Abstract
Segmenting perceptual experience into meaningful events is a key cognitive process that helps us make sense of what is happening around us in the moment, as well as helping us recall past events. Nevertheless, little is known about the underlying neural mechanisms of the event segmentation process. Recent work has suggested that event segmentation can be linked to regional changes in neural activity patterns. Accurate methods for identifying such activity changes are important to allow further investigation of the neural basis of event segmentation and its link to the temporal processing hierarchy of the brain. In this study, we introduce a new set of elegant and simple methods to study these mechanisms. We introduce a method for identifying the boundaries between neural states in a brain area and a complementary one for identifying the number of neural states. Furthermore, we present the results of a comprehensive set of simulations and analyses of empirical fMRI data to provide guidelines for reliable estimation of neural states and show that our proposed methods outperform the current state-of-the-art in the literature. This methodological innovation will allow researchers to make headway in investigating the neural basis of event segmentation and information processing during naturalistic stimulation.
Highlights
To understand the world around us as it unfolds over time, two processes are essential; information integration and segmentation
In the first simulation, we evaluated the performance of the greedy state boundary search (GSBS) in detecting state boundaries in simulated data
These distances are not uniformly distributed but show a peak around the middle (10–12 TRs distance), suggesting that the method has a tendency to recover states with similar lengths. These results were very similar for a different number of states (k = 30, see supplementary Fig. 1). These results show that the GSBS method performs better in recovering neural states, especially when states can vary in length
Summary
To understand the world around us as it unfolds over time, two processes are essential; information integration and segmentation. We integrate current sensory input with information from the past to make sense of speech or actions that unfold over time (Buonomano and Maass, 2009; Kiebel et al, 2008). Behavioral research has shown that segmenting information into meaningful events enables us to understand ongoing perceptual input (Zacks et al, 2001) and recall distinct events from our past (Flores et al, 2017; Sargent et al, 2013; Zacks et al, 2006). Segmentation plays a fundamental role in the way we perceive and remember information in daily life, a lot remains unknown about the neural mechanisms that underlie these abilities. We introduce a new method to investigate those mechanisms
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