Cholinergic modulation of motor sequence learning Voegtle, Angela; Mohrbutter, Catharina; Hils, Jonathan ...
European journal of neuroscience/EJN. European journal of neuroscience,
July 2024, Letnik:
60, Številka:
1
Journal Article
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The cholinergic system plays a key role in motor function, but whether pharmacological modulation of cholinergic activity affects motor sequence learning is unknown. The acetylcholine receptor ...antagonist biperiden, an established treatment in movement disorders, reduces attentional modulation, but whether it influences motor sequence learning is not clear. Using a randomized, double‐blind placebo‐controlled crossover design, we tested 30 healthy young participants and showed that biperiden impairs the ability to learn sequential finger movements, accompanied by widespread oscillatory broadband power changes (4–25 Hz) in the motor sequence learning network after receiving biperiden, with greater power in the theta, alpha and beta bands over ipsilateral motor and bilateral parietal–occipital areas. The reduced early theta power during a repeated compared with random sequence, likely reflecting disengagement of top‐down attention to sensory processes, was disrupted by biperiden. Alpha synchronization during repeated sequences reflects sensory gating and lower visuospatial attention requirements compared with visuomotor responses to random sequences. After biperiden, alpha synchronization was greater, potentially reflecting excessive visuospatial attention reduction, affecting visuomotor responding required to enable sequence learning. Beta oscillations facilitate sequence learning by integrating visual and somatosensory inputs, stabilizing repeated sequences and promoting prediction of the next stimulus. The beta synchronization after biperiden fits with a disruption of the selective visuospatial attention enhancement associated with initial sequence learning. These findings highlight the role of cholinergic processes in motor sequence learning.
Participants performed a serial reaction time task following the acetylcholine receptor antagonist biperiden or placebo. Biperiden impaired the ability to learn sequential finger movements, accompanied by widespread oscillatory broadband power changes (4–25 Hz) in the motor sequence learning network. The power difference between biperiden and placebo conditions was greater over ipsilateral motor and bilateral parietal–occipital areas responding to a repeated (left) than random (right) sequence.
Objective. Convolutional neural networks (CNNs) have proven successful as function approximators and have therefore been used for classification problems including electroencephalography (EEG) signal ...decoding for brain-computer interfaces (BCI). Artificial neural networks, however, are considered black boxes, because they usually have thousands of parameters, making interpretation of their internal processes challenging. Here we systematically evaluate the use of CNNs for EEG signal decoding and investigate a method for visualizing the CNN model decision process. Approach. We developed a CNN model to decode the covert focus of attention from EEG event-related potentials during object selection. We compared the CNN and the commonly used linear discriminant analysis (LDA) classifier performance, applied to datasets with different dimensionality, and analyzed transfer learning capacity. Moreover, we validated the impact of single model components by systematically altering the model. Furthermore, we investigated the use of saliency maps as a tool for visualizing the spatial and temporal features driving the model output. Main results. The CNN model and the LDA classifier achieved comparable accuracy on the lower-dimensional dataset, but CNN exceeded LDA performance significantly on the higher-dimensional dataset (without hypothesis-driven preprocessing), achieving an average decoding accuracy of 90.7% (chance level = 8.3%). Parallel convolutions, tanh or ELU activation functions, and dropout regularization proved valuable for model performance, whereas the sequential convolutions, ReLU activation function, and batch normalization components reduced accuracy or yielded no significant difference. Saliency maps revealed meaningful features, displaying the typical spatial distribution and latency of the P300 component expected during this task. Significance. Following systematic evaluation, we provide recommendations for when and how to use CNN models in EEG decoding. Moreover, we propose a new approach for investigating the neural correlates of a cognitive task by training CNN models on raw high-dimensional EEG data and utilizing saliency maps for relevant feature extraction.
The network of brain structures engaged in motor sequence learning comprises the same structures as those involved in tremor, including basal ganglia, cerebellum, thalamus, and motor cortex. Deep ...brain stimulation (DBS) of the ventrointermediate nucleus of the thalamus (VIM) reduces tremor, but the effects on motor sequence learning are unknown. We investigated whether VIM stimulation has an impact on motor sequence learning and hypothesized that stimulation effects depend on the laterality of electrode location. Twenty patients (age: 38–81 years; 12 female) with VIM electrodes implanted to treat essential tremor (ET) successfully performed a serial reaction time task, varying whether the stimuli followed a repeating pattern or were selected at random, during which VIM‐DBS was either on or off. Analyses of variance were applied to evaluate motor sequence learning performance according to reaction times (RTs) and accuracy. An interaction was observed between whether the sequence was repeated or random and whether VIM‐DBS was on or off (F1,18 = 7.89, p = .012). Motor sequence learning, reflected by reduced RTs for repeated sequences, was greater with DBS on than off (T19 = 2.34, p = .031). Stimulation location correlated with the degree of motor learning, with greater motor learning when stimulation targeted the lateral VIM (n = 23, ρ = 0.46; p = .027). These results demonstrate the beneficial effects of VIM‐DBS on motor sequence learning in ET patients, particularly with lateral VIM electrode location, and provide evidence for a role for the VIM in motor sequence learning.
Motor sequence learning enables activities like playing the piano without conscious thought. Tremor engages similar brain structures to those supporting motor learning. Stimulation of the ventrointermediate nucleus of the thalamus is effective in treating tremor, and we demonstrate that it also improves motor sequence learning, with greater performance modulation when the stimulating electrode is more lateral.
Retrospective cohort study of health care costs associated with the treatment of chronic low back pain (CLBP) in the United Kingdom.
To assess 12-month health care costs associated with the treatment ...of CLBP, using the UK General Practice Research Database.
CLBP is a common health problem.
Data were obtained from the General Practice Research Database, a computerized database of UK primary care patient data. Patients with CLBP were identified for the study period (January 1, 2007, to December 31, 2009) using diagnostic records and pain relief prescriptions (n = 64,167), and 1:1 matched to patients without CLBP (n = 52,986) on the basis of age, sex, and general practitioner's practice. Index date was defined as the first date of CLBP record; the same index date was assigned to matched controls. Multivariate analyses were performed to compare resource use costs (2009 values) in the 12 months after the index date between patients with and without CLBP. A sensitivity analysis was carried out with a more stringent definition for the control group by excluding a broad range of pain conditions.
Total health care costs for patients with CLBP were double those of the matched controls (£1074 vs. £516; P < 0.05). Of the cost difference, 58.8% was accounted for by general practitioner's consultations, 22.3% by referrals to secondary care, and the rest by pain relief medications. The sensitivity analysis revealed an even greater cost difference between the 2 groups (£1052 vs. £304; P < 0.05). Because of the use of a retrospective administrative claims database, this study is subject to selection bias between study cohorts, misidentification of comorbidities, and an inability to confirm adherence to therapy or assess indirect costs and costs of over-the-counter medications.
Our findings confirm the substantial economic burden of CLBP, even with direct costs only.
Pupillary contagion is a form of autonomic mimicry in which faces with dilated pupils elicit larger pupils in observers whereas faces with constricted pupils elicit smaller pupils. Autonomic ...reactivity may be fundamental to higher order social processes, yet older adults may be less likely to register other's autonomic signals. We explored pupillary contagion in younger and older adult observers. We presented younger and older observers with partial-face photographs of women with the pupils manipulated to be small, medium, or large. The faces were either young (20s) or old (70s). There were two tasks: To judge the model's age and to judge which pupil was larger. In the pupil judgment task, the magnitude of response was lower in older adults than in younger adults, but both younger and older observers showed equivalent pupillary contagion. In the age judgment task, which did not draw attention to the pupils, we found no evidence of pupillary contagion in either age-group. Registration of the autonomic signal of pupil dilation does not appear to be impaired in older adults.
Public Significance Statement
The autonomic nervous system (ANS) regulates involuntary physiological processes such as heart rate, blood pressure, respiration, sexual arousal, and pupillary dilation. ANS activation and deactivation can provide important information about a person's state and often lead to mimicry of the state by an observer, either consciously or nonconsciously. Here, we ask whether one aspect of that nonverbal dyadic signaling is maintained into old age: Are pupillary dilation and contraction in a target reciprocated by similar or different changes in younger and older observers?
Do the nonverbal signals used to make social judgements differ depending on the type of judgement being made and what other nonverbal signals are visible? Experiment 1 investigated how nonverbal ...signals across three channels (face: angry/fearful, posture: expanded/contracted, lean: forward/backward), when viewed together, were used for judgements of emotion, threat, and status. Experiment 2 replicated Experiment 1 and explored how use of the body channels differed in making social judgements when the face channel was obscured. Both experiments found facial anger linked to high anger, threat, and status ratings; facial fear was linked to low ratings. Expanded body posture increased threat and status judgements, while backward lean decreased anger and threat. With the face channel blocked (Experiment 2B), the influence of body posture increased across emotion, threat, and status judgements, while body lean was more consistent. Findings demonstrate that despite the face's importance across types of social judgements, the body channels differentially contribute to judgements of emotion, threat and status. Further, they are differentially affected by the absence of facial information. How much face and body-related channels are used in social judgements is moderated by the type of judgement being made and the availability of other (particularly facial) channel information.
Pupillary synchrony or contagion is the automatic unconscious mimicry of pupil dilation in dyadic interactions. This experiment explored electrophysiological event-related potential (ERP) ...concomitants of pupillary synchrony. Artificial pupils (black dots) were superimposed on either partial faces (eyes, nose, brow) or random textures. Observers were asked to judge dot size (large, medium, or small). There was clear evidence of pupillary synchrony with observer pupil dilation greater to large dots than to small or medium dots. The pupillary synchrony increased in magnitude throughout the trial and was found both with faces and with textures. When the stimuli were partial faces with artificial pupils (dots), there was ERP activity related to target dot size in the period at P250 and P3. A face specific N170 was also found. When the stimuli were random textures with dots, there was ERP activity at P1 and in the interval from 140 to 200 ms post-stimulus onset. The use of ERP with pupillometry revealed results for faces that were consistent with a social explanation of pupillary synchrony whereas results for textures were consistent with a local luminance explanation.
Commands in brain-computer interface (BCI) applications often rely on the decoding of event-related potentials (ERP). For instance, the P300 potential is frequently used as a marker of attention to ...an oddball event. Error-related potentials and the N2pc signal are further examples of ERPs used for BCI control. One challenge in decoding brain activity from the electroencephalogram (EEG) is the selection of the most suitable channels and appropriate features for a particular classification approach. Here we introduce a toolbox that enables ERP-based decoding using the full set of channels, while automatically extracting informative components from relevant channels. The strength of our approach is that it handles sequences of stimuli that encode multiple items using binary classification, such as target vs. nontarget events typically used in ERP-based spellers. We demonstrate examples of application scenarios and evaluate the performance of four openly available datasets: a P300-based matrix speller, a P300-based rapid serial visual presentation (RSVP) speller, a binary BCI based on the N2pc, and a dataset capturing error potentials. We show that our approach achieves performances comparable to those in the original papers, with the advantage that only conventional preprocessing is required by the user, while channel weighting and decoding algorithms are internally performed. Thus, we provide a tool to reliably decode ERPs for BCI use with minimal programming requirements.
We explored neural processing differences associated with aging across four cognitive functions. In addition to ERP analysis, we included task-related microstate analyses, which identified stable ...states of neural activity across the scalp over time, to explore whole-head neural activation differences. Younger and older adults (YA, OA) completed face perception (N170), word-pair judgment (N400), visual oddball (P3), and flanker (ERN) tasks. Age-related effects differed across tasks. Despite age-related delayed latencies, N170 ERP and microstate analyses indicated no age-related differences in amplitudes or microstates. However, age-related condition differences were found for P3 and N00 amplitudes and scalp topographies: smaller condition differences were found for in OAs as well as broader centroparietal scalp distributions. Age group comparisons for the ERN revealed similar focal frontocentral activation loci, but differential activation patterns. Our findings of differential age effects across tasks are most consistent with the STAC-r framework which proposes that age-related effects differ depending on the resources available and the kinds of processing and cognitive load required of various tasks.
•ERP and microstate analyses showed that age effects differed across four tasks.•Microstates with ERPs help distinguish among current theories of neural aging.•Spatial distributions of neural processing phases differ by age across time and task.•Different age-related effects across tasks were most consistent with STAC-r.
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