It is far from conclusive what distinguishes the inattentive (ADD) and the combined (ADHD-C) subtype of ADHD on the neuronal level. Theoretical considerations suggest that especially interval timing processes may dissociate these subtypes from each other. Combining high-density EEG recordings with source localization analyses, we examine whether there are ADHD-subtype specific modulations of neurophysiological processes subserving interval timing in matched groups of ADD (n = 16), ADHD-C (n = 16) and controls (n = 16). Patients with ADD and ADHD-C show deficits in interval timing, which was correlated with the degree of inattention in ADD patients. Compared to healthy controls, patients with ADHD-C display a somewhat weaker, yet consistent response preparation process . In patients with ADD, the early CNV is interrupted, indicating an oscillatory disruption of the interval timing process. This is associated with activations in the supplemental motor areas and the middle frontal gyrus. Patients with ADD display adequate feedback learning mechanisms , which is not the case in patients with ADHD-C. The results suggest that altered pacemaker-accumulation processes in medial frontal structures distinguish the ADD from the ADHD-C subtype. Particularly in patients with ADD phasic interruptions of preparatory neurophysiological processes are evident, making this a possible diagnostic feature. Deficits in executive control are common in patients with ADHD4. They affect multiple domains of everyday functioning8 and are likely to emerge from structural abnormalities in medial/superior frontal and basal ganglia structures11 as well as from dysfunctions in the dopaminergic system14. However, ADHD is not a homogenous disorder, but patients can be classified as belonging to the inattentive, the hyperactive/impulsive or the combined ADHD subtype depending on symptomatology. The inattentive (ADD) and the combined (ADHD-C) subtype are the most prominent16. Despite the fact that research has made considerable progress in the understanding of neuronal mechanisms differing between ADD and ADHD-C17, the picture showing what dissociates these subtypes is far from clear.Attention Deficit Hyperactivity Disorder (ADHD) is one of the most prevalent neuropsychiatric disorders in childhood25. These studies examine how well patients with ADHD are able to dissociate different durations of presented stimuli or how well they are able to perform motor actions after a particular time interval has passed . Studies on interval timing show dysfunctions in ADHD, which is plausible since dopaminergic mechanisms and frontal-striatal networks - which are affected in ADHD - are central for such processes27.One important cognitive function that has attracted considerable research interest in ADHD refers to ‘time estimation’ and ‘interval timing’28. Conceptual accounts (i.e. pacemaker-counter models)30 as part of the striatal beat-frequency theory (SBF) explaining timing and time perception processes hold that attention and arousal can speed up or slow down timing by closing or opening a switch that allows pulses generated by an “oscillating clock” to be counted31. A faster running “clock” makes time intervals seem longer and it has been suggested that this is the case in ADHD24. As both attention and arousal have been suggested to be modulators of the “clock”, patients with different subtypes of ADHD can be expected to show differential interval timing abilities. An attention deficit (as it is common to patients with ADD and ADHD-C) alone would already result in dysfunctions time estimation skills. The hyperactivity/impulsivity occurring solely in patients with ADHD-C significantly increases fluctuations of arousal34 and thus very likely represents an additional influence on time estimation abilities in this group. Overall, we thus expect for time estimation abilities to vary between the two ADHD-subgroups as the interaction between attention and hyperactivity/impulsivity leads to qualitative differences mainly in arousal.However, the important and yet unanswered questions are (i) how neurophysiological processes and associated functional neuroanatomical structures are modulated on occasions where the production of time intervals is successful in ADHD and (ii) in how far this makes it possible to distinguish between ADHD subtypes. This is of clinical relevance since it has been suggested that time estimation processes are indeed useful to distinguish between ‘real ADHD’ and ‘pseudo-ADHD’35. The CNV has been shown to be a correlate of interval timing functions as it reflects expectancy36 and processes reflected by the CNV are known to be dysfunctional in ADHD37. We hypothesize that the pattern of the CNV differs in patients with ADHD compared to controls. Aside from simple amplitude differences, differences in the temporal course of the CNV could occur between the different ADHD subtypes. Especially the early time periods of the CNV immediately following the presentation of a stimulus indicating the beginning of a preparatory/timing processes have been linked to modulations by arousal and attention38. Thus, subtype-specific modulations should especially occur in these early phases of interval timing. Since the early CNV involves the supplementary motor area and the anterior cingulate cortex (ACC)38 and these areas have been shown to be important for interval timing functions26, we expect group dependent modulations to be associated with these areas.Neurophysiologically, processes relevant to interval timing are reflected by the ‘contingent negative variation’ (CNV)39. These are usually driven by external feedback to adjust processes subserving interval timing40; i. e, the theoretical concepts stress that reinforcement learning processes are needed to adjust and select the set of neuronal oscillators that best represent event duration. Such feedback processes are reflected by the feedback-related negativity (FRN). The FRN is affected by the dopaminergic system41 and these processes have been shown to be dysfunctional in ADHD43. It is therefore central to examine whether differences between ADHD-subtypes in interval timing processes may rather be explained by altered integration of external feedback during early phases of interval timing.However, while theoretical concepts stress the role of attention and arousal in early phases of interval timing, learning mechanisms may also play a very important roleResponse  = 67.8; p ≤ 0.001; ηp2 = 0.75), showing that significantly more responses were given in the correct time window than too early or too late (both p ≤ 0.001). More errors occurred due to too early than due to too late responses (p = 0.02). We found a significant Response*Group interaction  = 4.24; p = 0.003; ηp2 = 0.16). Further analysis showed that participants in all three groups displayed more correct than early  or late responses . In healthy controls and patients with ADD, the number of too early and too late responses did not differ significantly (p > 0.2). Only participants with ADHD-C responded too early more frequently than too late (p = 0.02).The behavioral data, i.e. rate of correct (in-time), early and late responses is given in Table 44. We found a negative correlation  between the number of correct responses and the severity of inattention in patients with ADD only. None of the other correlations between accuracy and symptom severity were significant in any of the three groups .We further examined the relations between behavioural performance on the time estimation task and ADHD symptoms as measured by the ADHD Symptom ChecklistAccuracy  = 1.05; p = 0.31; ηp2 = 0.02) or Group  = 0.13; p = 0.88; ηp2 = 0.01) and no interaction between these factors  = 0.21; p = 0.81; ηp2 = 0.01). All analyses containing the factor Electrode were also not significant . Similarly, the repeated-measures ANOVA of the N1 ERP-component also did not reveal a main effect of Accuracy  = 0.03; p = 0.87; ηp2 = 0.01) or Group  = 0.31; p = 0.74; ηp2 = 0.01) or an interaction between them  = 1.0; p = 0.38; ηp2 = 0.04). All analyses containing the factor Electrode were also insignificant .The P1 and N1 ERP-components are shown in Fig. Time Window  = 26.9; p ≤ 0.001; ηp2 = 0.65). Pair-wise comparisons revealed significant differences between the four time windows in all cases  apart from when comparing time windows 1 and 2 (p = 0.09). This indicates a steady increase of the CNV throughout its course. There also was a main effect of Group  = 6.04; p = 0.005; ηp2 = 0.21), with CNV amplitudes being generally more negative in healthy controls compared to patients with ADD (p = 0.003) and ADHD-C (p = 0.008). The two clinical groups did not differ from each other (p = 0.7). Furthermore, we found a significant interaction between Time Window, Accuracy and Group  = 2.5; p = 0.026; ηp2 = 0.15). Analyzing this interaction in more detail, it became apparent that there was no Time Window * Group interaction in error trials  = 1.4; p = 0.21; ηp2 = 0.09) . Therefore, the correct trials were analyzed in more detail.The CNV is shown in Fig. Time Window  = 7.5; p = 0.004; ηp2 = 0.63). The CNV amplitude turned positive in time window 2 (4.4 ± 14.4 µV/m2) compared to time window 1 (−7.3 ± 11.6 µV/m2) (p = 0.002), indicating a phasic activity. The sLORETA analysis comparing time window 1 and 2 within the ADD group revealed activation differences in the supplemental motor areas (SMA) (BA6) and the medial frontal gyrus (BA6). Within the ADD group, the CNV amplitude in time window 4 (−16.9 ± 4.2 µV/m2) was significantly more negative than that in time windows 2 and 3 (0.03 ± 12.4 µV/m2) (both p = 0.001). Such a phasic activity of the CNV (i.e. negative in time window 1 and positive in time window 2) was not seen in ADHD-C patients and controls. Even though there was a main effect of Time Window in controls  = 8.6; p = 0.002; ηp2 = 0.67) and the patients with ADHD-C  = 9.65; p = 0.001; ηp2 = 0.69), it is shown that both groups were not characterised by a positive-going amplitude change between time windows 1  and 2  . In patients with ADHD-C (−17.7 ± 4.2  µV/m2) and the control group (−27.2 ± 4.2 µV/m2), the CNV was more negative in time window 4 than time window 1 . In the ADHD-C group, there were also differences between time windows 1 and 3 (−6.32 ± 14.2 µV/m2) as well as between 2 and 3 .As can be seen in Fig. Group  = 4.03; p = 0.03) in time window 1, showing a significantly more negative early CNV amplitude in healthy controls compared to patients with ADHD-C (p = 0.021) but not when compared to those with ADD (p = 0.61). The two clinical groups did not differ from each other (p = 0.39). In CNV time window 2, the main effect of Group was also significant  = 6.3; p = 0.004): the CNV was significantly more pronounced in healthy controls compared to both patients with ADD (p = 0.005) and ADHD-C (p = 0.034). Again, there were no significant differences between these two patient groups (p > 0.99). The sLORETA analysis revealed differences between the control and the ADD group in the supplemental motor areas (SMA) (BA6) and the medial frontal gyrus (BA6). In CNV time window 3  = 4.14; p = 0.02), the amplitude in the control group (−15.3 ± 18.2 µV/m2) was significantly more negative than that in patients with ADD (p = 0.02), but not when compared to those with ADHD-C (p = 0.3). The difference between the two patient groups was not significant (p = 0.072). No main effect of Group was present in CNV time window 4  = 1.86; p = 0.17).Analyzing between-group differences in the different time windows, we found a significant main effect of Group  = 4.8; p = 0.01): the amplitude difference between correct and error trials was larger in healthy controls (−18.2 ± 11.9 µV/m2) than in ADHD-C patients (4.9 ± 26.9 µV/m2) (p = 0.01). No difference was found between the healthy control group and the ADD patients (−6.8 ± 21.5 µV/m2) (p = 0.40). The two clinical groups did not differ from each other (p = 0.37).The feedback-related negativity (FRN) is shown in Fig. 28. The patients with ADD and ADHD-C performed on a similar level with the only difference being the comparatively low number of late responses in the ADHD-C group. Interestingly, more pronounced symptoms of inattention were associated with fewer correctly timed responses in patients with ADD only. Medication status did not have a significant effect on these results. Importantly, when time production was successful, the neurophysiological data revealed very specific differences between the groups.In the current study we examined time estimation/interval timing processes in children with ADHD with special emphasis on differential modulation between the ADD and the ADHD-C subtypes. We examined the system neurophysiological processes underlying successful time production processes in these groups. In line with previous studies, the behavioural data show clear time production deficits in ADHD compared to controls49, but in the CNV. This suggests that the basic processing of the stimulus indicating to start the timing of the response does not modulate the observed differences between ADHD subtypes. Rather, changes were specific for the timing phase and neurophysiological processes before the timed responses was executed. Most importantly, we observed a multi-phasic pattern in preparatory processes selectively in ADD patients. Initially, the ADD patients and healthy controls showed negative deflections in the CNV that were stronger than in the ADHD-C group  (BA6) and the medial frontal gyrus (BA6). These modulations were observed when contrasting the early time window 1 between controls and ADD patients and also when contrasting brain activation within the ADD group between CNV time windows 1 and 2. These regions have frequently been implicated to play a role in interval timing processes18. Since these regions have also been shown to reveal structural neuroanatomical changes in ADHD11, it may be speculated that the observed changes may reflect an indirect effect of an altered structural neuroanatomy in ADHD. Together, it seems that altered pacemaker-accumulation processes in medial frontal structures distinguish between clinically relevant diagnostic categories; i.e. the ADD and the ADHD-C subtype. It seems that the ADD-specific clinical profile, which is mainly characterized by inattention, underlines the observed modulations. Since differences in timing-related neurophysiological processes have repeatedly been demonstrated in patients with ADHD and we were now able to show very specific differences between ADHD subgroups, this aspect may be incorporated in biomarker-51 and treatment-53 approaches to ADHD.However, thereafter, the ADD group showed a positive deflection about 800 ms prior to the response, which was absent in all other groups. These results suggest that neurophysiological processes supporting time production processes are interrupted in the ADD group. Interestingly, particularly this early period has been suggested to be modulated by arousal and attention39, is unlikely to explain the observed ADHD subtype-specific modulations. Evidence for this comes from the analysis of the FRN. The FRN is affected by the dopaminergic system41 and especially dopaminergic deficiencies may reflect the relevant mechanism behind already observed reductions of the FRN in ADHD43. Importantly, the ADD group did not show reductions in the FRN compared to controls. Such an amplitude reduction was only present in patients with ADHD-C. This shows that there is a double-dissociation between pacemaker-accumulation  and feedback processes in ADD and ADHD-C: In patients with ADD, pacemaker-accumulation processes are altered, while feedback-related neurophysiological processes are intact. Patients with ADHD-C display a consistent and stable preparatory period but do not show an adequate neurophysiological reaction to the given feedback. Therefore, interval timing deficits in ADD are likely to be due their profound inattention and changes in error-feedback processing alone are unlikely to explain differences between ADHD subgroups. It seems that even though error feedback information is processed in a similar manner in patients with ADD and controls, this information is not, or cannot, be used by ADD patients to adjust interval neurophysiological timing processes. Patients with ADHD-C, who are in addition characterized by increased activity and impulsivity, are able to successfully initiate and maintain pacemaker accumulation. Albeit speculative, a possible explanation for this could be that this may act as a counter-mechanism to the inattention and leads to a different pattern than it is the case in patients with ADD.Another theoretically important factor, i.e. learning mechanisms driven by external feedbackIn summary, the study shows that there are ADHD subtype specific modulations in neurophysiological mechanisms subserving interval timing processes in the medial frontal cortex. The results suggest that altered pacemaker-accumulation processes in medial frontal structures distinguish the ADD from the ADHD-C subtype. Only in patients with ADD phasic interruptions of preparatory neurophysiological processes possibly resulting from fluctuations in the tuning to the “clock” are evident, which is in line with theoretical concepts stressing the importance of attentional/arousal processes during interval timing. Such alterations in the tuning of the “clock” are not evident in patients with ADHD-C. Due to the lack of feedback processing, it seems like the “clock” needs to be reset continuously. It is possible that the inherent heightened arousal is what makes adequate performance possible in some cases. Participants’ medication status did not influence these results significantly. This is probably due to the fact that all testings took place in the afternoons when even extended-release medication was no longer effective.44 , parents rated their children in regards to inattention  = −3.6, p = 0.001), hyperactivity  = −8.2, p < 0.001) and impulsivity  = −7.7; p < 0.001), thus confirming ADHD symptomatology and the two subtypes. A group of healthy control children  was included, who did not display symptoms of ADD or ADHD-C according to parental report on the ADHD Symptom Checklist44 . Healthy controls were recruited simultaneously from an in-house data base and via advertisements. None of them had previously participated in a study concerning time estimation. Controls were not included if they presented with acute and/or severe psychiatric or somatic disorders  according to parent report. Healthy controls and the two patient groups thus did not differ in regards to age (p = 0.85) or IQ (p = 0.32). All subjects and their parents or legal guardians provided written informed consent in accordance with the Helsinki Declaration of 1975, as revised in 2008. The study was approved by the local ethics committee of the Medical Faculty of the TU Dresden.In all patients with ADD and ADHD-C, diagnoses had been determined according to established clinical guidelines. This included parent and child interviews, reports from teachers, symptom questionnaires, testing of general IQ level and attention and various medical tests . Patients were only included if they fulfilled diagnostic criteria according to ICD-10 . Patients were excluded if they presented with additional acute and/or severe psychiatric or somatic comorbidities . Overall, 16 patients with ADD  and 16 patients with ADHD-C  were included in the study. Using the ADHD Symptom ChecklistThe task is shown in Fig. 55. Responses given between 1000 and 1400 ms were accepted as correct. Responses given between 400 and 1000 ms after cue onset were classified as early responses. Responses occurring between 1400 and 2000 ms were classified as late answers. In the neurophysiological analyses, the early and late trials are combined to error trials increase the signal to noise ratio in the analysis. Any key press before 400 ms or after 2000 ms was classified as a missed response and not analyzed further. Visual feedback was given after every key press. In the case of correct trials, a green happy smiley and the word “correct” were presented. In the case of early/late trials (including those later characterized as misses), a red sad smiley and the word “too early”/“too late” was presented. The words “did not react” were displayed if no response had occurred within 3000 ms after stimulus onset. Altogether, participants performed 300 trials in three blocks with short breaks in between them. The intertrial interval was randomized between 800 and 2200 ms. All laboratory testings took place in the afternoon (between 2 and 5 pm) on weekdays.Participants were asked to estimate a time of 1200 ms following a visual stimulus (white square on black background) and to press a key at the correct time56. At first, data was stimulus-locked and segmented from 2000 ms before to 3000 ms after target onset. The interval from −200–0 ms before the stimulus was used for baseline correction. To examine whether any differences were present between the groups in early visual processing, we examined the P1  and N1  components over electrodes P7, P8, P9 and P10.EEG was recorded from 60 equidistant passive Ag/AgCl electrodes . Data was pre-processed off-line by down-sampling to 256 Hz. Then, a band-pass filter  was applied and technical artefacts were removed through a raw data inspection. Periodic artefacts  were removed using independent component analysis. This was followed by a segmentation and a baseline correction (see below). Afterwards, an automated artefact rejection procedure was applied to exclude any remaining trials containing artefacts . All data preprocessing procedures combined removed 7 ± 6% of data in the healthy control group, 10 ± 8% in the patients with ADD and 9 ± 7% in the patients with ADHD-C. The proportion of removed segments did not differ significantly between correct and error trials or between the three groups . Thus, in all cases a sufficient amount of trials could be included in further analyses. A current source density (CSD) transformation was used to allow a reference-free evaluation of the EEG data and to identify the electrodes showing the strongest effectsSubsequently, we analysed the preparatory phase before the response . To account for the varying time interval between the stimulus and participants’ responses, the stimulus-locked and baseline-corrected data (see above) was now re-segmented and locked to the given response (segmentation window: −2000 ms to 1000 ms around the given response). In this way, we analyzed the processes immediately preceding the response and still maintain a fixed pre-stimulus baseline for all participants. The CNV amplitude was analysed in four separate pre-response time windows in each of the three groups  at electrode Cz.57.Finally, we examined the feedback related negativity (FRN). Here, the unsegmented data was response-locked (segmentation window: −200–1500 ms around the response) and baseline-corrected to the pre-response interval of −200–0 ms. In this way, we analyzed the activity immediately after the response independent of response time variation and independent of the activation occurring before the actual response. To quantify the FRN, we first determined the peak-to-peak amplitude of the two negative deflections (electrode FCz) following the given response in each group . The FRN was then determined as the difference of this amplitude between correct and error trials58: Within each of the time windows selected by visual inspection, the mean peak amplitude was extracted for all 60 electrodes. Each electrode was subsequently compared against the average of all other electrodes using Bonferroni-correction for multiple comparisons . Only electrodes that showed significantly larger mean amplitudes  than the remaining electrodes were selected. Of note, this pattern of electrodes matched the electrodes found in the visual inspection of the data. In all neurophysiological analyses, trials with correct responses were contrasted with error trials .All choices of electrodes and time windows were validated using a statistical procedure described in59), providing a single solution to the inverse problem60. For sLORETA, the intracerebral volume is partitioned into 6239 voxels at 5 mm spatial resolution. Then, the standardized current density at each voxel is calculated in a realistic head model61 based on the MNI152 template62. It has been mathematically proven that sLORETA provides reliable results without a localisation bias60. Moreover, there is evidence from EEG/fMRI and neuronavigated EEG/TMS studies underlining the validity of the sources estimated using sLORETA63. In this study, the voxel-based sLORETA images were compared between groups and between time windows of the CNV within a group using the sLORETA-built-in voxel-wise randomization tests with 2000 permutations, based on statistical nonparametric mapping (SnPM). Voxels with significant differences  between contrasted conditions were located in the MNI-brain www.unizh.ch/keyinst/NewLORETA/sLORETA/sLORETA.htm.Source localisation was conducted using sLORETA  and the between-subjects factor Group  were used for analysis. The analysis of neurophysiological data contained the within-subject factor Accuracy  and also the between-subject factor Group . The factor Electrode was included whenever necessary . For the analysis of the CNV, we further used the within-subject factor Time Window . One-way ANOVAs and t-tests were used to further examine any main effects or interactions. Pearson correlations were used for correlational analyses. When necessary, Bonferroni- and Greenhouse-Geisser-corrections were applied. In all analyses, medication status did not have a significant effect on results .Mixed effects analyses of variance (ANOVAs) were used to analyze behavioural and neurophysiological data. For the behavioural data, the within-subjects factor The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008.Supplementary Figure 1


Background: Neurofeedback (NF) in children with attention-deficit/hyperactivity disorder (ADHD) has been investigated in a series of studies over the last years. Previous studies did not unanimously support NF as a treatment in ADHD. Most studies did not control for unspecific treatment effects and did not demonstrate that self-regulation took place. The present study examined the efficacy of NF in comparison to electromyographic (EMG) feedback to control for unspecific effects of the treatment, and assessed self-regulation of slow cortical potentials (SCPs).Methods: A total of 150 children aged 7–9 years diagnosed with ADHD  were randomized to 25 sessions of feedback of SCPs (NF) or feedback of coordination of the supraspinatus muscles (EMG). The primary endpoint was the change in parents’ ratings of ADHD core symptoms 4 weeks after the end of treatment compared to pre-tests.Results: Children in both groups showed reduced ADHD-core symptoms . NF showed a significant superiority over EMG . This yielded an effect size (ES) of d = 0.57 without and 0.40 with baseline observation carried forward (BOCF). The sensitivity analysis confirmed the primary result. Successful self-regulation of brain activity was observed only in NF. As a secondary result teachers reported no superior improvement from NF compared to EMG, but within-group analysis revealed effects of NF on the global ADHD score, inattention, and impulsivity. In contrast, EMG feedback did not result in changes despite more pronounced self-regulation learning.Conclusions: Based on the primary parent-rated outcome NF proved to be superior to a semi-active EMG feedback treatment. The study supports the feasibility and efficacy of NF in a large sample of children with ADHD, based on both specific and unspecific effects.Trial Register: Current controlled trials ISRCTN76187185, registered 5 February 2009. Attention-deficit/hyperactivity disorder (ADHD) is a common neurobehavioral disorder in childhood. According to DSM-IV-TR , core symptoms include impaired attention, hyperactivity, and impulsivity . StimulaAmong additional or alternative treatments for ADHD neurofeedback (NF) has gained promising empirical support in recent years. Based on the observation of deviant slow event-related potentials in children with ADHD, feedback of slow cortical potentials (SCPs-NF) aims at improving the neurophysiological profile of children with ADHD by self-regulation of cortical excitation thresholds . SCPs arA recent meta-analysis failed to support NF as an effective treatment for ADHD but this result may reflect methodological weaknesses of the available studies rather than the weakness of NF as such . When thActive control conditions do not control for unspecific effects as the independent variables causing them differ as regards, e.g., to setting, expectation, interaction, time, and effort. For example, medication cannot control for the unspecific effects of time and attention spent concentrating on the challenging self-regulation task, and for the experience of learning with contingent feedback. Double-blind studies which employ a sham condition may provide strong unbiased evidence regarding efficacy and specificity, and thus have clear merits in NF research . To disentangle NF-specific and unspecific effects influencing the outcome of any treatment the choice of a control condition is of major importance . Active research  which maresearch . While dcipation . Anothercipation . Recent cipation . Therefocipation . To induThe aim of this investigation was to assess the effectiveness, specificity and feasibility of SCP-NF in comparison to EMG feedback in a prospective, randomized and controlled study, while neurophysiological data and more detailed learning analyses and correlations with clinical outcomes will be published elsewhere .Figure 1 depicts the design and study flow.Study design, methods, and data analysis plan are described in detail in the study protocol published by Inclusion criteria comprised age from 7 to 9 years, and a diagnosis of ADHD combined type according to DSM-IV TR verified in a semi-structured interview under the supervision of clinical psychiatrists/licensed psychologists . In the As the interventions were considered an add-on to treatment as usual pharmacotherapy for ADHD, Oppositional Defiant Disorder and Conduct Disorder were allowed.Patients were randomly assigned in a 1:1 ratio with varying block size to either the experimental or the control group. This assignment was realized by a computer-generated, web-based tool provided by the Interdisciplinary Center for Clinical Trials (IZKS) Mainz. Randomization was stratified per trial site and sex. Medical consultants rating clinical impairments were blinded. Participants were not blinded, because they were instructed according to their group assignment. Parents were not informed about treatment allocation but as the children were given instructions according to their treatment group, parents could infer their child’s group assignment.Figure 1).After screening, there was a washout period of 2 weeks for children with psychostimulants and 4 weeks for participants with atomoxetine. Pre-tests and post-tests 2 were conducted without medication. After the pre-test, children resumed their medication until completion of post-tests 1. The main outcome therefore was assessed by changes in post-tests 2 compared to pre-tests .SCPs are very slow shifts in the EEG near to 0 Hz, typically generated in an event-related design for several seconds. A negative shift reduces the excitability of the underlying cortical area while a positive shift is understood as inhibition of excitation and/or consummation of energy. As event-related potentials they prepare adequate cognitive as well as motor responses. In the feedback paradigm, participants were prompted to either produce negative (reducing the excitability threshold of the underlying cortex) or positive shifts (inhibition of excitation) in a randomized order. After session 12, the ratio of negativity to positivity trials was increased from 50 to 80%. The convention in SCP training so far has been to train and reinforce both polarities to improve self-regulation, but particularly toward the end focus on that polarity which is thought to be related to the disease e.g., . As the As a semi-active control condition EMG feedback of coordination in the supraspinatus muscles was chosen. Participants were instructed either to contract or to relax the left relative to the right supraspinatus muscle. This protocol was chosen to induce differential EMG control corresponding to the “polarities” comparable to the NF condition, without requiring simple relaxation or tension. This allowed us to use the same device and the same representation of the feedback signal on the screen. We did not choose a standard EMG feedback protocol because the control condition should be as unspecific as possible but include the possibility to learn self-regulation, i.e., the unspecific variable of any biofeedback treatment.All interventions took place in outpatient clinics. Setting, training devices, electrode montage, feedback and transfer trials, number of sessions, transfer exercises, and the possibility to earn tokens were the same in both groups.Figure 2) for each session comprised four blocks of 40 trials each. Each trial lasted for 10 s . In all sessions, the third block operated without continuous feedback; only the sun was shown at the end if the trial had been successful . These trials were part of several measures to carry over self-regulation skills to everyday life:The treatment schedule . The EEG electrode was placed at Cz, referenced against the mastoid behind the right ear. Four electrodes were used to record the vertical and horizontal electrooculogram (EOG) and one electrode behind the left ear was used as ground. EMG was recorded with one electrode per shoulder placed at the upper area of the right and left supraspinatus muscle.EEG and EMG were recorded and fed back with a multichannel amplifier . For training data, EEG was filtered off-line using a 0.01 Hz high cut-off filter (12 dB/octave) plus 50 Hz notch filter, referenced with one mastoid, followed by ocular correction . Data weEach center was guided by a detailed manual to ensure equal handling of participants, testing, and treatment. Center representatives met for an initial 2-day training course and on a regular basis thereafter. Supervision visits took place to guarantee compliance with the manual.a priori as the primary endpoint to avoid residual medication confounds, and to focus on stable or sustained SCP-NF effects). Apart from IQ and cortical self-regulation, a detailed analysis of learning parameters, electrophysiological, neuropsychological outcomes, and 6-month follow-up data will be reported elsewhere.Psychometric properties of all pre-specified measures are reported in The primary endpoint was the parent-rated ADHD symptom severity assessed using the mean global score of the German ADHD rating scale (24). The scale consists of 20 items assessing the severity of inattention, hyperactivity, and impulsiveness. Each item, corresponding to one of the DSM-IV diagnostic criteria, is rated on a 4-point scale .Secondary endpoints were:–Parents’ ratings of ADHD subdomains  responder status assessed by a blinded clinician .–Comorbid symptoms . ANCOVA yielded a significant within-group difference for NF  but not for EMG . Data for all scales at pre-test and post-test 2 are reported in Table 5 (BOCF); for results without BOCF, see Supplementary Table The difference between groups based on teachers’ ratings of ADHD global scores . According to within-group analyses, improvements in global scale, inattention, and impulsivity were observed for NF only, albeit with small effect sizes.Clinicians did not observe significant differences between groups regarding the responder status. At post-test 2 the percentage of responders was 27% (NF) and 26% (EMG). The analysis was limited due to a large proportion of missing values (about 40% of the mITT population in both groups).No difference between groups was observed regarding changes in comorbid symptoms between pre-test and post-test 1, as assessed with parents’ ratings. Children were rated as slightly improved in both groups.p = 0.04, ES = -0.37). While the percentage rank in the EMG group declined from pre-  to post-assessment  it improved in the NF group from pre-  to post-assessment .A significant difference between groups was observed regarding the change in full scale IQ from pre-test to post-test 2  for NF and 4.4 (SD 1.4) for EMG on the 6-point Likert scale.N = 140) 119 AE were reported. At least one AE was reported in 33% of NF participants and 35% of EMG participants. A possible causal relation with the treatment was stated in 4 (6%) of NF participants and 5 (7%) of EMG participants. These children reported headaches , skin reactions , myalgia , and nausea . SAE were reported for two children in each group . One of these children (EMG group) was withdrawn from the study because ADHD symptoms deteriorated.In the safety population . Only the SCP-NF group differentiated between EEG polarities (p < 0.0001), achieving negative mean amplitudes in negativity trials and positive amplitudes in positivity trials. These correct polarities were only achieved in the feedback condition, while the transfer condition did not show significant differences between polarities or groups .For the SCP amplitude averaged over all training sessions, a significant interaction was observed between shift direction  and group  and a group × session interaction . The EMG-NF group achieved higher self-regulation rates compared to the SCP-NF group (p < 0.0001). Post hoc comparisons showed that the SCP-NF group improved significantly self-regulation at post 2, and the EMG group improved performance over sessions, however, there the last session was not different from the first one. For the transfer condition, repeated-measures ANOVA showed a significant main effect of session  but no group × session interaction. The EMG group achieved higher self-regulation rates compared to the SCP-NF group (p < 0.0001). Post hoc comparisons showed that only the EMG group enhanced performance over time .Repeated-measures ANOVA for self-regulation performance during feedback trials revealed a significant main effect of session . Based on BOCF analysis we observed 38% responder after NF and 25% after EMG feedback.t-test (Satterthwaite). Teachers rated symptoms as less severe than parents did (see Table 7).To explore possible reasons for the difference between parents’ and teachers’ ratings we computed an independent samples This is the first randomized controlled clinical trial to investigate the specificity of SCP feedback in children with ADHD, and the largest study on an outpatient ADHD sample treated with NF. We compared two treatments (SCP-NF and EMG feedback) using identical training setups to control for unspecific effects. For the first time in NF research a BOCF approach was used to handle missing data. This study confirmed specific positive effects of SCP-NF on parent-rated ADHD symptom severity, with a significant greater decrease in symptoms compared to EMG feedback. Sex, trial site, medication, parenting style, and parents’ expectation had no impact on the ADHD score change. Sensitivity analyses with multiple imputation and with the PP population generated comparable results. These results are in line with previous findings of trials comparing NF to semi-active control groups . SymptomOur study set out to assess both specific and unspecific effects of NF. An important hint for specificity is the demonstration of successful SCP self-regulation for children in the SCP-NF group only. The significant symptom improvement in NF may be regarded as a confirmation of specific effects of SCP-NF. The lack of SCP regulation during the transfer condition in the NF group may suggest either limited or delayed transfer and a restricted generalization into everyday life. Here we should wait for follow-up results as it was shown previously for patients with epilepsy  and chilIn addition, our results also point to a strong influence of unspecific variables on treatment outcome.We compared two treatments using identical conditions regarding tasks, time schedule, possible amount of reinforcement, and interaction. Children in the semi-active control group underwent the same intense treatment in an identical setting. In feedback treatments, contingent reinforcement of regulation of a physiological parameter improves self-efficacy and coping . Thus, Epost hoc within ES for our groups. Here, medium to large effect sizes of 0.78 (BOCF) and 1.09 (completer) for NF were observed, while the effect sizes for EMG were small with 0.35 (BOCF) and 0.48 (completer).The rather small (0.40 with BOCF) or medium (0.57 completer) effect size of the between group comparisons should be discussed in several respects. First, due to the considerable unspecific effects in the semi-active control group the clinical effects of NF  may have been underestimated. NF-studies in ADHD with waiting list controls tend to yield much higher effect sizes than those with active or semi-active control conditions see . In addiAccording to teachers, who can be regarded as possibly blinded raters, there was no group effect in favor of NF. This is of considerable concern in the light of a recent meta-analysis highlighting smaller effect sizes when applying probably blinded vs. non-blinded ratings . Whetherper se. Recently, Similar to findings from other ADHD studies e.g., , teacherPhysicians or clinical psychologists not involved in the study rated about 27% of children in both groups as responders based on CGI ratings. The almost identical response rate in both groups supports the assumption of large unspecific effects of the treatments. Unfortunately, there were about 40% missing values. Furthermore, the validity of the clinicians’ ratings is questionable, as some parents reported that the clinicians asked them about their own judgment and gave their ratings accordingly. To supplement the response ratings of clinicians, we determined how many parents described a reduction of ADHD total symptoms of more than 25% for their child. Here, 52% of NF and 35% of EMG children (mITT population) were rated as improved. This result is comparable to response rates reported by a priori decision to define parents’ ratings as “primary” was not only based on methodological requirements. Parents observe many facets of their children’s everyday family, social and academic life, and suffer from impairment in all these areas. This may not only explain the more severe ratings compared to those given by teachers but also points to the ecological validity of their judgments. Although parents were not informed about treatment allocation, we cannot rule out that information given to them by their children may have affected their ratings. Parents’ ratings were probably not blinded because children were instructed differently according to treatment allocation. Blinding of patients and staff may count as a gold standard of evidence-based medicine in drug research but may interfere in treatments where patients are expected to learn a certain behavior or skill. This holds true for psychotherapy in general and it is of utmost importance in feedback therapy aiming at the acquisition of a self-regulation skill. Without knowing which parameter has to be trained the patient may lose time, motivation and precision  the (amount of) specificity remains questionable. On the other hand, more children in the EMG group than in the NF-group learned to improve self-regulation, consistent with the results of ®, Version 16). The treatments were feasible and AE related to the treatment were observed in only a few children. While one child of the EMG group had to be withdrawn from the study because his symptoms deteriorated, the other AE in children of both groups remitted quickly.For the first time, AE and SAE of SCP-NF were investigated with the help of the WHO Adverse Reaction Terminology, included in the Medical Dictionary for Regulatory Activities for clinical studies  . Such faA difference in the change of the full scale IQ was observed between groups. While there was a slight increase in NF, performance of EMG participants declined. This may be due to EMG children investing less effort in the test, and to SCP-NF releasing attentional resources .Earlier studies have already reported improvements in children with ADHD after SCP-NF. We have moved a step forward in answering questions regarding specificity, efficacy and feasibility with this study. We included the largest sample treated with NF to date, used a semi-active control condition with an identical setting, a conservative statistical approach (BOCF), and SCPs as target for NF, which has been identified as a stable marker of ADHD. Major limitations of the present study are the lack of power regarding teacher ratings, and only few and questionable clinicians’ ratings. Compared with other studies, a possible shortcoming might lie in the fact that for pragmatic reasons, we chose to conduct only 25 training sessions since Further analysis of electrophysiological and neuropsychological data and long-term outcome will help to understand the mechanisms underlying the reported specific and unspecific effects. A major challenge for future studies will be to identify predictors to decide whether an individual patient would particularly benefit from SCP-NF.MH, US, and DW conceived and designed the trial. MH and US coordinated the trial. MH, US, SW, and MA designed and supervised the intervention component. MA, CB, LH, TB, SG, LH, SH, AM-M, SM, BP, SW, and YF conducted training sessions and pre-/post-measurements. DW and CR conducted the analyses of behavioral data, PA and DB the analysis of EEG data. US and MH interpreted the results and drafted the report. All authors revised the article for important intellectual content. MH and US are the principal investigators.AR is member of an advisory board and speakers’ bureau of Lilly, Shire, Medice, and Novartis. He has received research and travel support and an educational grant from Shire. CF has received speaker’s fees from Eli Lilly and Shire. DW has been employed at Boehringer Ingelheim since January 2015. His study specific contribution as the responsible statistician took place when he was employed at IZKS Mainz. TB has served in an advisory or consultancy role for Hexal Pharma, Lilly, Medice, Novartis, Otsuka, Oxford Outcomes, PCM Scientific, Shire, and Vifor Pharma. He has received conference attendance support and conference support or received speaker’s fees from Lilly, Medice, Novartis, and Shire. He is/has been involved in clinical trials conducted by Lilly, Shire, and Vifor Pharma. MH has served in an advisory or consultancy role for Medice and Shire, and has received conference attendance support or was paid for public speaking by Lilly, Medice, neuroConn, and Shire. US has been paid for public speaking by Novartis, Medice, neuroCare, the German Society for Biofeedback, and Akademie König und Müller. DB serves as an unpaid scientific consultant of an EU-funded neurofeedback trial. The other 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.


Problems with cognitive function are found in many major psychiatric disorders. In schizophrenia and attention deficit hyperactivity disorder (ADHD), they are among the core symptoms. Based on a growing recognition that there is little diagnostic specificity for any single cognitive impairment, there is an increasing emphasis on investigating impairments across psychiatric disorders. This approach, which is consistent with the NIMH Research Domain Criteria initiative, is expected to lead to a better understanding of the neurobiological mechanisms involved in cognitive deficits.An increase in neuronal background noise has been identified as a neuronal correlate of inattention. Because the dopamine system has been found to play a critical role in modulating neuronal noise, dopamine dysfunction may play a substantial role in generating the excessive noise that has been found to characterize information processing in both schizophrenia and ADHD. This issue can be studied noninvasively via electrophysiological examination of the retina, a distinct neural network. Both basic research and human studies indicate that retinal information processing is under strong dopaminergic modulation . We have previously demonstrated an elevated level of background noise at a very early stage in visual information processing in untreated patients with ADHD . Moreover, background noise was associated with inattention measures in these subjects. To further address the hypothesis that elevated retinal noise reflects dopaminergic dysfunction, we report here on a new study that compared retinal background noise in patients with ADHD both before and after therapy, as well as in patients with schizophrenia.Neuronal noise was assessed using pattern electroretinogram (PERG), an objective electrophysiological measure for retinal network function from the photoreceptors to the retinal ganglion cells. A total of 20 patients diagnosed with ADHD were tested both before and after treatment with methylphenidate (MPH). The control group consisted of 21 healthy subjects. The PERGs were recorded in a steady state mode in response to checkerboard stimuli of 12 reversals/s. Data collection with people with schizophrenia is ongoing, and results will be reported at SIRS.Before treatment, the patients with ADHD presented with elevated background noise (higher by 127%) in comparison to the control group. After treatment, noise level did not differ from what was observed in the control group. Retinal background noise was found to be highly correlated with the severity of the ADHD symptoms. The results will be discussed in relationship to our findings in patients with schizophrenia.These data provide further evidence for the hypothesis that elevated background noise is linked to ADHD and cognitive deficits. The findings are of special relevance because ADHD is a disorder with a dedicated treatment option for cognitive symptoms. Interestingly, a similar pathophysiological mechanism for cognitive dysfunction has been proposed for both schizophrenia and ADHD. However, because ADHD medications, such as MPH, typically elevate dopamine levels, potentially leading to exacerbation of psychotic symptoms, different approaches for treating cognitive symptoms in schizophrenia need to be explored. On this basis, current approaches used to target neuronal noise and cognitive symptoms in patients with schizophrenia will be discussed and their relevance for future research will be addressed.


Viperin is an interferon-inducible antiviral protein, responsible for antiviral response to a variety of viral infections. Here, we show that silencing viperin by antisense oligonucleotides (ASO) protects against diet-induced glucose intolerance, and yet exacerbates adipose tissue inflammation. In high-fat diet-fed mice, viperin ASO improves glucose homeostasis, reduces plasma triglyceride concentrations and ameliorates diet-induced hepatic steatosis. Peripheral delivery of viperin by adeno-associated virus elevates fasting plasma glucose and insulin concentrations and reduces insulin-stimulated glucose uptake in skeletal muscle. Viperin overexpression reduces epinephrine- stimulated lipolysis in white adipose tissue, whereas viperin ASO increases expression of lipolytic genes. Targeting viperin by antisense oligonucleotides promotes reciprocal regulation of hepatic and adipose lipogenesis by reducing hepatic lipid content and increasing triacylglycerol content in adipose tissue. These findings reveal viperin as an important target to improve glucose metabolism, and suggest that suppressing antiviral potential may improve the metabolic adaptability to high-fat diet. Type 2 diabetes and obesity are associated with chronic inflammation characterized by increased proinflammatory responses and macrophage infiltration into adipose tissues , 2. TherSuccessful antiviral therapy can induce remission of type 2 diabetes. Recent case reports in humans suggest that antiviral treatment of HCV improved glycemic control in type 2 diabetes , 13. VipWe evaluated the expression pattern of viperin in several tissues of insulin-resistant mice, which indicated that adipose tissues express the lower levels of viperin. However, specific knockdown of viperin with antisense oligonucleotides (ASO) in HFD-fed mice ameliorated glucose tolerance and enhanced adipose tissue inflammation. Viperin overexpression elevated fasting plasma glucose and inhibited adipocyte lipolysis. Silencing viperin induced reciprocal regulation of hepatic and adipose lipid metabolism under the challenge of high-fat diet. These findings suggest a previously unknown function for viperin in linking glucose metabolism to antiviral activity.-/- mice (db/db mice). In the two mouse models of insulin resistance, viperin expression was consistently decreased in WAT and BAT - and HFD-fed mice with viperin ASO twice a week for 4 weeks. Antisense oligonucleotides (ASOs) are well designed to bind to the target RNA and reduce expression of the target gene primarily in liver and adipose tissue -glucose uptake was measured after incubation. For ex vivo analysis of epinephrine- stimulated lactic acid release, intact muscles were incubated for 15 min with epinephrine 2, 5, 10, 20, 30, or 40μg/mL, and then lactic acid content in culture medium was measured after incubation. For ex vivo analysis of epinephrine-stimulated glycerol release, WAT and liver were respectively incubated for 180 min with epinephrine. Glycerol contents in culture medium were measured per 30 min. Lactic acid and glycerol contents were measured using spectrophotometer following the manufacturers’ protocols (Nanjing Jianchen Biotech).Intactgastrocnemius muscle and epididymal fat (WAT) from mice were preincubated for 2 h at 30°C in oxygenated (95% O2 and 5% CO2) Krebs-Ringer bicarbonate HEPES buffer (KRBH) containing (mM): 129 NaCl, 5 NaHCOPlasma concentrations of insulin were measured by ELISA. Plasma glucose, triglycerides , free fatty acid (NEFA), and cholesterol were determined with enzymatic colorimetric assay following the manufacturers’ protocols (Nanjing Jianchen Biotech).Tissue TAG was extracted using the method described previously . Pieces -ΔΔct relative to the control group, respectively.Total RNA was isolated from tissues using TRIzol (Invitrogen), according to the manufacturer's instructions. RNA was reverse-transcribed . cDNA was amplified by real-time PCR in a total reaction volume of 20μl using SYBR Green Realtime PCR Master Mix . Real-time PCR reactions were cycled in StepOne™ Real-Time PCR System (Applied Biosystems). Target gene expression was normalized to housekeeping gene 18S or GAPDH and expressed as 2For frozen tissue, lysates were prepared using a RIPA lysis buffer (50mM Tris (pH7.4), 150mM NaCl, 2mM EDTA, 1% Nonidet P-40, 50mM NaF, 0.1% SDS and 0.5% sodium deoxycholate with PhosStop Phosphatase-Inhibitor Cocktail tablet and protease-inhibitor cocktail tablet (Roche). The homogenate was centrifuged at 4°C for 10 min at 14,000g and the supernatant was used for western blot. The protein content of the supernatant was quantified using bicinchoninic acid reagents and BSA standards. Equal amounts of protein were separated using a polyacrylamide SDS-PAGE gel. After SDS-PAGE, proteins were transferred to PVDF membrane. The membrane was blocked for 1 h at room temperature followed by incubation overnight at 4°C with viperin antibody (Abcam), phospho-PKCμ, phospho-ACC, phospho-Akt, or GAPDH antibodies . After overnight incubation, the blots were incubated with HRP- conjugated secondary antibodies at a dilution of 1:5,000 for 1 h at room temperature. Bands were visualized by ECL plus (Thermo Scientific) according to the manufacturer's instructions and quantified using Image lab software.Data are shown as Mean ± SEM. Differences between groups were analysed statistically using Student's t test, and differences among the four groups were analysed with analysis of variance followed by post-hoc Bonferroni tests in Graphpad Prism 5.0. P-value < 0.05 was considered significant.


Compared with general population rates, prevalence rates of ADHD have been consistently reported to be higher in both male and female offender populations, the latter estimated to range between 10–29%. Research in forensic institutional settings has reported that aggressive behaviour is a particularly prominent source of impairment among men with ADHD. However there is a paucity of research investigating the type of behavioural incidents that may arise in female offenders with ADHD. This pilot study therefore aimed to further our understanding of ADHD within a cohort of female mentally disordered offenders by ascertaining estimated rates of ADHD and associated functional disturbance presenting in this population. Fifty female offenders completed the Barkley ADHD rating scales. Data on aggressive and self-harming behaviours were obtained from patients' clinical records. Almost one-third of patients (28%) screened positive for ADHD, most commonly hyperactive/impulsive and combined subtypes. They were significantly younger than their peers and there were no significant differences in behavioural disturbance records between groups. When controlling for age, hyperactive/impulsive symptoms and combined symptoms were significantly and positively correlated with measures of behavioural disturbance. ADHD symptoms correlated more strongly with self-harm than outward aggression, which is a novel finding. This pilot study has contributed to the knowledge base about the rate and functional problems of female offenders with ADHD. Future research should replicate the study using a larger sample and explore the effect of treatment  on the reduction of ADHD symptoms, behavioural disturbance, length of stay and quality of life. Indeed, institutional records of critical incidents have shown a strong association between ADHD symptoms and aggressive behaviours in males with and without mental disorders detained in forensic settings Retz and RöslerImpulsivity has been associated with self-harming behaviours. Research has identified strong associations between impulsivity, aggression and suicidal behaviour within psychiatric populations This pilot study therefore aimed to further our understanding of ADHD within a cohort of female mentally disordered offenders by ascertaining estimated rates of ADHD and associated behavioural problems presenting in this population. The study utilised ADHD screening tools to determine childhood and current adult ADHD symptomology. Behavioural disturbance was identified from a review of patients' clinical notes.Consistent with the literature, it was hypothesised that: (H1) rates of estimated ADHD would be considerably higher than that reported in the general population for females; (H2) that female mentally disordered offenders with ADHD symptoms would have greater behavioural impairments  compared with their Non-ADHD peers; and (H3) that there would be a positive correlation between behavioural disturbance and ADHD symptoms and, in particular, hyperactive/impulsive symptoms.2.2.1M = 30.85, SD = 9.81) who were detained under the UK Mental Health Act participated in the study. Exclusion criteria included patients who were too mentally unstable to participate at the time of the assessment, or who had severe cognitive deficits and/or who lacked capacity to consent to participate in the study. A cohort of eighty patients was available for participation. In two cases, the nursing staff and clinical team advised that the patients were in acute psychological distress and were therefore too mentally unwell to approach. Twenty eight patients did not give consent.The study took place over a 14-month period at an adult medium secure hospital. Fifty females between 18 and 52 years of age, (The primary diagnoses of the 50 patients who agreed to participate were as follows: 30% (N = 15) schizophrenia, 26% (N = 13) emotionally unstable personality disorder, 16% (N = 8) schizoaffective disorder, 10% (N = 5) bipolar disorder, 10% (N = 5) post-traumatic stress disorder, two patients had Asperger's Syndrome, one had depression and one had dissocial personality disorder.Participants were prescribed a range of medication, including anti-psychotics, anti-depressants, mood stabilisers, benzodiazepines and ADHD stimulant medications. A total of fourteen patients  were being treated with stimulant medication during the assessment period.2.2, predominantly inattentive subtype , or combined subtype . In addition, all ratings were summed to provide a total Barkley score for each participant.The self-rated Barkley ADHD Scales Demographic and behavioural data were obtained from a review of clinical files documenting primary diagnosis, age, length of stay (in years) at the hospital, and the frequency and severity of aggressive and self-harming behaviours recorded over the 12 weeks prior to participation in the study. Behavioural disturbance was categorised using the previous methodology of Young and colleagues A verbal threat without actualisation.Harm to self or others not requiring response team/medical attention.Harm to self or others requiring response team/medical attention.Harm to self or others requiring hospitalisation.Composite scores were calculated for aggressive behaviour and self-harming behaviour by adding the total frequency of incidents and the severity rating for these incidents. A total composite score of behavioural disturbance, combining both aggressive and self-harming behaviour, was also calculated for each patient. Thus, seven main measures were calculated: Frequency of Aggression, Severity of Aggression, Composite Score of Aggression, Frequency of Self-Harm, Severity of Self-Harm, Composite Score of Self-Harm, and Total Composite Score.2.3The study was approved by the South East London Research Ethics Committee and by the Research and Development Office, King's College London, (08/HO807/17 and R&D2008/007 respectively). Prior to their recruitment, patients were given an information sheet regarding the nature and purpose of the study and were given the opportunity to ask questions about the research. After giving informed written consent, patients completed the ADHD screens with the researcher. The demographic and behavioural data were then obtained from a review of their clinical records.2.4All statistical analyses were performed using SPSS for Windows, Version 20. Descriptive statistics were used to characterise the sample. Mann-Whitney U tests were conducted to compare differences in behavioural disturbance between the ADHD group and the Non-ADHD Group. Spearman's Rank Order Correlation analysis was used to examine the relationship between ADHD subtypes and behavioural disturbance. One tailed tests with the significant level set at 0.05 were used to test hypotheses.3.3.1Just under one-third  of the sample met the screening criteria for adult ADHD, based on childhood and current symptoms. Of these, 43% (N = 6) were classified as hyperactive/impulsive subtype, 43% (N = 6) as combined subtype and; the remaining 14% (N = 2) of patients were of the inattentive subtype.M = 24.59, SD = 5.11) than the Non-ADHD Group  = 4.00, p < 0.001). There were no significant differences between the groups for length of stay  = 0 .60, NS). Data was missing for one case from the Non-ADHD group.The ADHD Group were significantly younger  with primary diagnoses of severe mental illness  and 47.2% (N = 17) had Non-SMI primary diagnoses. Around two thirds  of the ADHD Group was comprised of patients with primary diagnoses of SMI and the remaining 35.7% (N = 5) of patients had Non-SMI primary diagnoses.3.2U tests were conducted to assess for differences in the total number and severity of incidents between the ADHD and Non-ADHD Groups  screened positively for ADHD, most of whom met screening criteria for either hyperactive/impulsive subtype (43%) or combined subtype (43%), highlighting the considerable presence of hyperactivity and impulsivity within this population. However, screening questionnaires alone may lack specificity for the diagnosis, with high rates of false positives having been identified in previous research The second hypothesis was not supported as levels of behavioural disturbance did not significantly differ between groups. However, although no significant differences were found between the mean scores, the ADHD group obtained higher ratings for frequency and severity of aggressive and self-harming behaviours than the non-ADHD group and it is possible that an effect may have been found with a larger sample. The ADHD group had considerably greater variation in their behaviour scores and were significantly younger. Future research should employ a larger sample size and/or match groups by age. When controlling for age, hyperactive/impulsive and total Barkley score were significantly correlated with all measures of behavioural disturbance, with the exception of the Frequency of Aggression, partly supporting the third hypothesis. Inattentive symptoms did not correlate significantly with the measures of behavioural disturbance, although all correlations were in the positive direction. These findings suggest that ADHD symptom scores are associated with increased aggressive behaviour, and that this effect appears to be due to hyperactive/impulsive symptoms rather than inattention symptoms alone. Further to this, and a novel finding, the ADHD symptoms were more strongly correlated with self-harm than outward aggression (medium versus low effect size). This differs from previous research into male prisoners, where the observation of self-harm is very rare and is not related to ADHD symptoms This study highlights the potential impact of ADHD symptoms among female offenders with severe mental health disorders, a population that has hardly been studied. Yet there are several limitations that should be addressed in future research. The current pilot is limited by its small sample size; recruitment was hampered by the high refusal rate (35%) and this should be factored in when planning future studies in a similar population. As a result, the study may have been vulnerable to selection bias, limiting generalisability of the findings. Whilst screening tools may have utility to identify those who require a more comprehensive assessment, they have the limitations acknowledged above and those measures that require retrospective recall of childhood symptoms may be susceptible to memory bias 5.This pilot study of a cohort of patients detained at a medium secure service has contributed to the knowledge base about the rate and functional problems of female offenders with ADHD. Future research should replicate the study using a larger sample and explore the effect of treatment  on the reduction of ADHD symptoms, behavioural disturbance and quality of life. Treatment that combines both pharmacological and psychological approaches, in particular, is likely to be necessary to improve the functional long-term outcomes of individuals with complex presentations. In turn this has the potential to reduce the length of stay in costly secure mental health hospitals.


Objective: The aim of this study was to examine the types of errors made by youth with and without a parent-reported diagnosis of attention deficit and hyperactivity disorder (ADHD) on a math fluency task and investigate the association between error types and youths’ performance on measures of processing speed and working memory.Method: Participants included 30 adolescents with ADHD and 39 typically developing peers between 14 and 17 years old matched in age and IQ. All youth completed standardized measures of math calculation and fluency as well as two tests of working memory and processing speed. Math fluency error patterns were examined.Results: Adolescents with ADHD showed less proficient math fluency despite having similar math calculation scores as their peers. Group differences were also observed in error types with youth with ADHD making more switch errors than their peers.Conclusion: This research has important clinical applications for the assessment and intervention on math ability in students with ADHD. Attention Deficit Hyperactivity Disorder (ADHD) is a developmental disorder characterized by symptoms of inattention, impulsivity, and hyperactivity  which arMath appears to be an area of challenge for a number of individuals with ADHD . Tosto eOne way to gain insight into the nature of the challenges youth with ADHD experience with math fluency is to examine the type of errors that the students make and to assess whether they are similar or different to those made by peers. Although prior studies have explored error patterns in mathematics tasks in children with ADHD , it is nPrior research on math error types and ADHD has focused on children and has identified errors that appear to be related to inattentiveness as well as working memory . For exaWhile inattentiveness and working memory  and youth without ADHD. Given the importance of mathematics to an individual’s future employment status , we beliIn the present study, we used the Woodcock Johnson Test of Achievement- Third Edition WJ-III;  Math FluWe expected that youth with ADHD would exhibit weakness in math fluency relative to their typically developing peers given the association between ADHD and math fluency reported in previous studies . We alsoSummarizing, the objectives of the present study was to analyze the types of errors made from adolescents with ADHD in a math fluency task compared to their peers and the association between the types of errors and working memory and processing speed.T ≥ 70) on the Diagnostic and Statistical Manual of Mental Disorders-IV inattention (α = 0.93), hyperactivity-impulsivity (α = 0.92), or global index subscales of the Conners Third Edition Parent Rating Scales (T ≤ 65); (2) An estimated intelligence quotient (IQ) ≥ 70 based on the Wechsler Abbreviated Scale of Intelligence  examining academic performance and text comprehension in adolescent with and without ADHD. The inclusion criteria for ADHD group were: (1) At least one clinically significant score  A pg Scales  non-verbce WASI;  non-verbWe focused in this study on youth who were not perceived to have a concurrent math disability in basic computation skills according to the performance on the WJ-III Math Calculation subtest. However, as there is no ‘gold standard’ to define mathematical ability , we deciTable 1. Parent education was gathered from a parent demographic survey with 1 = No schooling; 2 = Some elementary; 3 = Completed elementary; 4 = Some secondary; 5 = Completed secondary; 6 = Some college; 7 = Completed college program; 8 = Some university; 9 = Completed undergraduate; 10 = Master’s degree; 12 = Doctoral degree.Therefore, our sample included 30 students  with ADHD and 39  TD peers who were matched on age, IQ and parent education level . Group demographic characteristics are presented in This study was carried out in accordance with the recommendations of the second author’s institutional research ethics board with written informed consent from all subjects’ parents/guardians. All subjects gave written informed consent in accordance with the Declaration of Helsinki. An intake screen was first completed by telephone with the interested parents/guardians to determine each youth’s eligibility for the study. Parents/guardians of eligible youth were provided with an information and consent letter to inform them of the study. All parents of the participating youth in this study provided their written consent for the youth to participate in the study. In addition, at the start of each visit to the lab, the research assistant explained the study to each youth and acquired their verbal assent to take part in the study. All youth were reminded that it was their choice to take part in the study and then could stop taking part at any time. Research assistants worked individually for about 5 h with each participant and all participants were provided with breaks when needed. During the assessment, the adolescents completed standardized achievement tests and a battery of self-report measures relating to beliefs and attributions for behavior that were part of a larger study.T-scores.The Conners Third Edition- Parent and Adolescent (Conners 3) is a reliable and well-validated diagnostic instrument for ADHD, including adolescent self-report and parent versions . The LeaT-score with a mean of 50 and a standard deviation (SD) of 15. The reliability coefficients reported in the manual for Vocabulary in children aged 14 to 16 the range is 0.90 to 0.93 and for Matrix Reasoning they ranged from 0.86 to 0.91.The Wechsler Abbreviates Scale of Intelligence WASI;  is a briMath abilities were assessed through two tests of WJ-III: Math Calculations and Math Fluency . Math CaThe Test of Memory and Learning – Second Edition is a well-validated, standardized assessment of memory ability . From thSD of 3. The coefficient alpha for Digit Naming for youth aged 14–16 range from 0.85 to 0.93 whereas the Color Naming reliability ranges from 0.81 to 0.86.We administered the Rapid Digit and Color Naming subtests from the Comprehensive Test of Phonological Processing CTOPP;  which isWe decided to analyze four types of errors in Math Fluency. First, we reviewed previous studies examining math errors  and from(a)Incorrect operation errors: this type of error is when the participant gave a response that could be correct if the sign of the operation was different .(b)Basic errors: the type of error is a basic error in operations and seems to show a lack of understanding of the operation .(c)Switch errors: this type of perseverative error occurred when the student’s error on the math problem was incorrect and it showed the persistence of using the operation from the previous question on the test .(d)Zero errors: This type of error is a specific type of basic error in which the operation contained a 0 .The numbers of error for each category were calculated as the percentage of error on the total numbers of solved operations in the 3-min time limit . For exaWe calculated the interrater reliability of the math errors types. We asked a second coder with clinical training in administering the WJ-III Math Fluency measure to rate a random sample of 15% of the total sample of protocols. IRR was assessed using a two-way mixed, absolute agreement ICC  predicted error rates controlling for ADHD group status.We compared adolescents with ADHD and TD students on math measures using a univariate analysis of variance (ANOVA). The differences between the two groups in the type of errors in Math Fluency were analyzed using a Mann–Whitney Table 2 presents the results of the first set of analyses on the Math Calculation and Fluency subtests as well as the math error types. There was no statistically significant difference between the ADHD and TD peers on the WJ-III Math Calculation subtest. However, youth with ADHD did score significantly lower than their TD peers on the WJ-III Math Fluency subtest . There was a significant difference between the two groups on the two processing speed tests, Digit Naming  and Color Naming  with youth with ADHD showing slower processing speed relative to their peers on both tasks. There were no statistically significant differences in working memory performance between the two groups. There were no statistically significant differences in the math error types although we found that the effect size for the number of switch errors was moderate in size  with the ADHD group making more switch errors that the typically developing comparison group. Interestingly, the opposite was found for the basic errors and the incorrect operation errors with the comparison group making more of these types of errors relative to the youth with ADHD. We analyzed the frequencies of students who made the distinct types of errors in the two groups as well. We found that 12 (31%) TD students compared to 5 (17%) youth with ADHD made incorrect operations errors, 16 (41%) TD adolescents in comparison with 8 (27%) youth with ADHD made basic errors and 7 (18%) TD students compared to 11 (37%) youth with ADHD made switch errors. Only 4 (10%) TD adolescents made zero errors.r = -0.335, p = 0.013). Considering the correlations between the types of errors and the two working memory measures we found a negative correlation between the switch errors and the Digit Backward test (r = -0.213). Therefore, participants with a high number of switch errors tended to have lower scores (slower naming speed) on the Color Naming and Digit Backward subtest. We decided not to analyze the zero errors due to the low frequency of this kind of errors. The correlations was analyzed even separately for the two groups but being similar we decided to consider the correlation in the whole sample.When we analyzed the Spearman correlations between the types of errors and the two processing speed measures we found a significant negative correlation between the switch errors and the Color Naming test (p = 0.010). Youth with ADHD were at increased risk relative to their peers of being members of the switch errors subgroup. However, as shown in Table 3, none of the variables  when entered together were significant unique predictors of membership in the switching errors subgroup. However, youth with better Color Naming tended to be at less risk  which is consistent with the correlation between Color Naming and switch errors. Also, when entered alone, Color Naming was a predictor of group membership with youth with better Color Naming at lower risk of being a member of the switch errors group . Considering the interaction between ADHD status and Color naming it was not significant .As the distributions of the errors were not normal, with many students making no errors, or many making only one to two errors of a particular variety, we decided to create new dichotomous variable for switch errors. One group was comprised of youth who made no switch errors vs. those who made at least one error . A logistic regression was then conducted to predict switch error type using the Digit Backward and Color Naming subtests  as predictors with ADHD status entered first. We only included these subtests as it were the only shown to be correlated with switch errors. Different variables were introduces in different blocks. Preliminary analyses indicated that ADHD status when entered alone was a significant predictor of being a member of the switch error group  but the same effect could be expected for the Math Fluency. Instead, consistent with prior research , there wConcerning processing speed, we found that students with ADHD had a lower performance in Color Naming relative to the comparison group. This finding is consistent with previous literature that found an impairment in processing speed in children with ADHD  and in rWhen we conducted the logistic regression to determine if the switch errors in Math Fluency were predicted by the two cognitive measures, we found that Color Naming was not a unique predictor when concurrently entered along with ADHD status and working memory. However, when entered on its own, the results of the logistic regression revealed that it was a significant contributor to classification and better Color Naming was associated with lower odds of a youth being a member of the switch errors group.In summary, even though the adolescents with ADHD in our sample demonstrated average performance in a math calculation task, they performed significantly lower on the math fluency task compared to their non-affected peers. The math fluency measure we used requires youth not only to use their math abilities but also switch from one operation to another in a 3-min time limit. It is likely that the poorer performance on the math measure is in part due to slow fluency (as indicated by the Color Naming speed task) but also from the nature of the task as it required careful monitoring of problem type and the ability to quickly switch operation types. Previous research suggests that students with ADHD exhibit problems when completing tasks where they must inhibit irrelevant task information when switching from one task to another , so in tAnother important variable is time. In the Math Fluency task students were only permitted 3 min to complete as much as possible of the task. Previous research examining timed tasks , has shoThis study has some important from a clinical point of view inasmuch as we are interested in acquiring knowledge of “actual” math fluency in students with ADHD. It would be interesting in future research to compare the performance of timed tasks in blocks  vs. mixed. Similar to research with individuals with ADHD on task switching e.g., , it is pAlthough this research analyzed an understudied and interesting topic concerning computation error types during a math fluency task in adolescents with ADHD, there are some limitations that needed to be considered. First, our sample was small and we included only one measure of math fluency and only few measures of EFs and processing speed. It would be important to replicate our findings with a more diverse sample (perhaps children and youth) using different subgroups . In addition, it would be interesting to compare the performance on math fluency tasks that vary in switching demands to better understand the nature of the math fluency weaknesses in children and youth with ADHD. From a clinical standpoint, this research was useful as it suggests that in some cases students with ADHD could have a lower performance on tasks assessing fluency in comparison with their peers as a result of the nature of the task (mixed blocks vs. single operation blocks). This finding suggests that from a practical perspective, it might be important for educators to consider using math fluency tasks that do not require switching between operations to better understand if the issue is fluency or the executive control needed to switch sets rapidly.Finally, given the importance of math to future life success, it is important that more research addresses mathematics in youth with ADHD. More research is needed in this field to understand which processes , compromise the performance of adolescents with ADHD. Furthermore, multi-digit arithmetic operation should be investigated in this range of age to analyze if the pattern of errors remains the same or change with the complexity of the task and with or without the time and the switching request.http://www.research.utoronto.ca/faculty-and-staff/research-ethics-and-protections/humans-in-research/). Parents/guardians were asked to provide their consent for their child’s participation and all youth were asked to provide their assent for participation. We ensured that all assent information for the youth was presented in a way that enhanced comprehension and we prompted youth to ask questions for clarification several times during the assent process.The study from which this data was obtained was approved for ethical clearance by the University of Toronto’s Research Ethics Committee which follows the Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans (2010) (AC and RM contributed to the design and implementation of the research. AC contributed to the analysis of the results and to the writing of the manuscript. RM contributed to drafting the article and to the critical revision of the article.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. The reviewer MCPF and handling Editor declared their shared affiliation.