Selectivity of timing: A meta-analysis of temporal processing in neuroimaging studies using activation likelihood estimation and reverse inference

Front Hum Neurosci. 2023 Jan 5:16:1000995. doi: 10.3389/fnhum.2022.1000995. eCollection 2022.


Over the last few decades, many researchers have investigated time perception and how it is processed in the brain. Past studies have identified cortical and subcortical regions that play an important role in implicit and/or explicit timing tasks. In regard to timing, different regions appear to have roles of varying importance depending on the duration (sub-second vs. supra-second), type of task (such as involving motor responses or passively observing stimuli), and modality (such as auditory, visual, and sensorimotor) resulting in the literature reporting divergent results that are contingent on the specifics of the task. This meta-analysis aims at identifying regions that show activation only for explicit timing tasks through reverse inference. As such, two datasets (the first including studies that involved explicit timing tasks while the second did not) were compared using the activation likelihood estimation (ALE) algorithm. Reverse inference was implemented through Bayes factor modeling, which allowed for the comparison of the activated regions between the two ALE-maps. Results showed a constellation of regions that exhibited selective activation likelihood in explicit timing tasks with the largest posterior probability of activation resulting in the left supplementary motor area (SMA) and the bilateral insula. Some areas that have been dubbed critical for time perception in past studies (i.e., the cerebellum) did not exhibit prevalent activation after analyses.

Keywords: ALE; SMA; meta-analysis; reverse inference; temporal processing.