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Fidelity and Replication: Modelling the Impact of Protocol Deviations on Effect Size
Cognitive science and cognitive neuroscience researchers have agreed that the replication of findings is important for establishing which ideas (or theories) are integral to the study of cognition across the lifespan. Recently, high-profile papers have called into question findings that were once thought to be unassailable. Much attention has been paid to how p-hacking, publication bias, and sample size are responsible for failed replications. However, much less attention has been paid to the fidelity by which researchers enact study protocols. Researchers conducting education or clinical trials are aware of the importance in fidelity – or the extent to which the protocols are delivered in the same way across participants. Nevertheless, this idea has not been applied to cognitive contexts. This seminar discusses factors that impact the replicability of findings alongside recent models suggesting that even small fidelity deviations have real impacts on the data collected.
ReproNim: Towards a culture of more reproducible neuroimaging research
Given the intrinsically large and complex data sets collected in neuroimaging research, coupled with the extensive array of shared data and tools amassed in the research community, ReproNim seeks to lower the barriers for efficient: use of data; description of data and process; use of standards and best practices; sharing; and subsequent reuse of the collective ‘big’ data. Aggregation of data and reuse of analytic methods have become critical in addressing concerns about the replicability and power of many of today’s neuroimaging studies.
Impact evaluation for COVID-19 non-pharmaceutical interventions: what is (un)knowable?
COVID-19 non-pharmaceutical intervention (NPI) policies have been one of the most important and contentious decisions of our time. Beyond even the "normal" inherent difficulties in impact evaluation with observational data, COVID-19 NPI policy evaluation is complicated by additional challenges related to infectious disease dynamics and lags, lack of direct observation of key outcomes, and a multiplicity of interventions occurring on an accelerated time scale. Randomized controlled trials also suffer from what is feasible and ethical to randomize as well as the sheer scale, scope, time, and resources required for an NPI trial to be informative (or at least not misinformative). In this talk, Dr. Haber will discuss the challenges in generating useful evidence for COVID-19 NPIs, the landscape of the literature, and highlight key controversies in several high profile studies over the course of the pandemic. Chasing after unknowables poses major problems for the metascience/replicability movement, institutional research science, and decision makers. If the only choices for informing an important topic are "weak study design" vs "do nothing," when is "do nothing" the best choice?
A Manifesto for Big Team Science
Progress in psychology has been frustrated by challenges concerning replicability, generalizability, strategy selection, inferential reproducibility, and computational reproducibility. Although often discussed separately, I argue that these five challenges share a common cause: insufficient investment of resources into the typical psychology study. I further suggest that big team science can help address these challenges by allowing researchers to pool their resources to efficiently and drastically increase the amount of resources available for a single study. However, the current incentives, infrastructure, and institutions in academic science have all developed under the assumption that science is conducted by solo Principal Investigators and their dependent trainees. These barriers must be overcome if big team science is to be sustainable. Big team science likely also carries unique risks, such as the potential for big team science institutions to monopolize power, become overly conservative, make mistakes at a grand scale, or fail entirely due to mismanagement and a lack of financial sustainability. I illustrate the promise, barriers, and risks of big team science with the experiences of the Psychological Science Accelerator, a global research network of over 1400 members from 70+ countries.
How to combine brain stimulation with neuroimaging: "Concurrent tES-fMRI
Transcranial electrical stimulation (tES) techniques, including transcranial alternating and direct current stimulation (tACS and tDCS), are non-invasive brain stimulation technologies increasingly used for modulation of targeted neural and cognitive processes. Integration of tES with human functional magnetic resonance imaging (fMRI) provides a novel avenue in human brain mapping for investigating the neural mechanisms underlying tES. Advances in the field of tES-fMRI can be hampered by the methodological variability between studies that confounds comparability/replicability. To address the technical/methodological details and to propose a new framework for future research, the scientific international network of tES-fMRI (INTF) was founded with two main aims: • To foster scientific exchange between researchers for sharing ideas, exchanging experiences, and publishing consensus articles; • To implement the joint studies through a continuing dialogue with the institutes across the globe. The network organized three international scientific webinars, in which considerable heterogeneities of technical/methodological aspects in studies combining tES with fMRI were discussed along with strategies to help to bridge respective knowledge gaps, and distributes newsletters that are sent regularly to the network members from the Twitter and LinkedIn accounts.