Phillip M. Alday

Effects of neural noise on predictive model updating across the adult lifespan

This study shows that older adults show reduced adaptation of prediction error signals in language processing compared to younger adults, linked to neural noise and changes in aperiodic EEG metrics.

EEG and behavioral correlates of attentional processing while walking and navigating naturalistic environments

This study examines attentional processing during walking and navigation in natural environments using EEG, finding differences in neural responses compared to lab settings.

Oscillatory responses to generated and perceived rhythms

This study investigates whether neural oscillations reflect rhythm perception or generation, finding that meter-related oscillations occur only when rhythms are actively generated.

Linguistic structure and meaning organize neural oscillations into a content-specific hierarchy

The paper investigates how neural oscillations reflect linguistic content beyond acoustic and rhythmic features during speech comprehension.

The Decision Decoding ToolBOX (DDTBOX) - A multivariate pattern analysis toolbox for event-related potentials

DDTBOX is an open-source toolbox for multivariate pattern analysis of EEG data, enabling classification and regression of experimental variables through spatiotemporal decoding.

Alpha Oscillations Prior to Encoding Preferentially Modulate Memory Consolidation during Wake Relative to Sleep

The paper investigates how pre-encoding alpha oscillations affect memory consolidation during wake versus sleep, finding that higher alpha power during wake enhances memory retention.

Towards a reliable, automated method of individual alpha frequency (IAF) quantification

This paper introduces an automated method for estimating individual alpha frequency (IAF) using spectral smoothing, showing improved reliability compared to simpler methods.

Commentary on Sanborn and Chater: Posterior Modes are Attractor Basins

This paper discusses Sanborn and Chater's theory of cognitive and brain function using Bayesian sampling and explores its connections to free-energy principles and attractor-basin dynamics.