¿Sabías que la actividad cerebral en reposo puede predecir cómo respondemos a ciertas técnicas de neuromodulación? Una investigación reciente utiliza aprendizaje automático para analizar la actividad cerebral y descubrir patrones que pueden ayudar a tratar la depresión y el trastorno obsesivo-compulsivo. ¿Cuál es tu enfoque para manejar el estrés y la ansiedad? #Neurociencia #Resiliencia #Grit
https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1014154

Complexity of resting cortical activity predicts neurophysiological responses to theta-burst stimulation but fails to generalize: A rigorous machine-learning approach
Author summary Repetitive transcranial magnetic stimulation (rTMS) is a promising non-invasive neuromodulation technique approved by FDA to treat medication-resistant depression, obsessive-compulsive disorder and smoking addiction, with active research for potential treatment of anxiety, bipolar II disorder and improve post-stroke motor rehabilitation. It’s also used experimentally to modify brain excitability, neural plasticity and behavior. However, it currently suffers from low inter- and intra-individual reliability, with some individuals showing improvement from rTMS while others don’t. To better understand the underlying mechanism as well as potentially improve its clinical efficacy, we developed a machine learning model that can identify neurophysiological features that will distinguish people who demonstrates cortical target engagement to rTMS apart from those who don’t. In order to capture both inter- and intra-individual variability, our participants completed identical rTMS protocols twice, initial session for the first time and retest session for the second time. Our results suggested that the relationship between features and rTMS responses changed over time, limiting our model’s ability to generalize. We finally concluded that single session of rTMS isn’t effective and suggested that multiple sessions with personalized rTMS parameters are needed to show reliable neurophysiological effects.







