Animal research

Community Bulletin: Theory of Mind, Using Historical Control Data for Animal Research | Spectrum

Illustration by Laurène Boglio

Hello and welcome to this week’s community newsletter! I am your host, Chelsey B. Coombs, Spectrumengagement editor.

This week we start with a thread of Kevin Tan, a graduate student at the University of California, Los Angeles, and researcher of the pre-print study published on Research Square, titled “Human electrocorticography reveals a common neurocognitive pathway for mentalization of self and others. “

Mentalization, also known as theory of mind, describes the ability to understand the desires, intentions and beliefs of others. Previous research suggests that this ability is impaired in some people with autism. The new study used electrocorticography (ECoG) to record which regions of the Default Mode Network (DMN) activate during mentalization in neurotypical people.

Tan wrote on Twitter that functional magnetic resonance imaging (fMRI) has shown that mentalization occurs in the network in default mode, but it has been difficult to identify the functions of various regions of the DMN due to the “Low temporal resolution of fMRI, which cannot resolve neurocognitive dynamics at the millisecond scale.”

But the ECoG found that mentalizing oneself and others activated areas of the visual cortex, then DMN temporo-parietal regions, and finally, regions of the median prefrontal cortex. “Critically, regions with subsequent activations showed greater functional specificity for mentalization, greater self / other differentiation, and stronger associations with behavioral response times,” the researchers wrote.

The study attracted a lot of attention from researchers on social media.

Uta frith, professor emeritus of cognitive development at University College London in the UK, who co-created one of the first tests to assess theory of mind, tweeted: “Great thing!

Oscar woolnough, postdoctoral researcher at UTHealth in Houston, TX, added, “The other area you show in the PFC in the subparietal sulcus lines up quite well with the active areas when naming faces and recalling. information about familiar people. “

João Guassi Moreira, another graduate student from the University of California, Los Angeles, tweeted: “This type of work is * invaluable * in the field.”

Jonathan wynn, a health scientist in the Department of Veterans Affairs’ Greater Los Angeles Healthcare System, said he needed to re-read the “fantastic and fascinating work … over and over again and share it with our lab.”

The following thread comes from Valeria bonapersona, a graduate student of UMC Utrecht in the Netherlands, whose new study, “Increase the statistical power of animal experiments with historical control data, ”Was published in Neuroscience of nature. Bonapersona began his thread by saying that for animal researchers it is a “must-read on a sensitive subject: the statistical power of #search and the number of animals used.

Bonapersona and his colleagues show statistically that “the inclusion of data from control groups of previous studies could halve the minimum sample size required to achieve canonical power by 80% or increase the power using the same number of animals ”.

In 2019, the group also released a pre-print on bioRxiv on their open source tool called RePAIR, which allows other scientists to use historical monitoring data.

Bonapersona concluded his thread by saying, “I dream of the day when animal research is no longer necessary, but it might not be in my lifetime. For now, we can be creative with analytical techniques to reduce animal testing.

Mathias schmidt, research group leader at the Max Planck Institute of Psychiatry in Munich, Germany, and contributor to the RELACS Consortium, and whose data validated the method, tweeted: “If you are working with animals in research , you should drop whatever you’re doing right now and read this thread!

Jelle knop, a graduate student from UMC Utrecht, tweeted that the method “could literally save countless animal lives while improving the statistical power of animal studies.”

Resting Leonardo, Scientific Director of the Neuro-Behavioral Analysis Unit at the University of Lausanne in Switzerland, wrote: “I am picking up many signals that the field is ready to become Bayesian.

Although he thought the document presented a “smart solution”, Nathan T. Fried, assistant professor of biology at Rutgers University-Camden in New Jersey, tweeted: “Lab-to-lab variability, genotype-to-genotype variability, even experimenter-to-experimenter variability within a single lab, combined with the continuing dearth of methodological details in rodent articles make this nearly impossible.

That’s it for this week’s edition of Spectrumthe community newsletter of. If you have any suggestions for any interesting social posts you’ve seen in autism research this week, please feel free to email me at [email protected] See you next week!