Early psychosis shows reduced low-frequency sensorimotor fluctuations tied to dexterity

In a new study that sharpens the neural timeline of early psychosis, researchers report that a core measure of brain dynamics—low frequency fluctuation (LFF) in the sensorimotor cortex—shows reduced amplitude soon after onset. The work links these altered intrinsic signals to both motor performance and a pattern of excessive connectivity, offering a mechanistic bridge between symptoms, brain function, and behavior.

Low frequency fluctuation, derived from resting-state functional MRI, reflects how strongly spontaneous neural activity varies over time at slow timescales. By focusing on amplitude rather than connectivity alone, the team aimed to determine whether early psychosis involves not only how regions talk, but also how powerfully sensorimotor systems internally “wobble” when the brain is not engaged in a task.

The investigators used a cohort of participants in the early stages of psychosis and compared their resting-state LFF profiles with those of healthy controls. Sensorimotor cortex regions exhibited a significant drop in LFF amplitude, suggesting that baseline excitability or local network integrity may be weakened at a stage when many patients are still relatively early in their illness trajectory.

Crucially, the reduced LFF amplitude was not merely a biomarker of diagnosis. It correlated with motor dexterity, implying that intrinsic sensorimotor dynamics may contribute to subtle motor inefficiencies that can precede or accompany psychotic symptoms. In other words, the brain’s resting “noise structure” appears to track real-world motor function.

The authors also report an association with hyperconnectivity—an observation increasingly implicated in psychosis research. Patients showing stronger aberrant network coupling tended to display the LFF changes observed in the sensorimotor cortex. This supports a model in which local signal weakening coexists with network-level over-integration, producing complex dynamics rather than a simple on/off defect.

Technically, the analysis pipeline accounted for typical confounds in resting-state imaging, including head motion and nuisance signals, aiming to ensure that measured amplitude differences reflect neural processes rather than artifacts. The relationship between LFF and behavior further strengthened the interpretation that intrinsic cortical dynamics are behaviorally meaningful.

If validated in larger, longitudinal samples, the findings could inform future interventions that target early circuit dysfunction. By connecting a quantifiable resting-state property to motor capability and connectivity patterns, the study provides a testable framework for early risk stratification and monitoring.

For patients and clinicians, the prospect is compelling: a measurable neural signature in early psychosis may help explain why motor control can be affected even before disease becomes entrenched. More broadly, it underscores that psychosis involves distributed alterations in both local activity and large-scale communication.