Christina Stier
@cstier.bsky.social
PostDoc Systems Neuroscience | Studying M/EEG's across the lifespan at IBB Münster | 🧠
Imaging Genetic Epilepsies at UniMedGöttingen & UKTübingen | 🧬⚡️
Imaging Genetic Epilepsies at UniMedGöttingen & UKTübingen | 🧬⚡️
Temporal autocorrelation is predictive of age — out now!
www.pnas.org/doi/10.1073/...
We used @camcan-2010.bsky.social #MEG data and massive time-series feature extraction (hctsa) to understand which aspects of neural activity predict a person's age. #PNAS #aging #MEG #Neuroscience #Neuroskyence
www.pnas.org/doi/10.1073/...
We used @camcan-2010.bsky.social #MEG data and massive time-series feature extraction (hctsa) to understand which aspects of neural activity predict a person's age. #PNAS #aging #MEG #Neuroscience #Neuroskyence
March 4, 2025 at 4:29 PM
Temporal autocorrelation is predictive of age — out now!
www.pnas.org/doi/10.1073/...
We used @camcan-2010.bsky.social #MEG data and massive time-series feature extraction (hctsa) to understand which aspects of neural activity predict a person's age. #PNAS #aging #MEG #Neuroscience #Neuroskyence
www.pnas.org/doi/10.1073/...
We used @camcan-2010.bsky.social #MEG data and massive time-series feature extraction (hctsa) to understand which aspects of neural activity predict a person's age. #PNAS #aging #MEG #Neuroscience #Neuroskyence
Temporal autocorrelation emerged as the most robust indicator. This feature captures age-related signal changes, including periodic and aperiodic components, while also being sensitive to the regional waveform shape.
May 14, 2024 at 11:25 AM
Temporal autocorrelation emerged as the most robust indicator. This feature captures age-related signal changes, including periodic and aperiodic components, while also being sensitive to the regional waveform shape.