were never fulfilled in the first place. In this commentary I suggest that this problem can be ameliorated, though not solved, through organizing workshops, journal clubs, or independent studies courses in which the students and the instructors learn and teach each other in short-course format. In addition, web-available teaching materials such as targeted video clips are plentifully available on the internet. To attract and maintain student interest, qauntitative instruction and learning should occur in neuroscience context.

Undergraduate neuroscience education: Meeting the challenges of the 21st century.

The dedication of undergraduate neuroscience faculty to their students could not have been more evident than what these educators demonstrated when the COVID-19 pandemic impacted colleges and universities across the United States. These faculty faced the crisis head-on to provide their students with exceptional instruction in virtual formats that many faculty had never used for instruction before the pandemic. This same tenacious attitude has been reflected in pedagogical efforts that undergraduate neuroscience faculty have undertaken since the mid-1990s. The challenges of providing cutting-edge neuroscience education to undergraduates in a dynamic field have produced a series of curricular designs and approaches that capitalize on discipline-based education research. This article reviews curricular models and pedagogical strategies aimed at enhancing the educational experiences of undergraduate neuroscience students whose lived experiences and academic backgrounds reflect the richly kaleidoscopic demographics of college students in the 21st century. The future of undergraduate neuroscience education is bright as faculty and their students collaborate on their journey of discovery in neuroscience.

Cultivation of an interdisciplinary, research-based neuroscience minor at hope college.

Hope College is an undergraduate liberal arts college with an enrollment of approximately 3,000 students. In the spring of 2005, we began to offer an interdisciplinary neuroscience minor program that is open to all students. The objective of this program is to introduce students to the field of neuroscience, and to do so in such a way as to broaden students' disciplinary perspectives, enhance communication and quantitative skills, and increase higher-level reasoning skills by encouraging collaboration among students who have different disciplinary backgrounds. This is a research-based program that culminates in a one-year capstone research course. Here we present the story of the program development at Hope College, including a description of our newly developed curriculum, our initial assessment data, and the lessons we have learned in developing this program.