Lag-adjusted functional network connectivity reveals sensorimotor and higher cognitive network alterations in depression.

Major Depressive Disorder (MDD) involves large-scale brain network disruption at rest. Canonical zero-lag functional connectivity methods often miss temporal offsets (or "lags") in interactions. Lag-adjusted functional connectivity captures intrinsic neural timescales (INTs) and directional signaling, offering a more sensitive framework to characterize network-level alterations. Here, we applied the NeuroMark framework to resting-state scans from 235 MDD and 284 healthy controls, identifying 105 intrinsic connectivity networks (ICNs) and their time series. To enable sub-TR estimation, time series were upsampled to 100 ms resolution. Lag-adjusted connectivity was computed as the maximal cross-correlation for each ICN pair within a ±2s window sampled at 0.1s intervals. Group differences were assessed using a regression model. Significant differences emerged between groups (p<0.05). Specifically, MDD revealed hyperconnectivity in salience-sensorimotor and sensorimotor-temporoinsular networks, alongside hypoconnectivity in salience-higher cognitive temporal and frontal networks and temporoparietal-visual systems, indicating altered coordination among sensory, emotional, and cognitive processes. An exploration of the lags revealed a non-random bias in the temporal ordering of networks operating at different INTs. This was characterized by earlier relative cortical coupling in MDD, suggesting compressed inter-network timing. These findings underscore the utility of lag-adjusted approaches for detecting impaired neural coordination, beyond alterations in connectivity strength.