2019 Conference on Cognitive Computational Neuroscience

13-16 September 2019    Berlin, Germany

Technical Program

Paper Detail

Paper: PS-2B.9
Session: Poster Session 2B
Location: H Fläche 1.OG
Session Time: Sunday, September 15, 17:15 - 20:15
Presentation Time:Sunday, September 15, 17:15 - 20:15
Presentation: Poster
Publication: 2019 Conference on Cognitive Computational Neuroscience, 13-16 September 2019, Berlin, Germany
Paper Title: Detecting sub-second activation sequences with sequential fMRI pattern analysis
Manuscript:  Click here to view manuscript
License: Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 Unported License.
DOI: https://doi.org/10.32470/CCN.2019.1253-0
Authors: Lennart Wittkuhn, Nicolas W. Schuck, Max Planck Institute for Human Development, Germany
Abstract: Mental computations are often reflected in fast changes of neural activation patterns, for instance during so called replay events in the hippocampus. A major challenge for human neuroscience is therefore to capture such fast changes with sufficient spatial resolution using noninvasive neuroimaging. Here, we demonstrate that functional magnetic resonance imaging (fMRI) with a conventional repetition time (TR) of 1.25 s can be used to investigate sequentially activated neural patterns separated by less than 100 ms. We investigated the statistical properties of neural activation patterns following the presentation of fast sequential visual stimuli by extracting multivariate probabilistic estimates for the presence of a neural event over time. The time-course of the probabilistic classifier evidence resembled the expected shape of the hemodynamic response function (HRF). Importantly, by disentangling temporally and spatially overlapping BOLD signals our analysis technique allowed us to detect the order of sequentially activated neural patterns separated by only 64 ms. Providing such enhanced temporal resolution, our method promises to lay the groundwork for investigations into cognitive processes that require extracting temporal information from fast neural event sequences, such as hippocampal replay.