- Email: [email protected]
EP 128. Motor learning: TDCS effects vary with baseline performance
e294
Abstracts / Clinical Neurophysiology 127 (2016) e210–e303
movement direction is inverted relative to the hand movement (e.g., a joystick movement to the left will move the ball to the right). Further tests assessed simple (i.e. non-inverse) two-hand visuomotor coordination, one-hand visuomotor coordination (Trail Making Test [TMT-A and -B]), one-hand motor control (Motor Performance Series), inhibitory control (Go/Nogo task), divided attention, and cognitive flexibility (difference between TMT-B and -A). To identify potential predictors of inverse bimanual coordination (IBC), we compared performance in all tests between those older participants who were able (n = 13) and those who were unable (n = 7) to perform the IBC task. Test scores showing a significant group difference were included in a binary logistic regression analysis to test how well they predict group affiliation (IBC success vs. failure). Linear regression analysis examined how well these scores explain different aspects of IBC performance across all (young and old) successful IBC performers (n = 31). Results: Significantly decreased performance in the IBC failure subgroup was observed for TMT-A and TMT-B, Go/Nogo task (mean reaction time), and simple bimanual coordination (average speed and error duration). In a logistic regression model, these 5 scores predicted group affiliation with 88.9% accuracy. In a linear regression, all 5 scores significantly contributed to predicting IBC performance, jointly explaining 40% of variance in speed, 50% in error duration, and 95% in percentage error duration. Discussion: Our results show that specific aspects of executive functioning, rather than motor skills per se, explain IBC performance across age. This indicates that the limitations in older adults to perform the task may arise from cognitive aspects of this complex ‘‘motor task” (e.g. intentional movement de-coupling, input–output coordinate transformation, error monitoring). We suggest that these parallel cognitive processing demands lead to mutual interference and eventually, reflecting well-known multitasking deficits in the elderly, may lead to a complete breakdown of complex visuomotor coordination.
Fig. 1.
to 3D objects of balls, office objects, and low-calorie fruits, crucially. Exploratory analyses of the hand movement trajectories are presented and we discuss the implications for and limitations of the use of Virtual Reality in the assessment of biased behavior. An embodied perspective on the development and maintenance of biased cognitive processing may opt further therapeutic applications of (full-) body tracking technologies and may suggest the involvement of motor regions in addition to a fronto-limbic network.
References Schroeder P, Lohmann J, Butz M V, Plewnia C. Behavioral bias for food reflected in hand movements: a preliminary study with healthy subjects. Cyberpsychol Behav Soc Netw 2015. doi:10.1089/cyber.2015.0311. Wiers RW, Eberl C, Rinck M, Becker ES, Lindenmeyer J. Retraining automatic action tendencies changes alcoholic patients’ approach bias for alcohol and improves treatment outcome. Psychol Sci 2011;22:490–7.
doi:10.1016/j.clinph.2016.05.167 doi:10.1016/j.clinph.2016.05.168
EP 126. Virtual Reality in the assessment of a manual bias towards food—P.A. Schroeder a,*, J. Lohmann b, M.V. Butz b, C. Plewnia a (a University Tübingen, Dept. of Psychiatry and Psychotherapy, Tübingen, Germany, b University Tübingen, Dept. of Computer Science, Tübingen, Germany) ⇑
Corresponding author.
Biased attentional and cognitive processes are documented for various psychiatric conditions, mostly linked with illness-specific stimuli. Prominent cognitive bias modification paradigms aim at addressing specific cognitive-behavioral deviations and corroborate therapy outcomes. Interestingly, because bodily and motivational tendencies might contribute to biased behavior, actual movements are starting to be included in bias modification paradigms in the form of approach-avoidance trainings (Wiers et al., 2011). Here, we introduce a novel experimental setup in Virtual Reality to include actual hand ward and grasp movements in manual interactions with critical stimuli (Fig. 1). The aim of this study was to identify motor contributions to the attentional bias towards food, a wellestablished finding. First, an attentional bias towards food was replicated during the course of grasping 3D objects of palatable objects as compared to ball objects. Food objects were collected faster than ball objects and the difference increased with larger body-mass indices of the healthy subjects (Schroeder et al., 2015). This finding was replicated in a larger sample, but the behavioral bias towards food was driven by high-calorie food objects exclusively, as compared
ePoster Presentations – Neuroplasticity EP 128. Motor learning: TDCS effects vary with baseline performance—V. Krause *, A. Keitel, J. Focke, S. Kemmet, T. Kuntz, A. Sturm, B. Pollok (Heinrich-Heine-University, Institute of Clinical Neuroscience and Medical Psychology, Duesseldorf, Germany) ⇑
Corresponding author.
Transcranial direct current stimulation (tDCS) allows the noninvasive modulation of cortical excitability. Anodal tDCS is associated with an increase of cortical excitability, while cathodal tDCS yields its decrease. Beyond altered excitability, tDCS to the primary motor cortex (M1) has been proven to modulate motor performance, but effects considerably vary across participants. To further elucidate the indicative role of baseline performance on the impact of tDCS, we subdivided 72 participants after baseline reaction time recordings into fast and slow performers by median split. Subsequently, participants implicitly learned a motor sequence with the right hand using the serial reaction time task. M1 is assumed to contribute to motor sequence acquisition and early motor memory consolidation, while the premotor cortex (PMC) may be relevant for later phases of consolidation. In half of the participants, tDCS was applied to the left M1 and in the other half to the left PMC. Since tDCS effects also vary with respect to timing of stimulation, tDCS was applied either prior to or during motor sequence learning. Anodal vs. cathodal vs. sham tDCS
Abstracts / Clinical Neurophysiology 127 (2016) e210–e303
was applied in three separate sessions. When tDCS was applied prior to learning, anodal M1 tDCS facilitated subsequent sequence acquisition. Most interestingly, this effect became evident in participants with slow baseline reaction times only. When tDCS was applied during learning, anodal M1 tDCS yielded an unspecific facilitation of reaction times – again in participants with slow baseline performance only. Cathodal and sham tDCS as well as PMC tDCS had no such effect. Fast performers did not benefit from tDCS possibly due to a ceiling effect. Beyond underpinning the relevance of M1 for initial motor sequence acquisition, the present results complement evidence that behavioural tDCS effects may strongly depend on the behavioural status quo at time of stimulation. doi:10.1016/j.clinph.2016.05.169
EP 129. The effect of tDCS over M1 prior to and during implicit motor sequence learning—T. Kuntz *, A.P. Sturm, V. Krause, B. Pollok, A. Keitel (Heinrich-Heine-Universität, Institut für Klinische Neurowissenschaften und Medizinische Psychologie, Düsseldorf, Germany) ⇑
Corresponding author.
Motor learning is an essential skill allowing the acquisition of new movement patterns. Transcranial direct current stimulation (tDCS) has been shown to modulate neuronal excitability along with behavioural performance in a polarity-dependent manner. Besides polarity, the effects of tDCS on motor learning also vary with the timing of stimulation. In order to gain a better understanding regarding the optimal timing of tDCS application to modulate implicit motor sequence learning, motor-cortical tDCS was applied prior to and during training on a serial reaction time task (SRTT). The SRTT employs a fixed sequential pattern of button presses allowing the assessment of implicit motor sequence learning. A random pattern served as control condition. 36 healthy subjects were assigned to one of two experiments: tDCS was applied prior to (experiment 1) or during (experiment 2) SRTT training. Anodal vs. cathodal vs. sham tDCS was applied to the left primary motor cortex (M1) for ten minutes in a counterbalanced order. Reaction times of the right hand were measured at Baseline and after SRTT training (End of Acquisition (EoA)). Anodal tDCS prior to SRTT training yielded a beneficial effect on the acquisition of the motor sequence, i.e. reaction times decreased significantly from Baseline to EoA in the sequential pattern. Moreover, at EoA, reaction times were significantly faster following anodal as compared to cathodal tDCS. Reaction times of the random pattern were not differentially modulated by stimulation polarity indicating a sequence-specific effect. In contrast, tDCS applied during SRTT training did not differentially modulate the acquisition of the motor sequence. These results indicate that the timing of tDCS is a crucial parameter yielding distinct effects on implicit motor sequence learning. Anodal tDCS prior to SRTT training resulted in a facilitation emphasising a beneficial effect of increased left M1 excitability for the subsequent acquisition of a new motor sequence. In contrast, modulation of motor-cortical excitability by tDCS during SRTT training yielded no differential effects. This finding implies that tDCS effects may vary with the activation level during stimulation (rest vs. movement). doi:10.1016/j.clinph.2016.05.170
e295
EP 131. Real-time fMRI neurofeedback training in elderly leads to cognitive improvement and changes in cerebral connectivity— C. Hohenfeld a,b,c,*, N. Nellessen a,b,c, I. Dogan a,b,c, H. Kuhn a,b,c, C. Müller a,b,c, F. Papa a,b,c, S. Ketteler a,b,c, N.J. Shah a,b,c, J. Schulz a,c, M. Reske b,c, K. Reetz a,b,c (a Universitätsklinikum RWTH Aachen, Neurologie, Aachen, Germany, b Forschungszentrum Jülich GmbH, Institut für Neurowissenschaften und Medizin (INM-4, 6), Jülich, Germany, c JARA – Translational Brain Medicine, Aachen/Jülich, Germany) ⇑
Corresponding author.
Introduction: During past years real-time functional MRI (rtfMRI) has been shown to be a feasible tool for neurofeedback (NFB). This is a technique, which aims at subjects learning to voluntarily modulate activation of specific brain regions. It has already been applied successfully clinically and non-clinically. We conducted rtfMRI NFB training of the left parahippocampal gyrus (PHG) in healthy elderly with the hypothesis subjects are indeed able to modulate left PHG activation and that this training leads to increased cognitive performance. Here, we also focus on brain connectivity over the course of the training. Methods: 16 subjects (mean age 63.5 y, 9 male) completed the protocol of five examination days (T1–T5). On T1 the neuropsychological pre-test was done (see table), followed by the encoding of a real-world footpath (one out of three variants). On T2–T4 the rtfMRI NFB training was carried out. Activation of the left PHG was fed back visually by a thermometer bar. The task alternated between upregulation (recalling the path encoded on T1) and baseline (counting backwards). Three rtfMRI NFB runs were done per day. On T5 the neuropsychological post-test was done. For analysis of neuropsychological data ANCOVAs with examination day and variant of the footpath as factors and age, education and gender as covariates were calculated. For fMRI data a general linear model with upregulation as predictor was computed with BrainVoyager QX for each NFB run and the activation was then averaged across all runs. Activation was limited to a threshold of Bonferroni-corrected p < :05 and two voxels of cluster size. To conduct an analysis of connectivity, activation time courses were extracted from clusters active during upregulation and averaged for each day and region. With the statistical software R, a GrangerCausality-Analysis (GCA) for each training day was conducted for each combination of active regions (306 connections) with a lag size of 1 volume (2000 ms). P-values were corrected using the Bonferroni-Holm method. Results: Subjects showed improvements in the following neuropsychological tests: a visuo-spatial-memory task from the VVM (F(1,13) = 8.378, p = .013), the backward-digit-span task from the WMS (F(1,13) = 6.919, p = .021) and the MoCA (F(1,13) = 12.204, p = .004). Functional MRI analysis revealed that during NFB training the left PHG was indeed activated. Activation was further found in the right PHG, the left posterior cingulate, bilaterally in the precuneus, superior occipital lobe, middle frontal gyrus and the cerebellum. GCA revealed 133 connections on T2, 206 on T3 and 156 on T4. The main findings were: (1) activation was chiefly driven by both anterior lobes of the cerebellum, the left posterior cingulate and a cluster within the right precuneus, but these regions received only few input from other regions; (2) there was no connectivity between both PHG; (3) the amount of connections to both PHG increased over time, while the amount of connections from both PHG to other regions such as the right cerebellum and the right precuneus tended to decrease. Conclusions: The neuropsychological, activation and connectivity data from our NFB training in elderly suggest the following: (1)
Abstracts / Clinical Neurophysiology 127 (2016) e210–e303
movement direction is inverted relative to the hand movement (e.g., a joystick movement to the left will move the ball to the right). Further tests assessed simple (i.e. non-inverse) two-hand visuomotor coordination, one-hand visuomotor coordination (Trail Making Test [TMT-A and -B]), one-hand motor control (Motor Performance Series), inhibitory control (Go/Nogo task), divided attention, and cognitive flexibility (difference between TMT-B and -A). To identify potential predictors of inverse bimanual coordination (IBC), we compared performance in all tests between those older participants who were able (n = 13) and those who were unable (n = 7) to perform the IBC task. Test scores showing a significant group difference were included in a binary logistic regression analysis to test how well they predict group affiliation (IBC success vs. failure). Linear regression analysis examined how well these scores explain different aspects of IBC performance across all (young and old) successful IBC performers (n = 31). Results: Significantly decreased performance in the IBC failure subgroup was observed for TMT-A and TMT-B, Go/Nogo task (mean reaction time), and simple bimanual coordination (average speed and error duration). In a logistic regression model, these 5 scores predicted group affiliation with 88.9% accuracy. In a linear regression, all 5 scores significantly contributed to predicting IBC performance, jointly explaining 40% of variance in speed, 50% in error duration, and 95% in percentage error duration. Discussion: Our results show that specific aspects of executive functioning, rather than motor skills per se, explain IBC performance across age. This indicates that the limitations in older adults to perform the task may arise from cognitive aspects of this complex ‘‘motor task” (e.g. intentional movement de-coupling, input–output coordinate transformation, error monitoring). We suggest that these parallel cognitive processing demands lead to mutual interference and eventually, reflecting well-known multitasking deficits in the elderly, may lead to a complete breakdown of complex visuomotor coordination.
Fig. 1.
to 3D objects of balls, office objects, and low-calorie fruits, crucially. Exploratory analyses of the hand movement trajectories are presented and we discuss the implications for and limitations of the use of Virtual Reality in the assessment of biased behavior. An embodied perspective on the development and maintenance of biased cognitive processing may opt further therapeutic applications of (full-) body tracking technologies and may suggest the involvement of motor regions in addition to a fronto-limbic network.
References Schroeder P, Lohmann J, Butz M V, Plewnia C. Behavioral bias for food reflected in hand movements: a preliminary study with healthy subjects. Cyberpsychol Behav Soc Netw 2015. doi:10.1089/cyber.2015.0311. Wiers RW, Eberl C, Rinck M, Becker ES, Lindenmeyer J. Retraining automatic action tendencies changes alcoholic patients’ approach bias for alcohol and improves treatment outcome. Psychol Sci 2011;22:490–7.
doi:10.1016/j.clinph.2016.05.167 doi:10.1016/j.clinph.2016.05.168
EP 126. Virtual Reality in the assessment of a manual bias towards food—P.A. Schroeder a,*, J. Lohmann b, M.V. Butz b, C. Plewnia a (a University Tübingen, Dept. of Psychiatry and Psychotherapy, Tübingen, Germany, b University Tübingen, Dept. of Computer Science, Tübingen, Germany) ⇑
Corresponding author.
Biased attentional and cognitive processes are documented for various psychiatric conditions, mostly linked with illness-specific stimuli. Prominent cognitive bias modification paradigms aim at addressing specific cognitive-behavioral deviations and corroborate therapy outcomes. Interestingly, because bodily and motivational tendencies might contribute to biased behavior, actual movements are starting to be included in bias modification paradigms in the form of approach-avoidance trainings (Wiers et al., 2011). Here, we introduce a novel experimental setup in Virtual Reality to include actual hand ward and grasp movements in manual interactions with critical stimuli (Fig. 1). The aim of this study was to identify motor contributions to the attentional bias towards food, a wellestablished finding. First, an attentional bias towards food was replicated during the course of grasping 3D objects of palatable objects as compared to ball objects. Food objects were collected faster than ball objects and the difference increased with larger body-mass indices of the healthy subjects (Schroeder et al., 2015). This finding was replicated in a larger sample, but the behavioral bias towards food was driven by high-calorie food objects exclusively, as compared
ePoster Presentations – Neuroplasticity EP 128. Motor learning: TDCS effects vary with baseline performance—V. Krause *, A. Keitel, J. Focke, S. Kemmet, T. Kuntz, A. Sturm, B. Pollok (Heinrich-Heine-University, Institute of Clinical Neuroscience and Medical Psychology, Duesseldorf, Germany) ⇑
Corresponding author.
Transcranial direct current stimulation (tDCS) allows the noninvasive modulation of cortical excitability. Anodal tDCS is associated with an increase of cortical excitability, while cathodal tDCS yields its decrease. Beyond altered excitability, tDCS to the primary motor cortex (M1) has been proven to modulate motor performance, but effects considerably vary across participants. To further elucidate the indicative role of baseline performance on the impact of tDCS, we subdivided 72 participants after baseline reaction time recordings into fast and slow performers by median split. Subsequently, participants implicitly learned a motor sequence with the right hand using the serial reaction time task. M1 is assumed to contribute to motor sequence acquisition and early motor memory consolidation, while the premotor cortex (PMC) may be relevant for later phases of consolidation. In half of the participants, tDCS was applied to the left M1 and in the other half to the left PMC. Since tDCS effects also vary with respect to timing of stimulation, tDCS was applied either prior to or during motor sequence learning. Anodal vs. cathodal vs. sham tDCS
Abstracts / Clinical Neurophysiology 127 (2016) e210–e303
was applied in three separate sessions. When tDCS was applied prior to learning, anodal M1 tDCS facilitated subsequent sequence acquisition. Most interestingly, this effect became evident in participants with slow baseline reaction times only. When tDCS was applied during learning, anodal M1 tDCS yielded an unspecific facilitation of reaction times – again in participants with slow baseline performance only. Cathodal and sham tDCS as well as PMC tDCS had no such effect. Fast performers did not benefit from tDCS possibly due to a ceiling effect. Beyond underpinning the relevance of M1 for initial motor sequence acquisition, the present results complement evidence that behavioural tDCS effects may strongly depend on the behavioural status quo at time of stimulation. doi:10.1016/j.clinph.2016.05.169
EP 129. The effect of tDCS over M1 prior to and during implicit motor sequence learning—T. Kuntz *, A.P. Sturm, V. Krause, B. Pollok, A. Keitel (Heinrich-Heine-Universität, Institut für Klinische Neurowissenschaften und Medizinische Psychologie, Düsseldorf, Germany) ⇑
Corresponding author.
Motor learning is an essential skill allowing the acquisition of new movement patterns. Transcranial direct current stimulation (tDCS) has been shown to modulate neuronal excitability along with behavioural performance in a polarity-dependent manner. Besides polarity, the effects of tDCS on motor learning also vary with the timing of stimulation. In order to gain a better understanding regarding the optimal timing of tDCS application to modulate implicit motor sequence learning, motor-cortical tDCS was applied prior to and during training on a serial reaction time task (SRTT). The SRTT employs a fixed sequential pattern of button presses allowing the assessment of implicit motor sequence learning. A random pattern served as control condition. 36 healthy subjects were assigned to one of two experiments: tDCS was applied prior to (experiment 1) or during (experiment 2) SRTT training. Anodal vs. cathodal vs. sham tDCS was applied to the left primary motor cortex (M1) for ten minutes in a counterbalanced order. Reaction times of the right hand were measured at Baseline and after SRTT training (End of Acquisition (EoA)). Anodal tDCS prior to SRTT training yielded a beneficial effect on the acquisition of the motor sequence, i.e. reaction times decreased significantly from Baseline to EoA in the sequential pattern. Moreover, at EoA, reaction times were significantly faster following anodal as compared to cathodal tDCS. Reaction times of the random pattern were not differentially modulated by stimulation polarity indicating a sequence-specific effect. In contrast, tDCS applied during SRTT training did not differentially modulate the acquisition of the motor sequence. These results indicate that the timing of tDCS is a crucial parameter yielding distinct effects on implicit motor sequence learning. Anodal tDCS prior to SRTT training resulted in a facilitation emphasising a beneficial effect of increased left M1 excitability for the subsequent acquisition of a new motor sequence. In contrast, modulation of motor-cortical excitability by tDCS during SRTT training yielded no differential effects. This finding implies that tDCS effects may vary with the activation level during stimulation (rest vs. movement). doi:10.1016/j.clinph.2016.05.170
e295
EP 131. Real-time fMRI neurofeedback training in elderly leads to cognitive improvement and changes in cerebral connectivity— C. Hohenfeld a,b,c,*, N. Nellessen a,b,c, I. Dogan a,b,c, H. Kuhn a,b,c, C. Müller a,b,c, F. Papa a,b,c, S. Ketteler a,b,c, N.J. Shah a,b,c, J. Schulz a,c, M. Reske b,c, K. Reetz a,b,c (a Universitätsklinikum RWTH Aachen, Neurologie, Aachen, Germany, b Forschungszentrum Jülich GmbH, Institut für Neurowissenschaften und Medizin (INM-4, 6), Jülich, Germany, c JARA – Translational Brain Medicine, Aachen/Jülich, Germany) ⇑
Corresponding author.
Introduction: During past years real-time functional MRI (rtfMRI) has been shown to be a feasible tool for neurofeedback (NFB). This is a technique, which aims at subjects learning to voluntarily modulate activation of specific brain regions. It has already been applied successfully clinically and non-clinically. We conducted rtfMRI NFB training of the left parahippocampal gyrus (PHG) in healthy elderly with the hypothesis subjects are indeed able to modulate left PHG activation and that this training leads to increased cognitive performance. Here, we also focus on brain connectivity over the course of the training. Methods: 16 subjects (mean age 63.5 y, 9 male) completed the protocol of five examination days (T1–T5). On T1 the neuropsychological pre-test was done (see table), followed by the encoding of a real-world footpath (one out of three variants). On T2–T4 the rtfMRI NFB training was carried out. Activation of the left PHG was fed back visually by a thermometer bar. The task alternated between upregulation (recalling the path encoded on T1) and baseline (counting backwards). Three rtfMRI NFB runs were done per day. On T5 the neuropsychological post-test was done. For analysis of neuropsychological data ANCOVAs with examination day and variant of the footpath as factors and age, education and gender as covariates were calculated. For fMRI data a general linear model with upregulation as predictor was computed with BrainVoyager QX for each NFB run and the activation was then averaged across all runs. Activation was limited to a threshold of Bonferroni-corrected p < :05 and two voxels of cluster size. To conduct an analysis of connectivity, activation time courses were extracted from clusters active during upregulation and averaged for each day and region. With the statistical software R, a GrangerCausality-Analysis (GCA) for each training day was conducted for each combination of active regions (306 connections) with a lag size of 1 volume (2000 ms). P-values were corrected using the Bonferroni-Holm method. Results: Subjects showed improvements in the following neuropsychological tests: a visuo-spatial-memory task from the VVM (F(1,13) = 8.378, p = .013), the backward-digit-span task from the WMS (F(1,13) = 6.919, p = .021) and the MoCA (F(1,13) = 12.204, p = .004). Functional MRI analysis revealed that during NFB training the left PHG was indeed activated. Activation was further found in the right PHG, the left posterior cingulate, bilaterally in the precuneus, superior occipital lobe, middle frontal gyrus and the cerebellum. GCA revealed 133 connections on T2, 206 on T3 and 156 on T4. The main findings were: (1) activation was chiefly driven by both anterior lobes of the cerebellum, the left posterior cingulate and a cluster within the right precuneus, but these regions received only few input from other regions; (2) there was no connectivity between both PHG; (3) the amount of connections to both PHG increased over time, while the amount of connections from both PHG to other regions such as the right cerebellum and the right precuneus tended to decrease. Conclusions: The neuropsychological, activation and connectivity data from our NFB training in elderly suggest the following: (1)