The Effects of Methylphenidate on the Neural Signatures of Sustained Attention.

BACKGROUND: Although it is well established that methylphenidate (MPH) enhances sustained attention, the neural mechanisms underpinning this improvement remain unclear. We examined how MPH influenced known electrophysiological precursors of lapsing attention over different time scales. METHODS: We measured the impact of MPH, compared with placebo, on behavioral and electrocortical markers while healthy adults (n = 40) performed a continuous monitoring paradigm designed to elicit attentional lapses. RESULTS: MPH led to increased rates of target detection, and electrophysiological analyses were conducted to identify the mechanisms underlying these improvements. Lapses of attention were reliably preceded by progressive increases in alpha activity that emerged over periods of several seconds. MPH led to an overall suppression of alpha activity across the entire task but also diminished the frequency of these maladaptive pretarget increases through a reduction of alpha variability. A drug-related linear increase in the amplitude of the frontal P3 event-related component was also observed in the pretarget timeframe (3 or 4 seconds). Furthermore, during immediate target processing, there was a significant increase in the parietal P3 amplitude with MPH, indicative of enhanced perceptual evidence accumulation underpinning target detection. MPH-related enhancements occurred without significant changes to early visual processing (visual P1 and 25-Hz steady-state visual evoked potential). CONCLUSIONS: MPH serves to reduce maladaptive electrophysiological precursors of lapsing attention by acting selectively on top-down endogenous mechanisms that support sustained attention and target detection with no significant effect on bottom-up sensory excitability. These findings offer candidate markers to monitor the therapeutic efficacy of psychostimulants or to predict therapeutic responses.

Ocular exposure to blue-enriched light has an asymmetric influence on neural activity and spatial attention.

Brain networks subserving alertness in humans interact with those for spatial attention orienting. We employed blue-enriched light to directly manipulate alertness in healthy volunteers. We show for the first time that prior exposure to higher, relative to lower, intensities of blue-enriched light speeds response times to left, but not right, hemifield visual stimuli, via an asymmetric effect on right-hemisphere parieto-occipital α-power. Our data give rise to the tantalising possibility of light-based interventions for right hemisphere disorders of spatial attention.

Differential shift in spatial bias over time depends on observers׳ initial bias: Observer subtypes, or regression to the mean?

Healthy subjects typically exhibit a subtle bias of visuospatial attention favouring left space that is commonly termed 'pseudoneglect'. This bias is attenuated, or shifted rightwards, with decreasing alertness over time, consistent with theoretical models proposing that pseudoneglect is a result of the right hemisphere׳s dominance in regulating attention. Although this 'time-on-task effect' for spatial bias is observed when averaging across whole samples of healthy participants, Benwell, C. S. Y., Thut, G., Learmonth, G., & Harvey, M. (2013b). Spatial attention: differential shifts in pseudoneglect direction with time-on-task and initial bias support the idea of observer subtypes. Neuropsychologia, 51(13), 2747-2756 recently presented evidence that the direction and magnitude of bias exhibited by the participant early in the task (left biased, no bias, or right biased) were stable traits that predicted the direction of the subsequent time-on-task shift in spatial bias. That is, the spatial bias of participants who were initially left biased shifted in a rightward direction with time, whereas that of participants who were initially right biased shifted in a leftward direction. If valid, the data of Benwell et al. are potentially important and may demand a re-evaluation of current models of the neural networks governing spatial attention. Here we use two novel spatial attention tasks in an attempt to confirm the results of Benwell et al. We show that rather than being indicative of true participant subtypes, these data patterns are likely driven, at least in part, by 'regression towards the mean' arising from the analysis method employed. Although evidence supports the contention that trait-like individual differences in spatial bias exist within the healthy population, no clear evidence is yet available for participant/observer subtypes in the direction of time-on-task shift in spatial biases.