The literature on time perception in individuals with ADHD is extensive but inconsistent, probably reflecting the use of different tasks and performances indexes. A sample of 40 children/adolescents  was engaged in two identical psychophysical tasks measuring auditory time thresholds in the milliseconds (0.25–1 s) and seconds (0.75–3 s) ranges. Results showed a severe impairment in ADHD for milliseconds thresholds (Log10BF = 1.9). The deficit remained strong even when non-verbal IQ was regressed out and correlation with age suggests a developmental delay. In the seconds range, thresholds were indistinguishable between the two groups (Log10BF = − 0.5) and not correlated with milliseconds thresholds. Our results largely confirm previous evidence suggesting partially separate mechanisms for time perception in the ranges of milliseconds and seconds. Moreover, since the evidence suggests that time perception of milliseconds stimuli might load relatively less on cognitive control and working memory, compared to longer durations, the current results are consistent with a pure timing deficit in individuals with ADHD. ADHD children often show deficits in planning, organization and in executive functions, such as response inhibition, interference control, reasoning, hindsight, anticipation and working memory set-shifting2. Even if the literature and the clinical practice indicate an impaired time processing in ADHD, the highly heterogeneous results make it difficult to draw firm conclusions.Along with these deficits, findings suggest perceptual disfunctions related to time processing. Time perception in ADHD has been widely investigated but the results are mixed, probably reflecting the many different methods and performance parameters. Measures of time processing includes accuracy (how far from the target) and/or precision (response variability) measured by motor reproduction, verbal estimation, discrimination, and odd-ball tasks. Moreover, time processing has been investigated across different timing ranges  and across sensory modalities3. Another recent meta-analysis considering 12 studies, despite generally confirming a time deficit in ADHD, suggested that there was a stronger effect size for tasks involving relatively long intervals (5 s) and for specific tasks such as estimation and reproduction4. An example of how the task and the timing range could affect the results comes from the study conducted by Smith et al.5. The authors measured time discrimination thresholds in a sample of ADHD children by asking participants to indicate which one of two audio-visual stimuli, ranging around 1 s, lasted longer. Results revealed higher thresholds (lower precision) in children with ADHD. In contrast, no group differences were found when time processing was measured with a reproduction task or with a verbal estimation task with longer (5 s–10 s) stimuli. Toplak and Tannock6 also measured duration discrimination thresholds in a sample of ADHD adolescents for visual and auditory stimuli and for both short (around 200 ms) and longer (around 1 s) intervals. Results confirmed higher thresholds compared to controls, but across all the tasks. Similar impairments across vision and audition were later obtained by Rubia et al.7 with younger ADHD children and by Dölek et al.8 with adults. Plummer and Humphrey9 measured ADHD children’s timing performance with a motor reproduction task. Children were asked to reproduce, by key press, the duration of visual, auditory, or audio-visual stimuli ranging from 1 to 60 s. Results showed higher errors in ADHD across all the conditions. Radonovich and Mostofsky10 measured ADHD duration discrimination thresholds for short (around 0.5 s) and longer (around 4 s) auditory stimuli. At odds with some of the previous studies, the results showed no deficits for the shorter stimuli but poorer performance for longer intervals. Gooch et al.11 measured auditory time discrimination thresholds in ADHD by asking children to detect which of three sounds was different in duration (odd-one-out task) with stimuli ranging from 400 ms to 1 s. The results revealed higher thresholds (lower precision) in children with ADHD, compared to controls. The same results were obtained with a motor reproduction task for longer visual stimuli (from 2 to 10 s). Barkley12 measured time perception with a verbal estimation and a reproduction task testing the same visual stimuli, lasting from 2 to 60 s. The results revealed poorer time perception (accuracy) for the reproduction, but not for the estimation, task. Two independent studies employing similar visual time intervals found the same pattern of results14.A meta-analysis considering 27 studies on ADHD children and adolescents found a significant timing deficit in ADHD with impairments in both accuracy and precision and across visual and auditory stimuli17. A more recent study using imaging techniques showed that although there are many brain areas encoding both short (milliseconds) and longer (seconds) durations, short durations elicit relatively more activation in the parietal cortex18. The authors suggest that this higher activation reflects a higher involvement of attentional resources when encoding short stimuli. However, the distinction between the use or non-use of attentional control as a function of stimulus duration is not clear-cut and there is also evidence for the involvement of cognitive resources in intervals in the millisecond range, leaving this issue largely open19.Interestingly, psychophysical and pharmacological studies indicate that the perception of relatively long stimuli requires and loads on cognitive control as well as working memory, while relatively shorter intervals (< 1 s) might be automatically processed and targeting a “pure” sense of time20. However, given the heterogeneity of results, further investigation is needed. To this aim, 20 children/adolescents with ADHD were engaged in a testing protocol in which we psychophysically measured auditory time thresholds in the milliseconds (0.5 s) and seconds (1.5 s) ranges. To avoid methodological confounds, the same psychophysical technique  was used for both timing ranges. The performance on these tasks was compared to those obtained from 20 age-matched neurotypical controls. As many studies have found time perception deficits in children and adolescents with ADHD, we expected higher thresholds, on at least one of the timing ranges tested here. As perception of short stimuli has been suggested to depend relatively less on cognitive control and working memory, compared to longer durations, a specific deficit for short stimuli would suggest a pure time deficit.Overall, these and many other investigations suggest a time processing deficit in people with ADHD, with potentially relevant clinical and practical implications21 above 75, no neurological or sensory deficits, no psychiatric comorbidities, no current or past pharmacological treatment. Three children with ADHD met the criteria for a diagnosis of developmental dyslexia. Non-verbal reasoning skills were computed by a combined index of WISC-IV measuring Visual Perceptual Reasoning (IRP). The IQ of four ADHD participants was measured by an external independent institute and, for those participants, we were unable to calculate IRP. ADHD symptoms were measured by Conners Rating Scale (parent version). General clinical symptoms were measured by the Clinical Global Impression—Severity scale (CGI) and the Children Global Assessment Scale (CGAS). Detailed information about the group with ADHD is reported in Table Forty children/adolescents participated in this study: 20 with ADHD  and 20 neurotypical . Individuals with ADHD were enrolled from the Stella Maris Foundation Institute in Pisa, a main center for ADHD care in Italy. ADHD inclusion criteria were: clinical diagnosis of ADHD based on DSM-5, a total intelligence quotient (TIQ), evaluated with the Wechsler Intelligence Scale for Children-IV. Informed parental consent was obtained for each participant before the study. All experiments were performed in accordance with relevant guidelines and regulation.The participants with ADHD were compared to a neurotypical group of age matched children/adolescents. The inclusion criteria for the control group were: no medical history, negative neuro-psychiatric exam and no learning difficulties (reported by parents) and IQ  > 5° percentile. The study was approved by the Ethics Committee of the Meyer’s Hospital Time sensory thresholds were psychophysically measured with an auditory categorization task Fig. A. On eacinclusion indicating how much the data are likely to occur from a model including that specific factor (or interaction), compared to models not including them. By convention, LBF > 0.5 is considered substantial evidence in favour of the alternative hypothesis (difference between groups in this case) and LBF < − 0.5 substantial evidence for the null hypothesis (no difference). Absolute values greater than 1 are considered strong evidence, and those greater than 2 as definitive evidence.Data were analyzed by Repeated Measures Analyses of Variance (RM-ANOVA), Analysis of covariance (ANCOVA), t-test and Pearson correlations and α values corrected for multiple comparisons when necessary (Bonferroni correction). Frequentist statistics were supplemented with Bayesian statistics, calculating Bayes Factors, the ratio of the likelihood of the alternative to the null hypothesis, and reporting them as base ten logarithms . For RM-ANOVA and ANCOVA with report LBF2. Data were analyzed by JASP (Version 0.8.6), SPSS (Version 25) and R (Version 4.0.2) software.To make the ADHD Visual Perceptual Reasoning (IRP) index comparable to the non-verbal reasoning skills measured by Raven matrices on the control group, the indexes were both converted into z-scores . For technical reasons we did not collect data for two participants (one control and one ADHD) in the seconds timing task. Missing data were left empty and excluded analysis by analysis. Effects sizes were reported as Cohen-d and η(38) = 0.035, p = 0.97, d = 0.011, LBF = − 0.52) and male/female ratio . Non-verbal reasoning skills were slightly lower in the group with ADHD (t(32) = 1.8, p = 0.083, d = 0.6, LBF = 0).The ADHD and control groups did not differ in age  = 7.38, p = 0.01, η2 = 0.12, LBFincl = 2.31), suggesting different thresholds across tasks. Crucially the task*group interaction was highly statistically significant  = 18.04, p < 0.001, η2 = 0.29, LBFincl = 2.59) indicating that the groups performed differently across the tasks. Post-hoc analyses confirmed that time thresholds for milliseconds (0.5 s) stimuli were higher in the ADHD group compared to controls (t(38) = 3.98, p < 0.001, d = 1.26, LBF = 1.9). On this task, ADHD thresholds were, on average, almost double compared to controls (Wf = 0.23 and 0.12 for ADHD and controls respectively), indicating a severe impairment. Time thresholds for seconds (1.5 s) stimuli (t(36) = 0.26, p = 0.79, d = 0.08, LBF = –0.5) were statistically indistinguishable between the groups.A RM ANOVA with task  as repeated measures factor and group  as between participants factor, revealed a significant effect of task  = 20.11, p < 0.001, η2 = 0.33, LBFincl = 2.78).To explore the specificity of the impairment found for the time perception task in the milliseconds range, we ran a separate ANCOVA with time thresholds as the dependent variable, groups  as the fixed factor and age, non-verbal reasoning, and sex as covariates. Even when partialling out the effect of these covariates, the result remained unchanged with a significant effect of the group  as independent variable. The results revealed 72.5% of cases correctly classified. The sensitivity was 60% while specificity was 85%. As a sanity check, the same analysis on seconds stimuli thresholds (Wf) provides a near to chance level (53%) classification.partial = 0.367, p = 0.134, LBF = 0.09 ; controls: rpartial = 0.287, p = 0.25, LBF = –0.07).To investigate whether the deficit was stable across the age range, we studied the developmental trajectories. Time thresholds for seconds stimuli had a similar and not significant dependency with age across both groups , suggesting that both were near to a developmental plateau. The developmental trajectories of time thresholds in the milliseconds range were, in contrast, different between the groups. While the controls had reached an almost full developmental stage , the age dependence for participants with ADHD was steeper , suggesting a different developmental trend  and both general , using a random sample of the data , and then computed the correlation between those two measures, across participants. The process was reiterated 1,000 times. We found that mean correlations for milliseconds (0.5 s) and seconds (1.5 s) stimuli were very similar  and not statistically different (bootstrap sign-test p = 0.4). This last control rules out the possibility that the different pattern of results was generated by different reliability levels.It is theoretically possible that the different pattern of results provided by the two time tasks results from different reliability levels. To test this possibility, we measured and compared the reliability of the two psychophysical tasks. Following previous studiesThe paradigm used to measure time thresholds requires the ability to perceive both the stimuli mean and range extremes of the set. The group with ADHD could have had excessive contextual effects, which would have inflated thresholds. To check for this possibility, we measured (on aggregate data) the PSEs and thresholds as a function of the magnitude of the preceding stimulus (N-1). To this aim, separately for the two groups and the two tasks, we sorted the aggregated data into two categories in which the preceding stimulus (N-1) was shorter or longer than the stimulus tested in the current trial. The data were then fitted by psychometric functions providing PSEs and thresholds (Weber fraction). The analyses releveled very small effects on PSEs for both groups , suggesting similar contextual effects. More importantly, for both subdivisions , the difference between groups for thresholds in the milliseconds condition remained evident and constant  = 420.7, p < 0.01, η2 = 0.91) suggesting that PSEs change as a function of the task. Importantly, the task*group interaction was statistically significant  = 5.03, p = 0.031, η2 = 0.01) indicating that the groups performed differently across the tasks. The between factor “group” was not statistically significant  = 2.3, p = 0.13, η2 = 0.06) suggesting that, on average, the two groups performed similarly. To explore the interaction, we ran a series of post-hoc t-tests (α Bonferroni corrected = 0.025). In the range of milliseconds, the analysis revealed no differences between groups (t(38) = 0.91, p = 0.37, Cohen’s d = 0.28). In the range of seconds the group with ADHD, compared to the controls, showed a tendency to overestimate durations (t(36) = 2.03, p = 0.05, Cohen’s d = 0.65).After exploring the differences between groups in terms of sensory precision, we then analyzed estimations accuracy . Time thresholds for relatively longer stimuli (0.75-3 s) were unimpaired. Thresholds did not correlate between each other, and only thresholds for milliseconds durations showed a different developmental trajectory between groups, suggesting a developmental delay in participants with ADHD. Two control analyses ruled out the possibility that the pattern of results was driven by different tasks reliability levels and different use of contextual effects between groups. Consistent with previous studies25 found that administering ethanol impaired auditory temporal discrimination thresholds for long (1 s) but not shorter (50 ms) intervals. A similar pharmacological dissociation was later found by Rammsayer17 showing that auditory temporal processing of long durations (1 s) was significantly impaired by administration of haloperiodol (a dopamine receptor antagonist) and midazolam (benzodiazepine), whereas processing of extremely brief intervals (50 ms) was only affected by haloperidol. The authors suggested that temporal processing of longer intervals is mediated by working-memory functions, while temporal processing of intervals in the range of milliseconds is more dependent on the effective level of dopaminergic activity in the basal ganglia. Psychophysical experiments also supported this differentiation. For example, it has been demonstrated that increasing cognitive load by dual-task procedures deteriorates discrimination thresholds for relatively long (1 s), but not short (50 ms) auditory stimuli, suggesting that the encoding of longer intervals requires cognitive control and working memory, while relatively shorter intervals are automatically processed16. However, is worth mentioning that the link between time perception and cognition remains poorly understood and there is also evidence challenging whether or not cognitive control and working memory play a role merely based on stimulus length. For example, Holm et al.19 found that task cognitive and working memory loads both worsened repetitive motor timing (tapping) for durations in the millisecond range, more than in the seconds range. By a factor analyses approach Rammsayer et al. demonstrated that, while the model assuming two mechanisms underlying the processing of intervals in the seconds and the milliseconds ranges might be more appropriate, these two mechanisms are functionally overlapped, sharing 77% common variance26. Moreover, imaging studies suggest that, in addition to the duration of the stimuli, other factors such as the use of movement to define a temporal estimate and the continuity and predictability of the task may influence the engagement of different timing mechanisms, making the picture more complex than previously thought27.Time is not a unitary concept but encompasses many measurement scales, from a few milliseconds to several days. Even if there is not a defined boundary classifying a duration as “short” or “long”, one of the most classic distinctions is that between milliseconds and seconds stimuli. Clear dissociations have been previously found by pharmacological studies. Rammsayer et al.By showing a specific impairment of auditory time thresholds for relatively short (0.5 s) but not longer (1.5 s) intervals in ADHD, the current results fit well with the idea of different mechanisms for those regimes. The null correlation between thresholds across the two-timing regimes is also consistent with this hypothesis. Given that ADHD is often associated with deficits in cognitive control and working memory, it seems counterintuitive that timing thresholds for automatic, but not those under cognitive control, were impaired in our sample with ADHD, suggesting a pure time perception deficit. Leaving aside whether or not cognitive resources are engaged depending on the duration of the stimuli, an issue that has not been directly tested here, the current results (together with much previous evidence) are difficult to explain, suggesting a unique system for timing perception.10. In that study the authors measured auditory discrimination thresholds in controls and in children/adolescents with ADHD with short (550 ms) and longer (4 s) intervals and their results demonstrated worse thresholds for long but not short intervals. Although we do not have a definitive explanation to account for this difference, the different tasks could, even partially, account for that. The paradigm used by Radonovich et al. presented two pairs of tones, one with fixed delay and the other with variable delays, and participants were asked to report whether the second delay was shorter or longer than the first. Our paradigm required the presentation and categorization of a single tone. We find it reasonable to speculate that the Radonovich et al. task, compared to the task used here, would charge relatively more additional resources such as working memory and/or attention, which may account for the different pattern of results.It is worth noting that our results are opposite to those found by Radonovich et al.28 compared auditory time discrimination thresholds between controls and patients with focal lesions in the frontal cortex or in the cerebellum. The results indicate that frontal lesions impaired timing thresholds for long (4 s) but not short (0.4 s) intervals, while cerebellar lesions impaired both. Harrington et al.29, however, cast doubts on the involvement of the cerebellum in the auditory time perception of milliseconds intervals , with patients with cerebellar lesions showing similar thresholds compared to controls. On the other hand, cerebellar lesions have been demonstrated to have detrimental effects on visual time thresholds for longer (8–21 s) stimuli30. As mentioned before, basal ganglia have also been found to play a role in time perception. Gouvêa et al.31 trained rats to categorize sounds as belonging to a long or short category. Animals made few errors when categorizing the shortest and longest intervals (the extremes), but performance become worse for intervals near to the 1.5 s categorical boundary (range: 0.6–2.4 s). Recording from populations of single striatal neurons, the authors found cells firing at different times within the interval period, suggesting the existence of short and long preferring neurons. The causal role of striatal neurons was also demonstrated by injecting muscimol. As a result, the duration thresholds worsened significantly, compared to the control group injected with saline. The parietal cortex has also been shown to play a critical role in time perception35. Hayashi et al.36 correlated time discrimination thresholds measured in a sample of neurotypical adults, with gray matter (GM) volume in different parts of cortical and subcortical areas. Results showed that GM volume in the cerebellum but not in the parietal cortex correlated with milliseconds stimuli thresholds whilst, contrarily, GM volume in the parietal cortex but not in the cerebellum correlated with seconds stimuli thresholds. Moreover (as in the current study) threshold for milliseconds and seconds stimuli did not correlate with each other. In the same line, a meta-analysis of imaging studies also suggests that the parietal cortex, compared to the cerebellum, is more likely activated by seconds stimuli27. With the current psychophysical data, we cannot say much about the brain networks involved in milliseconds and seconds timing, but our findings are largely in line with the idea that those two functions engage distinct neural mechanisms.Regarding brain areas involved in the perception of milliseconds and seconds intervals, the literature, despite suggesting different networks, is not definitive. Mangles et al.Another interesting point emerges from the current results. The analysis of developmental trajectories Fig. A suggest38. Our results are in line with this idea. In the task testing durations in the seconds range, participants with ADHD provided more "long" judgements compared to controls, leading to a leftward shift of the psychometric curve. This bias indicates a duration overestimation, probably arising from a faster internal clock. In the task testing durations in the milliseconds range, there was no difference between groups, reinforcing the idea of partially independent mechanisms for short (ms) and longer (secs) intervals and replicating previous evidence37.Together with a sensory precision deficit, the existing literature has also shown that people with ADHD are more likely, compared to neurotypicals, to commit overestimation errors, suggesting a faster “internal clock”39, it would be interesting and potentially relevant to test whether both clinical conditions also share a similar pattern of deficits in time perception.A precise timing perception in the millisecond scale is crucial in perceiving and acting on the continuously changing environment. It has been suggested that this ability is automatic and allows complex human behaviours including speech perception and speech performance, music, driving, and many sports. The results of this study showed that children and adolescents with ADHD have a severe precision (thresholds) deficit in the duration perception of milliseconds (around 0.5 s) auditory stimuli. Time perception for relatively longer and more cognitively controlled stimuli was unimpaired. Although, with the current results, we cannot explain why the temporal perception of short stimuli is impaired in our sample with ADHD, it is surprising how such a simple and fast (4-min) psychophysical test succeeds in differentiating the two groups (LBF = 1.9). Moreover, while timing thresholds had a relatively low sensitivity power (60%), they turned out to have a good specificity (85%) level and were able to correctly classify 72.5% of cases. Finally, the timing thresholds deficit was resistant to the statistical controls of general but important covariates such as age, sex and non-verbal IQ, promoting it as a potential easy-to-administer tool for future studies. A better comprehension of time perception abnormalities in ADHD may give new insights in the neurological bases of the disorder. Furthermore, it may have relevant diagnostic and treatment implications. Understanding the functional consequences of these specific deficits in everyday life, in combination with other ADHD symptoms (i.e. impulsivity), may help to focus interventions on more specific goals, improving the clinical care of youth with ADHD. Moreover, as ADHD and autism might represent a continuum, sharing many pathophysiological features


P = 0.31) and high  Hgb levels. The mechanisms underlying this U-shaped association may include decreased plasma expansion during pregnancy and/or iron dysregulation resulting in placental disease. Further research is needed to explain the observed U-shaped relationship, to guide iron supplementation in pregnancy and to minimize the risk of LBW outcomes.Low birth weight (LBW) is associated with a higher risk of neonatal mortality and the development of adult-onset chronic disease. Understanding the ongoing contribution of maternal hemoglobin (Hgb) levels to the incidence of LBW in South Asia is crucial to achieve the World Health Assembly global nutrition target of a 30% reduction in LBW by 2025. We enrolled pregnant women from the rural Tangail District of Bangladesh in a Maternal Newborn Health Registry established under The Global Network for Women’s and Children’s Health Research. We measured the Hgb of pregnant women at enrollment and birth weights of all infants born after 20 weeks gestation. Using logistic regression to adjust for multiple potential confounders, we estimated the association between maternal Hgb and the risk of LBW. We obtained Hgb measurements and birth weights from 1,665 mother–child dyads between July 2019 and April 2020. Using trimester-specific cutoffs for anemia, 48.3% of the women were anemic and the mean (±SD) Hgb level was 10.6 (±1.24) g/dL. We identified a U-shaped relationship where the highest risk of LBW was seen at very low (< 7.0 g/dL, OR = 2.00, 95% CI = 0.43–7.01,  Inadequate iron stores at the start of pregnancy place women at risk for the development of iron-deficiency anemia.Here, we report findings on the association of maternal Hgb with risk of LBW from an ongoing Maternal and Newborn Health Registry. It is important to further clarify the relationship between anemia and LBW in Bangladesh to bolster progress toward meeting the global nutrition target of a 30% reduction in LBW by the year 2025.,This was a population-based study that is part of the National Institute of Child Health Global Network Maternal Newborn Health Registry (MNHR)  MNHR is a multisite, prospective, ongoing, and active surveillance system that is tracking pregnancies and births in defined geographic communities (clusters), each with approximately 300–400 deliveries per year. The Bangladesh site is located in the Tangail District of Bangladesh and is composed of 12 study clusters each with 17,500–19,500 people. Through a bimonthly house-to-house surveillance, pregnant women were identified and 99.7% of all eligible pregnant women were enrolled upon providing consent to participate. Mother–child dyads were followed up at birth (within 72 hours) and at 42 days postpartum for collection of maternal and newborn outcomes. Details of the registry are described elsewhere.LBW, the main outcome variable, was dichotomized as yes = 1  or no = 0 (otherwise). Birth weights were obtained in the field by trained personnel using an AWS H-110  digital hanging scale, calibrated daily. A large number of newborns in this region of Bangladesh are born at home or in small healthcare facilities, which presents a major challenge to collecting accurate birth weight information.Blood Hgb, the main explanatory variable, was collected in the field by trained personnel using a point of care hemoglobinometer . The HemoCue 301 analyzer has shown moderate agreement of Hgb level estimation when compared with the gold standard hematology autoanalyzer.,,,N = 1,665) and the group with missing key variables (N = 316). All variables found to have an association with the LBW outcome of interest on univariate analysis were included in this exploration and presented in Table The sociodemographic and obstetric characteristics were considered as explanatory variables of occurrence and nonoccurrence of LBW in newborns. The selection process to identify these explanatory variables drew on a range of studies carried out to assess the magnitude of LBW and to identify its determinants.t-tests as appropriate. In bivariate analysis, we used χP < 0.1) were included in a multivariable binomial logistic regression. A P value of < 0.05 was considered significant when interpreting associations identified by the multivariate analysis. Finally, we used a LOESS to visualize the relationship between maternal Hgb concentration and probability of LBW.Data were entered and calculated fields were determined at the study site before secure transmission to the central data center  where further data quality checks were performed before statistical analyses. Maternal characteristics were examined using descriptive statistics. Crude associations between maternal characteristics and LBW were assessed using χhttps://cran.r-project.org/). The MNHR study was reviewed and approved by the ICDDR,B’s  Research Review and Ethical Review Committees and the Institutional Review Boards of the corresponding U.S. partners . All women provided informed consent before participation.All statistical analyses were conducted in R . Maternal sociodemographic and obstetric characteristics are displayed in Table P = 0.0362). A LOESS plot of Hgb versus LBW revealed a U-shaped relationship with the lowest risk of LBW associated with Hgb concentrations between 9.0 and 11.0 g/dL .Infant birth weight outcomes by maternal Hgb category are displayed in Table P = 0.0385). Although the sample size was too small to reach statistical significance, a Hgb level < 7.0 g/dL was associated with a 2.7-fold risk of LBW . Moderate anemia was not significantly associated with LBW outcomes.In bivariate analysis, maternal BMI, age, education, socioeconomic status, sex of the infant, mode of delivery, inter-delivery interval, and type of household fuel were also associated with LBW status Table . RecogniN = 11) in this category. The prevalence of maternal anemia in Bangladesh is higher in this cohort than the global average previously described by the WHO, 48.3% versus 42% globally.The results from this study suggest that high maternal Hgb concentration (> 13 g/dL) is associated with a 2-fold increase in risk of LBW. On the other end of the spectrum, severe anemia (Hgb < 7 g/dL) may be associated with a similar risk of LBW but the relationship in this cohort was not significant likely due to small numbers  of eligible maternal–child dyads were excluded from this analysis due to missing key variables. Given the major challenges to obtaining these variables in a rural setting with limited antenatal care and a large number of home deliveries, the current study performed well when contrasted to comparable studies where as many as 71% of newborns show no birth information.The bimonthly house-to-house surveillance, and enrollment of eligible pregnant women into the MNHR highlights both a strength and a limitation of this study. Although the registry achieves an almost 100% catchment and enrollment of pregnant women in this rural area, a considerable number  were associated with an increased risk of neonatal LBW. These findings suggest that iron-deficiency anemia may not be a significant contributor to the high rate of LBW seen in this population. Further research is needed to understand the U-shaped association of maternal Hgb with LBW outcomes, particularly the biological mechanism underlying the association between adverse outcomes and high maternal Hgb values. Understanding this association will give further guidance to the benefits and possible dangers of routine universal iron supplementation during pregnancy.


To assess the profile of Sleep pattern, Psychiatric comorbidity and problematic electronic gadget use and explore demographic factors and correlations in children and adolescents with ADHD and Autism.Hypothesis: There are statistically significant problems and associations across sleep pattern, psychiatric comorbidity and gadget use in children and adolescents with autism and ADHD.Literature highlights increasing global trends and emerging concerns over the problematic use of electronic gadgets and sleep related problems in children and adolescents with autism and ADHD. There is sparse literature on the profile of sleep patterns, psychiatry comorbidity and problematic gadget use in children and adolescents with autism and ADHD from developing countries.This was an observational study conducted at the Child and Adolescent Psychiatry Clinic, Department of Psychiatry at a tertiary care Institution under the STS ICMR Project 2019 with Institutional Ethics Clearance. Apriori Sample size calculated was 70. Children and adolescents diagnosed with autism or ADHD as per ICD 10 criteria, fulfilling the inclusion criteria and willing to participate in the study were included. Informed consent was obtained from caregivers. Sleep Disturbance Scale for Children, Self Designed Parent based Problematic Electronic Gadget Use Scale, Vanderbilt ADHD scale, Indian scale for Assessment of Autism and the Child and Adolescent Psychiatry Clinic structured Performa were the tools for data collection. The results were analyzed with descriptive tests, chi square test and multiple logistic regressions using SPSS.Mean age of the sample was 9.1 years and majority (57%) were boys. Forty nine patients had ADHD and 21 patients had Autism. Problematic gadget use was higher in children ranging from 6 to 15 years of age and 12.8% had severe levels of problematic gadget use. 34.3% patients experienced severe problems in initiating and maintaining sleep. Oppositional-Defiant disorder was the most common comorbidity, predominantly inattentive type (76.4%) was the most common subtype of ADHD and mild autism (54.3%) was the most common type of autism in the sample. There were statistically significant associations (p < 0.05) between age and gadget use; hyperactive subtype of ADHD and problems with initiating and maintaining sleep and ADHD subtype, sex profile and problematic gadget use.We conclude that sleep problems, psychiatric comorbidity and problematic gadget use are prevalent with statistically significant associations in children and adolescents with autism and ADHD as per our study findings. Our study has relevant clinical, research and policy implications.


Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental condition characterized by attention problems, excessive physical activity, and impulsivity. ADHD affects not only the patients but also their families. The development and use of technologies such as virtual reality (VR), augmented reality (AR), and mixed reality (MR) for ADHD has increased over recent years. However, little is known about their potential usefulness. This overview aimed to clarify the current knowledge about the use of these three innovative technologies for the diagnosis and treatment of children with ADHD.This overview was conducted using the PubMed, Web of Science, and Scopus databases until January 24th, 2021. The following descriptive information was compiled from the identified studies: country, year of publication, sample size, study design, ADHD diagnosis methods, applied technology, hardware equipment, clinical target, and main findings.n = 22, 73%). Regarding the applied technology/hardware equipment, VR , head-mounted displays , VR-based continuous performance tests (VR-CPT)  were most frequently used. Most studies  used the DSM criteria for the diagnosis of childhood ADHD. They primarily evaluated the utility of these technologies in assessing ADHD symptoms  and improving the ADHD diagnostic process .The initial database searches yielded 409 articles, but 103 were removed as duplicates. Eventually, 30 eligible studies remained for analysis, the majority of which were case-control (This comprehensive overview evaluated the studies on the use of VR, AR, and MR technologies for children with ADHD. These technologies seem to be promising tools for improving the diagnosis and management of ADHD in this population.The online version contains supplementary material available at 10.1186/s12888-021-03632-1. Attention deficit hyperactivity disorder (ADHD) is a prevalent mental disorder in children and adults  with itsADHD causes primary and secondary complications such as a lack of self-confidence, relationship maladjustment with friends, and incompatibility with social and academic environments , 8. It iMedication and cognitive-behavioral therapy (CBT)  are the Recently, technological advancement has enabled the use of mobile phone applications, telemedicine, computer/mobile games, continuous performance tests (CPT), virtual reality (VR), and augmented classroom simulators for ADHD diagnosis and treatment –23. VR iAugmented reality (AR) is a subset of VR consisting of real-world features, digital information, and elements that enable users to interact with virtual objects and view the physical environment , 28. VR Several studies have indicated that VR and AR tools are remarkably effective in the promotion of general health, mental health treatment, and diagnosis , 35. VR,These technologies provide a virtual environment that allows individuals to experience various situations that may be difficult or even impossible to deal with in reality; as such, they are more effective and safer than traditional treatments . In thesVR, AR, and MR technologies are particularly effective with the design of attractive virtual environments that engage and increase users’ attention. Several studies have explored the use and effectiveness of VR, AR, and MR technologies in the treatment and diagnosis of children with ADHD –46. ThisFirst, we searched for relevant articles on ADHD published until January 24th, 2021, and available on PubMed, Web of Science, and Scopus. The articles were retrieved using various keywords, including  OR  OR ) AND ((attention deficit hyperactivity disorder) OR (ADHD)). The terms included in the search based on the PICO guideline are presented in Table Articles were selected in accordance with the PICO guidelines as follows: P-population (children and adolescents aged 4–18 years diagnosed with ADHD), I-intervention (using VR/AR/MR for ADHD diagnosis and management), C-comparison (VR/AR/MR intervention group vs. control group or groups before and after VR/AR/MR intervention), and O-outcome (the main outcomes of VR/AR/MR interventions).The inclusion criteria were being written in English, with a focus on VR, AR, or MR in ADHD patients, and recruiting patients younger than 18 years. Publications were excluded if they reported no data on VR, AR, and MR outcomes, if they were unavailable in full text, and if they were reviews, abstracts, notes, protocols, letters, or editorials,Two independent reviewers (Saeideh Goharinejad and Samira Goharinejad) assessed the methodological quality of the studies based on the Joanna Briggs Institute (JBI) . The JBIInitially, 409 articles were retrieved from the aforementioned databases. After eliminating 103 duplicates, 306 articles remained, the titles and abstracts of which were screened by two authors independently (Saeideh Goharinejad and Samira Goharinejad). Disagreements were resolved by consulting a third author (Sadrieh Hajsmaeel-Gohari). At this stage, 250 articles were also eliminated as they did not meet the inclusion criteria. Following that, the full texts of the remaining 56 articles were screened by two authors independently (Saeideh Goharinejad and Samira Goharinejad), and 26 articles were eliminated based on the exclusion criteria. Finally, 30 articles were selected for the final review , the United States , and Israel, Korea, and China  , 10 (33%) in 2020, four in 2018 and 2019 (13%), and three between 2009 and 2016 (10%) , while two studies did not specify the gender of the participants. The number of the studied patients varied from case studies  to larger samples of > 100 patients   were case-controls, three (10%) were cross-sectional, two (7%) were case studies, two (7%) were quasi-experimental, and one (3%) was a randomized controlled trial Table .n = 21; 70%). Three studies (10%) did not mention the method of ADHD diagnosis. In the remaining studies, inclusion in the ADHD group was based on interviews with parents and children, parental confirmation, or psychiatrists’ and clinical centers’ diagnoses  in most of the studies n = 1; 70%. Tn = 19; 63%), while others used different 3D glasses, computers, headsets, motion sensors, and robots  utilizing VR, two studies used AR  and only one study employed MR . Notably, these studies used a VR classroom continuous performance test (VR-CPT) , a VR classroom (VRC) environment , games , web-based VR , and an AR robot   . These studies included improving concentration  by cognitive therapy [n = 2; 6%) [n = 1; 3.%) using these technologies [The clinical objective of 10 studies (33%) was to evaluate the utility of these technologies in assessing ADHD symptoms, while seven studies (23%) focused on improving the ADHD diagnostic process Fig. . In the  therapy , 62, 76, therapy , memory  therapy , and con therapy , These s therapy , 77, and therapy . In addi= 2; 6%) , 72 and n = 28; 93%) reported that using VR/AR/MR tools helped meet at least one of the clinical objectives of the study. Six of the seven studies (86%) regarding the efficacy of VR/AR/MR technologies in diagnosing ADHD found these technologies to be helpful. Similarly, eight of the nine studies (83%) assessing the ability of these technologies to manage ADHD symptoms found they were beneficial. Using VRC technology, Blume [Most of the reviewed studies  had a fair quality, and only two studies (7%) implied low/moderate quality. On the other hand, most of the studies , especially case-control and cross-sectional studies, had limitations such as not evaluating the confounding factors and strategies to manage these factors.Additional file Recently, VR, AR, and MR technologies have become increasingly accessible to medical researchers seeking to improve diagnostic, therapeutic, and preventive measures for patients with mental disorders , 79. In According to our findings, VR-, AR-, and MR-based tools can be developed to improve the diagnosis and treatment of children with ADHD. Most of the reviewed studies (90%) revolved around the use of VR. Since MR technology is still in the developmental stages, most of the studies concerning its use are generally descriptive and published in lower-ranking academic journals as opposed to the studies concerning VR and AR . OverallIn total, 21 of the reviewed articles (70.0%) focused on the use of VR-CPT, with the first study published in 2007. In contrast, the studies regarding the application of AR and MR for this population have mostly been published in 2020. VR has been incorporated in some neuropsychological tests. Notably, VR-CPT is the most widely used non-traditional tool to diagnose and manage the symptoms of ADHD , 69. In Given the subjectivity of ADHD interviews and ADHD behavior rating scales, additional and more objective assessment of childhood ADHD has been recommended . UnfortuSeveral studies have concluded that VR-CPT technology is more efficient than traditional CPT in the treatment of children with ADHD , 55, 57.VR-based treatments may also have additional advantages over traditional interventions . For insBased on the findings, cost-efficient HMDs are the most frequently used hardware with VR, AR, and MR technologies . CompareBesides the merits of the reviewed studies, some of them mentioned limitations as well. First of all, the sample size of patients with ADHD in studies must be expanded to draw more accurate conclusions about the effectiveness of these technologies , 51, 58.As the search strategy was mainly focused on the titles and abstracts of relevant articles, some relevant studies may have been missed. In addition, it was not possible to access the full text of six articles, and they were excluded from the study. Potentially relevant non-English articles were excluded as well.According to the results of the reviewed studies, VR and AR technologies could be used as effective assessment tools to better assess ADHD symptoms and to improve the diagnosis of ADHD in children. Ample evidence also suggests that VR technology could augment traditional treatment options, thereby promoting their effectiveness in the management of ADHD symptoms.Additional file 1.


Understanding current levels, as well as past and future trends, of the percentage of infants born at low birthweight (LBW) in the United States is imperative to improving the health of our nation. The purpose of this study, therefore, was to examine recent trends in percentage of LBW, both overall and by maternal race and education subgroups. Studying disparities in percentage of LBW by these subgroups can help to further understand the health needs of the population and can inform policies that can close race and class disparities in poor birth outcomes.Trends of percentage of LBW in the U.S. from 2003 to 2018, both overall and by race/ethnicity, and from 2007 to 2018 by education and race by education subgroups were analyzed using CDC WONDER Natality data. Disparities were analyzed using between group variance methods.Percentage of LBW experienced a significant worsening in the most recent 5 years of data, negating nearly a decade of prior improvement. Stark differences were observed by race/ethnicity and by education, with all subgroups experiencing increasing rates in recent years. Disparities also worsened over the course of study. Most notably, all disparities increased significantly from 2014 to 2018, with annual changes near 2–5%.Recent reversals in progress in percentage of LBW, as well as increasing disparities particularly by race, are troubling. Future study is needed to continue monitoring these trends and analyzing these issues at additional levels. Targets must be set and solutions must be tailored to population subgroups to effectively make progress towards equitable birth outcomes and maternal health.The online version contains supplementary material available at 10.1186/s12889-021-11185-x. The percentage of infants born at low birthweight (LBW), or the percentage of live births where the infant weighed less than 2500 g, is an important population health outcome measure, reflecting both maternal health and infant health. LBW can serve as a reference for both current and future health of society’s youngest age group, serving as a predictor of premature mortality risk as well as morbidity over the child’s life course –3. ChildFor these reasons and numerous more, understanding current levels, as well as past and future trends, of percentage of LBW in the United States is imperative to improving the health of our nation. As a measure, percentage of LBW has its limitations, including relying on a relatively arbitrary weight cut-off and resulting from a multitude of upstream factors, some of which are expressly negative as mentioned above and some of which may be positive such as improvements in treating infertility or monitoring at-risk pregnancies. Yet, it remains a useful marker of population health. While there are groups that track and analyze trends in percentage of LBW in the United States –13, therData on percentage of LBW and maternal characteristics were collected from the CDC WONDER Natality files using single-year estimates, from 2003 to 2018 . NatalitTrends in percentage of LBW were examined with joinpoint, or segmented, regression modeling methods using the National Cancer Institute’s Joinpoint Regression Program version 4.6.0.0 . This isSince parity is inherently a comparative concept, choice of disparity metric is important, subjective, and reflects normative values and judgments . In ordeSecondary analyses examined trends for very low birthweight (VLBW), or the percentage of live births where the infant weighed less than 1500 g, to understand if the LBW cut-off of 2500 g strongly affected results. Multiple births, or babies born as twins, triplets, quadruplets, quintuplets, or higher, were also analyzed to understand outcomes and trends in this seldom-studied group. Additional analyses examined trends by advanced maternal age, defined by births from mothers aged 35 years and older, to understand if findings differ for mothers who choose to have children later in life or are more likely to use in vitro fertilization, both of which are associated with smaller infants , 21. AllTable Looking at trends by maternal race Fig. , percentExamining trends by maternal education Fig. , percentThe data were then further broken down into twenty mutually exclusive, race by education subgroups Fig. . PercentBGV trends are shown in Fig. When these analyses were restricted to percentage of VLBW, similar patterns of trends were observed with the exception of slightly decreasing racial disparities, potentially due to decreasing percentage of VLBW in more highly educated Black mothers  may play a role in this worsening trend and increasing racial disparities –24. For  may playWhile the focus of this study was on the relative disparities between race, education, and race by education subgroups, differences in the absolute occurrences of infants born at LBW are also important to consider as they represent the burden on the population. As an example, data showed that despite having less than half the LBW rate of Black mothers (5.3% vs 11.7%), White mothers accounted for close to twice as many absolute infants born at LBW , many more of which were to the highest educated Whites as compared to the lowest educated Whites . The wide-ranging consequences of LBW that burden the social service, education, and health care systems – from infant mortality to growth and cognitive problems in early life, to hypertension, diabetes, and cardiovascular disease later in the child’s life – highlight the fact that both rate and burden are valuable considerations for population health outcomes, and each deserve research and policy attention .There are several important things to note when reflecting on the findings of this study. For instance, due to changes in data collection, fewer years of study were able to be analyzed for the education subgroups. Furthermore, as an outcome measure, LBW has its limitations. This outcome measure was chosen for this study because of its reflection of infant and maternal health, its understandability to policy makers, and the quality and availability of its data at many levels. However, the defined cut-off for LBW at < 2500 g is somewhat arbitrary. Researchers have also called attention to assumptions widely held by the public health community about LBW, such as its utility as a marker of population health and, specifically, infant mortality risk. This study did not explore trends in other related measures of birth outcomes, such as preterm birth, small for gestational age, or infant mortality, which themselves have analytic limitations but could offer a refined understanding of and specific focus on perinatal risk .Additionally, disaggregating birthweight data by subgroups such as race/ethnicity or education groups can pose some issues. For example, babies may have differing birthweight distributions according to the ethnic origin of the mother, such as babies born to Asian mothers who tend to be smaller, which may misclassify them as at risk of increased morbidity , 36. TheFinally, it is possible that the worsening trends in percentage of LBW detected in the current study could be due, in part, to additional, extraneous reasons that are less critical from a population health perspective. For example, increases in multiple births (in part due to the increased use of in vitro fertilization), women choosing to have children later in life, greater insurance coverage of infertility treatment, and improvements in technologies used to monitor and improve outcomes for at-risk pregnancies are all associated with smaller infants , 37–40. Continued monitoring of recent trends is needed to see if they are temporary or representative of a persisting reversal of the progress made in reducing percentage of LBW over more than a decade. It is also important for future studies to analyze these trends and disparities at a finer grain geography, such as the state level, to understand whether these trends hold true across all states, or manifest in particular states or regions. Supplementary research could also be valuable in further exploring the under-studied population of multiple birth infants and how types of fertility treatment may impact these findings, with newly available information offered in CDC WONDER’s Natality Files starting with the year 2016. Furthermore, initiating some target-setting practices would be recommended to understand and communicate what we need to do as a country in order to embark on a path towards better health for our mothers and infants. It should be noted that the three different trend components in Fig. The percentage of infants born at low birthweight (LBW) as a measure effectually reflects the population health experience of society, representing maternal health and both current and future child health. Therefore, understanding current levels, disparities within the population, as well as past and future trends of percentage of LBW in the United States is imperative to improving health for all in our nation. This study showed that trends in percentage of LBW significantly worsened in the 5–6 years leading up to 2018. This recent rise directly nullifies the improvement our nation experienced in the previous decade. Race and class disparities in percentage of LBW have also been on the rise in recent years, further separating the divide between advantaged and disadvantaged groups. These increasing disparities are directly in conflict with achieving population health and equity in the U.S. Balancing considerations of both rate and burden for LBW is also essential for research and policy. Finally, this study has implications for future research. We must continue to monitor these trends, understand how they are playing out across the country, incorporate measurement of upstream drivers, and set targets for our nation in order to effectively make progress towards equitable birth outcomes and maternal health.Additional file 1. Data and Trends for LBW, VLBW, Advanced Maternal Age, and Multiple Births by Maternal Race, Education, and Their Combination, United States, 2003–2018. An additional file is provided, entitled ‘Additional File 1.xlsx’, containing the datasets supporting the conclusions of the article. The first sheet entitled ‘LBW Data’ includes the number of infants born at low birthweight, the total number of births, and the percentage of infants born at low birthweight overall, by race/ethnicity, by education, and by race and education subgroups for the years under study. The second sheet entitled ‘VLBW Data’ includes the same information for infants born at very low birthweight. The third sheet entitled ‘VLBW Trends’ includes the trend period years and annual percent changes for all groups and between group variances for infants born at very low birthweight. The fourth sheet entitled ‘AMA Data’ includes the number of infants born at low birthweight, the total number of births, and the percentage of infants born at low birthweight overall, by race/ethnicity, by education, and by race and education subgroups for mothers greater than or equal to 35 years of age and for mothers less than 35 years of age. The fifth sheet entitled ‘AMA Trends’ includes the trend period years and annual percent changes for all groups and between group variances for infants born at low birthweight for mothers ages 35 and over and for mothers less than age 35. The sixth sheet entitled ‘Multiples Data’ includes the number of infants born at low birthweight, the total number of births, and the percentage of infants born at low birthweight overall, by race/ethnicity, by education, and by race and education subgroups for multiple birth infants. Finally, the seventh sheet entitled ‘Multiples Trends’ includes the trend period years and annual percent changes for all groups and between group variances for multiple birth infants born at low birthweight.


Attention-Deficit/Hyperactivity Disorder (ADHD) is the most common neurodevelopmental disorder diagnosed in children. Questions regarding its increased diagnostic rates and pharmacological treatments in developing children have led to a more holistic review of the multi-system pathophysiology observed in ADHD. The dopaminergic neurotransmitter system, known for its influence on reward-motivated behaviors and motor control, and the frontostriatal systems, that mediate motor, cognition, and behavior, are associated with ADHD’s development. However, studies have shown that these neural systems do not wholly account for ADHD’s multilayered and heterogeneous symptom presentation. For instance, the literature suggests that emotional dysregulation, the inability to regulate one’s emotional responses to provoking stimuli, is associated with increased risk for social impairment in ADHD. A broader examination of physiological systems in children with ADHD has found potential markers in the heart-brain and gut-brain axes that correspond with certain behaviors associated with emotional dysregulation in recent studies. Hence, the purpose of this meta-analysis is to aggregate ten applicable published case studies and analyze task-related heart rate reactivity  and gut microbiota (n = 5 studies) data in children with and without ADHD. Data from a total of 531 youth with ADHD and 603 youth without ADHD revealed significant small and medium effect sizes for higher Chao1 levels and Actinobacteria levels in the ADHD group, respectively, but no evidence of altered task-related HRR. Thus, further research into multi-system psychophysiological measures of emotional dysregulation and ADHD is warranted. The clinical, empirical, and educational implications of these findings are discussed.https://www.crd.york.ac.uk/prospero/, identifier PROSPERO (CRD42021236819). Attention-Deficit/Hyperactivity Disorder (ADHD) is one of the most commonly diagnosed childhood neurodevelopmental disorders , with anCurrent hypotheses concerning the etiology and maintenance of ADHD, in addition to genetic factors, propose underlying metabolic and neuropsychological pathology, such as omnigenic  and environmental  factors. The cardiovascular system has also been indicated in regulating and mediating the autonomic stress system and the brain . This stRecommendations for the diagnostic evaluation of ADHD include a comprehensive interview addressing the child or adolescent’s developmental, medical, and psychosocial history, including academic performance, peer relations, and family functioning . Other cStill, there are significant issues associated with current diagnostic processes. Comprehensive evaluations for ADHD can be time-intensive and costly, often requiring upwards of five to eight hours of testing and thousands of dollars . A primaSuch findings regarding the discrepancies in diagnostic and treatment rates of ADHD have highlighted concerns surrounding the clinical process, including the appropriateness of intelligence testing and its application among non-European/Caucasian individuals , and theHistorically, ADHD has been treated with potent psychostimulants such as methylphenidate or amphetamine , 28. WhiPsychotherapy is frequently implemented in conjunction with medication. Behavioral therapy treatments often help children navigate peer relationships, which can be impaired by difficulties with emotional self-control . Organizvia the sensory systems and internal stimuli within the body via afferent autonomic nervous system activity and neuroendocrine pathways  axis  axis . Stress PA) axis .Abnormal diurnal cortisol patterns and acute cortisol reactivity indicating altered HPA axis functioning have also been associated with many adverse behavioral health problems, including impulsivity . For insGiven the arousal system’s effect on the heart and stimulant medication’s alteration of ANS activity , researcIn a recent literature review of 35 studies assessing cardiac functioning in children and adults with ADHD, 20 studies examining resting heart rate provided inconclusive results: six reported lower resting heart rate levels, two reported higher resting heart rate levels, and the remainder found no group differences between people with ADHD and those without ADHD . Howevervia the gut’s ability to synthesize neurochemicals and their precursors , PsycInfo (MJC), ProQuest Dissertations and Theses (TGC), and Web of Knowledge/Web of Science (JMB) databases from January 2021 to April 2021, using the following search terms for gut microbiota studies: (“attention deficit hyperactivity disorder” OR “attention deficit disorder” OR “ADD” OR “ADHD”) AND (child* OR adolescen* OR infant OR pediatric OR youth OR teen*) AND . The second outcome measure of this meta-analysis was heart rate reactivity. The following search terms were used to identify the relevant studies: (“attention deficit hyperactivity disorder” OR “attention deficit disorder” OR “ADD” OR “ADHD”) AND (child* OR adolescen* OR infant OR pediatric OR youth OR teen*) AND (“heart rate reactivity” or “heart rate responsivity” or “H.R. reactivity” or “H.R. responsivity” or “cardi* reactivity”), consistent with the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses PRISMA; . We examThe criteria for inclusion were studies that (1) used case-control, cohort, or observational designs; (2) examined gut microbiota or measured average heart rate in beats per minute (bpm) during the baseline and task study phases in humans up to 19 years old with an ADHD and non-ADHD control group; (3) included relevant effect size statistics; (4) were written in English; and (5) were published between within the past decade. The exclusion criteria were (1) review articles and (2) randomized clinical trials, primarily due to a lack of a non-ADHD control group. We obtained full-text articles of all studies that met all criteria before extracting the relevant data from each article. Any article for which inclusion status was unclear during the screening process was discussed among reviewers , and its status was resolved with a consensus decision.Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR or DSM-5). For details on the sample, methods, and variables of interest for all studies, please see For all studies, ADHD was defined according to the diagnostic criteria set forth by the fourth or fifth edition of the SDs, and independent p-values were utilized to determine the effect size for all included studies. Researchers from one study , sample size, and p-values were used to calculate the effect size. The SD and mean were calculated from the supplemental data from one study  discriminate between microbiota by grouping the number of unique nucleotide sequences within a sample by clusters . Alpha dne study .Due to the limited number of studies that met the criteria for inclusion , bias control and sensitivity analyses could not be conducted. Instead, the two primary analyses included the relevant data from all eligible published gut microbiota and heart rate reactivity studies. Secondary analyses examined associations between specific bacterial phyla concentrations, heart rate reactivity task types, and symptom severity in children with ADHD compared to control groups. The Comprehensive Meta-Analysis (CMA) software was utilized to conduct all meta-analytic statistical tests . Microsoft Excel was used to calculate descriptive statistics and create a codebook for the dataset.n=155), PsycInfo/EBSCO (n=32), Web of Science (n=144), and ProQuest Dissertations & Theses (n=92) as shown in n=6), did not provide quantitative data about microbiome composition (n=11), did not have a non-ADHD healthy control group (n=1), or clarifying data were not provided following data requests for additional information (n=4).Literature searches yielded 395 potential studies from PubMed  for quality assessment using a modified Newcastle-Ottawa Quality Assessment Scale to assess cohort and case-control studies NOS; . The NOSAll five studies in the present analysis used an electrocardiogram to measure electrical heart signals , 47, 73.The methods for assessing gut microbiology are shown in The most frequently used indices comparing microbiome samples were the OTUS, Chao1, Shannon diversity, and Simpson measures Table 4.2I statistic, with higher values indicating greater percentages of variation across studies that are not attributed to chance (2I > 50%). In all other cases, a fixed-effect model was adapted  and between-study heterogeneity (2I) of 66.31% for the HRR differences between children with ADHD and without ADHD  and low heterogeneity (2I = 0.92%), as shown in Two studies utilized cognitive tasks as an experimental stressor. One study utilized the computerized Tower of London planning task, which requires executive functioning skills to plan, memorize, and manipulate computerized blocks across four difficulty levels and construct a tower . Anothereneity I2 = 0.92%,p = .21; 95% CI: -0.58 to 0.13). A low heterogeneity between studies was observed (2I = 34.96%). Data are displayed in Two studies used the same emotional task, the International Affective Picture System (IAPS), as the psychological stressor , 47. A fserved I2 = 34.96%p = 0.83), with a pooled random-effects SMD estimate of -0.06 and no between-study heterogeneity (I2 = 0%).The differences in gut bacteria OTU were analyzed from three studies and are represented in 2I = 60.76%). The pooled fixed-effects SMD estimate was 0.08 between the two groups (p = 0.50) and 95% CI between -0.16 and 0.32. A random-effects model revealed a pooled SMD of 0.06 (95% CI: p = 0.78) and low heterogeneity attributed to chance across studies (2I = 15.27%). The 95% CI for the random-effects model was from -0.34 to 0.47 . The fixed-effects pooled SMD estimate was 0.21 (p = 0.18) with a 95% CI of -0.10 to 0.51 . A fixed-effect model revealed a significant pooled SMD estimate of 0.32 with a 95% CI from 0.06 to 0.6 (p = 0.02). These findings suggest that children with ADHD have greater alpha diversity, as measured by the Chao1 index than healthy children without ADHD  and moderate heterogeneity (2I = 50.13%). A random-effects model revealed a pooled SMD estimate of 0.58  and no between-study heterogeneity (2I = 0%). These findings suggest that children with ADHD have significantly greater concentrations of Actinobacteria in their fecal samples than healthy controls without ADHD . The concentration of Bacteroidetes between children with and without ADHD did not reach statistical significance . The random-effects model showed a non-significant pooled SMD estimate of -0.56 . These findings suggest that the concentration of Firmicutes in the gut microbiome of children with and without ADHD was not statistically different  are analogous with poor emotional regulation , examiniAlthough prior work suggested differences in microbiota populations in children with ADHD , 68, 75 via task-related HRR, was assessed in the five case-control studies that met the criteria for inclusion . The small number of studies investigating these phyla in children with ADHD may have limited the power and sensitivity of the present analysis to detect a significant small effect size. Nevertheless, control groups had greater absolute Firmicutes levels than those with ADHD in both studies reporting these bacterial concentrations  methodologies  and internalizing disorders  to learning disabilities and other neurodevelopmental conditions (e.g., ASD; e.g., Additionally, it will be important for researchers in this area to establish standardized protocols that permit appropriately nuanced evaluation of the microbiome and its potential contribution to ADHD. Developmental and contextual factors should be considered, given that gut microbiota composition fluctuates throughout the lifespan , 59, 76 Subsequent research may inform the application of findings regarding task-related HRR and other ANS indicators to the growing use of yoga, mindfulness, and other meditative interventions in youth with ADHD e.g., . SimilarRegarding gut microbiota, these findings support prior research that specific dietary components can modify the gut microbiota and alter activity in brain regions relevant to cognition, behavior, and symptoms of ADHD , 65, 70.Finally, the results of this review support using a combination of physiological and psychological measures in laboratory and real-world contexts to assess the relationship between emotional dysregulation and ADHD or the embodiment of emotional dysregulation linked to non-neurotypical development. Developmental stage, diet, gastrointestinal health, and medication use are also pertinent factors to consider. We recommend using behavioral and physiological measures to study the heterogeneous etiology and developmental trajectory of ADHD in children and adolescents to distinguish biotypes by stress response patterns and behavioral profiles.Physiotherapy methods, such as yoga, biofeedback breath control training, and probiotic biotherapy, can be paired with psychotherapy to help address physiological self-regulation . EvidencExisting evidence underscores that ADHD can no longer be conceptualized as primarily a neurocognitive disorder driven by a neurotransmitter imbalance. Due to impulsivity and hyperactivity symptoms, emotional dysregulation has also gained traction as a key component of ADHD . Given tAlthough limited by the small number of studies included in the present meta-analysis, our findings suggest that gut microbiota disruptions are linked to childhood ADHD; whether changes in the gut microbiota are a causal factor or symptom of the disorder remains unknown. However, these results suggest that utilizing a whole person lens – multiple physiological systems existing within several environmental contextual layers , 103 – wThe original contributions presented in the study are included in the article/As lead author, AP conceived the study aims, led the writing project, completed data analyses, created tables and figures, and was the primary writer for the majority of the first manuscript draft. MJC, TGC, and JMB were primary writers for portions of the introduction and discussion. AP, MJC, TGC, and JMB were involved in conducting the publication search and review of papers for meeting inclusion criteria. RPK provided clinical expertise and critical feedback during the writing and editing process. As senior author, JMB provided financial support for the statistical software and publication costs as well as oversaw and guided the study from inception through dissemination. All authors have edited, reviewed and approved the final version of the manuscript. JMB secured funds to support the analysis and publication of this paper; internal funds were awarded by the UNC Charlotte’s Atkins Library and Department of Psychological Science for publishing an open access article. In addition, JMB is supported by research funds from earning the Bonnie E. Cone Early-Career Professorship in Teaching. AP’s time and effort were supported by funds from the UNC Charlotte SciComm Fellowship grant from Burroughs Wellcome Fund, Psi Chi APAGS Junior Scientist Fellowship, UNC Charlotte Loch Walker Writing Award, the MENSA McGrew-Fruecht Scholarship, and the Health Psychology PhD program.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


It has been established that the selective α2A adrenoceptor agonist guanfacine reduces hyperactivity and improves cognitive impairment in patients with attention-deficit/hyperactivity disorder (ADHD). The major mechanisms of guanfacine are considered to involve the activation of the postsynaptic α2A adrenoceptor of glutamatergic pyramidal neurons in the frontal cortex, but the effects of chronic guanfacine administration on catecholaminergic and glutamatergic transmissions associated with the orbitofrontal cortex (OFC) are yet to be clarified. The actions of guanfacine on catecholaminergic transmission, the effects of acutely local and systemically chronic (for 7 days) administrations of guanfacine on catecholamine release in pathways from the locus coeruleus (LC) to OFC, the ventral tegmental area (VTA) and reticular thalamic-nucleus (RTN), from VTA to OFC, from RTN to the mediodorsal thalamic-nucleus (MDTN), and from MDTN to OFC were determined using multi-probe microdialysis with ultra-high performance liquid chromatography. Additionally, the effects of chronic guanfacine administration on the expression of the α2A adrenoceptor in the plasma membrane fraction of OFC, VTA and LC were examined using a capillary immunoblotting system. The acute local administration of therapeutically relevant concentrations of guanfacine into the LC decreased norepinephrine release in the OFC, VTA and RTN without affecting dopamine release in the OFC. Systemically, chronic administration of therapeutically relevant doses of guanfacine for 14 days increased the basal release of norepinephrine in the OFC, VTA, RTN, and dopamine release in the OFC via the downregulation of the α2A adrenoceptor in the LC, OFC and VTA. Furthermore, systemically, chronic guanfacine administration did not affect intrathalamic GABAergic transmission, but it phasically enhanced thalamocortical glutamatergic transmission. The present study demonstrated the dual actions of guanfacine on catecholaminergic transmission—acute attenuation of noradrenergic transmission and chronic enhancement of noradrenergic transmission and thalamocortical glutamatergic transmission. These dual actions of guanfacine probably contribute to the clinical effects of guanfacine against ADHD. Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental and neuropsychiatric disorder in children and adolescents  ,2. UsualThe treatment of ADHD usually combines pharmacotherapy and behavioural therapy . In pharGuanfacine is an approved agent for the treatment of ADHD as a non-stimulant class agent in Japan, the USA and Europe ,2,3,4. CGuanfacine is a selective agonist of the α2A adrenoceptor ,12,13,14Clinical imaging studies revealed that the functional disturbance associated with the orbitofrontal cortex (OFC) , ventralThe OFC receives catecholaminergic projections, including the selective dopaminergic pathway from the VTA and selective noradrenergic and dopamine/norepinephrine co-releasing pathways from the LC ,26,27,28To determine the effects of local administrations of guanfacine (200 nM) into the LC  on extratime = 7.0 (p < 0.01), Fadministration = 33.4 (p < 0.01), Fguanfacine = 4.8 (p < 0.05), Fguanfacine*time = 11.1 (p < 0.01), Fguanfacine*adminisdtration = 2.6 (p > 0.1), Fadminisdtration*time = 7.9 (p < 0.01), Fguanfacine*administration*time = 5.7 (p < 0.01)] , affected extracellular norepinephrine level in the OFC [F< 0.01)] . Acute a< 0.01)] A, wherea< 0.01)] B. Furthe< 0.01)] C. Thereftime = 1.3 (p > 0.1), Fadministration = 36.3 (p < 0.01), Fguanfacine = 0.4 (p > 0.1), Fguanfacine*time = 1.4 (p > 0.1), Fguanfacine*adminisdtration = 0.3 (p > 0.1), Fadminisdtration*time = 1.3 (p > 0.1), Fguanfacine*administration*time = 0.5 (p > 0.1)] , affected extracellular dopamine level in the OFC [F > 0.1)] . Acute a > 0.1)] A, and af > 0.1)] B. Howeve > 0.1)] C. These time = 5.2 (p < 0.01), Fadministration = 69.4 (p < 0.01), Fguanfacine = 1.7 (p > 0.1), Fguanfacine*time = 6.8 (p < 0.01), Fguanfacine*adminisdtration = 1.3 (p > 0.1), Fadminisdtration*time = 1.5 (p > 0.05), Fguanfacine*administration*time = 1.8 (p > 0.05)] , affected extracellular norepinephrine level in the VTA [F> 0.05)] . Acute a> 0.05)] A, wherea> 0.05)] B. Furthe> 0.05)] C. Thereftime = 11.8 (p < 0.01), Fadministration = 20.5 (p < 0.01), Fguanfacine = 3.2 (p > 0.05), Fguanfacine*time = 16.3 (p < 0.01), Fguanfacine*adminisdtration = 2.5 (p > 0.1), Fadminisdtration*time = 5.3 (p < 0.01), Fguanfacine*administration*time = 6.8 (p < 0.01)] , affected extracellular norepinephrine level in the RTN [F< 0.01)] . Acute a< 0.01)] A, wherea< 0.01)] B. Furthe< 0.01)] C. Thereftime = 6.6 (p < 0.01), Fadministration = 4.0 (p > 0.05), Fguanfacine = 1.9 (p > 0.1), Fguanfacine*time = 7.7 (p < 0.01), Fguanfacine*adminisdtration = 0.8 (p > 0.1), Fadminisdtration*time = 5.8 (p < 0.01), Fguanfacine*administration*time = 5.5 (p < 0.01)]  for 14 days, affected extracellular GABA level in the MDTN [F< 0.01)] . Acute a< 0.01)] A, wherea< 0.01)] B. Contra< 0.01)] C. The GATo determine the effects of local administrations of α1 adrenoceptor antagonist, 100 μM prazosin (PRZ) ,28,36,37time = 20.2 (p < 0.01), Fadministration = 26.9 (p < 0.01), Fguanfacine = 7.3 (p < 0.05), Fguanfacine*time = 19.2 (p < 0.01), Fguanfacine*adminisdtration = 0.2 (p > 0.1), Fadminisdtration*time = 3.5 (p < 0.01), Fguanfacine*administration*time = 1.9 (p > 0.05)]  for 14 days, affected extracellular dopamine level in the OFC [F> 0.05)] . Perfusi> 0.05)] A,B. Furt> 0.05)] C. These To determine the effects of local administrations of AMPA/glutamate receptor agonist, 100 μM AMPA into the MDTN on extracellular levels of norepinephrine, dopamine and L-glutamate in the OFC, after the systemically chronic administration of guanfacine (0 or 0.12 mg/kg/day) for 14 days using osmotic pump (N = 12), microdialysis probes were inserted into the MDTN and OFC. During the chronic guanfacine-free administration for 14 days, the perfusate in the MDTN was switched from MRS to MRS containing 100 μM AMPA (acute effects). During the systemically chronic administration of guanfacine (0.12 mg/kg/day) for 14 days, the perfusate in MDTN was switched from MRS to MRS containing AMPA (100 μM) (chronic effects).time = 44.8 (p < 0.01), Fadministration = 23.8 (p < 0.01), Fadminisdtration*time = 11.7 (p < 0.01)]  for 14 days, affected extracellular norepinephrine level in the OFC [F< 0.01)] A,B. Perf< 0.01)] A,B. Chro< 0.01)] A,C. Furt< 0.01)] A,B. time = 57.1 (p < 0.01), Fadministration = 45.5 (p < 0.01), Fadminisdtration*time = 25.6 (p<0.01)]  for 14 days, affected extracellular dopamine level in the OFC [Fp<0.01)] C,D. Perfp<0.01)] C,D. Chrop<0.01)] C,D. Furtp<0.01)] C,D.time = 53.7 (p < 0.01), Fadministration = 7.4 (p < 0.01), Fadminisdtration*time = 12.5 (p < 0.01)]  for 14 days, affected extracellular L-glutamate level in the OFC [F< 0.01)] E,F. Perf< 0.01)] E,F. Chro< 0.01)] E,F. Cont< 0.01)] E,F.p < 0.01], OFC  and VTA , respectively  and chronic (for 14 days) administration of guanfacine (0.12 mg/kg/days) using osmotic pump (N = 12), the total plasma membrane proteins were extracted using Minute Plasma Membrane Protein Isolation Kit . The control was treated with vehicle  for 14 days using osmotic pump. Subchronic (for 7 days) and chronic (for 14 days) guanfacine administrations time-dependently decreased α2A adrenoceptor expressions in the plasma membrane of LC [F = 9.2, ectively . Expressectively A. Contraectively B,C.Catecholaminergic neurons in the LC project catecholaminergic terminals to various brain regions, including the OFC, VTA and RTN ,34,35,38In our previous study, acute local administration into the LC and subchronic (0.12 mg/kg/day for 7 days) administrations of guanfacine decreased basal extracellular levels of dopamine and norepinephrine in the OFC ,35, wherContrary to the LC, both subchronic and chronic guanfacine administration time-dependently downregulated the α2A adrenoceptor in the VTA. In the VTA, the α2A adrenoceptor is mainly expressed on the presynaptic region and suppresses norepinephrine release , whereasThalamocortical glutamatergic transmission in the MDTN-OFC pathway plays important roles in cognitive/perception functions, including sensory integration and executive function ,42,44. MBoth acute guanfacine administration and chronic clonidine administration suppressed locomotion ,63. TherBoth atomoxetine (a selective norepinephrine transporter inhibitor) and guanfacine (a selective α2A adrenoceptor agonist) are approved for the treatment of ADHD as non-stimulant class medications in Japan ,24. ReceNoradrenergic transmission in the OFC is considered to be involved in fostering stability and flexibility against environmental changes . The perAtomoxetine acutely and chronically (for 21 days) enhanced frontal norepinephrine release, whereas atomoxetine-induced norepinephrine release was reduced by chronic atomoxetine administration . ConsideThe present study extensively explored the effects of acute and chronic administration of guanfacine on noradrenergic transmission associated with LC. Other noradrenergic nuclei, nucleus tractus solitarii, and the parabrachial nucleus also project noradrenergic terminals to various subcortical regions, such as the amygdala and thalamic nuclei, affecting cognition and emotions via interactions with monoaminergic transmissions ,74,75,76Guanfacine (selective α2A adrenoceptor agonist) was obtained from Cosmo Bio . Prazosin  and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid  were obtained from Fujifilm-Wako . +, 2.7 mM K+, 1.2 mM Ca2+, 1.0 mM Mg2+, and 154.4 mM Cl− adjusted to pH 7.4 using 2 mM phosphate buffer and 1.1 mM Tris buffer. For microdialysis study, guanfacine and AMPA were dissolved directly in MRS. PRZ was initially dissolved in dimethyl sulfoxide at 25 mM [All compounds were prepared on the day of experiments. All drugs were perfused in modified Ringer’s solution (MRS), 145 mM Naat 25 mM ,78. The To study the effects of systemically subchronic and chronic administrations of therapeutically relevant doses of guanfacine, male Sprague Dawley rats   were treated for 7 or 14 days with or without guanfacine (0.12 mg/kg/day), using osmotic pumps  implanted subcutaneously in the dorsal region, under 1.8% isoflurane anaesthesia. All rats were weighed prior to initiation of the study ,50,51,55Animal care, experimental procedures, and protocols for the animal experiments were approved by the Animal Research Ethics Committee of the Mie University School of Medicine . To determine the effects of guanfacine on catecholaminergic transmission, all rats were chronically (for 14 days) treated with 0.12 mg/kg/day guanfacine, since the continuous systemic administration of 0.12 mg/kg/day guanfacine for 7 days desensitizes the α2 adrenoceptor. Three days after osmotic pump removal , rats were anesthetized with 1.8% isoflurane and then placed in a stereotaxic frame. Concentric direct insertion-type dialysis probes were implanted in the OFC  , MDTN   at a lateral angle of 30°, VTA  or LC   according to the atlas of Paxinos and Watson ,54,55,79Following surgery, rats were individually housed in cages during recovery and the experiment, with food and water provided ad libitum. Perfusion experiments commenced 18 h after recovery from isoflurane anaesthesia. Rats were placed individually into the system for freely moving animals (Eicom), equipped with a two-channel swivel . The perfusion rate was set at 2 μL/min in all experiments, using MRS. Dialysate was collected every 20 min. Extracellular levels of norepinephrine, dopamine and L-glutamate were measured 8 h after the commencement of perfusion ,81. The After the microdialysis experiments, the brain was removed after cervical dislocation during isoflurane overdose anaesthesia. The locations of the dialysis probes were verified using brain tissue slices by stereoscopic microscope .The levels of L-glutamate were determined by UHPLC  with fluorescence detection  after dual derivatization with isobutyryl-L-cysteine and o-phthalaldehyde. Derivative reagent solutions were prepared by dissolving isobutyryl-L-cysteine (2 mg) and o-phthalaldehyde (2 mg) in 100 μL of ethanol followed by the addition of 900 μL of sodium borate buffer . Automated pre-column derivatization was carried out by drawing up a 5 μL aliquot sample, standard or blank solution and 5 μL of derivative reagent solution and holding them in reaction vials for 5 min before injection. The derivatized samples (5 μL) were injected using an autosampler . The analytical column  was maintained at 45 °C and the flow rate was set at 500 μL/min. A linear gradient elution program was performed over 10 min with mobile phases A  and B . The excitation/emission wavelengths of the fluorescence detector were set at 280/455 nm ,84,85,86The levels of norepinephrine and dopamine were determined by UHPLC  and electrochemical detection , with a graphite carbon electrode set at +450 mV (vs. Ag/AgCl reference electrode). The analytical column  was maintained at 25 °C and the flow rate of the mobile phase was set at 500 μL/min. The mobile phase was composed of 0.1 M acetate buffer containing 1% methanol and 50 mg/L EDTA-2Na; the final pH was 6.0 ,37,87.Total plasma membrane proteins of LC, OFC and VTA were extracted using Minute Plasma Membrane Protein Isolation Kit . The capillary immunoblotting analyses were performed using Wes  according to the mainly ProteinSimple user manual. The lysates of plasma membrane fraction were mixed with a master mix (ProteinSimple) to a final concentration of 1 × sample buffer, 1 × fluorescent molecular weight marker, and 40 mM dithiothreitol and then heated at 95 °C for 5 min. The samples, blocking reagents, primary antibodies, HRP-conjugated secondary antibodies, chemiluminescent substrate , and separation and stacking matrices, were also dispensed to the designated wells in a 25-well plate. After plate loading, the separation electrophoresis and immunodetection steps took place in the capillary system and were fully automated. A capillary immunoblotting analysis was carried out at room temperature, and the instrument’s default settings were used. Capillaries were first filled with a separation matrix followed by a stacking matrix, with about 40 nL of the sample used for loading. During electrophoresis, the proteins were separated by molecular weight through the stacking and separation matrices at 250 volts for 40–50 min and then immobilized on the capillary wall using proprietary photo-activated capture chemistry. The matrices were then washed out. The capillaries were next incubated with a blocking reagent for 15 min, and the target proteins were immunoprobed with primary antibodies followed by HRP-conjugated secondary antibodies . The antibodies of ADRA2A  and GAPDH  were diluted in an antibody diluent (ProteinSimple) ,82,83.p < 0.05 (two-tailed).Where possible, we randomized and blinded sample data. To determine extracellular transmitter levels and α2A adrenoceptor expression, the sample order was set on the autosampler according to a random number table. Drug doses and sample sizes were selected according to previous studies. All experiments in this study were designed with equally sized animal groups (N = 6) and all values were expressed as means ± standard deviation (SD). Differences were considered significant when p > 0.05), the F-value of MANOVA was analysed using sphericity-assumed degrees of freedom. When the assumption of sphericity was violated (p < 0.05), F-values were analysed using Chi–Muller’s corrected degrees of freedom by BellCurve for Excel. When F-values for drug factors were significant in MANOVA, the data were finally analysed using Tukey’s post hoc test with BellCurve for Excel. Transmitter levels were expressed as the area under the curve between 20 and 180 min (AUC20–180 min) after target agent administration. All statistical analyses complied with the recommendations for experimental design and analysis in pharmacology. The protein expression of α2A adrenoceptor in the LC, OFC and VTA in the plasma membrane fraction was analysed by a one-way ANOVA with Tukey’s multiple comparison using BellCurve for Excel.Regional transmitter concentrations were analysed using Mauchly’s sphericity test followed by multivariate analysis of variance (MANOVA) using BellCurve for Excel ver. 3.20 . The data were composed of average of pre-treatment period (1 point) and each time point during target agent administration (9 points). When the data did not violate the assumption of sphericity  pathway (from the LC to OFC) is also weakly suppressed by guanfacine, whereas thalamocortical glutamatergic transmission (MDTN-OFC) is enhanced via intrathalamic (RTN-MDTN) GABAergic disinhibition. In contrast with early-stage administration, chronic guanfacine administration (probably more than 2 weeks in duration) enhances noradrenergic transmission from the LC to OFC, VTA, and RTN due to the downregulation of the postsynaptic/somatodendritic and presynaptic α2A adrenoceptors. Furthermore, the attenuation of the inhibitory α2A adrenoceptor also produces an enhancement of the dopaminergic transmission in the LC-OFC co-releasing pathway and mesocortical (VTA-OFC) pathway. Unexpectedly, intrathalamic GABAergic transmission was not affected by acute guanfacine administration after chronic guanfacine administration, whereas thalamocortical glutamatergic transmission was enhanced via amplifying the integration of sensory/emotional inputs in the MDTN. These time-dependent actions of guanfacine, from the tonic-inhibition to tonic-activation of mesocortical catecholaminergic transmission, and phasic-activation associated with thalamocortical glutamatergic transmission support rapid onset and continuous efficacy in the treatment of ADHD.