Influence of Mental Training of Attentional Control on Autonomic Arousal Within the Framework of the Temporal Preparation of a Force Task.

While temporal preparation has frequently been examined through the manipulation of foreperiods, the role of force level during temporal preparation remains underexplored. In our study, we propose to manipulate mental training of attentional control in order to shed light on the role of the force level and autonomic nervous system in the temporal preparation of an action. Forty subjects, divided into mental training group (n = 20) and without mental training group (n = 20), participated in this study. The influence of the attentional control and force levels on the autonomic nervous system were measured using the skin conductance response and the heart rate variability; the accuracy of the motor responses was measured using a method derived from machine learning. Behaviorally, only the mental training group reinforced its motor and attentional control. When using short foreperiod durations and high force level, motor and attentional control decreased, consistent with the dominant sympathetic system. This resulted in an increased anticipation rate of responses with a higher reaction time compared to the long foreperiods duration and low force level, in which the reaction time significantly decreased, with enhancement of the expected force level, showing consistency with the dominant parasympathetic system. Interestingly, results revealed a predictive relationship between the sympathovagal balance and motor and attentional control during the long foreperiods and low force level. Finally, results demonstrate that attentional mental training leads to the reinforcement of interactions between the autonomic nervous system and attentional processes which are involved in the temporal preparation of a force task.

Motor imagery in amyotrophic lateral Sclerosis: An fMRI study of postural control.

BACKGROUND: The functional reorganization of brain networks sustaining gait is poorly characterized in amyotrophic lateral sclerosis (ALS) despite ample evidence of progressive disconnection between brain regions. The main objective of this fMRI study is to assess gait imagery-specific networks in ALS patients using dynamic causal modeling (DCM) complemented by parametric empirical Bayes (PEB) framework. METHOD: Seventeen lower motor neuron predominant (LMNp) ALS patients, fourteen upper motor neuron predominant (UMNp) ALS patients and fourteen healthy controls participated in this study. Each subject performed a dual motor imagery task: normal and precision gait. The Movement Imagery Questionnaire (MIQ-rs) and imagery time (IT) were used to evaluate gait imagery in each participant. In a neurobiological computational model, the circuits involved in imagined gait and postural control were investigated by modelling the relationship between normal/precision gait and connection strengths. RESULTS: Behavioral results showed significant increase in IT in UMNp patients compared to healthy controls (Pcorrected < 0.05) and LMNp (Pcorrected < 0.05). During precision gait, healthy controls activate the model's circuits involved in the imagined gait and postural control. In UMNp, decreased connectivity (inhibition) from basal ganglia (BG) to supplementary motor area (SMA) and from SMA to posterior parietal cortex (PPC) is observed. Contrary to healthy controls, DCM detects no cerebellar-PPC connectivity in neither UMNp nor LMNp ALS. During precision gait, bilateral connectivity (excitability) between SMA and BG is observed in the LMNp group contrary to UMNp and healthy controls. CONCLUSIONS: Our findings demonstrate the utility of implementing both DCM and PEB to characterize connectivity patterns in specific patient phenotypes. Our approach enables the identification of specific circuits involved in postural deficits, and our findings suggest a putative excitatory-inhibitory imbalance. More broadly, our data demonstrate how clinical manifestations are underpinned by network-specific disconnection phenomena in ALS.

Theoretical discrimination index of postural instability in amyotrophic lateral sclerosis.

To assess the usefulness of a theoretical postural instability discrimination index (PIth) in amyotrophic lateral sclerosis (ALS). Prospective regression analyzes were performed to identify the biomechanical determinants of postural instability unrelated to lower limb motor deficits from gait initiation factors. PIth was constructed using a logit function of biomechanical determinants. Discriminatory performance and performance differences were tested. Backward displacement of the pression center (APAamplitude) and active vertical braking of the mass center (Braking-index) were the biomechanical determinants of postural instability. PIth = - 0.13 × APAamplitude - 0.12 × Braking-index + 5.67, (P < 0.0001, RSquare = 0.6119). OR (APAamplitude) and OR (Braking-index) were 0.878 and 0.887, respectively, i.e., for a decrease of 10 mm in APAamplitude or 10% in Braking-index, the postural instability risk was 11.391 or 11.274 times higher, respectively. PIth had the highest discriminatory performance (AUC 0.953) with a decision threshold value [Formula: see text] 0.587, a sensitivity of 90.91%, and a specificity of 83.87%, significantly increasing the sensitivity by 11.11%. PIth, as objective clinical integrator of gait initiation biomechanical processes significantly involved in dynamic postural control, was a reliable and performing discrimination index of postural instability with a significant increased sensitivity, and may be useful for a personalized approach to postural instability in ALS.

Neural Correlates of Motor Imagery of Gait in Amyotrophic Lateral Sclerosis.

BACKGROUND: Gait impairment is poorly characterized in amyotrophic lateral sclerosis (ALS), despite increasing evidence of extrapyramidal and cerebellar dysfunction. Gait impairment adds to the considerable motor disability of ALS patients and requires targeted multidisciplinary interventions. PURPOSE: To assess gait imagery-specific networks and functional adaptation in ALS. STUDY TYPE: Prospective. POPULATION: Seventeen ALS patients with lower motor neuron predominant (LMNp) disability, 14 patients with upper motor neurons predominant (UMNp) disease, and 14 healthy controls were included. FIELD STRENGTH/SEQUENCES: 3T / gradient echo echo planar (GE-EPI). ASSESSMENT: Subjects performed a dual motor imagery task: normal and precision gait. The Movement Imagery Questionnaire - Revised Second Version (MIQ-rs) was used to appraise movement imagery in each participant. Study group-specific activation patterns were evaluated during motor imagery of gait. Additional generalized psychophysiological interaction analyses were carried out using the supplementary motor area, caudate, cerebellum, and superior parietal lobule as seed regions. STATISTICAL TESTS: Repeated-measures analysis of variance (ANOVA) was used to compare time imagery and MIQ-rs scores between groups. Size effects were also reported as partial eta squared (η2). One-way ANOVA was performed to explore differences in terms of connexions during motor imagery tasks. RESULTS: A significant increase in imagery time in UMNp patients compared to controls (P < 0.05) and LMNp (P < 0.05) during imagined gait was demonstrated. UMNp patients exhibited altered supplementary motor area, precentral gyrus, superior parietal lobule, and dorsolateral prefrontal cortex activation and increased orbitofrontal (pFDR(False Discovery Rate) < 0.05), posterior parietal (pFDR < 0.05) caudate (pFDR < 0.05), and cerebellar (pFDR < 0.05) signal during imagined locomotion. Increased effective connectivity of the striato-cerebellar and parieto-cerebellar circuits was also demonstrated. Additional activation was detected in the insula and cingulate cortex. DATA CONCLUSION: Enhanced striato- and parieto-cerebellar networks in UMNp ALS patients are likely to represent a compensatory response to impaired postural control. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 5.

Extrapyramidal deficits in ALS: a combined biomechanical and neuroimaging study.

INTRODUCTION: Extrapyramidal deficits are poorly characterised in amyotrophic lateral sclerosis (ALS) despite their contribution to functional disability, increased fall risk and their quality-of-life implications. Given the concomitant pyramidal and cerebellar degeneration in ALS, the clinical assessment of extrapyramidal features is particularly challenging. OBJECTIVE: The comprehensive characterisation of postural instability in ALS using standardised clinical assessments, gait analyses and computational neuroimaging tools in a prospective study design. METHODS: Parameters of gait initiation in the anticipatory postural adjustment phase (APA) and execution phase (EP) were evaluated in ALS patients with and without postural instability and healthy controls. Clinical and gait analysis parameters were interpreted in the context of brain imaging findings. RESULTS: ALS patients with postural instability exhibit impaired gait initiation with an altered APA phase, poor dynamic postural control and significantly decreased braking index. Consistent with their clinical profile, "unsteady" ALS patients have reduced caudate and brain stem volumes compared to "steady" ALS patients. INTERPRETATION: Our findings highlight that the ALS functional rating scale (ALSFRS-r) does not account for extrapyramidal deficits, which are major contributors to gait impairment in a subset of ALS patients. Basal ganglia degeneration in ALS does not only contribute to cognitive and behavioural deficits, but also adds to the heterogeneity of motor disability.

Neural mechanisms associated with treatment decision making: An fMRI study.

Great progress has been made in understanding how people make financial decisions. However, there is little research on how people make health and treatment choices. Our study aimed to examine how participants weigh benefits (reduction in disease progression) and probability of risk (medications' side effects) when making hypothetical treatment decisions, and to identify the neural networks implicated in this process. Fourteen healthy participants were recruited to perform a treatment decision probability discounting task using MRI. Behavioral responses and skin conductance responses (SCRs) were measured. A whole brain analysis were performed to compare activity changes between "mild" and "severe" medications' side effects conditions. Then, orbitofrontal cortex (OFC), ventral striatum (VS), amygdala and insula were chosen for effective connectivity analysis. Behavioral data showed that participants are more likely to refuse medication when side effects are high and efficacy is low. SCRs values were significantly higher when people made medication decisions in the severe compared to mild condition. Functionally, OFC and VS were activated in the mild condition and were associated with increased likehood of choosing to take medication (higher area under the curve "AUC" side effects/efficacy). These regions also demonstrated an increased effective connectivity when participants valued treatment benefits. By contrast, the OFC, insula and amygdala were activated in the severe condition and were associated with and increased likelihood to refuse treatment. These regions showed enhanced effective connectivity when participants were confronted with increased side effects severity. This is the first study to examine the behavioral and neural bases of medical decision making.