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/lp/springer-journals/meg-event-related-desynchronization-and-synchronization-deficits-bGscgjVWNN
- Publisher
- Springer Journals
- Copyright
- Copyright © 2008 by Dockstader et al; licensee BioMed Central Ltd.
- Subject
- Biomedicine; Neurosciences; Neurology; Behavioral Therapy; Psychiatry
- eISSN
- 1744-9081
- DOI
- 10.1186/1744-9081-4-8
- pmid
- 18269747
- Publisher site
- See Article on Publisher Site
Abstract
Background: Attention-Deficit/Hyperactivity Disorder (ADHD) is a prevalent, complex disorder which is characterized by symptoms of inattention, hyperactivity, and impulsivity. Convergent evidence from neurobiological studies of ADHD identifies dysfunction in fronto-striatal-cerebellar circuitry as the source of behavioural deficits. Recent studies have shown that regions governing basic sensory processing, such as the somatosensory cortex, show abnormalities in those with ADHD suggesting that these processes may also be compromised. Methods: We used event-related magnetoencephalography (MEG) to examine patterns of cortical rhythms in the primary (SI) and secondary (SII) somatosensory cortices in response to median nerve stimulation, in 9 adults with ADHD and 10 healthy controls. Stimuli were brief (0.2 ms) non- painful electrical pulses presented to the median nerve in two counterbalanced conditions: unpredictable and predictable stimulus presentation. We measured changes in strength, synchronicity, and frequency of cortical rhythms. Results: Healthy comparison group showed strong event-related desynchrony and synchrony in SI and SII. By contrast, those with ADHD showed significantly weaker event-related desynchrony and event-related synchrony in the alpha (8–12 Hz) and beta (15–30 Hz) bands, respectively. This was most striking during random presentation of median nerve stimulation. Adults with ADHD showed significantly shorter duration of beta rebound in both SI and SII except for when the onset of the stimulus event could be predicted. In this case, the rhythmicity of SI (but not SII) in the ADHD group did not differ from that of controls. Conclusion: Our findings suggest that somatosensory processing is altered in individuals with ADHD. MEG constitutes a promising approach to profiling patterns of neural activity during the processing of sensory input (e.g., detection of a tactile stimulus, stimulus predictability) and facilitating our understanding of how basic sensory processing may underlie and/or be influenced by more complex neural networks involved in higher order processing. Page 1 of 13 (page number not for citation purposes) Behavioral and Brain Functions 2008, 4:8 http://www.behavioralandbrainfunctions.com/content/4/1/8 measures (i.e., accuracy, reaction time), which cannot Background Attention-Deficit/Hyperactivity Disorder (ADHD) is an assess moment-by-moment activities that are driving impairing neurodevelopmental disorder that remains these processes on the order of milliseconds. inadequately understood. Along with the observable behavioral symptoms of inattention and hyperactivity/ Our aim was to examine basic sensory processing of pre- impulsivity, there is robust evidence of structural, func- dictable and non-predictable stimuli in those with ADHD tional, and neurochemical brain differences in ADHD [1- using magnetoencephalography (MEG), a non-invasive 3] particularly in regions involved in vital executive func- functional neuroimaging technique that records neural tions (EFs) that regulate the ability to identify, extract, and activity on the order of a millisecond. This high temporal interpret what is relevant for executing the correct resolution combined with novel source reconstruction response, as well as monitoring, inhibiting, and changing techniques capable of mm spatial resolution makes MEG the prepotent response as needed [4,5]. The pathophysi- an optimal technique for capturing spatial and temporal ology of ADHD remains unclear, although converging evi- information during sensory processing for which the time dence suggests that alterations in brain structure, scale is on the order of milliseconds. MEG studies of the function, and physiology likely arise from an interaction human somatosensory system using median nerve stimu- of genetic and environmental causes and experience [5-8]. lation have shown that only the contralateral primary For example, structurally, prominent volumetric decreases somatosensory cortex (SI) responds to unilateral tactile are evident in the posterior-inferior lobules of the cerebel- information whereas bilateral secondary somatosensory lar vermis in both male and female children with ADHD cortices (SII) show activity in response to unilateral stim- [9-12]. There are decreases in prefrontal volume, particu- ulation [31,32]. The earliest somatosensory activity occurs larly the right prefrontal cortex [9,13]. Also reported are at approximately 20 ms post-stimulation in SI just caudal regional differences in cerebral blood flow in the cerebel- to the central sulcus in the corresponding topographical lum, striatum [14] and prefrontal cortex (PFC) [15]. location. Subsequent somatosensory activation occurs in Moreover, differences in baseline oscillatory activity the bilateral parietal opercula located in the dorsal regions between those with ADHD and controls have been of the lateral sulci [32-34]. Source activity in SI and SII, observed in frontal regions, particularly the PFC [16,17]. following median nerve stimulation, is composed of both Consistent with the neuroimaging findings, psychological alpha and beta cortical rhythms [35]. In association with research indicates clearly that subtle but impairing prob- MEG, median nerve stimulation has been used to exam- lems in EFs are correlates of ADHD, regardless of gender ine evoked responses to somatosensory stimuli in order to or age [18]. examine somatosensory cortical function [31,36,37] and ascending pathways from the peripheral receptors to the While the majority of ADHD research focuses on deficits spinal cord, brainstem, thalamus, and cortex [38]. This in EF, it is apparent that not all individuals with ADHD technique has also been used to examine physical and have EF deficits [18,19] and that not all neuropsychologi- cognitive impairments in individuals with Alzheimer's cal difficulties can be explained by EF theory alone [20]. [39], stroke patients [40], and infantile autism [41], for Moreover, EF tasks in which individuals with ADHD do example. Using MEG, we investigated the oscillatory show deficits often include processing and responding to changes during somatosensory activation in adults with simple sensory stimuli that vary in predictability. This sug- and without ADHD. gests that deficits in anticipatory or perceptual processing of simple stimuli could also contribute to impairments on The general assumption of cortical oscillations is that tasks that assess higher-order functions. Accordingly, an populations of neurons exist in varying states of syn- important goal of ADHD research is to address not only chrony as they respond to externally or internally gener- the concept of multiple forms of impairment but also of ated events. Event-related desynchrony (ERD) and event- multiple sources of impairment. Emerging evidence not related synchrony (ERS) phenomena are thought to repre- only shows abnormalities in neural regions governing sent decreases and increases, respectively, in synchroniza- higher order function but also in regions governing basic tion within a specific frequency range in relation to an function such as somatosensory cortex [21-24], motor event [42]. Previous MEG studies of cortical activity fol- cortex [21,25,26] and visual cortex [27]. Although people lowing median nerve stimulation in healthy adults report with ADHD have shown behavioural deficits in respond- brief suppression of mu (an alpha wave variant oscillating ing to simple stimuli during sensorimotor tasks [28-30], at approximately 10 Hz) and beta (15–30 Hz) cortical methodological shortcomings in the limited studies avail- activity in primary and secondary somatosensory cortex able have precluded an adequate understanding of the (ERD) followed by a marked increase in beta band activity role of neural networks in processing predictable and above baseline (late-ERS, known as beta rebound) [42]. non-predictable stimuli in ADHD. Specifically, existing Basic or complex sensory processing requires a dynamic studies have relied almost exclusively on behavioural interaction between groups of neurons oscillating at par- Page 2 of 13 (page number not for citation purposes) Behavioral and Brain Functions 2008, 4:8 http://www.behavioralandbrainfunctions.com/content/4/1/8 ticular frequencies and differing degrees of coupling. Head position in relation to the MEG sensors was deter- Oscillations in the alpha and beta bands are of particular mined by measuring the magnetic field generated by 3 interest in ADHD research as these frequencies are fiducial reference coils just before and after each experi- thought to mediate perception [43,44] and attention [45- mental session. T -weighted structural magnetic reso- 47]. To our knowledge, MEG has not yet been used to nance images (MRI) (axial 3D spoiled gradient echo investigate changes in SI alpha or beta oscillations in indi- sequence) were obtained for each participant using a 1.5 viduals with ADHD. Accordingly, our aim was to charac- Tesla Signal Advantage system (GE Medical Systems, Mil- terize ERD and ERS in the alpha and beta bands in SI and waukee, USA). During MRI data acquisition, 3 radio- SII in response to randomly and predictably presented graphic markers were positioned on the same anatomical electrical stimulation of the median nerve in adults with landmarks as the fiduciary coils to allow coregistration and without ADHD. Comparison of random versus pre- accuracy of the MEG and MRI data. Single equivalent cur- dicted median nerve stimulation is a novel approach to rent dipole (ECD) models were also fit to the N20m determine whether basic somatosensory processing dif- median nerve responses in order to confirm coregistration fers between those with ADHD and healthy controls and accuracy. if stimulus predictability differentially influences somato- sensory processing in those with ADHD compared to con- Experimental Paradigm trols. Individuals were asked to lie comfortably on a bed in the MEG room and relax. Stimuli were non-painful, current The neural basis of predictive responding to the absence of pulses of 0.2 ms duration, presentation rate of 0.5 Hz (ISI: a stimulus in both SI and SII will be described in a subse- 2000 ms between onset of each stimulus), just above quent report. motor threshold (eliciting a small, passive, thumb twitch) applied cutaneously to the right median nerve. Somato- Methods sensory stimuli were presented in two counterbalanced Participants conditions: a) Predicted Stimulus Pattern and b) Random We studied nine adults (4 females/5 males) with a diagno- Stimulus Pattern. In the Predicted Pattern, stimuli sis of ADHD (mean age: 34.6 +/- 3.28 years) and ten occurred in trains of four followed by a long break before healthy age-matched controls (4 females/6 males; mean the next train (4000 ms) giving 332 stimulus events (83 age of 34.13 +/- 4.6 years). All were right-handed. Adults trains) and 83 breaks in between trains. In the Random with ADHD were recruited from an outpatient neuropsy- Pattern, stimuli and long breaks (4000 ms) were ran- chiatry clinic in a mental health centre in a large metro- domly dispersed throughout a 415 event trial (totaling politan city. All had completed the same comprehensive 332 stimuli and 83 breaks). Each condition was 12 min- clinical diagnostic assessment including: a clinical diag- utes in length. Participants were naïve as to the specific nostic interview and various self-report rating scales patterns that were presented. Upon completion of both including the Conners Scales [48]; Wender Utah Rating stimulus conditions, each participant was asked if they Scale [49], Brown Attention Deficit Disorder Scales recognized a presentation pattern or not in each of the (Brown, 1996); and Adult Self-Report Scale [50]. Healthy paradigms. adult volunteers were recruited by means of advertise- ments placed in the same institution and in other com- This research was conducted in compliance with the Hel- munity organizations. All participants completed a sinki Declaration and approved by the Research Ethics telephone-based Intake Screening Questionnaire (screens Board at The Hospital for Sick Children, Toronto, Canada, for psychopathology and education level) and the Adult File Number 1000010728. ADHD Self-Report Scale [51] at the time of participation Data analyses to estimate current levels of ADHD symptomatology. Par- ticipants were excluded if they wore orthodontic braces, Neural activities during the experiments were analyzed had any non-removable metal, or had a diagnosis of psy- with respect to brain location, latency, and frequency to chosis, neurological disorder, or uncorrected sensory determine spatiotemporal profiles of event-related activ- impairments. ity time-locked to stimulus presentation. Initial spatial analyses were performed using a novel application of a MEG Recordings minimum-variance beamformer algorithm (synthetic A whole-head 151 channel MEG system (VSM MedTech aperture magnetometry: SAM) [52-54]. In order to map Ltd, Vancouver, Canada) was used to measure somatosen- the median nerve initial response we created SAM differ- sory evoked fields. Participants lay in a supine position in ential images by subtracting control periods (-200 to 0 ms a magnetically shielded room with their head resting in prior to stimulus or gap onset) from active periods (0 to the MEG helmet. The MEG signals were bandpass filtered 200 ms after stimulus or gap onset) and filtering the data at 0.3 – 300 Hz and recorded at a 1250 Hz sampling rate. from 3 – 50 Hz. This resulted in high resolution (2 mm) Page 3 of 13 (page number not for citation purposes) Behavioral and Brain Functions 2008, 4:8 http://www.behavioralandbrainfunctions.com/content/4/1/8 three-dimensional differential images which were time- SAM analysis indicated that for individuals in both the locked to median nerve stimulation and averaged over comparison and ADHD groups, the control period time to identify peak activation sites in the brain during showed little or no somatosensory activation with average the active period relative to baseline. Grand averaged peak values being approximately 5% of active period val- localizations of regional activity peaks for each group ues (for average peak values during control and active were determined by warping SAM images to a template periods see Additional files 1 &2 for control and ADHD brain and averaging across subjects using Statistical Para- groups, respectively). During the active period, maximal metric Mapping software [55]. Source activity was over- peak activity was localized specifically to the hand area, laid on the template brain and imaged using mri3dX area 3b, in the contralateral primary somatosensory cortex software [56]. (SI) (Figure 1). The virtual sensor of each individual's con- tralateral SI location identified that for the control group We then computed the single trial output of the spatial fil- the grand-averaged maximal activity occurred at 22.02 ms ters ('virtual sensors') for peak locations of source activity +/- 0.74 SEM post-stimulus and at 21.78 ms +/- 0.86 SEM in the SAM images displaying millisecond changes in for the ADHD group. There was no statistical difference of source power. Time-frequency response (TFR) plots were response time [t(17) = 0.303, p > 0.05]. constructed from the virtual sensor data using a wavelet- based technique which demonstrates both phase-locked Time-Frequency Representation (TFR) plots clearly dem- and non-phase-locked changes in power at different fre- onstrated that there were three distinct phases of rhythmic quencies over time relative to the baseline period (-100 changes in the somatosensory cortex. These occurred in ms to 0 ms prior to stimulus onset). both primary and secondary cortices (SI and SII, respec- tively) in both controls and those with ADHD; (i) early- Following TFR results we wished to examine group differ- ERS (approximately 20 to 200 ms post-stimulus); (ii) ERD ences for specific frequency sets. Selected bandwidths (approximately 200 to 400 ms post-stimulus); and (iii) were averaged across subjects, demonstrating the time late-ERS, known as beta rebound (approximately 400+ ms course of averaged group response amplitude for a chosen post-stimulus). In the control group, the early ERS in SI frequency set. Regions on the line graphs were highlighted was a broad-frequency increase in power occurring wherever standard errors did not overlap between con- approximately 20 to 200 ms post-stimulus. This immedi- trols and those with ADHD in order to exemplify band- ate response was followed by a broad-frequency ERD; a widths where the two groups diverged significantly over transitory suppression of source power below baseline time. To determine statistical differences between groups that occurred from 200 to 400 ms post-stimulus. Follow- and conditions for each separate time-frequency value we ing the suppression, the final phase of activity demon- used a permutation program that extracted the normal- strated a rebound of ERS specific to the beta band that ized, source power value for each time-frequency bin. Individual data were subject to 1000 permutations and then collapsed across participants within a specific group and experimental condition to derive a mean value which could then be statistically compared between groups or conditions. The group mean difference for each pixel was plotted (i.e. – control group data minus ADHD group data for SI random condition) and subsequently thresh- olded so that only statistically significant differences remained, being expressed as a P-Value plot. Multiple comparison corrections (such as a Bonferroni correction) were not made to the data as each TFR point was not inde- pendent. Results Primary somatosensory cortex (SI) Random stimulus presentation Neural activity captured from each of the 151 MEG chan- nels was averaged over the total number of trials in which Gran and ADHD (re Figure 1 d Mean Contra d) Based latera on SAM D l SI localization for ifferential Anal Control (blue) yses a stimulus was presented, and then spatial analyses were Grand Mean Contralateral SI localization for Control performed using SAM to create differential images that (blue) and ADHD (red) Based on SAM Differential represented changes from baseline in neural activity. Analyses. Page 4 of 13 (page number not for citation purposes) Behavioral and Brain Functions 2008, 4:8 http://www.behavioralandbrainfunctions.com/content/4/1/8 began approximately 400 ms after median nerve stimula- Group comparisons revealed that adults with ADHD tion and lasted for about 1200 ms (Figure 2A). Our find- showed substantially less power between 10 and 15 Hz ings are consistent with previous research showing that during the early ERS, compared to the control group and beta rebound begins between 250 ms [57,58] and 500 ms substantially less power during beta rebound (Figure 2C). [58] following median nerve stimulation. The group differences in neural response reached statisti- cal significance between 30 and 180 ms and ranges from In the ADHD group the early SI ERS, occurring approxi- 11 to 14 Hz during the immediate response (Figure 2D). mately 20 to 200 ms post-stimulus, was characterized by This is highlighted in the line graph (Figure 2E) where one strong early ERS in the lower bandwidths (theta and low can observe the considerable divergence of the two groups alpha) and high beta band (25+ Hz), with more moderate in amplitude of response across this particular frequency activity in the midrange (10 to 22 Hz) compared to base- range over the first 200 ms of the trial (i.e., marked area in line. ERD occurred across the spectrum of frequencies which there is no overlap of group standard error bars). from 200 to 400 ms post-stimulus while beta rebound Adults with ADHD also showed substantially less ERS ERS commenced at approximately 400 ms but continued than controls between 15 and 30 Hz in the latter half of for only 600 ms which was considerably shorter in dura- the trial (1000+ ms) (also Figure 2D), indicating that indi- tion than controls (Figure 2B). viduals with ADHD experienced a significantly shorter beta rebound following a somatosensory event. The line graph demonstrates the power divergence of the entire S Figure 2 I Group Differences in Frequency and Power During Random Presentation of a Somatosensory Stimulus SI Group Differences in Frequency and Power During Random Presentation of a Somatosensory Stimulus. (A) Grand Mean TFR of the individual, virtual channel, spatially-filtered single trials for control subjects. In both control subjects and subjects with ADHD the plot was baselined using the average spectral energy observed in the pre-stimulus period (-100 – 0 ms). (B) Grand Mean TFR of the individual, virtual channel, spatially-filtered single trials for subjects with ADHD. (C) Group mean differences of the group TFRs. (D) Statistically significant values remaining once group differences were thresholded to p </= 0.05. (E) Divergence of early response to the stimulus in controls and ADHD. (F) Divergence of power in beta rebound in the latter portion of the trial between controls and ADHD. Page 5 of 13 (page number not for citation purposes) Behavioral and Brain Functions 2008, 4:8 http://www.behavioralandbrainfunctions.com/content/4/1/8 beta bandwidths between groups during the rebound ditions from 1200 to 1500 ms in the 17 to 25 Hz range period (Figure 2F). (Additional file 4). Predicted stimulus presentation In the control group, the TFR analysis of the early SI ERS For controls, the temporal onset of the grand averaged SI revealed intense activity from 5 Hz to 50+ Hz followed by response occurred at 21.30 ms +/- 0.94 SEM which did not ERD and a strong beta rebound ERS (Figure 3A). Notably, statistically differ from the onset of the averaged control SI mu rhythm showed ERD (150 ms to 900 ms) and beta random response [t(9) = 0.79, p > 0.05]. Permutation rebound ERS (900 ms to 1600 ms) following tactile stim- analysis revealed that the grand averaged time-frequency ulation. The somatosensory region endogenously oscil- responses for controls did not differ statistically between lates around this bandwidth [59,60] and SI mu the random and predicted stimulus conditions (Addi- synchronizations and desynchronizations have been tional file 3). Similarly, the grand averaged SI temporal identified consistently in response to median nerve stim- onset of the ADHD group response occurred at 21.62 ms ulation [61]. +/- 1.14 SEM which did not differ from their averaged ran- dom onset [t(8) = 0.198, p > 0.05] or from the control pre- The TFR analysis of the ADHD group showed a strong dicted temporal onset [t17) = -0.225, p > 0.05]. early ERS in the lower bandwidths (theta and low alpha) Interestingly, permutation analyses of the ADHD TFRs and high beta band (25 to 40 Hz), but little power in the suggested a a slight within-group difference between con- midrange (10 to 22 Hz) followed by ERD and a rebound Figure 3 SI Group Differences in Frequency and Power During Predicted Presentation of a Somatosensory Stimulus SI Group Differences in Frequency and Power During Predicted Presentation of a Somatosensory Stimulus. (A) Grand Mean TFR of the individual, virtual channel, spatially-filtered single trials for control subjects. In both control sub- jects and subjects with ADHD the plot was baselined using the average spectral energy observed in the pre-stimulus period (- 100 – 0 ms). (B) Grand Mean TFR of the individual, virtual channel, spatially-filtered single trials for subjects with ADHD. (C) Group mean differences of the group TFRs. (D) Statistically significant values remaining once group differences were thresh- olded to p </= 0.05. (E) Groups show no divergence of early response to the stimulus in controls and ADHD. (F) Divergence of power in beta rebound in the pre-stimulus period between controls and ADHD. Page 6 of 13 (page number not for citation purposes) Behavioral and Brain Functions 2008, 4:8 http://www.behavioralandbrainfunctions.com/content/4/1/8 ERS composed of strong activation during the first half of the rebound period and reduced activation in the latter half (Figure 3B). Additionally, there was a subtle, transient beta response just prior to stimulus onset observed in the ADHD TFR grand mean (Figure 3B, circled). Even though we observed some general group differences in power of the early ERS, ERD, and beta rebound ERS in the Predicted condition Group comparisons between con- trols and those with ADHD (Figure 3C) there were no sta- tistical differences in power changes between groups during any of these phases (Figure 3D). The lack of a dif- ference in beta activity during these phases is exemplified in the beta bandwidth line graph analyses (Figure 3E). However, examining SI activity in the pre-stimulus phase of the trial we observed a significant between-group differ- Grand and ADHD ( Figure 4 Mean contral red) based on SA ateral SII lo M differential an calization for control ( alyses blue) ence that may suggest anticipatory neural responses in the Grand Mean contralateral SII localization for control ADHD group (also Figure 3D) when at approximately 170 (blue) and ADHD (red) based on SAM differential ms prior to stimulus onset the two group responses began analyses. to diverge (Figure 3F) and the ADHD group showed an early increase in beta power that the control group did not. Group comparisons revealed that overall, SII responding Secondary somatosensory cortex (SII) of adults with ADHD showed markedly less source power SAM analyses showed prominent activation of secondary than that of controls (Figure 5C). These group differences somatosensory cortices (SII) within the parietal opercu- were substantiated in the permutation analyses which lum. Bilateral SII activation was observed with contralat- revealed that adults with ADHD displayed significantly eral and ipsilateral activity profiles being very similar. For less ERD and significantly shorter beta rebound ERS brevity, only contralateral SII information, the recipient of across both alpha and beta activities (Figure 5D). The neu- contralateral SI information, is reported. ral responses of the two groups diverged considerably dur- ing broad-spectrum ERD (Figure 5E) and during the Random stimulus presentation ensuing beta rebound ERS (Figure 5F). The control and ADHD groups both showed consistent, robust peak activity in SII (Figure 4). For controls, the Predicted stimulus presentation grand-averaged virtual sensor identified the first activity In the control group, the temporal onset of the grand aver- peak at 41.20 ms +/- 2.43 SEM following a stimulus: for aged control SII response (41.85 ms +/- 1.20 SEM) did not adults with ADHD it occurred at 43.15 ms +/- 3.16 SEM statistically vary between random and predicted condi- which did not statistically differ from the onset of the tions [t(9) = -0.318, p > 0.05]. Grand averaged time-fre- averaged control random response [t(17) = -0.803, p > quency responses did not statistically vary between the 0.05]. two conditions they experienced (Additional file 5). Cor- respondingly, the grand averaged SII temporal onset of The grand-averaged TFR In the control group showed response of adults with ADHD (40.38 ms +/- 1.97 SEM) strong early ERS in the trial followed by strong ERD and did not vary in the predicted condition compared to the beta rebound ERS activity similar to that observed in SI. random condition [t(8) = 0.92, p > 0.05] or from the SII The early ERS and the ERD was characterized by robust control predicted temporal onset [t(17) = 0.651, p > 0.05] activity from 5 to 20 Hz, with the strongest activity oscil- Grand averaged time-frequency responses did not statisti- lating around 7 Hz while frequencies 15 to 30 Hz contrib- cally vary between the two conditions the ADHD group uted to the ensuing rebound (Figure 5A). By contrast, in experienced except for the period of ERD in which the SII the ADHD group the grand-averaged TFR showed a mod- response showed significantly more desynchrony in the est early ERS response characterized by clusters of source alpha band (between 8 and 10 Hz) in the predicted con- power oscillating at theta, alpha, and beta frequencies. dition than in the random one (Additional file 6). Moreover, minimal ERD power was present in the alpha and low beta bandwidths and this was followed by a very In the control group, SII exhibited strong early ERS from brief, modest beta rebound ERS (Figure 5B). 5 Hz to 25 Hz followed by ERD and beta rebound ERS, consistent with the control Random SII response. Similar Page 7 of 13 (page number not for citation purposes) Difference in Source Power Source Power Difference in Source Power Source Power Behavioral and Brain Functions 2008, 4:8 http://www.behavioralandbrainfunctions.com/content/4/1/8 SII Random Stimulus Response Control E 5-30 Hz Activity B ADHD 1.0 1 50 Control Control 0.8 SE Control 0.8 0.8 45 SE Control AA DHD DHD 0.6 0.6 0.6 40 SE ADHD SE ADHD 0.4 0.4 0.4 35 0.2 0.2 0.2 30 30 0 0 -0.2 -0.2 -0.2 20 20 -0.4 -0.4 -0.4 -0.6 -0.6 -0.6 10 10 -0.8 -0.8 5 -0.8 -1.0 -1 -1 0 0.1 0.2 0.3 0.4 0.5 0.6 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 Time (sec) Time (sec) Time (sec) Group Mean Difference (Control - ADHD) P-Value Plot, p </= 0.05 15-30Hz Activity 0.4 0.4 50 50 1.0 Control 45 0.9 0.3 0.3 SE Control 40 0.8 ADHD 0.2 0.2 SE ADHD 35 35 0.7 0.1 0.1 0.6 30 30 0 0.5 25 25 0.4 -0.1 -0.1 control 0.3 15 15 -0.2 -0.2 0.2 10 10 -0.3 -0.3 0.1 5 5 -0.4 -0.4 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 Time (sec) Time (sec) Time (sec) SII Group Differ Figure 5 ences in Frequency and Power During Random Presentation of a Somatosensory Stimulus SII Group Differences in Frequency and Power During Random Presentation of a Somatosensory Stimulus. (A) Grand Mean TFR of the individual, virtual channel, spatially-filtered single trials for control subjects. In both control sub- jects and subjects with ADHD the plot was baselined using the average spectral energy observed in the pre-stimulus period (- 100 – 0 ms). (B) Grand Mean TFR of the individual, virtual channel, spatially-filtered single trials for subjects with ADHD. (C) Group mean differences of the group TFRs. (D) Statistically significant values remaining once group differences were thresh- olded to p </= 0.05. (E) Divergence of the ERD response to the stimulus in controls and ADHD. (F) Divergence of power in beta rebound in the latter portion of the trial between controls and ADHD. to the SI Predicted response and contrary to the SII Ran- and significantly shorter beta rebound ERS than the con- dom response, the SII Predicted control response showed trols (Figure 6D). The two group responses diverged con- mu ERD followed by a rebound ERS late in the trial (Fig- siderably within the ERD (alpha bandwidth) and beta ure 6A). rebound ERS phases (beta bandwidth) (Figure 6E &6F, respectively). In the ADHD group, the SII predicted response showed modest early ERS composed mostly of alpha and some Debriefing interview beta oscillations followed by corresponding ERD and a There were no group differences in their detection of stim- small beta rebound ERS. Minor activation around 10 Hz ulus patterns during median nerve stimulation: where no from 1000 ms to 1600 ms suggests a faint mu rebound participants detecting a pattern during the random condi- effect (Figure 6B). tion and all participants reported detecting a pattern dur- ing the predicted stimulus condition. Group comparisons revealed that, as in SII Random, the overall responding of adults with ADHD was considerably Discussion less than the controls (Figure 6C). The permutation anal- This study used MEG with median nerve stimulation to yses corroborated the findings revealing that individuals determine whether somatosensory processing was altered with ADHD displayed exhibited significantly less ERD in adult ADHD. We measured frequency specific changes Page 8 of 13 (page number not for citation purposes) Frequency (Hz) Frequency (Hz) Frequency (Hz) Frequency (Hz) Amplitude of Response Amplitude of Response Amplitude of Response Behavioral and Brain Functions 2008, 4:8 http://www.behavioralandbrainfunctions.com/content/4/1/8 8-12 Hz Activity Figure 6 SII Group Differences in Frequency and Power During Predicted Presentation of a Somatosensory Stimulus SII Group Differences in Frequency and Power During Predicted Presentation of a Somatosensory Stimulus. (A) Grand Mean TFR of the individual, virtual channel, spatially-filtered single trials for control subjects. In both control sub- jects and subjects with ADHD the plot was baselined using the average spectral energy observed in the pre-stimulus period (- 100 – 0 ms). (B) Grand Mean TFR of the individual, virtual channel, spatially-filtered single trials for subjects with ADHD. (C) Group mean differences of the group TFRs. (D) Statistically significant values remaining once group differences were thresh- olded to p </= 0.05. (E) Divergence of the ERD response to the stimulus in controls and ADHD. (F) Divergence of power in beta rebound in the latter portion of the trial between controls and ADHD. in evoked spatiotemporal patterns of neural activation in somatosensory information is less well-characterized at a response to non-painful electrical stimuli in adults with basic neural level in those with ADHD. Irrespective of and without ADHD. Major findings included a marked whether stimuli were randomly or predictably presented, reduction in the duration of beta rebound in the ADHD the ADHD group showed substantive power decreases in group compared to controls in both SI and SII. Beta SII alpha and beta ERD and SII beta rebound ERS relative rebound is a post-stimulus beta phenomenon which com- to controls as well as a significantly shorter SII beta mences approximately 400 – 600 ms after median nerve rebound. From SI, somatosensory information is thought stimulation. Additionally, the ADHD group showed a to project to SII, where stimulus information is integrated substantial decrease in SII alpha and beta power during and contextualized [62,63]. Without sufficient consolida- ERD (decreases in power of cortical oscillations below tion at SI the deficit may become even more profound as baseline) and ERS (increases in power of cortical oscilla- the information is volleyed to the higher processing tions above baseline). region of SII. This would explain the marked reduction in SII ERD and ERS in the ADHD group. When the stimuli were randomly presented, the ADHD group showed reduced SI ERS power during the immedi- To our knowledge this is the first demonstration of ate N20m response and a significantly shorter SI beta reduced duration of somatosensory evoked beta rebound rebound than the controls. This suggests that incoming in a clinical population. Little is known regarding the Page 9 of 13 (page number not for citation purposes) Behavioral and Brain Functions 2008, 4:8 http://www.behavioralandbrainfunctions.com/content/4/1/8 functional significance of the beta rebound response. His- Our findings support the notion that cortical oscillations torically, beta rebound was thought to be an epiphenom- are altered during somatosensory processing in those with enon that originated in the motor cortex in response to ADHD. It is possible that impaired somatosensory volitional movement [64]. More recent MEG recordings processing may impede sensorimotor development, as show that beta rebound also occurs in somatosensory cor- has been found in a substantial proportion of children tex and can be initiated by a tactile stimulus, in the with ADHD [71-74]. Our data may explain, in part, why absence of volitional movement [47]. Moreover, attend- individuals with ADHD perform poorly on tasks that ing to a stimulus can suppress beta rebound relative to require somatosensory feedback such as externally-paced that occurring when the stimulus is intentionally ignored finger-tapping tasks [28,30,75,76] especially when the [47]. Both movement imagery [65] and observation [66] tasks require that tactile information be integrated in have been found to suppress the rebound effect. Collec- higher processing regions. Alternatively, it is possible that tively, these findings suggest that beta rebound can be deficits in attention or executive functions may exert top- associated with cognitive state. down influences on somatosensory processing in the ADHD group. Further evidence supports the notion that beta rebound plays a significant role in cortical inhibition of neural Our study is limited by the fact that we were unable to regions unrelated to current task performance [42]. For investigate effects of gender, comorbidity, or treatment instance, Chen et al [67] showed that the brain is less history as the sample of adults with ADHD used in this responsive to transcranial magnetic stimulation during study was small and heterogeneous, with variation in age, the period of beta rebound following median nerve stim- comorbidity, and/or medication (although medication ulation. If cortical inhibition is indexed by levels of beta was stopped for at least 24 hours prior to the study). Addi- activity then it might be argued that the lower levels of tionally, right hemisphere SI activity was not investigated beta activity in individuals with ADHD reflect increases in as median nerve stimulation was only delivered to the cortical activity. Functional imaging studies indicate that dominant arm. In spite of these limitations, several find- individuals with ADHD activate more widespread brain ings reach statistical significance, emphasizing the power- regions than controls during task performance (review: ful nature of the differences in somatosensory processing [68]). between the two groups. Future studies will investigate the effects of gender, comorbidity, and medication, as well as To our knowledge, this is the first application of MEG to the activity of the right SI in response to a contralateral investigate changes in somatosensory alpha or beta power stimulus. Future steps to examine the cortical activity in in individuals with ADHD. Here we demonstrate that regions that are in communication with the somatosen- adults with ADHD showed less changes in source power sory cortex are necessary goals to further elucidate differ- in the alpha and beta bands overall in response to a som- ences in basic processing in individuals with ADHD. atosensory stimulus. Correspondingly, reduced alpha and beta powers have consistently been associated with In summary, this study revealed several novel observa- ADHD EEG profiles (review: [69]). Intriguingly, when the tions regarding somatosensory activity in an ADHD pop- adults in the ADHD group were able to predict the onset ulation. It is the first to profile somatosensory ERS and of an impending event, their SI response to a stimulus did ERD in ADHD and the first to show that beta rebound is not differ statistically from controls. It may be that the not a uniform phenomenon but one that can be modified small sample size precluded our ability to detect an under- in the presence of a psychiatric disorder. Profiling lying effect, as the group mean time frequency plots for impaired cortical rhythms in response to basic sensory the SI Predicted condition in the ADHD and control processing in ADHD will provide a more in depth under- groups appear different, however these differences did not standing of the breadth of deficits in individuals with reach statistical significance. Alternatively, it may be the ADHD and aid in reconstructing the conceptualization case that, when a stimulus is predictable, individuals with and clinical understanding of ADHD. ADHD are able to recruit additional resources to facilitate somatosensory processing, thereby concealing underlying Competing interests primary deficits. A similar effect has been observed in The author(s) declare that they have no competing inter- individuals with obsessive-compulsive disorder whose ests. behavioural performance was the same as controls in a visual working memory task [70]. This occurred in spite of Authors' contributions the fact that these patients had significantly weaker desyn- CD developed the design of the study, carried out MEG chrony in the alpha band in response to a visual stimulus recordings (subject testing), statistical analyses, and during the task with a distracter present but not when the drafted the manuscript. WG participated in the design of distracter was absent [70]. the study, contributed to the interpretation of the results. Page 10 of 13 (page number not for citation purposes) Behavioral and Brain Functions 2008, 4:8 http://www.behavioralandbrainfunctions.com/content/4/1/8 DC participated in the design of the study and contributed Additional file 5 to the development of the source analysis methods and Control SII Frequency and Power Dynamics During Predicted versus interpretation of the results. FW carried out MEG record- Random Presentation of a Somatosensory Stimulus (A). Grand Mean ings, statistical analyses, and computer programming. TFR of the individual, virtual channel, spatially-filtered single trials for FXC contributed to the interpretation of the results. RT control subjects during Predicted presentation of a stimulus. The plot was participated in the overall conceptualization and supervi- baselined using the average spectral energy observed in the pre-stimulus sion of project, including the design and interpretation of period (-100 – 0 ms). (B) Grand Mean TFR of the individual, virtual the results, All authors read, contributed to, and approved channel, spatially-filtered single trials for control subjects during Random presentation of a stimulus. (C) Mean TFR differences between conditions. the final manuscript. (D) Statistically significant values remaining once condition differences were thresholded to p </= 0.05. Additional material Click here for file [http://www.biomedcentral.com/content/supplementary/1744- 9081-4-8-S5.pdf] Additional file 1 Example of a control subject's SAM peak locations and values during con- Additional file 6 trol (SAM peak value = 2.0) and active (SAM peak value = 16.3) states ADHD SII Frequency and Power Dynamics During Predicted versus in somatosensory cortex Random Presentation of a Somatosensory Stimulus (A). Grand Mean Click here for file TFR of the individual, virtual channel, spatially-filtered single trials for [http://www.biomedcentral.com/content/supplementary/1744- subjects with ADHD during Predicted presentation of a stimulus. The plot 9081-4-8-S1.pdf] was baselined using the average spectral energy observed in the pre-stim- ulus period (-100 – 0 ms). (B) Grand Mean TFR of the individual, vir- Additional file 2 tual channel, spatially-filtered single trials for subjects with ADHD during Example of an ADHD subject's SAM peak locations and values during Random presentation of a stimulus. (C) Mean TFR differences between control (SAM = 1.3) and active (SAM peak value = 15.0) states in som- conditions. (D) Statistically significant values remaining once condition atosensory cortex differences were thresholded to p </= 0.05. Click here for file Click here for file [http://www.biomedcentral.com/content/supplementary/1744- [http://www.biomedcentral.com/content/supplementary/1744- 9081-4-8-S2.pdf] 9081-4-8-S6.pdf] Additional file 3 Control SI Frequency and Power Dynamics During Predicted versus Random Presentation of a Somatosensory Stimulus (A). Grand Mean Acknowledgements TFR of the individual, virtual channel, spatially-filtered single trials for Many thanks to Travis Mills for developing the permutation program for control subjects during Predicted presentation of a stimulus. The plot was statistical analyses of TFR data and to Sonya Bells for her help running par- baselined using the average spectral energy observed in the pre-stimulus ticipants in the MEG facility. period (-100 – 0 ms). (B) Grand Mean TFR of the individual, virtual channel, spatially-filtered single trials for control subjects during Random We greatly appreciated funding provided by a National Institute of Mental presentation of a stimulus. (C) Mean TFR differences between conditions. Health Operating Grant (FXC, RT), Hospital for Sick Children Psychiatry (D) Statistically significant values remaining once condition differences Endowment (RT and CD), Canada Research Chair Program (RT), a Post- were thresholded to p </= 0.05. Doctoral Fellowship from the Hospital for Sick Children Research Training Click here for file [http://www.biomedcentral.com/content/supplementary/1744- Centre (CD), and operating grants from the Canadian Institutes of Health 9081-4-8-S3.pdf] Research (DC). Additional file 4 References 1. Seidman LJ, Valera EM, Bush G: Brain function and structure in ADHD SI Frequency and Power Dynamics During Predicted versus adults with attention-deficit/hyperactivity disorder. Psychiatr Random Presentation of a Somatosensory Stimulus (A). Grand Mean Clin North Am 2004, 27(2):323-347. TFR of the individual, virtual channel, spatially-filtered single trials for 2. Krain AL, Castellanos FX: Brain development and ADHD. Clin subjects with ADHD during Predicted presentation of a stimulus. The plot Psychol Rev 2006, 26(4):433-444. was baselined using the average spectral energy observed in the pre-stim- 3. di Michele F, Prichep L, John ER, Chabot RJ: The neurophysiology ulus period (-100 – 0 ms). 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Published: Feb 12, 2008