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Moderate cycling exercise enhances neurocognitive processing in adolescents with intellectual and developmental disabilities
Research in Developmental Disabilities 34 (2013) 2708–2716
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Research in Developmental Disabilities
Moderate cycling exercise enhances neurocognitive processing in adolescents with intellectual and developmental disabilities Tobias Vogt a,*, Stefan Schneider a, Volker Anneken b, Heiko K. Stru¨der a a
Department of Exercise Neuroscience, Institute of Movement and Neurosciences, German Sport University, Am Sportpark Mu¨ngersdorf 6, 50933 Cologne, Germany Research Institute for Inclusion Through Physical Activity and Sport, Ro¨merstraße 100, 50226 Frechen, Germany
b
A R T I C L E I N F O
A B S T R A C T
Article history: Received 8 April 2013 Received in revised form 16 May 2013 Accepted 21 May 2013 Available online 14 June 2013
Research has shown that physical exercise enhances cognitive performance in individuals with intact cognition as well as in individuals diagnosed with intellectual and developmental disabilities. Although well identified in the field of health (for example, the transient hypofrontality theory), the underlying neurocognitive processes in intellectual and developmental disabilities remain widely unclear and thus characterize the primary aim of this research. Eleven adolescents with intellectual and developmental disabilities performed moderate cycling exercise and common relaxation. Cross-over designed, both 10-min meetings were randomly allocated at the same time of day with 24h time lags in between. Conditions were embedded in ability-modified cognitive performance (decision-making processes). Participants’ reaction times and their equivalent neurophysiological parameters were recorded using standard EEG and analyzed (spatial activity, N2). Exercise revealed a decrease in frontal electrocortical activity, most pronounced in the medial frontal gyrus (10%). To that effect, reaction time (p < 0.01) was decreased and mirrored in decreased N2 latency (p < 0.01) after exercise. In contrast, relaxation revealed no significant changes. Results of this research suggest exercise temporarily enhances neuronal activity in relation to cognitive performance for adolescents with intellectual and developmental disabilities; further research is needed to explore possible future effects on enhancing neurocognitive development. ß 2013 Elsevier Ltd. All rights reserved.
Keywords: EEG Intellectual and developmental disability Exercise Cognitive performance Reaction time N2
1. Introduction Today, exercise is recommended to maintain physical and mental health in humans (Brisswalter, Collardeau, & Rene´, 2002; Hagen et al., 2012). Numerous neurophysiological and behavioral research studies address the duration, intensity, and – more recently – individual exercise preferences in relation to well-being and cognitive performance (Schneider, Bru¨mmer, Abel, Askew, & Strueder, 2009). Although this research covers an extensive span of life and class of population, little is known about exercise-induced neurocognitive processes in intellectual and developmental disabilities (IDD). According to the American Association on Intellectual and Developmental Disabilities (AAIDD), IDD is characterized by limited intellectual functioning; e.g. learning, reasoning, and problem solving, as well as adaptive behavior; e.g. conceptual, social and practical skills that originate in adolescence. Adolescence is a time of considerable neurocognitive and behavioral
* Corresponding author at: Department of Neuroscience, Institute of Movement and Neurosciences, German Sport University Cologne, Am Sportpark Mu¨ngersdorf 6, 50933 Cologne, Germany. Tel.: +49 221 4982 4260; fax: +49 221 4973 454. E-mail address: [email protected] (T. Vogt). 0891-4222/$ – see front matter ß 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.ridd.2013.05.037
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development (Blakemore & Choudhury, 2006; Blakemore, 2012; Hartman, Houwen, Scherder, & Visscher, 2010). Hence, research focuses on beneficial processes to improve neurocognitive behavior in IDD during adolescence (Leggett, Jacobs, Nation, Scerif, & Bishop, 2010; Silver et al., 2008). Recently, a first attempt at using exercise to specifically benefit neural behavior in IDD has been suggested (Vogt, Schneider, Abeln, Anneken, & Stru¨der, 2012). To that effect, increased social acceptance and participation further underline the needs to broaden the understanding of exercise-induced changes on cognitive performance in IDD. While relaxation setups (‘snoezelen’; Mertens, 2008) are commonly used in rehabilitation facilities to improve concentration in IDD (Hogg, Cavet, Lambe, & Smeddle, 2001), additional research suggests moderate exercise to contribute to general well-being and cognitive performance in IDD (Cervantes & Porretta, 2010; Hutzler & Korsensky, 2010). However, underlying neurocognitive processes are mainly disregarded (Temple, Frey, & Stanish, 2006) or are not considered in IDD-modified assessments of cognitive performance (Vogt et al., 2012). While commonly used in the field of clinical and cognitive neuroscience to explore IDD, electroencephalography (EEG) is still a relatively new method to record brain cortical activity in exercise physiology. However, recent technological developments enable the use of EEG in exercise setups, combining enhanced temporal and spatial resolution with a reduction of moving artifacts. To that effect, traditional EEG recordings enable low-resolution brain electromagnetic tomography (LORETA). The LORETA method (University Hospital of Psychiatry, Zurich, Switzerland) has previously been described and validated in clinical (Fuchs, Kastner, Wagner, Hawes, & Ebersole, 2002; Jurcak, Tsuzuki, & Dan, 2007; PascualMarqui, Esslen, Kochi, & Lehmann, 2002; Pascual-Marqui, 2002) and exercise research (Schneider, Bru¨mmer, et al., 2009; Schneider, Vogt, Frysch, Guardiera, & Struder, 2009; Vogt et al., 2012). This research indicates that cognitive processes relate to specific electrocortical activity patterns, particularly in frontal brain areas that are fundamental for cognitive performance. During exercise, the transient hypofrontality theory (Dietrich, 2006) suggests a shift of cortical resources away from brain areas that are rather negligible for movement processing but for cognitive performance. Neurocognitive research indicates that essential areas of the frontal lobe associate to sensory information processing (superior frontal gyrus, SuFG), motor control and movement processing (precentral gyrus, PrG and inferior frontal gyrus, InFG) and executive functions (medial frontal gyrus, MeFG), including decision-making processes such as go/no-go tasks (Chouinard & Paus, 2006; Ko¨no¨nen et al., 2005; Liakakis, Nickel, & Seitz, 2011; Talati & Hirsch, 2005). In addition, EEG recordings enable analyses and interpretation of event-related potential waveforms, sensitive to stimulus probability in amplitude and latency. Generally associated with cognitive control, the N2 component, as an event-related potential component, covers a concept of strategic monitoring and control of movement responses (Folstein & van Petten, 2008). Developments of cognitive control are reflected by decreases in the N2 amplitude and latency, indicating better cognitive performance (Lamm, Zelazo, & Lewis, 2006). Following stimulus onset in the averaged EEG waveform, the N2 peaks negatively between 200 and 350 ms. Its visual modality is prominent in occipital electrode sites. In order to modulate and assess neural responses of cognitive performance, previous research suggests the use of expected and unexpected sensory stimuli (Mangun, 1995). The consistent temporal modulation of N2 is suggested to indicate both an attentional preparation of decision-making, as well as ˜ ez, Madrid, & Tudela, 2006). Recent clinical research suggests that N2 latency in early motor processing (Correa, Lupia´n particular shows a correlation between cognitive performance and IDD (Papaliagkas, Kimiskidis, Tsolaki, & Anogianakis, 2011). 1.1. Hypotheses Accordingly, the primary aim of this research is to explore exercise-induced neurocognitive changes compared to common relaxation in adolescents with IDD. It is hypothesized that: (1) frontal electrocortical activity decreased after 10 min of moderate cycling exercise compared to 10 min of relaxation; (2) reaction time is improved after exercise compared to relaxation and (3) coinciding with neural responses of cognitive control – particularly in the N2 latency. 2. Materials and methods 2.1. Participants Approved by the University’s Human Research Ethics Committee, eleven right-handed adolescents (6 males, 5 females) volunteered to participate in this research (16 1.34 years, 167.27 10.01 cm, 69.36 7.80 kg). According to the AAIDD definition (Schalock et al., 2010), previously published characterizations (Vogt et al., 2012; World Health Organization, 1997) as well as medical records and school reports, participants were classified as adolescents with intellectual and developmental disabilities. Furthermore, participants were excluded if they were unable to differentiate between colors and shapes. Prior to involvement, participants attended an informatory meeting, including medical screening and familiarization with the experimental procedures. On agreement, legal guardians provided written informed consent. All participants were familiar with exercising–cycling, in particular. All procedures were in compliance with the Declaration of Helsinki for human participants. 2.2. Design This research was conducted in cooperation with schools for special needs education, focusing on intellectual and learning disabilities. Each participant attended two experimental meetings, differing in exercise and relaxation conditions.
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Exercise meant moderate cycling at self-paced intensity (please refer to Section 3.1 for heart rate results and power outputs) on a bicycle ergometer (Ergoline ER 900, Ergoline, Bitz, Germany), whereas relaxation meant resting while seated and listening to music. Music and the procedure were familiar from the participants’ common relaxations previously experienced in class and described as ‘snoezelen’ (Mertens, 2008; Hogg et al., 2001). Cross-over designed, both conditions lasted for 10 min (Ekkekakis, Hall, VanLanduyt, & Petruzzello, 2000; Schneider, Vogt, et al., 2009). Orders of experimental meetings were randomly allocated at the same time of day with at least 24-h time lags in between. Prior to the experiment, baseline electrocortical activity (EEG) was recorded for 2 min while seated with eyes closed (t0EEGexc/rel). To assess cognitive performance (COG), participants performed a reaction time task before (t1COGexc/rel) and after (t4COGexc/rel) each condition. Recordings were repeated during (t1EEGexc/rel) and following the initial cognitive performance (t2EEGexc/rel), right after the condition (t3EEGexc/rel) and again during (t4EEGexc/rel,) and following the final cognitive performance (t5EEGexc/rel) (see Fig. 1). Further details on the EEG recordings and analysis as well as the cognitive performance are provided below. Heart rate was recorded to determine exercise-induced changes. 2.3. EEG recordings This research used a 32-channel portable EEG system (actiCAP, Brain Products, Munich, Germany). A flexible EEG cap, equipped with active Ag/AgCl electrodes, adapted to individual head size and a chinstrap prevented shifting during exercise. Approximate 5 cm distances between electrodes averted possible salt bridge-related cross talk. According to the international 10:20 system for standardized EEG application, electrocortical activity was recorded (sampling interval 2000 mS; sampling rate 500 Hz) on positions Fp1, Fp2, F7, F3, Fz, F4, F8, FC5, FC1, FC2, FC6, T7, C3, Cz, C4, T8, CP5, CP1, CP2, CP6, TP9, P7, P3, Pz, P4, P8, TP10, PO9, O1, Oz, O2, PO10. Additional reference (FCz) and ground (AFz) electrodes were mounted. Electrode gel (SuperViscTM, Easycap GmbH, Herrsching, Germany) was filled in each electrode, serving conductivity to optimize signal transduction. Finally, analog electrocortical signals were amplified and converted into digital signals (Brain Vision Recorder 1.1 Software, Brain Products, Munich, Germany). 2.4. EEG analyses Electrodes exceeding impedance of 10 kV were excluded from further analysis. Following low and high cut off filtering of electrocortical signals, a frequency range between 0.5 and 50.0 Hz (notch filter) remained for analyses (time constant 0.3183099 s; 48 dB/octave). Next, data were separately segmented to analyze low-resolution electromagnetic tomography (LORETA) and the N2 component of the event-related potential. 2.4.1. Low-resolution brain electromagnetic tomography (LORETA) Following segmentation into equally sized 4 s segments and an automatic artifact rejection (gradient < 35 mV; max/min amplitude 100 to 100 mV), segmented data were baseline corrected (0–4000 ms) and analyzed by spectral analysis (FFT, resolution 0.244 Hz; Hanning window, 10%). Then anatomical regions of interest, known to compose essential areas of the frontal lobe, were defined: superior frontal gyrus (SuFG), inferior frontal gyrus (InFG), medial frontal gyrus (MeFG), middle frontal gyrus (MiFG) and precentral gyrus (PrG). Subsequently, minimums of 60 s were transformed and electrode sitespecific cortical current densities (mV2/mm4) were exported (Brain Vision Analyser Software 2.0, Brain Products, Munich, Germany) for statistical analyses of LORETA’s cortical current densities. 2.4.2. Event-related potential – N2 component Following segmentation based on stimulus onset (100 to 500 ms), segmented data were baseline corrected (100 to 0 ms) and averaged (minimums of n > 50) over occipital electrode sites (PO9, O1, Oz, O2, PO10). Pooled electrodes were topographically interpolated, if previously excluded due to exceeding 10 kV. Subsequently, negative peaks (ms/mV) were exported (Brain Vision Analyser Software 2.0, Brain Products, Munich, Germany) for statistical analyses of N2. 2.5. Cognitive performance Based on standardized, computerized methods of assessment, cognitive performance in this research was performed as reaction time, assessing basic cognitive functions (i.e. decision-making processes, motor responses). As previously
Fig. 1. Electrocortical (EEG), heart rate (HR) and cognitive performance (COG) recordings in time (t), referring to the exercise (exc) and relaxation (rel) condition.
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suggested, the design to assess reaction time has been modified, optimizing adaptation processes for adolescents with intellectual and developmental disabilities (Vogt et al., 2012). A standard 12.1-in. touchscreen (gray background) was placed on a desk, easy to reach in the participants’ visual field. Participants were asked to rest their right index finger on a black square (starting position, 3 cm 3 cm), centered at the bottom of the touchscreen. A yellow light (d = 8 cm) randomly flashing between 2 and 5 s in the center of the touchscreen served as a stimulus source. Instructions to the participants were, ‘‘please tap the yellow light upon flashing, using your right index finger only – then back to the black square’’. Tapping and re-resting were obligatory before timing and flashing the next stimulus. Reaction times were recorded and distinguished between flashing and participants’ finger lifting off the black square (defined as lifting reaction time, RTlift) as well as finger lifting to pressing the yellow light (defined as pressing reaction time, RTpress). Real time markers were set in the EEG recordings respectively. Times were exported for statistical analyses of reactions. 2.6. Statistical procedures Statistical analyses were performed using STATISTICA program 7.1 (StatSoft, Tulsa, USA). In order to display condition-induced changes, generalized linear models of repeated measures ANOVA were computed. For LORETA’s percentages of cortical current density, three-way repeated measures with trial (exc, rel), time (t0, t2, t3, t5) and area (SuFG, InFG, MeFG, MiFG, PrG) were computed. For N2, two-way repeated measures with trial (exc, rel) and time (t1, t4) were computed. For cognitive performances, three-way repeated measures with trial (exc, rel), time (pre, post) and reaction (lift, press) were computed. And for heart rates, two-way repeated measures with trial (exc, rel) and time (t0, t2, t3, t5) were computed. If appropriate, Fisher’s least significance difference test (LSD) served as post hoc analysis. Three participants resisted wearing the EEG cap. For this reason only 11 out of previously 14 scheduled participants were considered for statistical procedures and reporting respectively. The level of significance was set at p < 0.05. Data in the text are presented as means (8) standard deviation (SD). 3. Results 3.1. Heart rate and power Repeated measures analysis for heart rate revealed significant changes (F(3,60) = 178.74 with p = 0.0000, power(1 Post hoc analysis showed increased heart rate after exercise (p < 0.001), whereas heart rate was decreased after relaxation (p < 0.001) compared to baseline. Mean heart rate was 81.45 9.03 bpm prior to exercise and 143.09 14.40 bpm after exercise, whereas mean heart rate was 79.73 5.83 bpm prior to relaxation and 70.55 7.69 bpm after relaxation. Participants cycled mean powers of 61.82 7.83 watts at 70.09 6.52 rpm for 10 min.
b err prob) > 0.99).
3.2. LORETA Repeated measures analysis for LORETA’s percentages of cortical current density revealed significant changes (F(12,150) = 2.1770 with p = 0.01545, power(1 b err prob) > 0.99). Post hoc analysis showed decreased cortical current density in the MeFG right after exercise (p < 0.001) compared to baseline (see Fig. 2). Compared to baseline, neither exercise nor relaxation obtained further significances in any essential area of the frontal lobe. 3.3. Cognitive performance Repeated measures analysis for distinguished reaction times revealed significant changes (F(1,10) = 9.9507 with p = 0.01025, power(1 b err prob) > 0.89). Post hoc analysis showed decreased reaction times in RTpress (p < 0.01) after exercise compared to initial assessments (see Fig. 3). Compared to initial assessments, neither exercise nor relaxation obtained further significances in RTlift. 3.4. N2 component Repeated measures analysis for peaked N2 latencies revealed significant changes (F(1,20) = 6.3371 with p = 0.02046, power(1 b err prob) > 0.45). Post hoc analysis showed decreased latencies (p < 0.01) after exercise compared to initial recordings (see Figs. 4 and 5). Repeated measures analysis obtained no significances for peaked N2 amplitudes (F(1,20) = 0.47357 with p = 0.49925, power(1 b err prob) < 0.09) (see Table 1). 4. Discussion This research aimed to explore exercise-induced neurocognitive responses in participants with IDD, comparing moderate cycling exercise with a common relaxation method. After exercise, frontal electrocortical activity decreased, most
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Fig. 2. Changes over time of LORETA’s percentages of cortical current density in the exercise (exc) and relaxation (rel) condition. Recordings are at t0 prior to exercise, t2 following cognitive performance prior to exercise, t3 after exercise and t5 following cognitive performance after exercise. Regions of interest are superior frontal gyrus (SuFG), inferior frontal gyrus (InFG), medial frontal gyrus (MeFG), middle frontal gyrus (MiFG) and precentral gyrus (PrG). Asterisks mark the level of significance (***p < 0.001) referring to baseline (t0) within exc.
pronounced in the MeFG. To that effect, cognitive performance revealed a decrease in pressing reaction time after exercise, which was mirrored in decreased N2 latency, but not amplitude. After relaxation, similar effects failed to appear in neither electrocortical activity nor in reaction times and N2 latency or amplitude. Electrocortical activity decreased in the MeFG following the moderate cycling exercise, but not following relaxation. Dietrich’s transient hypofrontality theory (Dietrich, 2006) indicates a rearranging of limited cortical resources in relation to exercise. The theory suggests a shift of cortical activity away from frontal brain areas that are rather nonrelevant for motor control and movement processing during and after exercise. With previous neurocognitive research associating the MeFG to play a major role in executive functions, including decision-making processes such as go/no-go tasks (Santesso & Segalowitz, 2008; Talati & Hirsch, 2005), it seems reasonable to have identified decreased electrocortical activity in the MeFG. To that effect, these results add to previous neurophysiological exercise research studies supporting the transient hypofrontality theory (Schneider et al., 2013), which, in addition, has previously been explored in IDD (Vogt et al., 2012). While this research addressed essential areas of the frontal lobe according to the literature (e.g. according to Talati & Hirsch, 2005), the percentage distribution is noticeable with the MeFG, covering nearly 50% of the total frontal electrocortical activity recorded. Other essential areas of the frontal lobe are far less activated, which might underscore the importance of the MeFG to the frontal lobe in general, however less important in motor control and movement processing (loss after exercise nearly 10%). Although failing significance, an increase by trend compared to baseline could be observed in SuFG, InFG and PrG. Thus, the shared involvement of the SuFG, InFG and PrG in motor control and movement processing might be another explanation (Chouinard & Paus, 2006; Ko¨no¨nen et al., 2005; Liakakis et al., 2011). The cognitive performance assessment revealed decreased (accelerated) pressing reaction time after exercise but not after relaxation. Recent research suggests moderate exercise benefits a general state of vigilance (Huertas, Zahonero, ˜ ez, 2011). And although perceptual processes of motor coordination are compromised in IDD (Carmeli, Sanabria, & Lupia´n Bar-Yossef, Ariav, Levy, & Liebermann, 2008; Frey & Chow, 2006; Simons et al., 2008; Vuijk, Hartmann, Scherder, & Visscher, 2010), it seems reasonable, therefore, to have pressing reaction time accelerated after exercise. With respect to the transient hypofrontality theory, this is additionally in line with the exercise-induced LORETA results. A general state of vigilance might also explain why pressing reaction time seems to decelerate by trend after relaxation (failed significance). To that effect,
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Fig. 3. Pre (t1) to post (t4) changes of cognitive performance for lifting (RTlift) and pressing (RTpress) reaction times in the exercise (exc) and relaxation (rel) condition. Asterisks mark the level of significance (**p < 0.01) within exc.
Fig. 4. Changes of peaked N2 latencies (in ms) recorded pre (t1) and post (t4) in the exercise (exc) and relaxation (rel) condition. Asterisks mark the level of significance (**p < 0.01) within exc.
although undocumented, participants appeared sleepier after relaxation than after exercise. While previous research suggests a somewhat temporal similarity of motor (press) and perceptual (lift) processes (Hartman et al., 2010; Ridler et al., 2006), lifting reaction time interestingly failed significances in both exercise and relaxation. Results of the event-related potential analyses mirrored the results for the cognitive performance’s reaction time. N2 latency decreased (accelerated) after exercise, but not after relaxation. Previous research associates the N2 with the monitoring of strategic cognitive control (Folstein & van Petten, 2008). To that effect, the N2 latency has previously been shown to reflect reaction time (Nieuwenhuis, Yeung, van den Wildenberg, & Ridderinkhof, 2003), covering the immediate control of action (e.g. ‘how fast am I responding’ – ‘how fast should I be responding’; Folstein & van Petten, 2008). Thus, it
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Fig. 5. Displayed are averaged pre (t1) and post (t4) N2 components, recorded between 100 and 500 ms of stimulus onset (at 0 ms) in the exercise (exc) and relaxation (rel) intervention.
Table 1 N2 amplitude.
exc
N2 N2rel
t1
t4
8 11.30 SD 7.39 mV 8 9.46 SD 5.61 mV
8 10.92 SD 7.69 mV 8 10.91 SD 4.62 mV
Means (8) standard deviations (SD) of peaked N2 amplitudes (in mV) recorded pre (t1) and post (t4) in the exercise (exc) and relaxation (rel) condition.
seems reasonable that the participants’ regulation and adaptation processes to stimulus onset were faster after exercise. It is ¨ hman, Hamm, & Hugdahl, 2000), which might explain why further discussed that the N2 pictures motor responses (O pressing reaction time was accelerated, but not lifting reaction time. Also, the surprising absence of changes in lifting reaction time might be due to larger time windows, causing blur. Possible lower levels of stimulus probability (Bruin & Wijers, 2002; Nieuwenhuis et al., 2003) might be an explanation for N2 amplitudes failing significance in both exercise and relaxation. 4.1. Limitations We are well aware that the modified method to assess neurocognitive processes is rather unconventional, however adaptive to the heterogeneous ability levels in IDD. To that effect, the low number of participants – also due to careful recruitment – limits the present research. We are also aware that the present research lacks evaluation of muscle tone, to exclude possible interference with the interpreted findings.
5. Conclusions Taken together, the results of this research suggest that moderate cycling exercise rearranges electrocortical activity patterns in IDD. The cortical resources provided add to an accelerated pressing reaction time that is mirrored in decreased N2 latency. With relaxation seeming to fail these effects, exercise is suggested to improve reaction times and decision-making processes in IDD. Acknowledgements The German Sport University Cologne, who awarded the research grant HIFF920079 to the authors of this publication, funded this research. Sincere thanks go to the executive boards and administrations of both cooperating schools for special needs education, the ‘Mosaikschule’ and the ‘Paul-Kraemer-Schule’, realizing the relevance of this approach and fully supporting this research. Further thanks to the parents for agreeing and the participants for spending some of their valuable school time for this research.
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Contents lists available at SciVerse ScienceDirect
Research in Developmental Disabilities
Moderate cycling exercise enhances neurocognitive processing in adolescents with intellectual and developmental disabilities Tobias Vogt a,*, Stefan Schneider a, Volker Anneken b, Heiko K. Stru¨der a a
Department of Exercise Neuroscience, Institute of Movement and Neurosciences, German Sport University, Am Sportpark Mu¨ngersdorf 6, 50933 Cologne, Germany Research Institute for Inclusion Through Physical Activity and Sport, Ro¨merstraße 100, 50226 Frechen, Germany
b
A R T I C L E I N F O
A B S T R A C T
Article history: Received 8 April 2013 Received in revised form 16 May 2013 Accepted 21 May 2013 Available online 14 June 2013
Research has shown that physical exercise enhances cognitive performance in individuals with intact cognition as well as in individuals diagnosed with intellectual and developmental disabilities. Although well identified in the field of health (for example, the transient hypofrontality theory), the underlying neurocognitive processes in intellectual and developmental disabilities remain widely unclear and thus characterize the primary aim of this research. Eleven adolescents with intellectual and developmental disabilities performed moderate cycling exercise and common relaxation. Cross-over designed, both 10-min meetings were randomly allocated at the same time of day with 24h time lags in between. Conditions were embedded in ability-modified cognitive performance (decision-making processes). Participants’ reaction times and their equivalent neurophysiological parameters were recorded using standard EEG and analyzed (spatial activity, N2). Exercise revealed a decrease in frontal electrocortical activity, most pronounced in the medial frontal gyrus (10%). To that effect, reaction time (p < 0.01) was decreased and mirrored in decreased N2 latency (p < 0.01) after exercise. In contrast, relaxation revealed no significant changes. Results of this research suggest exercise temporarily enhances neuronal activity in relation to cognitive performance for adolescents with intellectual and developmental disabilities; further research is needed to explore possible future effects on enhancing neurocognitive development. ß 2013 Elsevier Ltd. All rights reserved.
Keywords: EEG Intellectual and developmental disability Exercise Cognitive performance Reaction time N2
1. Introduction Today, exercise is recommended to maintain physical and mental health in humans (Brisswalter, Collardeau, & Rene´, 2002; Hagen et al., 2012). Numerous neurophysiological and behavioral research studies address the duration, intensity, and – more recently – individual exercise preferences in relation to well-being and cognitive performance (Schneider, Bru¨mmer, Abel, Askew, & Strueder, 2009). Although this research covers an extensive span of life and class of population, little is known about exercise-induced neurocognitive processes in intellectual and developmental disabilities (IDD). According to the American Association on Intellectual and Developmental Disabilities (AAIDD), IDD is characterized by limited intellectual functioning; e.g. learning, reasoning, and problem solving, as well as adaptive behavior; e.g. conceptual, social and practical skills that originate in adolescence. Adolescence is a time of considerable neurocognitive and behavioral
* Corresponding author at: Department of Neuroscience, Institute of Movement and Neurosciences, German Sport University Cologne, Am Sportpark Mu¨ngersdorf 6, 50933 Cologne, Germany. Tel.: +49 221 4982 4260; fax: +49 221 4973 454. E-mail address: [email protected] (T. Vogt). 0891-4222/$ – see front matter ß 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.ridd.2013.05.037
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development (Blakemore & Choudhury, 2006; Blakemore, 2012; Hartman, Houwen, Scherder, & Visscher, 2010). Hence, research focuses on beneficial processes to improve neurocognitive behavior in IDD during adolescence (Leggett, Jacobs, Nation, Scerif, & Bishop, 2010; Silver et al., 2008). Recently, a first attempt at using exercise to specifically benefit neural behavior in IDD has been suggested (Vogt, Schneider, Abeln, Anneken, & Stru¨der, 2012). To that effect, increased social acceptance and participation further underline the needs to broaden the understanding of exercise-induced changes on cognitive performance in IDD. While relaxation setups (‘snoezelen’; Mertens, 2008) are commonly used in rehabilitation facilities to improve concentration in IDD (Hogg, Cavet, Lambe, & Smeddle, 2001), additional research suggests moderate exercise to contribute to general well-being and cognitive performance in IDD (Cervantes & Porretta, 2010; Hutzler & Korsensky, 2010). However, underlying neurocognitive processes are mainly disregarded (Temple, Frey, & Stanish, 2006) or are not considered in IDD-modified assessments of cognitive performance (Vogt et al., 2012). While commonly used in the field of clinical and cognitive neuroscience to explore IDD, electroencephalography (EEG) is still a relatively new method to record brain cortical activity in exercise physiology. However, recent technological developments enable the use of EEG in exercise setups, combining enhanced temporal and spatial resolution with a reduction of moving artifacts. To that effect, traditional EEG recordings enable low-resolution brain electromagnetic tomography (LORETA). The LORETA method (University Hospital of Psychiatry, Zurich, Switzerland) has previously been described and validated in clinical (Fuchs, Kastner, Wagner, Hawes, & Ebersole, 2002; Jurcak, Tsuzuki, & Dan, 2007; PascualMarqui, Esslen, Kochi, & Lehmann, 2002; Pascual-Marqui, 2002) and exercise research (Schneider, Bru¨mmer, et al., 2009; Schneider, Vogt, Frysch, Guardiera, & Struder, 2009; Vogt et al., 2012). This research indicates that cognitive processes relate to specific electrocortical activity patterns, particularly in frontal brain areas that are fundamental for cognitive performance. During exercise, the transient hypofrontality theory (Dietrich, 2006) suggests a shift of cortical resources away from brain areas that are rather negligible for movement processing but for cognitive performance. Neurocognitive research indicates that essential areas of the frontal lobe associate to sensory information processing (superior frontal gyrus, SuFG), motor control and movement processing (precentral gyrus, PrG and inferior frontal gyrus, InFG) and executive functions (medial frontal gyrus, MeFG), including decision-making processes such as go/no-go tasks (Chouinard & Paus, 2006; Ko¨no¨nen et al., 2005; Liakakis, Nickel, & Seitz, 2011; Talati & Hirsch, 2005). In addition, EEG recordings enable analyses and interpretation of event-related potential waveforms, sensitive to stimulus probability in amplitude and latency. Generally associated with cognitive control, the N2 component, as an event-related potential component, covers a concept of strategic monitoring and control of movement responses (Folstein & van Petten, 2008). Developments of cognitive control are reflected by decreases in the N2 amplitude and latency, indicating better cognitive performance (Lamm, Zelazo, & Lewis, 2006). Following stimulus onset in the averaged EEG waveform, the N2 peaks negatively between 200 and 350 ms. Its visual modality is prominent in occipital electrode sites. In order to modulate and assess neural responses of cognitive performance, previous research suggests the use of expected and unexpected sensory stimuli (Mangun, 1995). The consistent temporal modulation of N2 is suggested to indicate both an attentional preparation of decision-making, as well as ˜ ez, Madrid, & Tudela, 2006). Recent clinical research suggests that N2 latency in early motor processing (Correa, Lupia´n particular shows a correlation between cognitive performance and IDD (Papaliagkas, Kimiskidis, Tsolaki, & Anogianakis, 2011). 1.1. Hypotheses Accordingly, the primary aim of this research is to explore exercise-induced neurocognitive changes compared to common relaxation in adolescents with IDD. It is hypothesized that: (1) frontal electrocortical activity decreased after 10 min of moderate cycling exercise compared to 10 min of relaxation; (2) reaction time is improved after exercise compared to relaxation and (3) coinciding with neural responses of cognitive control – particularly in the N2 latency. 2. Materials and methods 2.1. Participants Approved by the University’s Human Research Ethics Committee, eleven right-handed adolescents (6 males, 5 females) volunteered to participate in this research (16 1.34 years, 167.27 10.01 cm, 69.36 7.80 kg). According to the AAIDD definition (Schalock et al., 2010), previously published characterizations (Vogt et al., 2012; World Health Organization, 1997) as well as medical records and school reports, participants were classified as adolescents with intellectual and developmental disabilities. Furthermore, participants were excluded if they were unable to differentiate between colors and shapes. Prior to involvement, participants attended an informatory meeting, including medical screening and familiarization with the experimental procedures. On agreement, legal guardians provided written informed consent. All participants were familiar with exercising–cycling, in particular. All procedures were in compliance with the Declaration of Helsinki for human participants. 2.2. Design This research was conducted in cooperation with schools for special needs education, focusing on intellectual and learning disabilities. Each participant attended two experimental meetings, differing in exercise and relaxation conditions.
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Exercise meant moderate cycling at self-paced intensity (please refer to Section 3.1 for heart rate results and power outputs) on a bicycle ergometer (Ergoline ER 900, Ergoline, Bitz, Germany), whereas relaxation meant resting while seated and listening to music. Music and the procedure were familiar from the participants’ common relaxations previously experienced in class and described as ‘snoezelen’ (Mertens, 2008; Hogg et al., 2001). Cross-over designed, both conditions lasted for 10 min (Ekkekakis, Hall, VanLanduyt, & Petruzzello, 2000; Schneider, Vogt, et al., 2009). Orders of experimental meetings were randomly allocated at the same time of day with at least 24-h time lags in between. Prior to the experiment, baseline electrocortical activity (EEG) was recorded for 2 min while seated with eyes closed (t0EEGexc/rel). To assess cognitive performance (COG), participants performed a reaction time task before (t1COGexc/rel) and after (t4COGexc/rel) each condition. Recordings were repeated during (t1EEGexc/rel) and following the initial cognitive performance (t2EEGexc/rel), right after the condition (t3EEGexc/rel) and again during (t4EEGexc/rel,) and following the final cognitive performance (t5EEGexc/rel) (see Fig. 1). Further details on the EEG recordings and analysis as well as the cognitive performance are provided below. Heart rate was recorded to determine exercise-induced changes. 2.3. EEG recordings This research used a 32-channel portable EEG system (actiCAP, Brain Products, Munich, Germany). A flexible EEG cap, equipped with active Ag/AgCl electrodes, adapted to individual head size and a chinstrap prevented shifting during exercise. Approximate 5 cm distances between electrodes averted possible salt bridge-related cross talk. According to the international 10:20 system for standardized EEG application, electrocortical activity was recorded (sampling interval 2000 mS; sampling rate 500 Hz) on positions Fp1, Fp2, F7, F3, Fz, F4, F8, FC5, FC1, FC2, FC6, T7, C3, Cz, C4, T8, CP5, CP1, CP2, CP6, TP9, P7, P3, Pz, P4, P8, TP10, PO9, O1, Oz, O2, PO10. Additional reference (FCz) and ground (AFz) electrodes were mounted. Electrode gel (SuperViscTM, Easycap GmbH, Herrsching, Germany) was filled in each electrode, serving conductivity to optimize signal transduction. Finally, analog electrocortical signals were amplified and converted into digital signals (Brain Vision Recorder 1.1 Software, Brain Products, Munich, Germany). 2.4. EEG analyses Electrodes exceeding impedance of 10 kV were excluded from further analysis. Following low and high cut off filtering of electrocortical signals, a frequency range between 0.5 and 50.0 Hz (notch filter) remained for analyses (time constant 0.3183099 s; 48 dB/octave). Next, data were separately segmented to analyze low-resolution electromagnetic tomography (LORETA) and the N2 component of the event-related potential. 2.4.1. Low-resolution brain electromagnetic tomography (LORETA) Following segmentation into equally sized 4 s segments and an automatic artifact rejection (gradient < 35 mV; max/min amplitude 100 to 100 mV), segmented data were baseline corrected (0–4000 ms) and analyzed by spectral analysis (FFT, resolution 0.244 Hz; Hanning window, 10%). Then anatomical regions of interest, known to compose essential areas of the frontal lobe, were defined: superior frontal gyrus (SuFG), inferior frontal gyrus (InFG), medial frontal gyrus (MeFG), middle frontal gyrus (MiFG) and precentral gyrus (PrG). Subsequently, minimums of 60 s were transformed and electrode sitespecific cortical current densities (mV2/mm4) were exported (Brain Vision Analyser Software 2.0, Brain Products, Munich, Germany) for statistical analyses of LORETA’s cortical current densities. 2.4.2. Event-related potential – N2 component Following segmentation based on stimulus onset (100 to 500 ms), segmented data were baseline corrected (100 to 0 ms) and averaged (minimums of n > 50) over occipital electrode sites (PO9, O1, Oz, O2, PO10). Pooled electrodes were topographically interpolated, if previously excluded due to exceeding 10 kV. Subsequently, negative peaks (ms/mV) were exported (Brain Vision Analyser Software 2.0, Brain Products, Munich, Germany) for statistical analyses of N2. 2.5. Cognitive performance Based on standardized, computerized methods of assessment, cognitive performance in this research was performed as reaction time, assessing basic cognitive functions (i.e. decision-making processes, motor responses). As previously
Fig. 1. Electrocortical (EEG), heart rate (HR) and cognitive performance (COG) recordings in time (t), referring to the exercise (exc) and relaxation (rel) condition.
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suggested, the design to assess reaction time has been modified, optimizing adaptation processes for adolescents with intellectual and developmental disabilities (Vogt et al., 2012). A standard 12.1-in. touchscreen (gray background) was placed on a desk, easy to reach in the participants’ visual field. Participants were asked to rest their right index finger on a black square (starting position, 3 cm 3 cm), centered at the bottom of the touchscreen. A yellow light (d = 8 cm) randomly flashing between 2 and 5 s in the center of the touchscreen served as a stimulus source. Instructions to the participants were, ‘‘please tap the yellow light upon flashing, using your right index finger only – then back to the black square’’. Tapping and re-resting were obligatory before timing and flashing the next stimulus. Reaction times were recorded and distinguished between flashing and participants’ finger lifting off the black square (defined as lifting reaction time, RTlift) as well as finger lifting to pressing the yellow light (defined as pressing reaction time, RTpress). Real time markers were set in the EEG recordings respectively. Times were exported for statistical analyses of reactions. 2.6. Statistical procedures Statistical analyses were performed using STATISTICA program 7.1 (StatSoft, Tulsa, USA). In order to display condition-induced changes, generalized linear models of repeated measures ANOVA were computed. For LORETA’s percentages of cortical current density, three-way repeated measures with trial (exc, rel), time (t0, t2, t3, t5) and area (SuFG, InFG, MeFG, MiFG, PrG) were computed. For N2, two-way repeated measures with trial (exc, rel) and time (t1, t4) were computed. For cognitive performances, three-way repeated measures with trial (exc, rel), time (pre, post) and reaction (lift, press) were computed. And for heart rates, two-way repeated measures with trial (exc, rel) and time (t0, t2, t3, t5) were computed. If appropriate, Fisher’s least significance difference test (LSD) served as post hoc analysis. Three participants resisted wearing the EEG cap. For this reason only 11 out of previously 14 scheduled participants were considered for statistical procedures and reporting respectively. The level of significance was set at p < 0.05. Data in the text are presented as means (8) standard deviation (SD). 3. Results 3.1. Heart rate and power Repeated measures analysis for heart rate revealed significant changes (F(3,60) = 178.74 with p = 0.0000, power(1 Post hoc analysis showed increased heart rate after exercise (p < 0.001), whereas heart rate was decreased after relaxation (p < 0.001) compared to baseline. Mean heart rate was 81.45 9.03 bpm prior to exercise and 143.09 14.40 bpm after exercise, whereas mean heart rate was 79.73 5.83 bpm prior to relaxation and 70.55 7.69 bpm after relaxation. Participants cycled mean powers of 61.82 7.83 watts at 70.09 6.52 rpm for 10 min.
b err prob) > 0.99).
3.2. LORETA Repeated measures analysis for LORETA’s percentages of cortical current density revealed significant changes (F(12,150) = 2.1770 with p = 0.01545, power(1 b err prob) > 0.99). Post hoc analysis showed decreased cortical current density in the MeFG right after exercise (p < 0.001) compared to baseline (see Fig. 2). Compared to baseline, neither exercise nor relaxation obtained further significances in any essential area of the frontal lobe. 3.3. Cognitive performance Repeated measures analysis for distinguished reaction times revealed significant changes (F(1,10) = 9.9507 with p = 0.01025, power(1 b err prob) > 0.89). Post hoc analysis showed decreased reaction times in RTpress (p < 0.01) after exercise compared to initial assessments (see Fig. 3). Compared to initial assessments, neither exercise nor relaxation obtained further significances in RTlift. 3.4. N2 component Repeated measures analysis for peaked N2 latencies revealed significant changes (F(1,20) = 6.3371 with p = 0.02046, power(1 b err prob) > 0.45). Post hoc analysis showed decreased latencies (p < 0.01) after exercise compared to initial recordings (see Figs. 4 and 5). Repeated measures analysis obtained no significances for peaked N2 amplitudes (F(1,20) = 0.47357 with p = 0.49925, power(1 b err prob) < 0.09) (see Table 1). 4. Discussion This research aimed to explore exercise-induced neurocognitive responses in participants with IDD, comparing moderate cycling exercise with a common relaxation method. After exercise, frontal electrocortical activity decreased, most
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Fig. 2. Changes over time of LORETA’s percentages of cortical current density in the exercise (exc) and relaxation (rel) condition. Recordings are at t0 prior to exercise, t2 following cognitive performance prior to exercise, t3 after exercise and t5 following cognitive performance after exercise. Regions of interest are superior frontal gyrus (SuFG), inferior frontal gyrus (InFG), medial frontal gyrus (MeFG), middle frontal gyrus (MiFG) and precentral gyrus (PrG). Asterisks mark the level of significance (***p < 0.001) referring to baseline (t0) within exc.
pronounced in the MeFG. To that effect, cognitive performance revealed a decrease in pressing reaction time after exercise, which was mirrored in decreased N2 latency, but not amplitude. After relaxation, similar effects failed to appear in neither electrocortical activity nor in reaction times and N2 latency or amplitude. Electrocortical activity decreased in the MeFG following the moderate cycling exercise, but not following relaxation. Dietrich’s transient hypofrontality theory (Dietrich, 2006) indicates a rearranging of limited cortical resources in relation to exercise. The theory suggests a shift of cortical activity away from frontal brain areas that are rather nonrelevant for motor control and movement processing during and after exercise. With previous neurocognitive research associating the MeFG to play a major role in executive functions, including decision-making processes such as go/no-go tasks (Santesso & Segalowitz, 2008; Talati & Hirsch, 2005), it seems reasonable to have identified decreased electrocortical activity in the MeFG. To that effect, these results add to previous neurophysiological exercise research studies supporting the transient hypofrontality theory (Schneider et al., 2013), which, in addition, has previously been explored in IDD (Vogt et al., 2012). While this research addressed essential areas of the frontal lobe according to the literature (e.g. according to Talati & Hirsch, 2005), the percentage distribution is noticeable with the MeFG, covering nearly 50% of the total frontal electrocortical activity recorded. Other essential areas of the frontal lobe are far less activated, which might underscore the importance of the MeFG to the frontal lobe in general, however less important in motor control and movement processing (loss after exercise nearly 10%). Although failing significance, an increase by trend compared to baseline could be observed in SuFG, InFG and PrG. Thus, the shared involvement of the SuFG, InFG and PrG in motor control and movement processing might be another explanation (Chouinard & Paus, 2006; Ko¨no¨nen et al., 2005; Liakakis et al., 2011). The cognitive performance assessment revealed decreased (accelerated) pressing reaction time after exercise but not after relaxation. Recent research suggests moderate exercise benefits a general state of vigilance (Huertas, Zahonero, ˜ ez, 2011). And although perceptual processes of motor coordination are compromised in IDD (Carmeli, Sanabria, & Lupia´n Bar-Yossef, Ariav, Levy, & Liebermann, 2008; Frey & Chow, 2006; Simons et al., 2008; Vuijk, Hartmann, Scherder, & Visscher, 2010), it seems reasonable, therefore, to have pressing reaction time accelerated after exercise. With respect to the transient hypofrontality theory, this is additionally in line with the exercise-induced LORETA results. A general state of vigilance might also explain why pressing reaction time seems to decelerate by trend after relaxation (failed significance). To that effect,
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Fig. 3. Pre (t1) to post (t4) changes of cognitive performance for lifting (RTlift) and pressing (RTpress) reaction times in the exercise (exc) and relaxation (rel) condition. Asterisks mark the level of significance (**p < 0.01) within exc.
Fig. 4. Changes of peaked N2 latencies (in ms) recorded pre (t1) and post (t4) in the exercise (exc) and relaxation (rel) condition. Asterisks mark the level of significance (**p < 0.01) within exc.
although undocumented, participants appeared sleepier after relaxation than after exercise. While previous research suggests a somewhat temporal similarity of motor (press) and perceptual (lift) processes (Hartman et al., 2010; Ridler et al., 2006), lifting reaction time interestingly failed significances in both exercise and relaxation. Results of the event-related potential analyses mirrored the results for the cognitive performance’s reaction time. N2 latency decreased (accelerated) after exercise, but not after relaxation. Previous research associates the N2 with the monitoring of strategic cognitive control (Folstein & van Petten, 2008). To that effect, the N2 latency has previously been shown to reflect reaction time (Nieuwenhuis, Yeung, van den Wildenberg, & Ridderinkhof, 2003), covering the immediate control of action (e.g. ‘how fast am I responding’ – ‘how fast should I be responding’; Folstein & van Petten, 2008). Thus, it
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Fig. 5. Displayed are averaged pre (t1) and post (t4) N2 components, recorded between 100 and 500 ms of stimulus onset (at 0 ms) in the exercise (exc) and relaxation (rel) intervention.
Table 1 N2 amplitude.
exc
N2 N2rel
t1
t4
8 11.30 SD 7.39 mV 8 9.46 SD 5.61 mV
8 10.92 SD 7.69 mV 8 10.91 SD 4.62 mV
Means (8) standard deviations (SD) of peaked N2 amplitudes (in mV) recorded pre (t1) and post (t4) in the exercise (exc) and relaxation (rel) condition.
seems reasonable that the participants’ regulation and adaptation processes to stimulus onset were faster after exercise. It is ¨ hman, Hamm, & Hugdahl, 2000), which might explain why further discussed that the N2 pictures motor responses (O pressing reaction time was accelerated, but not lifting reaction time. Also, the surprising absence of changes in lifting reaction time might be due to larger time windows, causing blur. Possible lower levels of stimulus probability (Bruin & Wijers, 2002; Nieuwenhuis et al., 2003) might be an explanation for N2 amplitudes failing significance in both exercise and relaxation. 4.1. Limitations We are well aware that the modified method to assess neurocognitive processes is rather unconventional, however adaptive to the heterogeneous ability levels in IDD. To that effect, the low number of participants – also due to careful recruitment – limits the present research. We are also aware that the present research lacks evaluation of muscle tone, to exclude possible interference with the interpreted findings.
5. Conclusions Taken together, the results of this research suggest that moderate cycling exercise rearranges electrocortical activity patterns in IDD. The cortical resources provided add to an accelerated pressing reaction time that is mirrored in decreased N2 latency. With relaxation seeming to fail these effects, exercise is suggested to improve reaction times and decision-making processes in IDD. Acknowledgements The German Sport University Cologne, who awarded the research grant HIFF920079 to the authors of this publication, funded this research. Sincere thanks go to the executive boards and administrations of both cooperating schools for special needs education, the ‘Mosaikschule’ and the ‘Paul-Kraemer-Schule’, realizing the relevance of this approach and fully supporting this research. Further thanks to the parents for agreeing and the participants for spending some of their valuable school time for this research.
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