# Human brain integrates both unconditional and conditional timing statistics to guide expectation and behavior

## TL;DR

The human brain combines different timing expectations from past experiences to predict events, using distinct brain regions for each type of prediction and integrating them in the posterior cingulate cortex.

## Contribution

This study identifies how the brain integrates unconditional and conditional temporal predictions using distinct neural regions and reveals a hierarchical network for predictive coding of time.

## Key findings

- Behavioral models show that integrating unconditional and conditional predictions best explains reaction times.
- EEG source signals are best reconstructed when both types of predictions are integrated.
- The posterior and anterior brain regions separately encode unconditional and conditional predictions, with integration occurring in the right posterior cingulate area.

## Abstract

Our brain uses prior experience to anticipate the timing of upcoming events. This dynamic process can be modeled using a hazard function derived from the probability distribution of event timings. However, the contexts of an event can lead to various probability distributions for the same event, and it remains unclear how the brain integrates these distributions into a coherent temporal prediction. In this study, we create a foreperiod sequence paradigm consisting of a sequence of paired trials, where in each trial, participants respond to a target signal after a specified time interval (i.e., foreperiod) following a warning cue. The prediction of the target onset in the second trial can be based on two probability distributions: the unconditional probability of the second foreperiod and its conditional probability given the foreperiod in the first trial. These probability distributions are then transformed into hazard functions to represent the unconditional and conditional temporal predictions. The behavioral model incorporating both predictions and their mutual modulation provides the best fit for reaction times to the target signal, indicating that both temporal statistics are integrated to make predictions. We further show that electroencephalographic source signals are also best reconstructed when integrating both predictions. Specifically, the unconditional and conditional predictions are encoded separately in the posterior and anterior brain regions, and integration of these two types of predictive processing requires a third region, particularly the right posterior cingulate area. Our study reveals brain networks that integrate multilevel temporal information, offering insight into the hierarchical predictive coding of time.

How does the brain integrate different temporal predictions based on prior experience? This study shows that humans combine unconditional and conditional timing expectations to guide behavior, with distinct brain regions encoding each type and the posterior cingulate cortex integrating them, revealing a hierarchical network for predictive coding of time.