Danielle Bassett, J. Peter Skirkanich Professor in the departments of Bioengineering and Electrical and Systems Engineering, investigates how the shape of networks impact the phenomena that arises from them. Much of that research is focused on networks of neurons, and how the different ways they are wired together in different people can influence their mental traits, such as memory or executive function.
Bassett is also interested in networks of people, however, as the shapes of those networks can have a major impact on a society’s traits. Last year, she and her colleagues published a study that investigated the network of citations neuroscience researchers produced in the course of their work, demonstrating a systemic gender bias that left women underrepresented in the literature.
When a group of researchers at NYU Abu Dhabi published a paper in Nature Communications last fall suggesting that young women scientists should seek out men as mentors, the backlash was swift and vociferous. Countless scientists, many of them women, registered their indignation on Twitter—some even penning open letters and their ownpreprints in response. The original paper had found that female junior scientists who authored papers with male senior scientists saw their papers cited at higher rates. But a number of critics contested the assertion that this result established a link between male mentors and career performance. Scientists routinely coauthor articles with people who are not their mentors, they argued, and citation rates are just one metric of achievement. In response to these criticisms, the authors eventually retracted their paper. (They declined to comment to WIRED.)
But the paper had already stirred up a broader discussion about gender and mentorship in academia. For Danielle Bassett, a professor of bioengineering at the University of Pennsylvania, the methodological concerns that prompted the paper’s retraction were far from its worst sin. She herself has researched citation practices and found that, in neuroscience, papers with male senior authors are cited at a disproportionately high rate—primarily because other male scientists preferentially cite them. To suggest that young women should therefore try to author papers with men is, she believes, a grave error. “That was a problem in assigning blame,” she says. “The onus is on us to create a scientific culture that lets students choose a mentor that’s right for them.”
Connecting the human brain to electrical devices is a long-standing goal of neuroscientists, bioengineers, and clinicians, with applications ranging from deep brain stimulation (DBS) to treat Parkinson’s disease to more futuristic endeavors such as Elon Musk’s NeuraLink initiative to record and translate brain activity. However, these approaches currently rely on using implantable metallic electrodes that inherently provoke a lasting immune response due to their non-biological nature, generally complicating the reliability and stability of these interfaces over time. To address these challenges, D. Kacy Cullen, Associate Professor in Neurosurgery and Bioengineering, and Dayo Adewole, a doctoral candidate in Bioengineering, worked with a multi-disciplinary team of collaborators to develop the first “living electrodes” as an implantable, biological bridge between the brain and external devices. In a recent article published in Science Advances, the team demonstrated the fabrication of hair-like microtissue comprised of living neuronal networks and bundled tracts of axons — the signal sending fibers of the nervous system — protected within soft hydrogel cylinders. They showed that these axon-based living electrodes could be fully controlled and monitored with light — thus eliminating the need for electrical contact — and are capable of surviving and forming synapses with the brain as demonstrated in an adult rat model. While further advancements are necessary prior to clinical use, the current findings provide the foundation for a new class of “living electrodes” as a biological intermediary between humans and devices capable of leveraging natural mechanisms to potentially provide a stable interface for clinical applications.
While artificial intelligence is becoming a bigger part of nearly every industry and increasingly present in everyday life, even the most impressive AI is no match for a toddler, chimpanzee, or even a honeybee when it comes to learning, creativity, abstract thinking or connecting cause and effect in ways they haven’t been explicitly programmed to recognize.
This discrepancy gets at one of the field’s fundamental questions: what does it mean to say an artificial system is “intelligent” in the first place?
Seventy years ago, Alan Turing famously proposed such a benchmark; a machine could be considered to have artificial intelligence if it could successfully fool a person into thinking it was a human as well. Now, many artificial systems could pass a “Turing Test” in certain limited domains, but none come close to imitating the holistic sense of intelligence we recognize in animals and people.
Understanding how AI might someday be more like this kind of biological intelligence — and developing new versions of the Turing Test with those principles in mind — is the goal of a new collaboration between researchers at the University of Pennsylvania, Carnegie Mellon University and Johns Hopkins University.
The project, called “From Biological Intelligence to Human Intelligence to Artificial General Intelligence,” is led by Konrad Kording, a Penn Integrates Knowledge Professor with appointments in the Departments of Bioengineering and Computer and Information Science in Penn Engineering and the Department of Neuroscience at Penn’s Perelman School of Medicine. Kording will collaborate with Timothy Verstynen of Carnegie Mellon University, as well Joshua T. Vogelstein and Leyla Isik, both of Johns Hopkins University, on the project.
The Perelman School of Medicine has announced the winners of the 2020 Penn Medicine Awards of Excellence. The Office of the Dean says:
“These awardees exemplify our profession’s highest values of scholarship, teaching, innovation, commitment to service, leadership, professionalism and dedication to patient care. They epitomize the preeminence and impact we all strive to achieve. The awardees range from those at the beginning of their highly promising careers to those whose distinguished work has spanned decades.
Each recipient was chosen by a committee of distinguished faculty from the Perelman School of Medicine or the University of Pennsylvania. The contributions of these clinicians and scientists exemplify the outstanding quality of patient care, mentoring, research, and teaching of our world-class faculty.”
Two faculty members affiliated with Penn Bioengineering are among this year’s recipients.
Yale Cohen, PhD, Professor of Otorhinolaryngology with secondary appointments in Neuroscience and Bioengineering, is the recipient of the Jane M. Glick Graduate Student Teaching Award. Cohen is an alumnus of the Penn Bioengineering doctoral program and is currently the department’s Graduate Chair.
“Dr. Cohen’s commitment to educating and training the next generation of scientists exemplifies the type of scientist and educator that Jane Glick represented. His students value his highly engaging and supportive approach to teaching, praising his enthusiasm, energy, honesty, and compassion.”
“Dr. Smith is the foremost authority on diffuse axonal injury (DAI) as the unifying hypothesis behind the short- and long-term consequences of concussion. After realizing early in his career that concussion, or mild traumatic brain injury (TBI), was a much more serious event than broadly appreciated, Dr. Smith and his team have used computer biomechanical modeling, in vitro and in vivo testing in parallel with seminal human studies to elucidate mechanisms of concussion.”
When the COVID-19 pandemic began taking hold in the United States, one of the first “superspreader” events was an academic conference. Such conferences have long been a primary way for researchers to share new findings and launch collaborations, but with thousands of people from around the world, indoors and in close proximity, it quickly became clear that the traditional format for these events would need to radically change.
Konrad Kording, a Penn Integrates Knowledge Professor with appointments in the departments of Bioengineering and Computer and Information Science in Penn Engineering and the Department of Neuroscience at Penn’s Perelman School of Medicine, was ahead of the curve on this shift. With the issues of prohibitive costs and environmental impact of travel in mind, Kording had already started brainstorming ways of reinventing the traditional conference format when the pandemic made it a necessity.
The resulting event, Neuromatch, involved algorithmically analyzing participants’ work in order to connect researchers who might not otherwise meet. Building on the success of that “unconference,” Kording and his colleagues launched the Neuromatch Academy, a free-ranging online summer school organized around the same principles.
Kording already had experience quickly pulling together online events. Early in the pandemic, together with Dan Goodman, Titipat Achakulvisut and Brad Wyble, he developed an online ‘unconference,’ which featured both lectures and a virtual networking component designed to mimic the in-person interactions that make conferences so valuable. (For more, see “Designing a Virtual Neuroscience Conference.”) Soon after, they decided to spin that success into a full-fledged summer school offering live lectures with top computational neuroscientists, guided coding exercises to teach mathematical approaches to neural modeling and analysis, and community support from mentors and teaching assistants (TAs).
The result was a summer school with well-designed content, a diverse student body, including participants from U.S.-sanctioned Iran, and a determined group of organizers who managed to pull off the most inclusive computational neuroscience school yet. NMA now has its eye on a future with even broader representation across countries, languages and skill levels. This year has been incredibly difficult for many, but NMA has provided an important precedent for how to collaborate across, and even dismantle, all sorts of barriers.
Parkes will use the BBRF’s support to continue his research examining the link between the symptoms of mental illness and the brain. In particular, he seeks to uncover how individual patterns of abnormal neurodevelopment link to, and predict, the emergence of psychosis symptoms through childhood and adolescence using longitudinal data. In turn, Parkes’ work will discover prognostic biomarkers for the psychosis spectrum that will help inform clinical outcome tracking.
“I am honored to have been selected for a Young Investigator Grant from the BBRF this year,” Parkes says. “This award will support me to conduct research that I believe will make real inroads into understanding the pathways that link abnormalities in neurodevelopment to the symptoms of psychosis. I feel grateful for the opportunity to complete my postdoctoral training at Penn. Penn has connected me with wonderful people who I’m sure will be lifelong mentors, colleagues, and peers.”
The BBRF Young Investigator Grants are valued at more than $10.3 million and are awarded annually to 150 of the world’s most promising young scientists to support the work of early career investigators with innovative ideas for groundbreaking neurobiological research seeking to identify causes, improve treatments, and develop prevention strategies for psychiatric disorders.
Read more about the BBRF 2020 Young Investigators here.
In a ‘Wired’ feature, Bassett helps explain the growing field of network neuroscience and how the form and function of the brain are connected.
Early attempts to understand how the brain works included the pseudoscience of phrenology, which theorized that various mental functions could be determined through the shape of the skull. While those theories have long been debunked, modern neuroscience has shown a kernel of truth to them: those functions are highly localized to different regions of the brain.
Now, Danielle Bassett, Professor of J. Peter Skirkanich Professor of Bioengineering and Electrical and Systems Engineering, is pioneering a new subfield that goes even deeper into the connection between the brain’s form and function: network neuroscience.
In a recent feature article in Wired, Bassett explains the concepts behind this new subfield. While prior understanding has long relied on the idea that certain areas of the brain control certain functions, Bassett and other network neuroscientists are using advances in imaging and machine learning to reveal the role the connections between those areas play.
For Bassett, one of the first indicators that these connections mattered more than previously realized was the shape of the neurons themselves.
Speaking with Wired’s Grace Huckins, Bassett says:
“Neurons are not spherical — neurons have a cell body, and then they have this long tail that allows them to connect to many other cells. You can even look at the morphology of the neuron and say, ‘Oh, well, connectivity has to matter. Otherwise, it wouldn’t look like this.’”
Read more about Bassett and the field of network neuroscience in Wired.
Danielle Bassett, J. Peter Skirkanich Professor in the departments of Bioengineering and Electrical and Systems Engineering, has been called the “doyenne of network neuroscience.” The burgeoning field applies insights from the field of network science, which studies how the structure of networks relate to their performance, to the billions of neuronal connections that make up the brain.
Much of Basset’s research draws on mathematical and engineering principles to better understand how mental traits arise, but also applies them more broadly to other challenges in neuroscience.
The researchers used machine learning techniques to create a new classification system for neurodegenerative diseases, one which may redraw the boundaries between them and help explain clinical differences in patients who received the same diagnoses.
BioWorld’s Anette Breindl spoke with Bassett about the team’s findings.
Now, investigators have developed a new approach to classifying neurodegenerative disorders that used the overall patterns of protein aggregation, rather than specific proteins, to define six clusters of patients that crossed traditional diagnostic categories.
“We find that perhaps the way that clinicians have been diagnosing these disorders… is not necessarily the way these disorders work,” Danielle Bassett told BioWorld. “The way we’ve been trying to carve nature at joints is not the way that nature has joints. The joints are elsewhere.”
Continue reading Breindl’s article, “For neurodegeneration, a different way to slice the pie,” at BioWorld.
Among the key faculty involved in this new center is J. Peter Skirkanich Professor of Bioengineering Danielle Bassett. Bassett’s Complex Systems Lab studies biological, physical, and social systems by using and developing tools from network science and complex systems theory. Bassett, along with Assistant Professor of Psychiatry Desmond Oathes, will work to:
understand how TMS [i.e. transcranial magnetic stimulation] might improve working memory in healthy adults and those with ADHD by combining network control theory (a set of concepts and principles employed in engineering), magnetic stimulation of the brain, and functional brain imaging.
An interdisciplinary research team has found statistical evidence of women being under-cited in academic literature. They are now studying similar effects along racial lines.
By Izzy Lopez
Scientific papers are the backbone of a research community and the citation of those papers sparks conversation in a given field. This cycle of publication and citation leads to new knowledge, but what happens when implicit discrimination in a field leads to papers by minority scholars being cited less often than their counterparts? A new team of researchers has come together to ask this question and dig into the numbers of gender and racial bias in neuroscience.
The team members include physicist and neuroscientist Danielle Bassett, J. Peter Skirkanich Professor of Bioengineering at the University of Pennsylvania, with secondary appointments in the Departments of Neurology and Psychiatry in Penn’s Perelman School of Medicine, statistician Jordan Dworkin, then a graduate student in Penn Medicine’s Department of Biostatistics, Epidemiology and Bioinformatics, and ethicist Perry Zurn, an Assistant Professor of Philosophy at American University.
Their study on gender bias, which recently appeared in Nature Neuroscience, reports on the extent and drivers of gender imbalance in neuroscience reference lists. The team has also published a perspective paper in Neuron that makes practical recommendations for improving awareness of this issue and correcting for biases.
They are now working on a second study, led by Maxwell Bertolero, a postdoctoral researcher in Bassett’s lab, that considers the extent and drivers of racial imbalances in neuroscience reference lists.
Together, Bassett, Dworkin and Zurn are using their combined research strengths to uncover the under-citation of women or otherwise minority-led papers in neuroscience and to assess its significance. This research is fundamental in highlighting a true gap in representation in research paper citations, which can have detrimental effects for women and other minorities leading science. In addition, they provide actionable steps to address the problem and build a more equitable future.
Your research team is a distinctive one. How did you come together for a study about gender discrimination in neuroscience citations?
Jordan Dworkin: It was a fortunate coincidence. In the run-up to a big neuroscience conference, I started seeing discussions on Twitter about gender-based discrimination in neuroscience. There were stories being shared of women’s papers being overlooked and reviewers seeing reference lists that were almost entirely made up of men. It was illuminating, especially because some people in the discussion were hesitant to take those experiences at face value. This skepticism, and occasional combativeness, seemed to stem from the view that citations are an untouchable, scientific bastion where researchers’ decisions are fully objective. The tension between that view and scholars’ lived experiences encouraged me to explore the existing literature on this issue.
As it turns out, there is really strong literature on issues of diversity and citation in science. Some disciplines have done field-specific investigations, such as the foundational studies in political science, international relations, and economics, but there wasn’t yet any research in neuroscience. Since biomedical sciences often have different approaches to citation, it seemed that it would be worth doing a deeper neuroscience-specific investigation to give quantitative backing to the issue of gender bias in neuroscience research.
Danielle Bassett: When Jordan and I started working together on this project, I knew it was important. To do it right, we needed to present the information in a way that made it actionable, with clear recommendations about how each of us as scientists can help address the issue. We also needed to add someone to the team with expertise in gender theory and research ethics. We especially wanted to make sure we were discussing gender bias in a way that was informed by recent advances in gender studies. That’s when we brought Perry in.
Perry Zurn: I’m a philosopher by training, with a focus on ethics and politics. Citations are both an ethical and a political issue. Citations reflect whose questions and whose contributions are recognized as important in the scholarly conversation. As such, citations can either bring in marginalized voices, voices that have been historically excluded from a conversation, or they can simply replicate that exclusion. My own field of philosophy has just as much of a problem with gender and racial diversity as STEM fields, something Dani and I have been talking about for a long time. This work seemed like a natural point of collaboration.
Describe this study and what it means for promoting gender diversity in neuroscience.
Bassett: For years now, various scholars and activists in science have drawn attention to issues of gender and racial inequities in the field. Most of these conversations, however, have placed responsibility for change in the hands of people in power, such as journal editors, grant reviewers, department chairs, presidents of scientific societies, etc. But many of the imbalances people notice, whether in conversation with peers or through studies like ours, are perpetuated by researchers at all levels. Given that every research project is built on prior research, and therefore every paper has a reference list of citations, every researcher can make a difference. Who we choose to cite matters.
Dworkin: To understand the role of gender in citation practices, we looked at the authors and reference lists of articles published in five top neuroscience journals since 1995. We accounted for self-citations, and various potentially relevant characteristics of papers, and we found that women-led papers are under-cited relative to what would be expected if gender was not a consideration in citation behavior. Importantly, we also found that the under-citation of women-led papers is driven largely by the citation behavior of men-led teams. We also found that this trend is getting worse over time, because the field is getting more diverse while citation rates are generally staying the same.
For a very simple example, if there were 10 women and 90 men neuroscientists in 1980, then citing 10% women would be roughly proportional. But with a diversifying field, say there are now 200 women and 200 men neuroscientists and citations are still 10% women. Sure, the percentage of women cited didn’t go down, but that percentage is now vastly lower than the true percentage in the field. That’s a dramatic example, but it shows you that if we’re going to call for equality in scientific citation, the number of women-led papers on a given reference list should reflect, or even exceed, the number of available and relevant women-led papers in a field, and our work found that it does not.
Bassett: This under-citation of women scientists is a key issue because the gaps in the amount of engagement that women’s work receives could have detrimental downstream effects on conference invitations, grant and fellowship awards, tenure and promotion, inclusion in syllabi, and even student evaluations. As a result, understanding and eliminating gender bias in citation practices is vital for addressing gender imbalances in a field.
Why are citations important to gender representation in neuroscience?
Dworkin: Unlike hiring and grant funding, citations are something every researcher participates in. For example, as a graduate student I did not have any role on a faculty search committee, or any power in an academic society to decide on conference speakers, but I still have reference lists in all my papers. Citations are a unique area where all researchers play a direct role, where each person has a chance to reflect on their own practices and use those practices to create change in their field. Their ubiquity means that citations function as a conversation within a field, and their presence or absence can signal whose work is valued and whose is not. On a more concrete level, citations are often used as metrics for a variety of important, potentially career-defining, decisions.
Bassett: There are a lot of underrepresented scholars who have fantastic ideas and write really interesting papers but they’re not being acknowledged — and cited — in the way they deserve. And there are great role models for all the young women who are thinking about going into science, but unless the older women scientists are being cited, the younger ones will never see them. Without serious changes in the field, and a deep commitment to gender and racial diversity, many young women and minority scientists won’t stick with it, they won’t be hired, they won’t be promoted, and they won’t be put in the textbooks.
Zurn: Exactly. I think it’s important not only to think about who we’re citing as leading scientists, but also what sorts of people we’re representing as scientists at all. If you are looking at neuroscience as a field and you see predominantly white cisgender men in the research labs and the reference lists, then you begin to think that is what a neuroscientist looks like. But this homogeneity is neither representative of an increasingly diverse field like neuroscience, nor supportive of continuing efforts to diversify STEM in general. We need to expand what a scientist looks like and citations are one way to do that.
Danielle Bassett also has appointments in Penn Engineering’s Department of Electrical and Systems Engineering and Penn Arts & Sciences Department of Physics and Astronomy.
Jordan Dworkin is now an Assistant Professor of Clinical Biostatistics in the Department of Psychiatry at Columbia University.
Kristin Linn, Assistant Professor of Biostatics, Russell Shinohara, Associate Professor of Biostatistics, and Erin Teich, a postdoctoral researcher in Bassett’s lab, also contributed to the study published in Nature Neuroscience. It was supported by the National Institute of Neurological Disorders and Stroke through grants R01 NS085211 and R01 NS060910, the John D. and Catherine T. MacArthur Foundation, the Alfred P. Sloan Foundation, and the National Science Foundation through CAREER Award PHY-1554488.