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Artificial neural networks (ANNs) inspired by biology are beginning to be widely used to model behavioural and neural data, an approach we call ‘neuroconnectionism’. ANNs have been not only lauded as the current best models of information processing inthe brain butalsocriticized for failing to account for basic cognitive functions. In this Perspective article, we propose that arguing about the successes and failures of a restricted set of current ANNs is the wrong approach to assess the promise of neuroconnectionism for brain science. Instead, we take inspiration from the philosophy of science, and in particular from Lakatos, who showed that the core of a scientific research programme is often not directly falsifiable but should be assessed by its capacity to generate novel insights. Following this view, we present neuroconnectionism as a general research programme centred around ANNs as a computational language for expressing falsifiable theories about brain computation. We describe the core of the programme, the underlying computational framework and its tools for testing specific neuroscientific hypotheses and deriving novel understanding. Taking a longitudinal view, we review past and present neuroconnectionist projects and their responses to challenges and argue that the research programme is highly progressive, generating new and otherwise unreachable insights into the workings of the brain.
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Building the Research Innovation Workforce: Challenges and Recommendations from a Virtual Workshop to Advance the Research Computing Community
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Institutions of Higher Education are complex matrixed organizations that require collaboration across silos. Research Administration, Institutional Research, Enterprise IT, and Research Computing are important areas to leverage when building a research analytics program. Across these units, our work can look very different, and we likely have different mental models for how we think about and approach work. This can make cross-functional communication and collaboration difficult. This presentation will provide a mental model for working in higher education research analytics, discuss critical players, and how to get work moving forward. Finally, we will provide a list of key ingredients to consider when building your institution’s research analytics program and strategies for effective buy-in and collaboration.more » « less
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Engaging undergraduates in research has been shown to improve retention, increase students' sense of computer science identity, and increase their chances of continuing to graduate school. Yet research experiences at most universities are ad hoc, and many undergraduates-particularly those from groups underrepresented in computing-do not have the opportunity to participate. The Early Research Scholars Program (ERSP) is a structured, academic-year group-based undergraduate research program designed to help universities vastly increase participation in research for early computing undergraduates. ERSP launched at UC San Diego in 2014 where it now annually engages over 50 second-year undergraduates, 59% of whom are women, and 22% of whom are from underrepresented racial and ethnic groups. The program's portable design has enabled its expansion to 7 other colleges and universities. This workshop will train participants in launching ERSP (or any part of it) at their university to increase and diversify the undergraduates participating in research. Workshop leaders are the ERSP directors at four universities. They will address how to launch and run the program in different contexts. They will provide an interactive, hands-on experience of running the program covering the following topics: developing and teaching a research methods class, student application and selection to ensure a diverse and supportive cohort, and creating a dual-mentoring structure to engage and retain early undergraduates without overburdening faculty. Workshop participants will be invited to join the ERSP virtual community to get support launching their own version of ERSP.more » « less
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Designing research collaboratively: Socioenvironmental systems research in the French Basque CountryHighly participatory research and the co-production of knowledge are widely recognized as key to advancing sustainability research that produces useful and usable results. There is great variety in how different teams approach collaborative work, but the initial problem-framing stage is a critical moment of engagement. In this article, we describe our efforts to create a collaborative research project on climate and pastoralism in the northern Basque Country (southwestern France), focusing on our process for determining the research focus. We use the various funding proposals submitted along the way to illustrate concretely the ways in which integrating our different ways of knowing and different approaches led to different research questions than would have been the case had the scientists developed the project alone. We also discuss the difficult choices that must sometimes be made. Researchers and pastoralists worked together to produce this analysis and to make recommendations to others interested in following a similar path.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3491418.3530288
