Differential replay of reward and punishment paths predicts approach and avoidance

Abstract

Neural replay is implicated in planning, where states relevant to a task goal are rapidly reactivated in sequence. It remains unclear whether, during planning, replay relates to an actual prospective choice. Here, using magnetoencephalography (MEG), we studied replay in human participants while they planned to either approach or avoid an uncertain environment containing paths leading to reward or punishment. We find evidence for forward sequential replay during planning, with rapid state-to-state transitions from 20 to 90 ms. Replay of rewarding paths was boosted, relative to aversive paths, prior to a decision to avoid and attenuated prior to a decision to approach. A trial-by-trial bias towards replaying prospective punishing paths predicted irrational decisions to approach riskier environments, an effect more pronounced in participants with higher trait anxiety.The findings indicate a coupling of replay with planned behaviour, where replay prioritises an online representation of a worst-case scenario for approaching or avoiding.

Replay-triggered Brain-wide Activation in Humans

“…During mental simulation, we found 30-ms-time-lag on-task replay in EEG, which aligns with previously reported human replay speed 9,14,24,25,45 . Here we now show that the strength of this replay was associated with activation of hippocampus and mPFC, as revealed by fMRI, a finding consistent with previous fMRI replay findings 22 and MEG source localization 9,14,28,29,45 .…”

“… a , The mean cross validated decoding accuracy of EEG-based classifiers. As in previous studies 9,14,25,28,30,44,45 , classifiers were trained independently at each time point and tested on all time points, starting from 200 ms before stimulus onset to 800 ms post onset (10 ms time bin). Decoding accuracy peaked at 210 ms post-stimulus onset.…”

“… a, Two analysis methods for detecting replays. One is TDLM 42 , primarily used with MEG 9,14,28,30,44,45 , and recently EEG 25 . The other is a regression method, as per Wittkuhn and Schuck 26 and used in fMRI studies 27 .…”

Non-feature-specific elevated responses and feature-specific backward replay in human brain induced by visual sequence exposure

“…Learning-induced replay serves as a pivotal cortical plasticity mechanism to support various cognitive functions. Although previous studies have attempted to elucidate the properties of replay in humans, they exclusively focused on the hippocampus within task-dependent training contexts 18,19,35 . Here, we unveiled replay events in the human visual cortex through exposure-based sequence learning.…”

“…Replay refers to the sequential reactivation of neural activity patterns associated with prior experience. During replay, the neural representations of a past experience can be compressed in time [15][16][17][18][19] . These replay events frequently coincide with sharp-wave ripples (SWRs), which are high-frequency (150-220 Hz) ripple oscillations 20,21 observed in the local field potential 22,23 associated with learning processes [24][25][26] .…”