Author: Naomi Gaggi Editors: Elisa Guma, Elizabeth DuPre, Simon Steinkamp, Lavinia Uscatescu, Kevin Sitek
Dr. Puce shares her journey as part of the OHBM community, including her service as OHBM Chair from 2020-2022.
Dr. Aina Puce is an Eleanor Cox Riggs Professor of Psychological and Brain Science at Indiana University Bloomington. At the 2023 Annual Meeting, she was honored as a Fellow of OHBM for her contributions to the society and her outstanding academic and intellectual leadership. Her research career spans social neuroscience, multimodal neuroimaging (including electroencephalography [EEG] and magnetoencephalography [MEG]), and best practices in neuroimaging. Her book, MEG-EEG Primer—co-authored with Riitta Hari was just released in its second edition in 2023. Her current research focuses on the neural basis of social cognition and nonverbal communication.
Dr. Puce has been very involved in the OHBM organization, including chairing the society through the peak of the COVID-19 pandemic, and she has been attending the annual meetings since 1995. In this interview, she talks about her history with OHBM and the positions she had, including her service as OHBM Chair from 2020-2022. She talks about how she navigated several obstacles and changes throughout this time. Dr. Puce lays out lessons learned throughout her career and during her time in the OHBM community—chiefly, that people matter. She highlights how working with her colleagues with whom she has cultivated mutual respect in both scientific and OHBM-related endeavors has been one of the highlights of her career and a major part of her OHBM tenure. She talks about her research and how she is developing a new direction for her work, including integrating her passion for art into science. We are grateful to Dr. Puce for her continued commitment to OHBM, and for taking the time to participate in this blog post. If you’re curious about how OHBM managed during the pandemic and the consequential major changes, her interview has the answers!
Author: Elisa Guma Editors: simon steinkamp, Elizabeth dupre
Learn more from the SPM team about open science.
Queen Square, home of the FIL and other neuroscience / neurology departments, in the winter snow from a previous year (courtesy of Peter Zeidman)
Next in our award winner interview series, we had the chance to hear from this year’s Open Science Award winner, the Statistical Parametric Mapping (SPM) Team based out of the Functional Imaging Laboratory (FIL) at University College London. SPM is a free, open source, and widely used software suite designed for the analysis of brain imaging data across various modalities including PET, fMRI, EEG, MEG, and SPECT. Additionally, SPM provides different analysis approaches for neuroimaging data that go beyond the classic General Linear Model (GLM), such as Dynamic Causal Modelling (DCM) and Voxel Based Morphometry (VBM). SPM was first developed by Karl Friston (see an interview with him from 2017 on this blog) for the statistical analysis of Positron Emission Tomography (PET) and functional Magnetic Resonance Imaging (fMRI) data. Since then, it has gone through several technical improvements to reflect theoretical advances in the field (here is a history on their website and a retrospective piece about the software by Dr. John Ashburner). The current software version can be found here. In addition to maintaining and improving the software, the SPM team also offers in-person courses to help neuroimagers learn how to use their tools.
Since the early 1990s, SPM has been at the forefront of open science—even before the notion of open science was widespread in the neuroimaging community. Indeed, Dr. Karl Friston used to give away the software on floppy disks to those who asked; now it is freely available for download. Additionally, the SPM team has been leading substantial efforts to teach SPM and its methods by providing courses or publishing tutorials.
We are grateful to Peter Zeidman, Olivia Kowalczyk and the SPM team for being willing to answer a few questions about their work. Read on to learn more about the SPM team and their thoughts on open science!
Author: Alex Albury Edited by: Elisa guma, kevin sitek
Lay summary of article by Cuaya et al. about language representation in the dog brain.
If you have a pet, chances are you talk to them, though you may not expect them to actually understand you. But have you ever stopped to think about just how much your furry friends might be listening? Researchers in the Neuroethology of Communication Lab at Eötvös Loránd University in Hungary set out to find out just how much dogs understand from human language. To do this, they conducted a study examining what happens in a dog’s brain when they hear different languages.
Although language acquisition has been extensively studied for decades, we are still far from understanding how language learning happens in the brain. Some researchers have taken more of a comparative approach to this question by investigating language cognition in species other than humans, including macaques, parrots, and man’s best friend, dogs.
Language learning is believed to rely heavily on exposure; that is, we learn by hearing. A popular theory of language acquisition is statistical learning. Under this theory, the brain is viewed as a pattern detection machine that is constantly learning the regularities of the world around us. In language, these regularities include aspects of speech such as tone, rhythm, and word boundaries.
In her paper, Dr. Cuaya found unique patterns of brain activity in dogs when they were hearing voices in a familiar vs. unfamiliar language. The differences were stronger in older dogs, suggesting that more exposure to a particular language drives stronger representation of voices in that language in dogs. You can read a more in-depth summary of her paper here.
Dr. Cuaya is currently a postdoctoral researcher at the University of Vienna in Austria. Much of her work uses functional MRI to investigate how sensory stimulation—looking at faces, hearing voices, and touching objects—is represented in the brains of both humans and dogs. Before moving to Austria, Dr. Cuaya conducted research at Eötvös Loránd University in Budapest, Hungary and at the Instituto de Neurobiología, Universidad Nacional Autónoma de México (UNAM) in Querétaro, México.
Read on to learn about Dr. Cuaya’s experience working with canine participants in neuroimaging and what we should take away from her research!
Author: Lavinia Carmen Uscătescu Editors: Elisa Guma, Elizabeth Dupre, Kevin sitek
Lay summary of publication by Ji et al (2022): “Fetal behavior during MRI changes with age and relates to network dynamics”
That fetuses move inside the womb is nothing new, but how these early movement patterns could predict neonatal health is only beginning to be understood. So far, generally reduced intra-uterine movement has been associated with preterm birth and mild language delay, while more active fetuses have shown enhanced neonatal brain development. It could therefore prove useful to learn whether specific fetal movement patterns could be used as early indicators of potential developmental delays. Researchers at the New York University School of Medicine have set out to decode the hidden information in fetal movement patterns. Their paper, led by Dr. Lanxin Ji, “Fetal behavior during MRI changes with age and relates to network dynamics”, was awarded the Human Brain Mapping Editor's Choice Award at the 2023 OHBM Annual Meeting. Check out our interview with Dr. Ji here!
Prior to her work at NYU, she earned her PhD degree in Biomedical Imaging from Tsinghua University, which included a one year fellowship in the Department of Psychiatry at Yale University. During this time, she developed data-driven methods to measure neural compensation (i.e., the way in which the brain reorganizes itself in older adults to compensate for neural deterioration), and she studied the effects of exercise and cognitive training on brain plasticity over time in older adults.
We are grateful that Dr. Ji was willing to answer a few questions about her work. To read a lay summary of the research paper for which she won this award, please click here. Read on to learn more about Dr. Ji’s research!