Time-Perception Network and Default Mode Network Are Associated with Temporal Prediction in a Periodic Motion Task

Abstract

The updating of prospective internal models is necessary to accurately predict future observations. Uncertainty-driven internal model updating has been studied using a variety of perceptual paradigms, and have revealed engagement of frontal and parietal areas. In a distinct literature, studies on temporal expectations have also characterized a time-perception network, which relies on temporal orienting of attention. However, the updating of prospective internal models is highly dependent on temporal attention, since temporal attention must be reoriented according to the current environmental demands. In this study, we used functional magnetic resonance imaging (fMRI) to evaluate to what extend the continuous manipulation of temporal prediction would recruit update-related areas and the time-perception network areas. We developed an exogenous temporal task that combines rhythm cueing and time-to-contact principles to generate implicit temporal expectation. Two patterns of motion were created: periodic (simple harmonic oscillation) and non-periodic (harmonic oscillation with variable acceleration). We found that non-periodic motion engaged the exogenous temporal orienting network, which includes the ventral premotor and inferior parietal cortices, and the cerebellum, as well as the presupplementary motor area, which has previously been implicated in internal model updating, and the motion-sensitive area MT+. Interestingly, we found a right-hemisphere preponderance suggesting the engagement of explicit timing mechanisms. We also show that the periodic motion condition, when compared to the non-periodic motion, activated a particular subset of the default-mode network (DMN) midline areas, including the left dorsomedial prefrontal cortex (DMPFC), anterior cingulate cortex (ACC), and bilateral posterior cingulate cortex/precuneus (PCC/PC). It suggests that the DMN plays a role in processing contextually expected information and supports recent evidence that the DMN may reflect the validation of prospective internal models and predictive control. Taken together, our findings suggest that continuous manipulation of temporal predictions engages representations of temporal prediction as well as task-independent updating of internal models.

Tracking Temporal Hazard in the Human Electroencephalogram Using a Forward Encoding Model

“…The source space analysis of the TRF revealed activity in the precuneus around lag zero, only for the strongly predictive condition. This points toward an involvement of the precuneus in temporal prediction, in line with a previous study reporting enhanced precuneus (and default mode network) activation in a rhythmic temporal prediction task (Carvalho et al, 2016). Extracting only the data from the SMA in a post hoc analysis revealed a positive-to-negative deflection around lag zero for the TRF of the modulated hazard function in the strongly predictive condition only (see Fig.…”

Tracking temporal hazard in the human electroencephalogram using a forward encoding model

“…The source space analysis of the TRF revealed activity in the precuneus around lag zero, only for the strongly predictive condition. This points towards an involvement of the precuneus in temporal prediction, in line with a previous study reporting enhanced precuneus (and default mode network) activation in a rhythmic temporal prediction task (Carvalho et al, 2016). Extracting only the data from the SMA in a post-hoc analysis revealed a positive-to-negative deflection around lag zero for the TRF of the modulated hazard function in the strongly predictive condition only (see Figure 6B, C), which tentatively suggests that the SMA also processes the modulation of temporal hazard in that condition in an instantaneous way, but might not be the dominant region to do so.…”

Preferential activation of the posterior Default-Mode Network with sequentially predictable task switches

“…The preferential activation of a PCC/PrCC cluster with sequentially predictable switches highlights the complexity of cognitive control processes, and has implications for our understanding of the functional role of DMN sub-regions in cognition [11,40]. Imaging studies have reported the involvement of the PCC/PrCC when temporal regularities occur during experimental tasks [1,12] and in instances when actions become repetitive [63]. Our results compliment those and provide an additional facet by showing transient heightened activation was stronger when changes in task rules followed a predictable sequence of events.…”