ADHD presents a serious community-health problem through its links to a wide range of negative outcomes. These outcomes are exacerbated when ADHD symptoms co-occur with other mental health problems. Research evidence suggests high rates of co-comorbidity with a range of problems. However, there is a paucity of longitudinal research that examines the predictive links between ADHD symptoms and symptoms of other mental health problems. We examined a cross-lagged autoregressive model in order to assess homotypic and heterotypic continuity between ADHD symptoms, aggressive behavior, non-aggressive behavior problems and anxiety/depression in a community-based sample of 1571 youth  assessed annually from age 7 to 13 and again at age 15. Consistently significant correlations between each pair of problem behaviors provided support for concurrent comorbidity. Furthermore, significant autoregressive pathways provided support for homotypic continuity. Support for heterotypic continuity was limited to ADHD symptoms predicting both aggressive behavior and non-aggressive behavior problems, but not vice versa. Our study highlights the importance of focusing on ADHD symptoms to identify children at risk not only for continued ADHD symptomatology but also a range of externalizing behavior problems including different types of aggression and non-aggressive behavior problems, such as rule-breaking. Identifying these patterns in a community-based sample provides support for the possibility of early identification of risk for a range of problem  behaviors. Attention deficit hyperactivity disorder (ADHD) is one of the most common disorders in school-aged children and it is characterised by hyperactivity, impulsiveness, and/or inattention APA . It presn = 1919) met criteria for ADHD; of those 34% received a diagnosis of ADHD alone, while the other 66% met criteria for at least one other comorbid diagnosis. Similar findings were reported by Jensen and Steinhausen in 2015 in a sample of 14,825 Danish 4- to 17-year-old patients. While fewer studies have examined comorbidity utilising non-clinical samples, the available studies also suggest similar findings. For instance, Kadesjö and Gillberg . The authors found strong support for homotypic continuity, that is, each disorder predicted itself seven years later. They also found strong support for heterotypic continuity, particularly within the higher order domains of externalizing and internalizing problems; that is, one disorder predicted another disorder seven years later within the same domain. They also found support for some cross-domain heterotypic continuity, the strongest one being a significant link between ADHD symptoms at age 7.5 and internalizing disorders at age 14. According to the authors, these findings are consistent with the ‘dual failure model’ , 8.23 (n = 1343), 9.21 (n = 1294), 10.70 (n = 1269), 11.60 (n = 1064), 12.63 (n = 977), 13.88 (n = 1266), and 15.68 (n = 1288). Approximately 11% of the children were born outside of Switzerland. At baseline, 78% lived with both of their biological or adoptive parents, 20% with their biological mother only, and 2% with their biological father only, with foster parents or in residential care. Notably, 46% of the children had both parents who were born outside of Switzerland representing more than 80 countries of origin and contributing to an ethnically diverse sample. Twenty-five percent of the primary caregivers had little or no secondary education, 30% had vocational training, 29% had attended full-time vocational school, had a baccalaureate degree or advanced vocational diploma, and 16% had a university degree. In terms of household finances, 18% reported experiencing financial difficulties in the last year. Further information on the sample can be found at: http://www.jacobscenter.uzh.ch/en/research/zproso/aboutus.html as well as previous publications . Ethics approval for the study was provided by the Ethics Committee at the Faculty of Arts and Social Sciences of the University of Zurich. The target sample at the initial assessment was 1675 first graders from 56 public elementary schools. Schools were selected according to a stratified random sampling procedure that took into account school location and size. All children who entered first grade (aged ~7) in 2004 in one of these schools were invited to participate via their parents. Parents provided informed consent on behalf of their child until age 11, after which point the participants themselves provided consent. The current study includes 1571  participants with teacher-reported symptom data available for at least one measurement point. This represents 94% of the baseline target sample. Data was collected at eight time points spanning the duration of compulsory schooling in Zurich, Switzerland (child age 7–16). These are labelled according to the children’s age at each point rounded to the nearest whole number. The mean age and number of participants at each data collection point were 7.45  of primary school. Another teacher provided ratings from Grade 4 to 6 . Following this, children transitioned into secondary school, where a third teacher provided the ratings at ages 13 and 15. The number of teachers who provided ratings each year were 113, 148, 217, 274, 265, 258, 366, and 423, respectively. They provided ratings for 1 to 24 children, with an average ranging from 6 to 12 over all the data collection points. At each time point, the research team approached the so called ‘class teacher’ to complete the questionnaire. Class teachers are the Swiss equivalent of ‘home room teacher’ in US and Canada, with responsibilities to oversee each student’s progress. They are also the contact person for personal issues and liaise with the students’ parents. These teachers are also responsible for all of the teaching in primary school (up to age 13) and at least some of the teaching after that. The study requirement was that they have at least 4 lessons weekly with each rated student. If the ‘class teacher’ taught the class for less than 4 lessons per week, the rule was that the German language teacher should complete the questionnaires.To rate children’s behavior, teachers completed the Social Behavior Questionnaire . The non-aggressive externalizing problems scale (NAEX) included 6 items, such as “The child destroys things belonging to his/her family, or other children”. . The aggression scale included 11 items tapping three forms of common types of aggression – physical, proactive and reactive. Examples of items include: “The child physically attacks people”, “The child threatens people”, “The child reacts in an aggressive manner when teased”, respectively . The anxiety/depression scale consisted of 7 items, such as “The child is worried”, “The child has trouble enjoying him/herself” . Anxiety and depression were combined into one subscale as they were conceptualised as manifestations of the same underlying disorder  framework with the statistical software n with the same behavior at the following assessment point, at time tn + 1. In other words, they adjust for past levels of the outcome in order to predict change in levels of the outcome over time. Consistent with previous research the autoregressive pathways were allowed to vary across time to allow for the changes in the level of influence that behaviors at time tn have on the same behaviors at time tn + 1 as children grow older.First-order autoregressive and cross-lagged pathways of association along with concurrent correlations were simultaneously evaluated. In a first-order autoregressive model, variables are represented as predictors of themselves over time. Therefore, autoregressive pathways estimate the association between each of the behaviors at time tn and another behavior at time tn + 1 as well as the reciprocal association between the two behaviors at time tn and at time tn + 1. These effects were allowed to vary across time to examine change in the reciprocal association between behaviors from age 7 through to age 15. Concurrent residual correlations between pairs of behaviors at the same time of assessment were estimated and allowed to vary over time as were the residuals within construct variances.Cross-lagged models have been widely used in developmental research to assess bi-directional time-lagged relations , and a model in which these regression weights were constrained to be equal. Because the Following the assessment of model fit and provided a good fit was identified, correlations between each pair of problem behaviors were examined to assess concurrent co-occurrence, or comorbidity, of problem behaviors at each time point. Next, the autoregressive pathways were interpreted to evaluate homotypic continuity of each problem behavior  over time. Finally, to address the main goal of the study, the cross-lagged pathways were interpreted to evaluate heterotypic continuity, or prediction of different problem behaviors predicting each other over time.In the first step of the analyses, comparison of fit indices supported sex invariance (no significant sex differences) in the examined cross-lagged autoregressive model, which included eight time points and four mental health categories . The links at all ages were significant with respect to ADHD symptoms, Anxiety/Depression, and Aggression , suggesting that previous behavior significantly, and consistently predicted the same future behavior.As expected, with only one exception, mental health problems at time t were significantly related to the same mental health problem at tn were consistently and significantly linked to higher levels of teacher-observed Non-aggressive externalizing problems at time tn + 1 from age 7 through 15. However, higher levels of Non-aggressive externalizing problems at time tn were significantly linked to higher levels of ADHD symptoms only at ages 7 to 8 and 13 to 15.Next, we examined the cross-lagged effects between each pair of behaviors  bidirectional links between each of the four problem behaviors measured at the eight time points from age 7 to 15. Of the 84 possible pathways of heterotypic continuity, only 31 were statistically significant. Interestingly, ADHD symptoms consistently predicted aggressive behavior as well as non-aggressive behavior problems in every consecutive assessment/wave from age 7 to 15. However, the reverse was not the case consistently, as ADHD symptoms were predicted by aggression only from age 12 to 13 and by non-aggressive behavior problems from age 7 to 8 and 13 to 15. Previous research  in development with varied time-periods between them. However, given the implication of ADHD symptoms in school attainment, socialisation processes and peer relationships in adolescence, we expanded previous research by assessing the problem behaviors at ages 7, 8, 9, 10, 11, 13, and 15. This allowed for a fine-tuned insight into the links between problem behaviors over time but also, importantly, from year-to-year. In addition, because our study relies on continuous measures capturing symptoms of psychopathology and draws on a community-based cohort sample, it allowed us to report on a wide range of severity in problem behaviors. Furthermore, the study was carried out utilizing a normative sample of young people thus represents a broader range of problems and provides a better view of these patterns in the general population. As such, the results may be more reliably used to inform primary prevention practices targeting young people in the general community.In conclusion, our study provided support for consistent concurrent comorbidity and homotypic continuity from age 7 to 15. However, we only found limited support for heterotypic continuity when assessed year-by-year from entry to school to adolescence. Importantly, ADHD symptoms at each assessment period emerged as risk factors for both types of externalizing behaviors in subsequent years, but not for anxiety/ depression. Our findings highlight the importance of focusing on ADHD symptoms to inform prevention and early intervention practices specifically for externalizing behavior problems for both girls and boys. The findings also pointed to the importance of assessing these behaviors/ symptoms regularly at different developmental stages. Future studies should focus on identifying the mechanisms through which the links between ADHD symptoms and other problem behaviors are formed as well as on exploring the year-to-year predictors of both externalizing and internalizing problems.


Conduct disorder (CD) is associated with impairments in facial emotion recognition. However, CD commonly co-occurs with attention-deficit/hyperactivity disorder (ADHD); thus, it is unclear whether these impairments are explained by ADHD or by one of its core features—inattention. We explored whether emotion recognition impairments are specific to individuals with ADHD and comorbid CD while also examining the mechanisms that might explain such deficits.A total of 63 male and female adolescents with ADHD  and with (ADHD+CD) or without (ADHD) comorbid CD, and 41 typically developing controls  performed an emotion recognition task with concurrent eye-tracking.Participants with ADHD+CD were less accurate at recognizing fear and neutral faces, and more likely to confuse fear with anger than participants with ADHD alone and HC. Both ADHD subgroups fixated the eye region less than HC. Although there was a negative correlation between ADHD symptom severity and eye fixation duration, only CD severity was inversely related to emotion recognition accuracy.Only ADHD participants with comorbid CD showed impairments in emotion recognition, suggesting that these deficits are specific to individuals with conduct problems. However, lack of attention to the eye region of faces appears to be a characteristic of ADHD. These findings suggest that emotion recognition impairments in those with ADHD+CD are related to misinterpretation rather than poor attention, offering interesting opportunities for intervention. Children who receive a diagnosis of conduct disorder (CD) display a persistent pattern of behavior in which the rights of others are violated and major age-appropriate social norms are breached.One mechanism that has been found to be important in explaining the behavioral characteristics of CD is impairment in the recognition of facial expressions of emotion.14Despite evidence demonstrating emotion recognition impairments in those with CD, studies have failed to account for comorbid attention-deficit/hyperactivity disorder (ADHD). ADHD is comorbid in 30% to 50% of cases,why individuals with CD have emotion recognition impairments, and therefore which elements of interventions may be responsible for improvements in emotion recognition and behavior  between 11 and 18 years of age  with a clinical diagnosis of ADHD were recruited from psychiatric and pediatric clinics in Wales (UK) as part of a larger genetic study.Ethical approval was obtained from the Wales Multicentre Research Ethics Committee. Informed written consent was obtained from parents and adolescents more than 16 years of age, and written assent was obtained from adolescents less than 16 years of age.DSM-IV criteria (the DSM-5 had not been published at the start of the studyChild psychopathology in participants with ADHD was assessed using the Development and Well-Being Assessment (DAWBA) structured psychiatric research diagnostic interview, using both parents and children as informants.DSM-IV diagnostic criteria for conduct disorder; this resulted in an ADHD only (n = 36) subgroup and an ADHD with comorbid CD  subgroup.ADHD group membership was based on whether or not participants met CU traits were measured using the Youth Psychopathic traits Inventory (YPI),In those with ADHD, estimated IQ was obtained via two subtests of the Wechsler Abbreviated Scale of Intelligence.SES was estimated using the UK’s Office of National Statistics estimates of average house-hold weekly income based on participants’ postcodes .Emotion recognition was examined using the Facial Emotion Recognition task,31Participants were positioned 60 to 65 cm from a laptop screen, and a 9-point calibration was performed. The quality of calibration was checked and repeated as required. Calibration was followed immediately by facial stimuli. Eye-movements were recorded with a portable Tobii X2-60 compact eye-tracker sampling at 60 Hz with a screen resolution of 1920 × 1080. This equipment is robust to changes in head position, removing the need for a chin rest. An I-VT fixation filter with a minimum fixation criterion of 60 milliseconds sampled average raw data of both eyes to produce information on eye position and duration. Eye-gaze validity was checked using a sample rate percentage that gives an estimate of the quality of eye-tracking in a recording by providing a percentage score of successfully recorded data.Participants with ADHD and ADHD+CD were tested in a dimly lit laboratory room in a university clinic. HC participants were tested in a dimly lit room at school. Following eye-tracker calibration, each face was presented using a set of three slides. First, a noise screen was used to prevent visual carryover effects from the previous trial; second, a fixation cross-controlled starting eye position; and third, the face stimulus was presented. Noise and fixation screens were presented for 1 second each. The face stimulus had no time constraint, lasting for as long as it took to select an emotion.Percent correct recognition and percent incorrect emotion selected for each emotion and each intensity level were calculated.Tobii Studio was used to analyze eye gaze. Areas of interest (AOIs) were created around the eyes, mouth, and face as a whole; one AOI was created around the emotion options and another around the entire screen. Percentage of dwell time to the eyes was calculated by summing all fixations to the eye AOI divided by the total duration of time spent looking at the face AOI. We also analyzed time to first fixation on the eye (TFF). Values more than 2 standard deviations above the mean and trials with values of zero were excluded from the TFF analyses.t tests used to determine specific differences between groups and χ2 tests for binary variables. Pearson (Spearman rho where appropriate) correlations were used to examine relationships between demographic and clinical characteristics with recognition and eye-gaze measures. Mixed-model ANOVAs , with group  as a between-subjects factor and emotion  and intensity (50% and 75%) as within-subjects factors were used for the analysis of emotion recognition and eye-tracking measures. Where intensity was not found to interact with group, the two intensities were merged, and ANOVAs were rerun without intensity as a factor and the addition of neutral to the emotion factor. To limit the number of multiple comparisons, statistical analysis of confusion errors, using one-way ANOVAs, were limited to emotions where a significant group difference was found. Where the assumption of sphericity was violated, Greenhouse−Geisser corrections were used. Where follow-up tests were required, Bonferroni corrections were used. Effect sizes were calculated as partial eta squared .Analyses were carried out using SPSS version 20 . Differences in demographic and clinical characteristics between groups were analyzed with one-way analyses of variance (ANOVAs) for continuous variables, with Student 2(2) = 7.4, p = .025) and age . Emotion recognition accuracy did not differ between genders ; however, the relationship between age and emotion recognition approached significance (r104 = 0.054). ANOVAs were therefore conducted both with and without including age as a covariate. Both analyses resulted in the same pattern of results in terms of direction and significance, so results are reported below without using age as a covariate.p < .001) and more ADHD symptoms than ADHD alone (p = .042). There was a significant group difference in CU traits (p = .02), with ADHD+CD having a higher CU score than ADHD (p = .002) and controls (p .035), whereas ADHD and controls did not differ (p = .66).The ADHD+CD group had (as expected by definition) significantly more CD symptoms than the ADHD alone group and controls , with more accurate reports for higher intensity emotions . There was no interaction between intensity and group . Scores were therefore averaged across intensities, and analyses were rerun without intensity as a factor.There was a main effect of intensity , with highest accuracy scores to happy faces (mean = 94.23 SD = 9.65), followed by neutral , fear , angry , and sad . There was also a main effect of group , and a significant interaction between group and emotion . Groups differed in fear (p < .001) and neutral (p = .002) recognition but not in other emotions . ADHD+CD were less accurate in recognition of fear and neutral expressions than ADHD (p < .003 and p =.018 respectively) and HC (p < .001 and p < .001 respectively), whereas there was no difference in fear or neutral recognition between ADHD and HC (p > .05).Recognition accuracy scores are presented in F5.06,164.3 = 2.71, p = .02, ηp2 = 0.08), with ADHD +CD participants showing less accurate fear and neutral recognition accuracy than ADHD and controls  and no difference between ADHD and HC (p > .05). Although the small number of females precluded any statistical analysis of the performance of females only, the direction of results in females was the same as that of males and the sample as a whole.Because most studies focus on recognition accuracy in males only, we conducted a sensitivity analysis restricted to males and found the same pattern of results, with a significant interaction between emotion and group . ADHD+CD made this error more than HC (p < .002). There was no difference between ADHD+CD and ADHD. There was also a significant group difference in tendency to misinterpret fear faces as angry ; ADHD+CD made this error more than ADHD (p = .04) and HC (p = .003), with no difference between ADHD and HC (p > .05).Patterns of errors made by the groups are presented in F2,103 = 5.17, p = .007, ηp2 = 0.09). ADHD+CD was more likely to make this error than both ADHD and HC , whereas there was no difference between ADHD and HC (p > .05). There was also a group difference in the propensity to judge neutral faces as sad , with pairwise comparisons indicating that ADHD+CD made this error more than HC (p <.01); the differences between ADHD+CD and ADHD approached significance (p = .057). There were no group difference in the tendency to misinterpret neutral faces as angry , or fearful .There was a significant group difference in tendency to judge neutral faces as happy , with participants spending more time focusing on the eyes for higher-intensity  compared to lower-intensity  faces. There was no interaction between emotion and intensity , or between intensity and group . Scores were therefore averaged across emotion intensities.A three-way ANOVA with emotion and intensity as within-subjects factors and group as a between-subjects factor revealed a main effect of intensity  . Participants focused most on the eyes for sad faces , followed by fear , neutral , angry , and happy  faces. There was also a main effect of group , with both ADHD+CD and ADHD groups spending less time focusing on the eyes than HC , whereas there was no difference between ADHD+CD and ADHD (p > .05). There was no interaction between emotion and group . This pattern of findings did not change when we included time taken to identify the faces as a covariate.A main effect of emotion was found ( = 0.22) A. ParticAfter removing participants with a mean TFF of zero, 22 ADHD+CD, 31 ADHD, and 35 HC participants remained.F2,85 = 3.25, p = .04, ηp2 = 0.07), but no main effect of emotion , and no interaction between group and emotion . ADHD+CD were slower to fixate to the eyes than HC (p < .05), but there was no difference between ADHD+CD and ADHD or between ADHD and HC . Pairwise comparisons indicated that ADHD+CD were slower to fixate the eye region than HC for fear and angry faces , whereas ADHD+CD was slower than both ADHD and HC for neutral faces . There were no differences between groups for the other emotions .There was a main effect of group  of an increased tendency to interpret neutral faces as angry. Instead, there was evidence that ADHD+CD participants misinterpreted fear as anger, which could exacerbate behavioral problems.


The mechanisms underpinning attentional deficits are only partially understood. Here we ask if shifts in a child’s field of view (FOV) act as a mediator between symptoms of attention deficit hyperactivity disorder (ADHD) and associated cognitive anomalies, particularly in attentional processes. Real time measurement of shifts in FOV were obtained on 85 children (mean age 9.4 (SD 1.9) years; 45 with DSM 5-defined ADHD) as they completed the continuous performance task in a “virtual classroom”. We extracted measures reflecting focused and selective attention across the task, along with diffusion modelling of latent cognitive processes of information uptake, response conservativeness and non-decision time. Mediation analyses showed that shifts in FOV partially mediated the relationship between hyperactive impulsive symptoms and both poor focused attention and information uptake. Performance accuracy decreased and shifts in FOV increased during the task, but these changes over time did not differ by symptom severity. Employing virtual reality and mediation analysis, we implicate shifts in FOV as a mechanism linking symptoms of ADHD and deficits in focused attention and in the gathering of information to make decisions. The identification of mediating mechanisms might provide new targets for intervention. A large literature delineates how objective deficits in this demanding task are associated with the symptoms of ADHD10. Thus, shifting of the FOV away from targets could readily disrupt performance on attention-laden tasks. There is some empirical evidence supporting this concept. First, studies that track eye movements demonstrate that children with ADHD fail to maintain visual focus on a target, making excessive, off-target eye movements, or saccades14. However, maintaining gaze on a target without any other demands lacks the complexity of most tasks that require focused attention, and this paradigm does not probe selective attention. A second research strand monitors head movement in an effort to track shifts in a child’s FOV16. For example, one study found that compared to typically developing children, those with ADHD show excessive and distinct patterns of head movement while performing attention-demanding tasks17. However, the possibility of links between such shifts in FOV due to head movement and specific deficits in attentional skills is unexplored. The importance of identifying mediating mechanisms, such as shifts in FOV, lies partly in the possibility that they may be amenable to remediation.One possible mechanism to link ADHD symptoms with deficits in attention-demanding tasks is rapid shifts in a child’s field of view (FOV) resulting from eye or head movements. Concentrated attention on a target usually corresponds with the object falling at or near the center of the FOV18. More recent models argue for a generalized dysregulation of arousal in ADHD, most readily detected during tasks that required long periods of sustained focus20. Hyperactivity is seen as an attempt at autoregulation, as the child tries to attain stable levels of arousal. Building on this work, Sergeant argued that anomalies in arousal  are accompanied by deficits found in other ‘energetic’ pools: energy used to meet task demands (effort) and tonic changes in processes impacting response speed (activation)21. Sonuga-Barke and colleagues refined this model to argue physiological arousal per se is less pathophysiologically pertinent than the management of arousal into task-related activity22. Aligned with these arousal models, several theories tie deficient focused attention to anomalies in the coordinated, ‘intrinsic’ patterns of neural activity that emerge spontaneously when a subject is not engaged in task oriented behavior24. Here, ADHD is conceptualized as an imbalance between these intrinsic networks, particularly the default mode network, prominent during internally directed thought, and the networks supporting cognitive control and attention26. By this reasoning, lapses in attention are due to a loss in the counterbalanced activity of the default mode and task positive networks.Several models have been proposed to account for the links between ADHD symptoms, particularly hyperactivity-impulsivity, and objective, quantifiable attentional deficits. Some emphasize anomalies in the arousal of the central nervous system. Early versions posited CNS hypoarousal in ADHD which leads not only to deficient sustained attention but also to compensatory increases in motor activity to boost arousal28. Though response inhibition has been conceptualized to include three subcomponents including action withholding and action cancellation, it is interference control, the process of protecting self-directed responses from competing events, which is linked by some evidence to the observed deficits of attention in ADHD. Some studies, using the Simon and Flanker tasks, suggest that deficits in interference control lead to an initial misallocation of attentional resources and a subsequent inability to garner task-specific information30. A second body of research explores the effect of unique, salient, but otherwise extraneous environmental features, known as a singleton distractors, in capturing attention during attention-demanding tasks32. While such singleton distractors provide an intuitively plausible explanation for deficient attention, there is mixed evidence for a specific effect in individuals with ADHD35. These mechanisms thus provide at best a partial explanation of deficient attention. Here, we advance the field by examining how another mechanism—shifts in a child’s field of view—might also explain how ADHD symptoms are linked to deficits in observed behavior and underlying cognitive processes, using a virtual reality paradigm.By contrast, cognitive models have emphasized the roles of both impaired response inhibition and a specific vulnerability to the presence of singleton distractors during attention-demanding tasks. Impairement in response inhibition has been characterized as a core feature of ADHD37. We used a virtual reality tool developed by Rizzo and colleagues in which the child is asked to complete the CPT presented on a virtual chalkboard surrounded by a virtual teacher and virtual classmates38. The use of a virtual reality paradigm allows an examination of dynamic measures of changing behavior during the task, particularly how the magnitude of shifts in FOV might increase over the duration of a long, demanding task. Measuring performance over time is important as it has been argued that a core feature of ADHD is a more rapid decline in performance particularly during effortful, attention demanding tasks (i.e. there is a time by diagnosis interaction effect)39. As noted above, some theoretical models have linked this time-locked decline in performance to deficits in ‘energetic’ pools, particularly the allocation of effort over time40.Virtual reality is used for three reasons. First, it immerses the child entirely in a realistic setting that is completely controlled, and all participants experience the same visual and auditory reality. Importantly, the nature of distracting events is experimentally determined, unlike ‘real world’ settings where unexpected interruptions and distractions occur. Secondly, the head-set that is used to ‘present’ the virtual reality can simultaneously be used to monitor shifts in a child’s FOV. This allows moment by moment shifts in FOV to be tied to behavioral performance. Finally, virtual reality can readily incorporate well-established probes of attention, such as the continuous performance task42. Others have used the CPT to infer latent, underlying cognitive processes that elucidate how response time and accuracy vary between subjects. One such approach is diffusion modeling, and we employ a version, the EZ diffusion model. This model is suited to the version of the CPT we used, which has a modest number of trials and sometimes a low error rate. The EZ diffusion model infers three latent cognitive processes from response times, response time variance and accuracy rates. The first process is ‘information uptake’, which refers to the rate at which the individual acquires the information necessary to make a forced choice. The second is ‘response conservativeness’, denoting the degree of certainty an individual has to attain before making a choice. The final is the ‘non-decision time’, which indexes how long it takes to accomplish all of the cognitive tasks not directly involved in the discriminative choice. Here, we examine the associations between ADHD symptoms and both directly observed measures of attention and inferred underlying cognitive processes, and further relate these measures to shifts in FOV.Most analyses of the CPT focus on directly observed measures, often summarized by factors that explain most variance in performance. Such analyses have returned orthogonal domains of attention, specifically focused attention  and selective attention (characterized mainly by the accurate discrimination of targets and non-targets)We use a virtual reality paradigm to test the hypothesis that shifts in a child’s FOV will partly explain the association between ADHD symptoms and observed deficits in attentional performance on the CPT – see Fig. 44. General exclusion criteria were (1) neurological disorders known to affect movement, (2) the presence of gross anatomic anomalies on MRI, and (3) psychiatric disorders other than ADHD, oppositional defiant disorder or conduct disorder. In all children, we ascertained the symptoms of inattention (minimum of zero and maximum of nine) and hyperactivity/impulsivity (minimum of zero and maximum of nine) using the Diagnostic Interview for Children and Adolescents, a clinician administered interview with parents45. Medication histories were obtained from parents. Forty-five children met criteria for ADHD, of whom 13 were being treated in the community with psychostimulant medications. Working memory was estimated from the digit and spatial-span tasks of the Wechsler Intelligence Scale for Children46; and processing speed from the visual matching and decision speed subtests in the Woodcock Johnson Battery47. The procedures were approved by the Institutional Review Board of the National Human Genome Research Institute, and this study was conducted in accordance with the approved guidelines. All parents gave informed, written consent and children gave written and verbal assent.Eighty-five children participated. The general inclusion criteria were (1) age between 6 and 12 years and (2) an Intelligence Quotient of 75 or greater, defined using age-appropriate versions of the Wechsler Abbreviated Intelligence Scales38 and adapted by Digital MediaWorks (http://www.dmw.ca/). The CPT is presented on a chalkboard in the front of the virtual room. The objective is to detect and respond to the target stimulus “K”, if and only if it follows the letter “A” (the AK-CPT). Responses are made by pressing the left mouse button. Main errors consist of responses made to non-target letters (e.g. “X”) or to the target “K” when it is not preceded by the letter “A” but another letter (e.g. “B” then “K” or “C” then “K”). A total of 500 stimuli are presented in 5 blocks with an interstimulus interval of 1300–1400 milliseconds, 100 of which are the target “K” after the presentation of “A”. As the CPT proceeds, a series of classroom-based distractors are systematically presented, such as whispering classmates, paper airplanes being thrown and virtual school staff entering the room. To the extent a child turns his/her head, either to view these distractors or for other reasons, the CPT-relevant stimuli on the chalkboard move out of the center of the FOV.A virtual classroom was presented to children via the “ClinicalVR: Classroom CPT” program and a head mounted, immersive virtual reality device (Sony HMZ-T1). This task was developed by Rizzo and colleaguesShifts in the child’s FOV were captured using the Intersense Inertiacube 3, an inertial measurement unit (IMU) that possesses a 3 degree of freedom (3-DOF) gyroscope and a sampling rate of 180 Hz to record head rotations within 0.25 degrees of accuracy. These measurements are communicated to the virtual program where they are utilized to rotate the in-game camera, providing the perceptual effect of adjusting gaze or rotating one’s head within the virtual environment. Movement was measured in the horizontal (‘yaw’) and vertical planes (‘pitch’) and tilt (‘roll’). These measurements are centered to a zero-reference line from the participant’s position within the virtual classroom to the center of the active virtual chalkboard. The total extent of movement away from the central fixation point in each axis was determined for each of the five blocks, and also summed across the entire task. The task was well tolerated with no child reporting nausea due to the simulated environment. Data, from consenting participants, can be accessed upon request of the authors.48.For the entire task, we considered behavioral measures that reflected reaction times, their variability and the type and frequency of errors—see Supplemental Table 50. Examining the two symptom dimensions separately is also in keeping with reports that components of the CPT show different associations with symptoms of hyperactivity-impulsivity and symptoms of inattention51. Mediation analyses determine the degree of attenuation in the association between ADHD symptoms and the CPT performance variables in a model that includes the proposed mediator (shifts in the FOV). If this association is attenuated significantly, a significant indirect effect exists of symptoms on attentional performance through mediating shifts in FOV52. We used a bootstrapping approach, with 5000 resamples, to test the significance of the mediator. This provides a bias corrected confidence interval for estimates, and significant mediation is indicated when the 95% confidence interval does not cross zero53. We tested for the effects of sex, age and psychostimulant medication using moderated mediation models. We allowed these factors to interact with all paths in the mediation model and removed each interaction if it did not show significant moderation of that pathway. For each model, the indirect effect of symptoms on attention measures through the mediator is expressed as a linear function of the moderator  in the model. The slope of the line relating the indirect effect to the moderator is termed the index of moderated mediation. If the bootstrap confidence intervals of this index does not cross zero, then the moderation effect is taken to be significant. We used the PROCESS Macros for SPSS developed by Preacher and Hayes (processmacro.org/).Mediation analyses were used to determine if shifts in the FOV mediated the relationship between symptoms of hyperactivity-impulsivity and inattention and our measures of attention from the CPT. We include a dimensional approach, considering symptom number in our analysis, rather than solely diagnostic categories. Treating symptoms as a quantitative trait boosts power as traits contain more information about between-individual trait variability than a dichotomous diagnostic category. This approach is also in line with epidemiological evidence showing that symptoms of ADHD are distributed throughout the populationChanges in performance and the degree of shift in FOV over the five blocks were examined using repeated measures ANOVA. Block by block performance was the within-subject factor and diagnosis was the between subjects factor. The performance measures for each block were: accuracy, reaction time, reaction time variability and the extent of yaw, pitch and roll. We did not consider variables such as impulsive errors to targets only or reaction time variability to targets only, as these were too infrequent within each block to be considered in block by block analysis.Demographic and clinical characteristics of the 85 children are given in Table First, a principal components analysis on the behavioral data across the entire task extracted three factors—see Supplemental Table ADHD symptoms were significantly correlated with poor focused attention  but not with selective attention. Hyperactive-impulsive symptoms were also associated with the latent cognitive process of information gathering  and at a nominal level of significance to response conservativeness . Inattention correlated only with information gathering —Supplemental Table We found that the total amount of shifts in FOV  was associated with hyperactivity-impulsivity , but not inattention . To illustrate this association, we show the shifts in FOV during the task for two children; one child with nine symptoms of hyperactivity-impulsivity (the maximum number) and the other free from symptoms—see Fig. Mediation analyses determined whether the associations between ADHD symptoms and observed performance and latent cognitive processes  were mediated by shifts in FOV–see Supplemental Table Turning to inattentive symptoms, their relationship with poor focused attention, mediated through FOV . Similarly, the mediation pathways did not differ significantly between children who were and were not taking psychostimulant medication—see Supplemental Table We asked if other neuropsychological features might act as mediators of the associations between hyperactive-impulsive symptoms and poor focused attention. Significant mediation emerged for processing speed  increased block by block in a linear manner , and the shift in FOV overall was significantly greater in the ADHD group —See Fig. A similar finding emerged for other behavioral measures. Thus accuracy decreased across the five blocks in a linear fashion  and the ADHD group had lower overall accuracy —Fig. Using virtual reality, we show that shifts in a child’s FOV in part explain the link between hyperactive-impulsive symptoms and deficits in focused attention and information gathering. This link was specific as shifts in FOV did not contribute to deficits pertaining to selective attention nor to other latent cognitive processes, such as a conservative response style. While it is not the focus of the current study we also find that processing speed partially explains the same links between hyperactive-impulsive symptoms and both poor focused attention and information gathering.19. Aligned with these models are models that view lapses in attention as arising from a loss in the counterbalanced activity of the brain’s default mode and attention/cognitive control networks26. Such dysregulated inter-network connectivity is thought to cause subjects to repeatedly disengage from task-oriented processing. In turn such disengagement is thought to lead to longer and more variable response times. We find that more variable, slower response times loaded onto a factor reflecting poor focused attention, and this factor was correlated with ADHD symptom severity. It is possible that the increased shifts of FOV we detect in ADHD might also stem from dysregulated interactions between the default mode and task positive networks. Such atypical interactions could cause subjects to disengage in a task and then re-engage their attentional focus elsewhere54.We illustrate how a portable and non-invasive technology can probe the mechanisms linking ADHD symptoms to its associated cognitive profile. In interpreting these findings, we consider neurocognitive models that have been proposed to account for links between symptoms of hyperactivity-impulsivity and deficits in focused attention as well as the reduction in the rate of information uptake observed in children with ADHD. The first models, mentioned earlier, emphasize how deficits in CNS arousal—either pervasive under-arousal or dysregulated arousal—can lead directly to deficits during tasks demanding sustained focus, and to hyperactive, sensation seeking before, as an attempt to boost or regulate anomalous arousal16. In turn this postural instability may reflect cerebellar-cortical dysfunction. In support of this model, Teicher and colleagues showed that children with ADHD exhibited three times as much head movement as typical children during a continuous performance task, and there were diagnostic differences in the patterns of head movement17. However, this study by Teicher and colleagues did not directly examine how the degree of head movement mapped onto specific attentional deficits. We did define these links and show that shifts in FOV due to head movement were tied to deficits in focused but not selective attention. The next step is to define the neural substrates of this finding. Neuroimaging techniques such as Near Infrared Spectroscopy that allow relatively free head movements may be particularly useful in this context55.Others have directly linked anomalies in motor (head) control with attentional deficits, arguing that the head movements that drive shifts in FOV are a facet of postural instability in ADHD17. Similarly, changes in FOV that are caused by dysregulated inter-network connectivity, which in turn are tied to lapses in focus on relevant stimuli, could also result in atypical information gathering.Changes in FOV also mediated the relationship between symptoms of hyperactivity-impulsivity and the rate of information uptake necessary for decision making. Intuitively, shifts in FOV could disrupt the gathering of information, with the underlying deficit perhaps related to postural instability, as argued earlier57. Future studies are needed to determine whether impairments in selective attention might be underpinned by anomalies in this lateral-prefrontal-striatal-collicular circuitry.The current analysis did not show a relationship between shifts in FOV and selective attention, indicating that there are other mechanisms at play. Failures in selective attention, in which a child fails to attend and respond to targets rather than non-targets can be construed as failures in inhibitory control. In turn, deficits in inhibitory control have been linked with the failure of lateral prefrontal cortical centers to provide control over behaviors, such as eye movements, generated at lower striatal and collicular levels58. Perhaps unexpectedly, we find an association between more symptoms of hyperactivity-impulsivity and greater processing speed. We speculate that mediation by processing speed may represent quick decision making that precludes necessary information uptake for correct decision making. Further investigation is warranted to better understand the link between symptoms of hyperactivity-impulsivity, processing speed, and functional and clinical outcomes.Our analysis also pointed to processing speed as a partial mediator for the associations between symptoms of hyperactivity/impulsivity and poor focused attention as well as information uptake. Deficits in several measures of processing speed have been observed in children with a primarily inattentive, but not combined, ADHD subtype21. Deficits in effort are thought to be reflected in the rapid decline in performance seen over long, demanding tasks such as the CPT3. However, we did not find that ADHD was tied to a more rapid decline in performance, nor to a more rapid increase in shifts in FOV. Rather the deficits relative to unaffected controls were maintained at an essentially constant level throughout the task. This pattern—a difference in intercepts, but not slopes—argues that ADHD is not characterized by a more rapidly exhausted capacity for effortful self-control; rather there is a ‘fixed’ deficit which is immediately apparent and not exacerbated by time on task59. However, it is also possible that our virtual classroom, with its many extraneous distractors, served to activate the arousal system. The use of a version of the CPT without any such distractors might be better suited to detect time-on-task effects, particularly those tied to ADHD.It has been speculated that individuals with ADHD have deficits in several ‘energetic’ pools: phasic alertness , energy used to meet task demands (effort) and tonic changes in processes impacting response speed (activation)62. Secondly, some participants with ADHD were treated with psychostimulant medication, which can affect performance on the CPT acutely63. To mitigate the possibility of this medication confounding results, it was stopped a day prior to testing. Additionally, our moderation analyses found that usual treatment with psychostimulants did not impact the overall pattern of results. Thirdly, the age range included in the study spans significant developmental variation in cognition. We did not, however, find moderating effects of age on the mediation results—see Supplemental Table 64.This study has several limitations. First, shifts in FOV might ideally be monitored by combining the measurement of head position with eye-tracking. However, this is technically challenging to implement and head movements appear a more reliable index of how shifts in attention are tied to actionBy identifying a mechanism that mediates the link between ADHD symptoms and deficient focused attention, we provide a possible target for remediation. For example, it follows from the postural instability model that interventions to improve the control of head movement might boost a child’s skill in sustaining attention. Other interventions might include redirecting the child’s FOV to pertinent stimuli, perhaps through continuous feedback on the direction of gaze or head position. In conclusion, we illustrate how virtual reality can probe the mechanisms linking the symptoms of ADHD with its characteristic cognitive profile. Identification of these mediating mechanisms could provide new targets for intervention.Supplemental Info.


Rehmanniae radix preparata is extracted from wine-steaming the Rehmannia root, a scrophulariaceae plant. It has been used for thousands of years with effects of nourishing kidney-yin, benefiting essence and filling marrow based on traditional Chinese medicine (TCM) theory. Rehmanniae radix preparata has antioxidant, antisenescence, anti-inflammatory, and neuroprotective properties. It is the most popular Traditional Chinese medicinal compound (TCMC) used in attention deficit hyperactivity disorder (ADHD) therapy. However, few studies have been conducted exploring the effects and potential mechanisms of Rehmanniae radix preparata alone on ADHD. Recent studies have shown that Rehmanniae radix preparata inhibits spontaneous activity in mice, improves learning and memory in rats following thalamic arcuate nucleus injury, and exhibits antidepressant effects. Catalpol, an active component of Rehmanniae radix preparata, elevates brain-derived neurotrophic factor (BDNF), and attenuates neuronal apoptosis and energy metabolism failure. ADHD is characterized by hyperactivity-impulsivity and impairments in learning and memory. Its pathomechanism is closely related to structural abnormalities in the cortex that is mediated by dysfunction in neuronal development, apoptosis, and energy metabolism. We hypothesize that Rehmanniae radix preparata may be effective at treating ADHD by alleviating neurodevelopmental abnormalities, neuronal apoptosis, and energy metabolism failure. Attention deficit hyperactivity disorder (ADHD) is the most common cognitive and behavioral disorder diagnosed during childhood, and often continues into adolescence and adulthood. The worldwide prevalence of ADHD is 3.4% . It is cADHD is characterized by structural abnormalities in brain, especially the cortex –10. Abno Bencao Tujing (Commentaries on the Illustrations) states that Rehmanniae radix preparata, extracted by wine-steaming the root of Rehmannia, can benefit kidney essence, fill marrow, and enrich the blood.In TCM theory, the brain is defined as “the house of spirit” and “sea of marrow.” The brain marrow is the material basis for the generation of spirit. The brain is formed from marrow that originates from essence stored in the kidney. Thus, the kidney stores the mind, which is related to memory, consciousness, and thinking. TCM therapy supplements the kidney essence, replenishes marrow, and shows positive efficacy and safety in treating neurological and mental diseases, including ADHD . TCM the Pharmacopoeia of China (2010 version). Its molecular formula and weight are C15H22O10, and 362.33, respectively. Extensive research [ via neuroprotection, alleviating energy metabolism failure, and preventing neuronal apoptosis. These properties correlate with the pathogenesis of ADHD. Taken together, we deduced that Rehmanniae radix preparata is a potential therapeutic herb resource for ADHD treatment. Our hypothesis is discussed in this review.Rehmanniae radix preparata possesses several pharmacological properties, such as central inhibition , antioxiresearch  shown thADHD has been linked to dysfunction in several systems, including the dopaminergic , adrenerOther key morphologic features associated with ADHD include significant bilateral decreases in surface area and cortical folding, which results in a smaller cortical volume in children with ADHD . TomohirTranscription factors (TFs) and regulatory proteins (RPs) have timing-critical roles in cortex formation, including proliferation, migration, guidance targeting, and connectivity of neurons. It is widely accepted that classical neurotransmitters, such as dopamine and serotonin, play an early role in controlling neuron number within the prefrontal cortex (PFC). During critical phases of brain development, dysregulation of serotonin and dopamine can have significant consequences for the development of disorders of the PFC, and mediate cognitive impairment –37. via the up-regulation of BDNF [Brain-derived neurotrophic factor (BDNF) is associated with neurogenesis and neuroplasticity in the brain. It is essential for the regulation of neuronal growth, differentiation, and survival . Conditi of BDNF , 41.Tbr2 is required for the specification and proliferation of intermediate progenitor cells in the cerebral cortex during brain development. Reduced Tbr2 expression results in a reduced cortical surface and thickness , 43. In −/− mice exhibit significant hyperactivity [Cyclin-dependent kinase 5 (Cdk5) is a neuronal serine/threonine protein kinase critical to proper neuronal migration, corticogenesis, and the regulation of postsynaptic dopamine signal integration. Mice deficient in Cdk5 display severe defects in cerebral cortex formation , 48. Micactivity .N-methyl-D-aspartate receptors (NMDARs) are involved in the maturation of cortical neurons and in early synapse formation . NMDAR aIn summary, neurodevelopmental disorder-associated factors are involved in cortical development and maturation and sculpt the identity of cortex. Much evidence has shown that disturbed TFs and RPs are significant factors in the complex pathogenesis of ADHD. via oxidative phosphorylation, which is carried out by the respiratory chain complexes I, II, III, and V [ via neuronal apoptosis and impaired energy metabolic processes in the brain [ via increased lipid peroxidation and protein carbonylation and reduced antioxidant enzymatic systems, such as superoxide dismutase (SOD) and catalase (CAT) [Mitochondria play a crucial role in (adenosine triphosphate) ATP productionI, and V . AdditioI, and V . Mitochohe brain . In the he brain . The mithe brain . An incrhe brain . Moreovese (CAT) .Some neuropsychiatric disorders, including ADHD, can be viewed as cortical oxygen-dependent energy-deficit syndromes . SufficiEvidence suggests that there is a maturational delay in the development of frontostriatal neural networks in the SHR that is similar to the developmental delay seen in children with ADHD , which i−/− mice exhibit reduced attention control, increased impulsive behavior, and hyperactivity [Few studies have been carried out to validate the connection between apoptosis signaling pathways and ADHD. Strikingly, as a first-line therapeutic drug of ADHD, MPH activates the initial cascade of apoptosis, increasing Bax and reducing Bcl-2; however, it also inhibits apoptosis by reducing caspase-3 and cytochrome c . One stuactivity . vice versa. TCM theorizes that if this relationship changes beyond normal limits, the dynamic balance of yin and yang will not be maintained, and result in an excess or deficiency of yin or yang and the occurrence of diseases.According to TCM theory, the yin and yang are summarized as the two opposite aspects of interrelated items or phenomena in nature. The yin masters calmness and the yang masters movement. Yin-yang theory holds that the yin and yang are opposing and constraining; interdependent and mutually promoting each other. Physiologically, normal life activities of the human body result from the coordination between the yin and yang in a unity of opposites. Additionally, the yin and yang wane and wax in relation to each other; the waning of yin will lead to waxing of yang andThe theory of TCM argues that the kidney stores the essence that governs the mind. This kidney essence comes from parents and replenished by food-essence that is transformed by the spleen and stomach. Physiologically, the kidney contains insufficient essence in children, leading to immature function. Pathologically, congenital factors, such as premature labor, dystocia, injuries during birth, and low birth weight, are primary risk factors for a deficiency in kidney essence and can induce a reduction in blood flow, which may result in inadequate CBF related to ADHD. The literature examining the association of ADHD with pregnancy and delivery supports the idea that these adverse events can predispose children to ADHD .n = 72) was a “deficiency in kidney essence and marrow in the brain”. Ma and colleagues first proposed the hypothesis that there might be a maturational lag in the development of brain marrow, which was implicated in ADHD. They proposed that the deficiency in kidney essence, maturational retardation of marrow, and imbalance of yin and yang were the pathomechanisms of ADHD [The essence pertains to yin; therefore, a deficiency in kidney essence may lead to a relative and pathogenic exuberance of yang. This may affect mental activities and cause hyperactive and impulsive behavior. TCM theory states that the kidney also manufactures marrow, which originates from essence, gathers in and nourishes the brain ultimately. The brain is seen as the “the sea of marrow” and “the house of spirit” in TCM theory. It is associated with memory, consciousness, and thinking; therefore, a deficiency in kidney essence can lead to a reduction in debilitation brain marrow, resulting in attention deficits. Importantly, TCM theory argues the close connection between kidney essence, marrow, and the brain. Inadequate storage of kidney essence is the key pathogenesis in ADHD. This theory is supported by a cross-sectional retrospective study from Li and colleagues  who expl of ADHD . This hy−1; n = 51, 86.27%), with few side effects [Based on the syndrome differentiation, the deficiency in kidney essence and brain marrow suggests that ADHD therapy should supplement the kidney and replenish the essence. Chinese herbal medicine (CHM) formulae including prescriptions of several herbs, animal drugs, or minerals, to supplement the kidney and replenish the essence have been applied to clinical treatments of ADHD, for example, Yizhi Ningshen Granule, consisting of Rehmanniae radix preparata, Polygalae radix, and Rhizoma Acori Tatarinowii. In a randomized trial of 8 weeks treatment, children with ADHD (n = 55) treated with Yizhi Ningshen Granule had a higher effective percentage (90.91%) when compared with the MPH-treated group 10–20 mg·d effects . Similar effects , Xiaoer  effects , and Yiz effects  can suppLi has interpreted the modern biological basis of “kidney manufacturing marrow and the brain as a sea of marrow,” proposing that the nature of “brain marrow” is neurons and neurotrophic factors in the brain. A “deficiency in brain marrow” is caused by atrophy, loss of neurons, and decreased neurotrophic factors in the brain, resulting in cognitive impairment and neurodegenerative diseases, such as dementia. The modern biological basis of “supplementing the kidney to replenish marrow” includes improving the neuronal energy metabolism and utilization, enhancing endogenous neurotrophic effects, and decreasing the production of neurotoxins, therefore, reducing cell death and increasing the survival and regeneration of neurons . CHMs arThere are many effective CHM formulae used by TCM physicians to treat the different syndromes of ADHD in children . We perfβ) and a glutamate receptor agonist [β1–42 through a mitochondrial-dependent caspase pathway [(CSF)/AUC(plasma) of 5.8% and half-life (t1/2) of 1.5 h [Rehmanniae radix preparata can improve learning and memory function in rats with injured thalamic arcuate nuclei, induced by monosodium glutamate (MSG), by increasing the expression of hippocampal c-fos and nerve growth factor (NGF) . Rehmann agonist . Catalpo pathway . Catalpo pathway , 90. Mea pathway , 92. A sof 1.5 h .Overall, the structural abnormalities of the cortex play an important part in the pathomechanism of ADHD, which involves neuronal development disorders, neuronal apoptosis, and energy metabolism disorders. TCM theory argues that a deficiency in brain marrow induced by kidney essence results in symptoms such as hyperactivity, impulsive behavior, and attention deficit. The mechanisms of these are highly analogous to structural abnormalities in the cortex. The therapeutic principle of “supplementing the kidney and replenishing the essence” has been applied to clinical treatments of ADHD widely and proved effective and safe.Catalpol is the active ingredient of Rehmanniae radix preparata that is neuroprotective, antiapoptotic, and can attenuate energy metabolism failure. Rehmanniae radix preparata and catalpol can be used to benefit many neuropsychiatric disorders. Considerable evidence points to the important role of Rehmanniae radix preparata and catalpol in treating ADHD; however, they have not been used in studies assessing novel treatments for ADHD. via the effects of neuroprotection, antiapoptosis, and attenuating energy metabolism disorders. This may lead to the reversal of structural abnormalities in cortex (Coupled with recent evidence, we postulate that both Rehmanniae radix preparata and catalpol are promising natural medicines for the treatment of ADHDn cortex . Based o


Lactobacillus levels to be reduced. Also, we assessed nutritional influences, such as breastfeeding, ingestion of short-chain fatty acids (SCFAs) and polyunsaturated fatty acids (PUFAs) on the host′s microbiome and development of ADHD. Finally, we discussed the potential significance of Bifidobacterium as a biomarker for ADHD, the importance of preventing premature birth as prophylaxis and nutrition as a prospective therapeutic measurement against ADHD.The latest research cumulates staggering information about the correlation between the microbiota-gut-brain axis and neurodevelopmental disorders. This review aims to shed light on the potential influence of the microbiome on the development of the most prevalent neurodevelopmental disease, attention-deficit-hyperactive disorder (ADHD). As the etiology and pathophysiology of ADHD are still unclear, finding viable biomarkers and effective treatment still represent a challenge. Therefore, we focused on factors that have been associated with a higher risk of developing ADHD, while simultaneously influencing the microbial composition. We reviewed the effect of a differing microbial makeup on neurotransmitter concentrations important in the pathophysiology of ADHD. Additionally, we deduced factors that correlate with a high prevalence of ADHD, while simultaneously affecting the gut microbiome, such as emergency c-sections, and premature birth as the former leads to a decrease of the gut microbial diversity and the latter causes neuroprotective  It has been estimated that over 10I-tract) . The micI-tract) , and alsI-tract) .Research highlights this risk, as gut dysbiosis in child or adulthood has not only been associated with various diseases, such as irritable bowel syndrome  or obesiADHD is an early onset neurodevelopmental disease that, according to the fifth edition of Diagnostic and Statistical Manual (DSM-V), can be characterized into different representations: Hyperactivity and/or impulsivity, inattentiveness or all combined . The worThis literature review attempts to identify and discuss factors that may influence the microbiome, and thus, could be associated with the development or progression of ADHD. Thereby we concentrate solely on the influence of bacteria rather than archaea and eukaryota. Furthermore, we evaluate the biochemical changes in ADHD patients and to what extent these can be related to microbial alterations in the gut. Finally, we reconfirm known biomarkers and deduce possible new ones for the diagnosis of ADHD and conclude what factors worsen or alleviate the development and progression of ADHD as this might lead to potential intervention methods of the neurodevelopmental disorder.The key research question of this literature review is: What factors may influence the microbiome and could be associated with the development and/or progression of ADHD? The databases Pubmed and Scopus were searched until the 1 July 2019 with the following MeSH and search terms: “Microbiome”, “microbiota”, “gut-brain axis”, “microbiota-gut-brain-axis”, “ADHD”. Most of the research papers included in this review were published between 2010 and 2019.Articles were directly related to the topic;ADHD patients were diagnosed by a medical expert;Publication in a peer-reviewed journal;Availability of the full-text publication;Studies were written in English.As our primary focus was on bacteria, we excluded studies that concentrated on archaea and eukaryota. The incorporated studies had to fulfill all of the following inclusion criteria: A total of 208 citations were included in this article.2 cells per gram of content in the stomach to 108 cells per gram in the cecum [The influence of the microbiome on the ADHD pathophysiology is being intensively researched. The microbiota consists of the different microorganisms , and thehe cecum . Additiohe cecum . Therebyhe cecum , geographe cecum , diseasehe cecum , and agehe cecum .Escherichia coli and Neisseria lactamica, while Bacteroidetes is dominated by Bacteroides spp. [Mycoplasma and Ureaplasma [The GI-microbiota goes through a physiological change from its prenatal period until the age of three . For a ldes spp. . Other ides spp. , wherebyeaplasma .Escherichia coli and Actinobacteria by the genus Bifidobacterium longum [The colonization of the gut in the postnatal period is sensitive to environmental factors. Nonetheless, the normal composition of the microbiome in a newborn is low in diversity and shows dominance in Proteobacteria and Actinobacteria . More spm longum . As seenm longum .The gut-brain axis describes the bidirectional communication between the microbes, enteric nervous system and the CNS . So far,The neural pathway describes the hypothalamic-pituitary-adrenal axis (HPA axis), which is the most important efferent stress pathway. It is of great importance to understand to what extent the HPA axis plays a role in the pathogenesis of ADHD, as it influences pathways in the body that are often deviating in ADHD patients ,40 as foOne study using 69 healthy children and 123 children with ADHD observed an increase in salivatory cortisol in ADHD patients after waking up in the morning . The effThe neuroimmune communication pathway describes how intestinal microbes influence the function and maturation of immune cells in the CNS, whereby microglia cells play an important role . These cThe enteric nervous system communicates with the brain mainly through the parasympathetic vagus nerve , and parIt has become clear that all three ways of communication between the microbiome, gut, and CNS could play an important role in the pathophysiology of ADHD. The neural communication over the HPA axis shows abnormalities in ADHD patients. Additionally, studies detected that microbes influence the function of pro-inflammatory microglia, a key finding, as neuroinflammation in ADHD patients is commonly found. Finally, the autonomic nervous system shows aberrations as the main research results show an under-arousal of the parasympathetic nervous system.As the exact pathophysiology of ADHD is still unclear, its causes are still being researched. Nevertheless, it has been established that there is an interplay between genes and the environment resulting in a complex etiology. Genetic predisposition plays an important part in the pathophysiology of ADHD as children from parents that have been diagnosed with ADHD have a 50% higher chance to be diagnosed with the same disorder . SimilarResearch shows that the dysfunction of monoaminergic neurotransmitters, including noradrenaline (NE), serotonin (5-HT) and dopamine (DA), plays an important role in the pathophysiology of ADHD .DA is a catecholamine that acts both as a hormone and neurotransmitter (NT). It is a product of the essential amino acid L-phenylalanine, which must be provided in our diet. As seen in The dopamine hypothesis links ADHD to alterations in dopamine metabolism. The hypothesis describes the increased expression of presynaptic dopamine transports (DAT) in ADHD patients leading to an increased dopamine transporter density (DTD), and finally results in a decreased level of the bioavailable NT . The dopMoreover, recent research shows that not only the metabolization, but also the production of DA plays an important role in the pathophysiology of ADHD. One of the influencers on the production of NTs seems to be the microbiome in the GI-tract . BacteriStreptococcus spp., Enterococcus spp., and Escheria spp. are capable of producing this NT [Upon intestinal absorption into the bloodstream, the essential amino acid tryptophan can cross the blood-brain barrier (BBB). Thereby tryptophan can act as the precursor of the neurotransmitter 5-HT, which plays an important part in the microbiome-gut-brain axis . Althoug this NT . Most of this NT . Meanwhi this NT .Banerjee et al. showed that 5-HT may have an influence on hyperactive and impulsive symptoms in ADHD . AnotherTo demonstrate the importance of microbes on the 5-HT system, one study concluded that GF male mice have a 1.3 fold increased level of 5-HT in their hippocampus. This is an important finding as certain therapeutic medications of ADHD, such as escitalopram and lithium increase serotonin levels in a similar amount . Thus, tAlthough the studies do not allow us to make a precise conclusion in what way bacterial-produced 5-HT influences ADHD, they do make it clear that it is one of the several catecholamines that play an important role in the pathophysiology of ADHD.Although tryptophan is the key amino acid for the production of 5-HT, 90% of tryptophan is catabolized by the kynurenine pathway . This prIntermediate products, such as kynurenine, kynurenic acid (KA), xanthurenic acid (XA) and quilonoic acid (QA) can influence the immune system and neurotransmission . The thrStudies regarding levels of tryptophan and metabolites of the kynurenine pathway show inconclusive results. A Norwegian study, using 133 adult ADHD patients and 133, did not find that the ADHD group had lower levels of tryptophan and neuroprotective KA and XA . These dThe various steps of the kynurenine pathway are dependent on coenzymes, such as the activated form of vitamin B6, pyridoxal 5′-phosphate (PLP). One study found an inverse correlation between serum levels of vitamin B6 and ADHD including its symptom severity . SimilarHigh variability in gut flora prevents the growth of pathogenic bacteria, and thus, stops gut dysbiosis . The terAn imbalance of pro-inflammatory cytokines can also lead to allergic disease , and a pDialister spp. [Dialister spp. is shown to correlate with an altered temperament and impulsiveness in toddlers positively. These commonly found ADHD symptoms were measured using the Early Childhood Behavior Questionnaire (ECBQ), which measures extroversion, activity levels and feelings of high-intensity pleasure [Dialister spp. in comparison to healthy controls (HC), hinting towards decreased feelings of activity and lower levels of intense pleasure, and finally higher levels of IL-6 [An important pro-inflammatory cytokine is interleukin (IL-6). This has been inversely associated with the bacterium ter spp. . Dialistpleasure . Furtherpleasure . Nonethe of IL-6 .Dialister spp. and feelings of pleasure are new findings; and it is important to note that pro-inflammatory interleukin levels are increased in ADHD patients. As high levels of pro-inflammatory interleukins can be linked to neurological inflammation that can lead to a decrease of cortical volume and altered behavior [Although the association between behavior ,112, redFaecalbacteria spp. In the gut [Feacalbacteria spp. Cause an increase of inflammation which affects the development of the brain, and finally the pathogenesis of ADHD.Patients with th2-mediated atopic disorders, such as eczema, asthma and allergic rhinitis have a 30–50% higher chance of developing ADHD . Eczema  the gut . This sp the gut ,120. As As infants delivered by vaginal birth move through the birth canal, they get colonized by their mother′s vaginal microbiota, and thus, adopted a resembling gut microbiome. In contrast, infants born via c-section are colonized by the microbiota of their mother′s skin. Therefore, the delivery mode affects the composition of the gut microbiota in infants .Bifidobacterium spp. and Bacteroidetes, but increased levels Clostridium difficile [Results of various studies showed that in comparison to vaginally born infants, babies delivered by c-section had a decreased gut microbiota diversity including lower levels of ifficile  up untilifficile .Several research groups studied the correlation between c-section delivery and ADHD see . An animThe reasons for finding a positive correlation between intrapartum c-sections and ADHD development cannot unequivocally be explained as multiple confounders, such as unobserved familial factors, birth weight or gestational age also directly influence the mode of delivery and ADHD. However, there is a strong indication that the microbiota plays a subordinate role in this correlation as Axelsson et al. discovered that exposure of the newborn to ruptured vs. non-ruptured membranes prior to c-section did not influence the correlation between c-section and ADHD development . To conclude, the accumulative data show that the mode of delivery affects the composition of the gut microbiota. However, a clear correlation between c-section delivery and a higher chance of developing ADHD cannot be found as results depend on various confounders and the type of c-section, whereby intrapartum c-sections show a positive correlation with the development of ADHD in comparison to elective c-sections.A prospective follow up study, and a Dutch population-based cohort study concluded a correlation between prenatal maternal stress exposure and an increase in ADHD in their offspring ,133. ThiLactobacillus spp. [Lactobacillus spp. was also significantly decreased in the distal colon of the offspring of stress exposed mothers. Additionally, a review focusing on the immunomodulatory effects of Lactobacillus spp. shows that stress reduces the abundance of this species independent of the host being pregnant or not [Lactobacillus spp. is important for the synthesis of acetylcholine, while together with Bifidobacteria spp. it is contributing to the production of the main inhibitory neurotransmitter GABA [An animal study using quantitative PCR determined that maternal stress significantly decreased one of the most abundant taxa in the maternal vaginal flora, lus spp. . Consequt or not . Lactobater GABA . Alteratter GABA . Lactobacillus rhamnosus also has a preventive effect as the administration of this bacterium in the first six months of life reduced the risk of ADHD and Asperger Syndrome (AS) [Lactobacillus rhamnosus is, on the one hand, implicated in the development of tight junctions responsible for a strong gut barrier, and on the other hand, important for the immunoglobulin A and mucin production [As described above, several studies have associated low levels of cerebral GABA concentrations with symptoms of ADHD ,140,141.ome (AS) . The posoduction .Lactobacillus spp. and decreased concentrations of GABA are associated and how they precisely affect the development of ADHD remains unclear and has to be thoroughly investigated.Various factors influence the development of ADHD, among which the neuroinhibitory neurotransmitter GABA seems to play a crucial role. However, to what extent low levels of Lactobacillus spp. [Proteobacteria spp., while discovering undetectable levels of Lactobacillus spp. and Bifidobacteria spp. [Lactobacillus spp. show a protective trait towards the CNS. Preterm babies received strains of Lactobacillus reuteri and Lactobacillus rhamnous as probiotics for six weeks. This treatment resulted in a significantly reduced number of babies with neurological aberrations at one year of age in comparison to the group fed with Lactobacillus acidophilus and Bifidobacterium infantis [Preterm babies that, thus, have gone through stressful situations similarly show lower levels of lus spp. , and simlus spp. ,145,146.ria spp. ,147. Choinfantis .It is widely known that preterm infants own an immature immune system as the innate and adaptive immune system has not developed fully. Due to their immature immune response and their usual extended hospital stay, infants are highly susceptible to nosocomial spread infections . The incAs the prevalence of infection in premature newborns is high, the use of therapeutic antibiotics is similarly increased. Antibiotics have been associated with altering functions in the host′s brain , while sTo summarize, a preterm baby is exposed to increased levels of stress, may have underdeveloped brain structures and owns an immature immune system. All of these result in a higher susceptibility to infections, and finally may lead to increased exposure to therapeutic antibiotics. These factors influence the neurodevelopment either directly through inflammatory processes during infections or indirectly by changing the composition of the gut microbiome.Bifidobacterium [Studies have associated breastfeeding with a lower prevalence of ADHD . In contacterium ,164,165.Escherichia coli, Clostridium difficile, Bacteroides spp. and Lactobacilli [Lactobacillus acidophilus [Streptococcus, Veillonella parvula [Clostridium coccoides [Bifidobacterium is the most prevalent genus found in both groups, breastfed infants show more than double of Bifidobacteria cells in comparison to formula-fed infants [Bifidobacterium infantis has protective properties against pathogens as it supports the barrier function of the mucosa and concurrently has anti-inflammatory properties, thus, promotes a healthy immunological response [A systematic review by Guaraldi et al. showed that bottle-fed infants have a higher number of obacilli . As seendophilus , Strepto parvula , and Clooccoides , were fo infants . Bifidobresponse ,168.Although the effect on the microbial composition could be the main cause of developing ADHD when being formula-fed, one has to consider the fact that other ingredients in the formula may also act as important influences. One study found that there were more cases of ADHD in formula-fed infants in 2007, than in December 2011. During the latter, the neurotoxic chemical Bisphenol A (BPA) was significantly reduced in formula cans and baby bottles in comparison to the former, suggesting that BPA might be the actual trigger of the correlation .In summary, studies show that breastfeeding correlates negatively with the risk of developing ADHD, whereas formula-feeding increases this risk. Nevertheless, despite the highly nutritious content of breast milk, the gut microbiota of breastfed infants seems less diverse, but still contains the same or higher amount of protective components than formula-fed infants. Thus, alteration of the microbiome composition could potentially be a reason for the positive correlation between formula-feeding and the risk of developing ADHD.Bacteroides spp. and Clostridiae spp., are two of the most important microbes for the production of SCFAs [SCFAs are products of polysaccharides which could not be properly digested by the human digestive system, and thus, are broken down by microbial fermentation. Bacteria, such as of SCFAs . SCFAs rof SCFAs ,171. A sof SCFAs . Besidesof SCFAs .As ADHD, similar to autism, is a neurodevelopmental disease, it seems likely that SCFAs may affect the development of ADHD. Research shows that SCFAs influence the immune system, and as discussed earlier, this can influence the CNS . An animBesides hypothesizing a compensatory mechanism in ADHD children, a potential reason for these differing results could be varying methodology as Akay et al. measured BDNF levels in the serum, known to have a higher BDNF concertation in comparison to the plasma .In conclusion, SCFAs most probably affect the development of ADHD indirectly by influencing the production of BDNF.Another regulator of BDNF seems to be omega-3 polyunsaturated fatty acids (PUFAs). PUFAs are long chains of carbon atoms characterized by a carboxyl group at one end and a methyl group at the other end. As they are unsaturated, they own one or more double bonds between the carbon atoms. Naturally, plant and fish oils, such as flaxseed or salmon have a high content of omega-3 PUFAs . PUFAs pEnterobacteria and Bifidobacteria, which both strengthen intestinal permeability, reducing the risk of inflammation [An animal study showed that omega-3 PUFAs did not only affect the levels of BDNF, but also of glial cell-derived neurotrophic factor (GDNF). The latter is especially important for the recovery of dopaminergic neurons in Parkinson′s disease (PD) as it promotes the survival of the dopamine system in the nigrostriatum. Hence, GDNF is shown to be neuroprotective and supporting dopaminergic neurons in PD models, and thus, could potentially be utilized as a therapy against neurodegenerative diseases, especially PD ,184. Furammation . Finallyammation . Neverthammation ,190.Human studies have discovered a negative correlation between patients with ADHD and levels of PUFAs. An Italian study examined the levels of PUFAs in the blood of 51 ADHD and 22 non-ADHD patients. PUFA levels in the blood of ADHD patients were significantly lower and correlated with behavioral symptoms, but were not associated with cognitive skills . SimilarMoreover, a double-blind trial  assessedBifidobacterium roseburia and Lactobaccilus spp., all of which are important for the production of SCFAs and maintain an anti-inflammatory environment [Lastly, on a microbial level, an RCT showed that the intake of PUFAs does not seem to affect the alpha or beta diversity of the microbiota of the participants. Nevertheless, it did show a reversible increase in genera, such as ironment . Similarironment .Although the collected data show inconclusive results concerning the effect of PUFA supplementation as a therapeutic measurement for ADHD, the indirect effects of ingesting PUFAs and its impact on the microbiome may as well be crucial determinants that could modify the metabolism and consequently the behavioral and cognitive symptoms of ADHD.Enterobacter, Klebsiella, Citrobacter, and Pseudomonas and decrease anaerobic bacteria [Bifidobacteria in the first couple of months of life [Bifidobacteria, but also of Bacteroides when infants administered antibiotics [Although the development of antibiotics has made it possible to treat life-threatening infections, the use of antibiotics reduces the microbiota diversity in the GI-tract . Consequbacteria . For exa of life . Supportibiotics .Results concerning the correlation of early antibiotic use and later risk of developing ADHD seem to be incoherent. A Danish population-based cohort study did not find an association in sibling-stratified Cox model between antibiotic use in the first two years of life and the risk of developing ADHD . AnotherBy definition of the FAO/WHO probiotics are ”live microorganisms which when administered in adequate amounts confer a health benefit on the host” . BenefitBifidobacterium longum and breve led to a reduction of depression and anxiety symptoms [The influence of probiotic strains on psychiatric diseases has been examined by multiple studies, concluding a positive effect on such illnesses and are, thus, described as “psychobiotics” . An animsymptoms .Lactobacillus rhamnosus into 75 infants. The infants were monitored at three weeks, 3, 6, 12, 18 and 24 months, and finally, at 13 years of age. The authors concluded that at the age of 13 years, ADHD was diagnosed in 6/35 (17.1%) children using the placebo, whereas no children had this disorder in the probiotic group. These results, even if encouraging, do not identify any specific composition of the microbiota to the neurodevelopmental disease, and thus, might mean that probiotics decrease ADHD in a different way rather than influencing the composition of the microbiome [The seminal study by Pärtty et al. researched the effects of probiotic use on the development of ADHD in children by randomly administering strains of crobiome . HoweverBifidobacterium, belonging to the phylum Actinobacteria, seems to play a significant role in the pathogenesis of ADHD and is recurrently influenced by several factors. Bifidobacteria do not only protect the barrier function in the gut and support a healthy immune response [Bifidobacterium was decreased in offspring that were born (i) via c-section delivery  elivery (,198. Allpatients , Aarts epatients . Thus, fAdditionally, this article concludes that the concertation of neuroprotective BDNF, indirectly influenced by the microbiome , plays aIt is widely known that c-section delivery causes the offspring′s microbiome to be more similar to the mother′s skin rather than her vaginal flora. However, it is still under debate to what extent this change impacts the development of ADHD. We decided to concentrate on the more recent papers, that used a large sample size and a precise methodology by differentiating between elective and emergency c-sections. These studies show that not every c-section increases the risk of developing ADHD, but only those that were done intrapartum ,130. AltLactobacillus [Additionally, it has become increasingly clear to what extent prematurity plays a role in the development of ADHD. As the GI-tract and its colonization with bacteria are still underdeveloped, the microbiome shows lower levels of neuroprotective bacillus . Nonethebacillus . Thus, fTo determine to what extent the microbiome plays a role in the pathophysiology of ADHD, further studies are needed. We discussed several triggers that have been associated with ADHD, how these correlate with an altered microbial composition, and thus, how various microbes might act as possible biomarkers for ADHD. Further research, on the microbial composition of ADHD patients using large, well-diagnosed cohorts is needed in order to find future conclusive biomarkers and therapeutic methods to treat ADHD.