Sugoi & Yokunai

Firstly, results from sleep studies suggest that the amount of accumulated awake time is associated with the performance in attentional tasks, thus making attentional maintenance more variable and inconsistent. Secondly, such variability is manifested in errors of omission (i.e., failure to respond in a timely manner or attention lapses) and errors of commission (i.e., response to stimuli that are not present). These errors can be detected by specialized, reliable, and valid tests such as the Psychomotor Vigilance Test which is simple enough to avoid learning effects and is sensitive to sleep loss. Thirdly, brain studies have shown that sleep deprivation (SD) is positively correlated with decreased activity in the prefrontal cortex (PFC), visual, parietal, and premotor areas during attention tasks.

Firstly, sleep and physical activity are known to affect working memory. While sleep deprivation causes deficits in working memory performance, physical activity improves working memory function.

Regression models show diverse associations of external factors such as sleep, activity, mood, and physiology with brain network dynamics in the default mode, fronto-parietal, cingulo-opercular, and somatomotor networks. Time-lagged cross-correlation analyses suggest that the associations between brain connectivity and these external factors extend beyond the previous day, spanning up to 15 days in the past, possibly reflecting a more prolonged and sustained relationship between external factors and neural processes.

Fragmented sleep increases subjective fatigue and deteriorates inhibition, even when the total sleep duration remains unchanged. Therefore, it is not surprising that supporting our hypotheses, our results show that restlessness is strongly associated with changes in brain connectivity during sustained attention tasks. Indeed, repeated disruptions in sleep are known to progressively reduce attention, with vigilant attention deficits building up across consecutive days of sleep restriction in a dose-dependent manner.

Sleep also plays a crucial role in efficient functioning of working memory. We observed that longer sleep and more interruptions during sleep are associated with greater integration of the DMN and FPN. However, the effect of sleep duration on working memory does not seem to occur immediately but is observed after a 2-week delay.

Doctors w/o GPT-4:  73.7%
Doctors with GPT-4: 76.3%
but GPT-4 alone: 92.1% 

Not looking good for human doctors.  It was a timed test, so maybe some anxiety caused wrong answers, but the control group was allowed all their usual online resources except an LLM.  The study says that the doctors were selected from various institutions, but didn't disclose where.  First, machine learning models are great when you present them with nicely packaged clinical vignettes. The trick is to tease out the salient elements. But secondly, that doesn't exonerate the human doctors: they deliberately chose to ignore the right diagnosis in favor of something else. This dispels the notion that AI can help clinicians be better doctors.
Thirdly, it foreshadows the future of medicine – that diagnosticians will be replaced by human nurses who are paid to create clinical vignettes for a model to parse. Real geniuses will go into research and industry, and eschew clinical medicine, also largely because it will pay far less than their earning potential.