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Cannabis is the most widely used illicit drug in the United States and is often associated with changes in attention function, which may ultimately impact numerous other cognitive faculties (e.g. memory, executive function). Importantly, despite the increasing rates of cannabis use and widespread legalization in the United States, the neural mechanisms underlying attentional dysfunction in chronic users are poorly understood.
We used magnetoencephalography (MEG) and a modified Posner cueing task in 21 regular cannabis users and 32 demographically matched non-user controls. MEG data were imaged in the time−frequency domain using a beamformer and peak voxel time series were extracted to quantify the oscillatory dynamics underlying use-related aberrations in attentional reorienting, as well as the impact on spontaneous neural activity immediately preceding stimulus onset.
Behavioral performance on the task (e.g. reaction time) was similar between regular cannabis users and non-user controls. However, the neural data indicated robust theta-band synchronizations across a distributed network during attentional reorienting, with activity in the bilateral inferior frontal gyri being markedly stronger in users relative to controls (p's < 0.036). Additionally, we observed significantly reduced spontaneous theta activity across this distributed network during the pre-stimulus baseline in cannabis users relative to controls (p's < 0.020).
Despite similar performance on the task, we observed specific alterations in the neural dynamics serving attentional reorienting in regular cannabis users compared to controls. These data suggest that regular cannabis users may employ compensatory processing in the prefrontal cortices to efficiently reorient their attention relative to non-user controls.
The Cognitive Battery of the National Institutes of Health Toolbox (NIH-TB) is a collection of assessments that have been adapted and normed for administration across the lifespan and is increasingly used in large-scale population-level research. However, despite increasing adoption in longitudinal investigations of neurocognitive development, and growing recommendations that the Toolbox be used in clinical applications, little is known about the long-term temporal stability of the NIH-TB, particularly in youth.
The present study examined the long-term temporal reliability of the NIH-TB in a large cohort of youth (9–15 years-old) recruited across two data collection sites. Participants were invited to complete testing annually for 3 years.
Reliability was generally low-to-moderate, with intraclass correlation coefficients ranging between 0.31 and 0.76 for the full sample. There were multiple significant differences between sites, with one site generally exhibiting stronger temporal stability than the other.
Reliability of the NIH-TB Cognitive Battery was lower than expected given early work examining shorter test-retest intervals. Moreover, there were very few instances of tests meeting stability requirements for use in research; none of the tests exhibited adequate reliability for use in clinical applications. Reliability is paramount to establishing the validity of the tool, thus the constructs assessed by the NIH-TB may vary over time in youth. We recommend further refinement of the NIH-TB Cognitive Battery and its norming procedures for children before further adoption as a neuropsychological assessment. We also urge researchers who have already employed the NIH-TB in their studies to interpret their results with caution.
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