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Background:
Sleep is more than simple rest. When discussing sleep, we tend to focus on the quantity rather than the quality, how many hours of sleep we get versus the quality or depth of sleep. Duration is an important part of the picture, but understanding the stages of sleep and how certain mental health disorders affect those stages is a crucial part of the discussion.
Sleep is an active mental process where the brain goes through distinct phases of complex electrical rhythms. These phases can be broken down into non-rapid eye movement (NREM) and rapid eye movement (REM). The non-rapid eye movement phase consists of three stages of the four stages of sleep, referred to as N1, N2(light sleep), and N3(deep sleep). N4 is the REM phase, during which time vivid dreaming typically occurs.
Two of the most important measurable brain rhythms occur during non-rapid eye movement (NREM) sleep. These electrical rhythms are referred to as slow waves and sleep spindles. Slow waves reflect deep, restorative sleep, while spindles are brief bursts of brain activity that support memory and learning.
The Study:
A new research review has compiled data on how these sleep oscillations differ across psychiatric conditions. The findings suggest that subtle changes in nightly brain rhythms may hold important clues about a range of disorders, from ADHD to schizophrenia.
The Results:
People with ADHD showed increased slow-spindle activity, meaning those brief bursts of NREM activity were more frequent or stronger than in people without ADHD. Why this happens isn’t fully understood, but it may reflect differences in how the ADHD brain organizes information during sleep. Evidence for slow-wave abnormalities was mixed, suggesting that deep sleep disruption is not a consistent hallmark of ADHD.
Among individuals with autism spectrum disorder (ASD), results were less consistent. However, some studies pointed to lower “spindle chirp” (the subtle shift in spindle frequency over time) and reduced slow-wave amplitude. Lower amplitude suggests that the brain’s deep-sleep signals may be weaker or less synchronized. Researchers are still working to understand how these patterns relate to sensory processing, learning differences, or daytime behavior.
People with depression tended to show reduced slow-wave activity and fewer or weaker sleep spindles, but this pattern appeared most strongly in patients taking antidepressant medications. Since antidepressants can influence sleep architecture, researchers are careful not to overinterpret the changes. Nevertheless, these changes raise interesting questions about how both depression and its treatments shape the sleeping brain.
In post-traumatic stress disorder (PTSD), the trend moved in the opposite direction. Patients showed higher spindle frequency and activity, and these changes were linked to symptom severity which suggests that the brain may be “overactive” during sleep in ways that relate to hyperarousal or intrusive memories. This strengthens the idea that sleep physiology plays a role in how traumatic memories are processed.
The clearest and most reliable findings emerged in psychotic disorders, including schizophrenia. Across multiple studies, individuals showed: Lower spindle density (fewer spindles overall), reduced spindle amplitude and duration, correlations with symptom severity, and cognitive deficits.
Lower slow-wave activity also appeared, especially in the early phases of illness. These results echo earlier research suggesting that sleep spindles, which are generated by thalamocortical circuits, might offer a window into the neural disruptions that underlie psychosis.
The Take-Away:
The review concludes with a key message: While sleep disturbances are clearly present across psychiatric conditions, the field needs larger, better-standardized, and more longitudinal studies. With more consistent methods and longer follow-ups, researchers may be able to determine whether these oscillations can serve as reliable biomarkers or future treatment targets.
For now, the take-home message is that the effects of these mental health disorders on sleep are real and measurable.
Mayeli A, Sanguineti C, Ferrarelli F. Recent Evidence of Non-Rapid Eye Movement Sleep Oscillation Abnormalities in Psychiatric Disorders. Curr Psychiatry Rep. 2025 Dec;27(12):765-781. doi: 10.1007/s11920-024-01544-x. Epub 2024 Oct 14. PMID: 39400693.
Sleep disorders are one of the most commonly self-reported comorbidities of adults with ADHD, affecting 50 to 70 percent of them. A team of British researchers set out to see whether this association could be further confirmed with objective sleep measures, using cognitive function tests and electroencephalography (EEG).
Measured as theta/beta ratio, EEG slowing is a widely used indicator in ADHD research. While it occurs normally in non-ADHD adults at the conclusion of a day, during the day it signals excessive sleepiness, whether from obstructive sleep apnea or from neurodegenerative and neurodevelopmental disorders. Coffee reverses EEG slowing, as do ADHD stimulant medications.
Study participants were either on stable treatment with ADHD medication (stimulant or non-stimulant medication), or on no medication. Participants had to refrain from taking any stimulant medications for at least 48 hours prior to taking the tests. Persons with IQ below 80 or with recurrent depression or undergoing a depressive episode were excluded.
The team administered a cognitive function test, The Sustained Attention to Response Task (SART). Observers rated on-task sleepiness using videos from the cognitive testing sessions. They wired participants for EEG monitoring.
Observer-rated sleepiness was found to be moderately higher in the ADHD group than in controls. Although sleep quality was slightly lower in the sleepy group than in the ADHD group, and symptom severity slightly greater in the ADHD group than the sleepy group, neither difference was statistically significant, indicating extensive overlap.
Omission errors in the SART were strongly correlated with sleepiness level, and the strength of this correlation was independent of ADHD symptom severity. EEG slowing in all regions of the brain was more than 50 percent higher in the ADHD group than in the control group and was highest in the frontal cortex.
Treating the sleepy group as a third group, EEG slowing was highest for the ADHD group, followed closely by the sleepy group, and more distantly by the neurotypical group. The gaps between the ADHD and sleepy groups on the one hand, and the neurotypical group on the other, were both large and statistically significant, whereas the gap between the ADHD and sleepy groups was not. EEG slowing was both a significant predictor of ADHD and of ADHD symptom severity.
The authors concluded, These findings indicate that the cognitive performance deficits routinely attributed to ADHD are largely due to on-task sleepiness and not exclusively due to ADHD symptom severity. We would like to propose a simple working hypothesis that daytime sleepiness plays a major role in cognitive functioning of adults with ADHD. As adults with ADHD are more severely sleep deprived compared to neurotypical control subjects and are more vulnerable to sleep deprivation, in various neurocognitive tasks they should manifest larger sleepiness-related reductions in cognitive performance. One clear testable prediction of the working hypothesis would be that carefully controlling for sleepiness, time of day and/or individual circadian rhythms, would result in substantial reduction in the neurocognitive deficits in replications of classic ADHD studies.
A team of Spanish researchers performed a systematic search of the medical literature and found 28 studies that could be included in a series of meta-analyses of specific measures of sleep impairment. Except for a single meta-analysis with eight studies and 1,713 participants, however, all involved just three to five studies apiece, with anywhere from 121 to just over a thousand participants.
The team examined three sorts of measures:
· Subjective measures, based on self-reporting by ADHD patients.
· Polysomnography is an objective sleep study in which the subject is wired up and studied by technicians in a lab, usually overnight, monitoring multiple body functions, such as brain activity, eye movements, muscle activation, and heart rhythm.
· Actigraphy, a non-invasive objective means of monitoring sleep. The subject wears an actimetry monitor, which is usually worn like a wristwatch on the non-dominant arm. Because it is minimally intrusive, the subject may wear it for a week or more while engaging in normal activities.
In the subjective measures, adults with ADHD generally reported substantially higher sleep impairments than non-ADHD controls. In the largest meta-analysis, covering eight studies and 1,713 participants, adults with ADHD reported moderately longer latency times for falling asleep than controls. In meta-analyses of five studies with between 834 and 1,130 participants, they also reported moderately poorer sleep quality, more frequent night awakenings, being moderately less rested upon awakening in the morning, and moderate-to-strongly greater daytime sleepiness. There was no significant difference in perceived sleep duration.
Polysomnography measures, on the other hand, failed to confirm these subjective impressions. No significant differences were found between adults with ADHD and controls for the initial latency period until onset of sleep, sleep efficiency, waking after the onset of sleep, total sleep time, stage one or stage two sleep, slow-wave sleep, REM (rapid eye movement) sleep, and latency period until REM sleep.
As mentioned above, polysomnography is conducted in lab settings, and therefore inevitably diverges from normal patterns of behavior. Actigraphy helps bridge that gap, by monitoring normal behavior, though with more limited types and precision of data analysis.
And indeed, a meta-analysis of four studies with 222 participants confirmed self-reports that sleep efficiency was moderate to strongly lower in adults with ADHD and that the latency period until the onset of sleep was markedly longer. On the other hand, it found no significant difference in true sleep.
The researchers also looked at prevalence statistics. Whereas the prevalence of sleep-onset insomnia in the general population has been reported in the range of 13 to 15 percent, a meta-analysis of four studies with 466 participants found fully two-thirds of adults with ADHD reporting insomnia, a greater than four-to-one ratio. Similarly, a meta-analysis of three studies with 458 participants found one-third reporting daytime sleepiness, which is twice the rate reported in the general population.
There was no sign of publication bias in any of these results. The authors cautioned, however, about the small number of studies involved, stating this "compromises the generalizability of the findings." Also, some studies included patients undergoing pharmacological treatment for ADHD, "increasing the risk of confounding results."
Moreover, "Sleep onset latency and sleep efficiency were not significantly impaired in the polysomnography, which was incongruent with the actigraphy results. This may be due to a difference in the evaluation context. Whereas polysomnography is considered the gold-standard measure to objectively assess sleep architecture, actigraphy shows a more ecological approach, with the evaluation being conducted in a more naturalistic context for a longer period. However, actigraphy has more environmental influence, which can compromise the data recorded and the interpretation of the results, whereas, in polysomnography, multiple variables can be controlled in the laboratory setting to increase the internal validity of the results. On the contrary, polysomnography studies can produce artifacts due to the unusual circumstances in the setting, so results may need to be interpreted with caution."
The authors concluded, "The results found in the present study show the relevance of addressing sleep concerns in adult populations diagnosed with neurodevelopmental conditions."
We are only beginning to explore how ADHD affects sleep in adults. A team of European researchers recently published the first meta-analysis on the subject, drawing on thirteen studies with 1,439 participants. They examined both subjective evaluations from sleep questionnaires and objective measurements from actigraphy and polysomnography. However, due to differences among the studies, only two to seven could be combined for any single topic, generally with considerably fewer participants (88 to 873).
Several patterns emerged. Looking at results from sleep questionnaires, they found that adults with ADHD were far more likely to report general sleep problems (very large SMD effect size 1.55). Getting more specific, they were also more likely to report frequent night awakenings(medium effect size 0.56), taking longer to get to sleep (medium-to-large effect size 0.67), lower sleep quality (medium-to-large effect size 0.69), lower sleep efficiency (medium effect size 0.55), and feeling sleepy during the daytime(large effect size 0.75).
There was little to no sign of publication bias, though considerable heterogeneity on all but night awakenings and sleep quality.
Actigraphy readings confirmed some subjective reports. On average, adults with ADHD took longer to get to sleep (large effect size 0.80) and had lower sleep efficiency (medium-to-large effect size 0.68). They also spent more time awake (small-to-medium effect size 0.40). There was little to no sign of publication bias and there was little heterogeneity among studies.
None of the polysomnography measurements, however, found any significant differences between adults with and without ADHD. All effect sizes were small (under 0.20), and none came close to being statistically significant.
There were four instances where measurement criteria overlapped those from actigraphy and self-reporting, with varying degrees of agreement and divergence. There was no significant difference in total sleep time, matching findings from both the questionnaires and actigraphy. On percent time spent awake, polysomnography found little to no effect size with no statistical significance, whereas actigraphy found a small-to-medium effect size that did not quite reach significance, and self-reporting came up with a medium effect size that was statistically significant. Sleep onset latency and sleep efficiency, for which questionnaires and actigraphy found medium-to-large effects, the polysomnography measurements found little to none, with no statistical significance.
Polysomnography found no significant differences in stage 1-sleep, stage 2-sleep, slow-wave sleep, and REM sleep. Except for slow-wave sleep, there was no sign of publication bias. Heterogeneity was generally minimal.
One problem with the extant literature is that many studies did not take medication status into account.
The authors concluded, "future studies should be conducted in medicatio- naïve samples of adults with and without ADHD matched for comorbid psychiatric disorders and other relevant demographic variables."
In summary, these findings provide robust evidence that ADHD adults report a variety of sleep problems. In contrast, objective demonstrations of sleep abnormalities have not been consistently demonstrated. More work in medication-naïve samples is needed to confirm these conclusions.
Antidepressants are the primary drug treatment for depressive disorders, which affect 15–20% of pregnant women. They are among the most widely prescribed medications worldwide, and their use has increased in recent decades. Understanding their reproductive safety is critical to support informed, evidence-based prescribing during pregnancy.
A new meta-analysis sheds important light on one of the most debated concerns: whether children born to mothers who took antidepressants during pregnancy face a higher risk of ADHD.
The Study:
Pooling 14 studies covering more than 14 million participants, the analysis found that prenatal antidepressant exposure was associated with a 35% higher rate of ADHD in offspring compared to no exposure. A separate look at SSRIs (the most widely prescribed class of antidepressants, including Prozac and Zoloft) across 11 studies and over four million pregnancies found an even higher apparent risk (44%) after correcting for publication bias. On the surface, these are striking numbers.
Both associations came with an important caveat: enormous variation between individual studies, a statistical red flag suggesting the results may not reflect a true underlying effect. More tellingly, the apparent risk evaporated entirely when researchers applied a more rigorous method — comparing siblings within the same family, where one child was exposed to antidepressants in the womb, and another was not.
This sibling-comparison design is particularly powerful because it automatically controls for factors that run in families: shared genes, household environment, parenting, and socioeconomic conditions. When those influences are held constant, the link between antidepressant exposure and ADHD disappears. The same pattern held for SSRIs specifically.
Two other antidepressant classes, SNRIs (serotonin norepinephrine reuptake inhibitors) and tricyclics, showed no significant association in any analysis.
“Confounding by Indication”:
The probable driver of the initial association is what researchers call confounding by indication. The very condition being treated (depression) is itself a risk factor for ADHD in offspring, independently of any medication. Mothers with more severe depression are also more likely to be prescribed antidepressants, meaning the drug and the underlying illness are difficult to disentangle in standard analyses. Sibling studies cut through this problem cleanly.
The Take-Away:
The authors concluded that the association between antidepressants and ADHD risk was non-significant across all analyses designed to account for these confounding factors. This doesn’t mean antidepressants are without any reproductive considerations, but it does suggest that ADHD risk, at least, is driven by heritable and family-level factors rather than medication exposure itself.
For clinicians and patients weighing the risks of treating or not treating depression during pregnancy, this distinction matters considerably.
Executive functions are the mental processes that allow us to plan, adapt, and follow through. This encompasses working memory, inhibitory control, cognitive flexibility, goal-directed planning, and problem-solving. In people with ADHD, weaknesses in these areas compound the disorder's core symptoms, making it substantially harder to manage complex, real-world demands.
Background:
Medication remains the frontline clinical response. Stimulant medications can meaningfully reduce both executive function deficits and ADHD symptoms, and are often combined with behavioral or psychological therapies for better overall outcomes.
Medication, however, is not entirely without risk of side effects. These risks have spurred interest in new, non-pharmacological alternatives that target the same neural pathways. One of these new therapies is Computerized Cognitive Remediation Therapy (CCRT). This therapy uses digital programs delivered via computer, tablet, or smartphone that train attention, memory, and inhibitory control through structured cognitive exercises. A key feature of many CCRT platforms is adaptive difficulty: tasks adjust in real time to match the child’s current ability, keeping training both challenging and engaging.
The Study:
Despite this promise, the evidence base in younger populations has been limited. This meta-analysis pooled results from randomized controlled trials enrolling participants under 18 who either carried an ADHD diagnosis or scored above the threshold on a validated rating scale. Comparators included no treatment (waitlist), placebo (pharmacological or psychological), or treatment as usual. The primary outcomes (overall executive function and clinical symptom severity) were assessed via questionnaires and neuropsychological testing. Studies including participants with comorbid autism, tic disorders, epilepsy, or other psychiatric conditions were excluded.
The findings were informative, but overall results were mixed. CCRT produced a small but statistically meaningful reduction in inattention symptoms across 13 studies (885 participants), with consistent results across individual trials and no evidence of publication bias. However, it had no detectable effect on hyperactivity and impulsivity (12 studies, 833 participants) or on total ADHD symptom burden (10 studies, 731 participants).
The picture was more encouraging for executive function. Nine studies (500 participants) showed small overall improvements, with specific gains in working memory (454 participants), inhibitory control (428 participants), and planning (6 studies, 335 participants). Emotional control showed no significant change (5 studies, 265 participants), nor did cognitive flexibility (4 studies, 189 participants).
The Take-Away:
Taken together, these results are modest rather than transformative, but context matters. CCRT is low-cost, digitally scalable, and carries negligible side effects. For a population where medication often comes with a significant burden of adverse reactions, even small, reliable improvements in executive function represent a meaningful clinical option.
The evidence positions CCRT not as a replacement for established treatments, but as a practical and well-tolerated addition to the therapeutic toolkit for children and adolescents with ADHD.
Methylphenidate is an effective treatment for ADHD in adults who also have bipolar disorder (BD), but it carries a potential risk of triggering manic episodes. Current guidelines therefore recommend using it only alongside mood-stabilizing medication. A new study using French nationwide claims data sought to test and extend those recommendations with greater statistical power than previous research.
The study built on findings by Viktorin et al. (2017), who observed that adults with BD not taking mood stabilizers had more than a sixfold higher risk of manic events (defined as hospitalization for mania or a new antimanic prescription) within six months of starting methylphenidate. Patients on mood-stabilizing treatment, by contrast, showed nearly half the baseline risk in the first three months. Those findings were limited, however, by small event counts (fewer than 61 manic episodes) and an effect that did not persist beyond the initial three-month window.
To build on this, researchers drew on the French National Health Data System (which is a claims database covering more than 60 million people) spanning 2008 to 2024. The final sample included 6,022 adults with BD (56% women) who had started methylphenidate. Using a self-controlled design, the study compared each patient's rate of manic events in the six months before their first methylphenidate prescription with the rate in the six months after, effectively eliminating stable individual differences as a confound.
Patients were classified as receiving continuous mood-stabilizing treatment if they had been dispensed at least two courses of specific antipsychotics (aripiprazole, olanzapine, or quetiapine) or mood stabilizers (lithium or valproate) in the nine months before starting methylphenidate, including at least one dispensation in the final six months of that window.
The results largely confirmed the earlier findings. Among the 2,745 patients not on mood stabilizers, the rate of inpatient mania diagnosis was 5.1 times higher in the first three months after starting methylphenidate, though this elevation fell to a non-significant level over the subsequent three months. Patients receiving continuous mood-stabilizing treatment showed no statistically significant change in mania risk across the full six-month post-initiation period. A formulation-specific pattern also emerged: patients without mood-stabilizing treatment had a 2.5-fold higher risk associated with extended-release methylphenidate, while no significant risk increase was seen with the immediate-release formulation or in treated patients regardless of formulation.
The authors conclude that methylphenidate at doses below 30 mg does not appear to elevate manic relapse risk when prescribed alongside mood stabilizers. The elevated risk seen in untreated patients, particularly with extended-release formulations, must be interpreted cautiously, given limited statistical power and the likelihood that it partly reflects the natural fluctuation of manic relapse over time. The authors flag this as an inherent limitation of self-controlled survival analyses when studying drug-induced mania, where temporal trends in the underlying condition can be difficult to disentangle from treatment effects.
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