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The muscle synergy is a guiding concept in motor control research that relies on the general notion of muscles ‘ working together ’ towards task performance. However, although the synergy concept has provided valuable insights into motor coordination, muscle interactions have not been fully characterised with respect to task performance. Here, we address this research gap by proposing a novel perspective to the muscle synergy that assigns specific functional roles to muscle couplings by characterising their task-relevance. Our novel perspective provides nuance to the muscle synergy concept, demonstrating how muscular interactions can ‘ work together ’ in different ways: (1) irrespective of the task at hand but also (2) redundantly or (3) complementarily towards common task-goals. To establish this perspective, we leverage information- and network-theory and dimensionality reduction methods to include discrete and continuous task parameters directly during muscle synergy extraction. Specifically, we introduce co-information as a measure of the task-relevance of muscle interactions and use it to categorise such interactions as task-irrelevant (present across tasks), redundant (shared task information), or synergistic (different task information). To demonstrate these types of interactions in real data, we firstly apply the framework in a simple way, revealing its added functional and physiological relevance with respect to current approaches. We then apply the framework to large-scale datasets and extract generalizable and scale-invariant representations consisting of subnetworks of synchronised muscle couplings and distinct temporal patterns. The representations effectively capture the functional interplay between task end-goals and biomechanical affordances and the concurrent processing of functionally similar and complementary task information. The proposed framework unifies the capabilities of current approaches in capturing distinct motor features while providing novel insights and research opportunities through a nuanced perspective to the muscle synergy.

Despite recent progress in understanding multisensory decision-making, a conclusive mechanistic account of how the brain translates the relevant evidence into a decision is lacking. Specifically, it remains unclear whether perceptual improvements during rapid multisensory decisions are best explained by sensory (i.e., ‘Early’) processing benefits or post-sensory (i.e., ‘Late’) changes in decision dynamics. Here, we employ a well-established visual object categorisation task in which early sensory and post-sensory decision evidence can be dissociated using multivariate pattern analysis of the electroencephalogram (EEG). We capitalize on these distinct neural components to identify when and how complementary auditory information influences the encoding of decision-relevant visual evidence in a multisensory context. We show that it is primarily the post-sensory, rather than the early sensory, EEG component amplitudes that are being amplified during rapid audiovisual decision-making. Using a neurally informed drift diffusion model we demonstrate that a multisensory behavioral improvement in accuracy arises from an enhanced quality of the relevant decision evidence, as captured by the post-sensory EEG component, consistent with the emergence of multisensory evidence in higher-order brain areas. A conclusive account on how the brain translates audiovisual evidence into a rapid decision is still lacking. Here, using a neurally-informed modelling approach, the authors show that sounds amplify visual evidence later in the decision process, in line with higher-order multisensory effects.

Objective: Musculoskeletal (MSK) pain is being increasingly reported by patients as one of the most common persistent symptoms in post-COVID-19 syndrome or Long COVID. However, there is a lack of understanding of its prevalence, characteristics, and underlying pathophysiological mechanisms. The objective of this review is to identify and describe the features and characteristics of MSK pain in Long COVID patients. Methods: The narrative review involved a literature search of the following online databases: MEDLINE (OVID), EMBASE (OVID), CINAHL, PsyclNFO, and Web of Science (December 2019 to February 2022). We included observational studies that investigated the prevalence, characteristics, risk factors and mechanisms of MSK pain in Long COVID. After screening and reviewing the initial literature search results, a total of 35 studies were included in this review. Results: The overall reported prevalence of MSK pain in Long COVID ranged widely from 0.3% to 65.2%. The pain has been reported to be localized to a particular region or generalized and widespread. No consistent pattern of progression of MSK pain symptoms over time was identified. Female gender and higher BMI could be potential risk factors for Long COVID MSK pain, but no clear association has been found with age and ethnicity. Different pathophysiological mechanisms have been hypothesized to contribute to MSK pain in Long COVID including increased production of proinflammatory cytokines, immune cell hyperactivation, direct viral entry of neurological and MSK system cells, and psychological factors. Conclusion: MSK pain is one of the most common symptoms in Long COVID. Most of the current literature on Long COVID focuses on reporting the prevalence of persistent MSK pain. Studies describing the pain characteristics are scarce. The precise mechanism of MSK pain in Long COVID is yet to be investigated. Future research must explore the characteristics, risk factors, natural progression, and underlying mechanisms of MSK pain in Long COVID. Keywords: post-COVID-19 syndrome, post-acute COVID-19, chronic pain

When exposed to complementary features of information across sensory modalities, our brains formulate cross-modal associations between features of stimuli presented separately to multiple modalities. For example, auditory pitch-visual size associations map high-pitch tones with small-size visual objects, and low-pitch tones with large-size visual objects. Preferential, or congruent, cross-modal associations have been shown to affect behavioural performance, i.e. choice accuracy and reaction time (RT) across multisensory decision-making paradigms. However, the neural mechanisms underpinning such influences in perceptual decision formation remain unclear. Here, we sought to identify when perceptual improvements from associative congruency emerge in the brain during decision formation. In particular, we asked whether such improvements represent ‘early’ sensory processing benefits, or ‘late’ post-sensory changes in decision dynamics. Using a modified version of the Implicit Association Test (IAT), coupled with electroencephalography (EEG), we measured the neural activity underlying the effect of auditory stimulus-driven pitch-size associations on perceptual decision formation. Behavioural results showed that participants responded significantly faster during trials when auditory pitch was congruent, rather than incongruent, with its associative visual size counterpart. We used multivariate Linear Discriminant Analysis (LDA) to characterise the spatiotemporal dynamics of EEG activity underpinning IAT performance. We found an ‘Early’ component (∼100–110 ms post-stimulus onset) coinciding with the time of maximal discrimination of the auditory stimuli, and a ‘Late’ component (∼330–340 ms post-stimulus onset) underlying IAT performance. To characterise the functional role of these components in decision formation, we incorporated a neurally-informed Hierarchical Drift Diffusion Model (HDDM), revealing that the Late component decreases response caution, requiring less sensory evidence to be accumulated, whereas the Early component increased the duration of sensory-encoding processes for incongruent trials. Overall, our results provide a mechanistic insight into the contribution of ‘early’ sensory processing, as well as ‘late’ post-sensory neural representations of associative congruency to perceptual decision formation.

Older adults (OAs) are typically slower and/or less accurate in forming perceptual choices relative to younger adults. Despite perceptual deficits, OAs gain from integrating information across senses, yielding multisensory benefits. However, the cognitive processes underlying these seemingly discrepant ageing effects remain unclear. To address this knowledge gap, 212 participants (18–90 years old) performed an online object categorisation paradigm, whereby age-related differences in Reaction Times (RTs) and choice accuracy between audiovisual (AV), visual (V), and auditory (A) conditions could be assessed. Whereas OAs were slower and less accurate across sensory conditions, they exhibited greater RT decreases between AV and V conditions, showing a larger multisensory benefit towards decisional speed. Hierarchical Drift Diffusion Modelling (HDDM) was fitted to participants’ behaviour to probe age-related impacts on the latent multisensory decision formation processes. For OAs, HDDM demonstrated slower evidence accumulation rates across sensory conditions coupled with increased response caution for AV trials of higher difficulty. Notably, for trials of lower difficulty we found multisensory benefits in evidence accumulation that increased with age, but not for trials of higher difficulty, in which increased response caution was instead evident. Together, our findings reconcile age-related impacts on multisensory decision-making, indicating greater multisensory evidence accumulation benefits with age underlying enhanced decisional speed.

Do motor patterns of object lifting movements change as a result of ageing? Here we propose a methodology for the characterization of these motor patterns across individuals of different age groups. Specifically, we employ a bimanual grasp-lift-replace protocol with younger and older adults and combine measurements of muscle activity with grip and load forces to provide a window into the motor strategies supporting effective object lifts. We introduce a tensor decomposition to identify patterns of muscle activity and grip-load force ratios while also characterizing their temporal profiles and relative activation across object weights and participants of different age groups. We then probe age-induced changes in these components. A classification analysis reveals three motor components that are differentially recruited between the two age groups. Linear regression analyses further show that advanced age and poorer manual dexterity can be predicted by the coupled activation of forearm and hand muscles which is associated with high levels of grip force. Our findings suggest that ageing may induce stronger muscle couplings in distal aspects of the upper limbs, and a less economic grasping strategy to overcome age-related decline in manual dexterity.

Voluntary movement is hypothesized to rely on a limited number of muscle synergies, the recruitment of which translates task goals into effective muscle activity. In this study, we investigated how to analytically characterize the functional role of different types of muscle synergies in task performance. To this end, we recorded a comprehensive dataset of muscle activity during a variety of whole-body pointing movements. We decomposed the electromyographic (EMG) signals using a space-by-time modularity model which encompasses the main types of synergies. We then used a task decoding and information theoretic analysis to probe the role of each synergy by mapping it to specific task features. We found that the temporal and spatial aspects of the movements were encoded by different temporal and spatial muscle synergies, respectively, consistent with the intuition that there should a correspondence between major attributes of movement and major features of synergies. This approach led to the development of a novel computational method for comparing muscle synergies from different participants according to their functional role. This functional similarity analysis yielded a small set of temporal and spatial synergies that describes the main features of whole-body reaching movements.

Advances in neuronal recording techniques are leading to ever larger numbers of simultaneously monitored neurons. This poses the important analytical challenge of how to capture compactly all sensory information that neural population codes carry in their spatial dimension (differences in stimulus tuning across neurons at different locations), in their temporal dimension (temporal neural response variations), or in their combination (temporally coordinated neural population firing). Here we investigate the utility of tensor factorizations of population spike trains along space and time. These factorizations decompose a dataset of single-trial population spike trains into spatial firing patterns (combinations of neurons firing together), temporal firing patterns (temporal activation of these groups of neurons) and trial-dependent activation coefficients (strength of recruitment of such neural patterns on each trial). We validated various factorization methods on simulated data and on populations of ganglion cells simultaneously recorded in the salamander retina. We found that single-trial tensor space-by-time decompositions provided low-dimensional data-robust representations of spike trains that capture efficiently both their spatial and temporal information about sensory stimuli. Tensor decompositions with orthogonality constraints were the most efficient in extracting sensory information, whereas non-negative tensor decompositions worked well even on non-independent and overlapping spike patterns, and retrieved informative firing patterns expressed by the same population in response to novel stimuli. Our method showed that populations of retinal ganglion cells carried information in their spike timing on the ten-milliseconds-scale about spatial details of natural images. This information could not be recovered from the spike counts of these cells. First-spike latencies carried the majority of information provided by the whole spike train about fine-scale image features, and supplied almost as much information about coarse natural image features as firing rates. Together, these results highlight the importance of spike timing, and particularly of first-spike latencies, in retinal coding.

Polyamines (PAs) exert a protective effect against stress challenges, but their molecular role in this remains speculative. In order to detect the signaling role of apoplastic PA-derived hydrogen peroxide (H₂O₂) under abiotic stress, we developed a series of tobacco (Nicotiana tabacum cv Xanthi) transgenic plants overexpressing or downregulating apoplastic polyamine oxidase (PAO; S-pao and A-pao plants, respectively) or downregulating S-adenosyl-L-methionine decarboxylase (samdc plants). Upon salt stress, plants secreted spermidine (Spd) into the apoplast, where it was oxidized by the apoplastic PAO, generating H₂O₂. A-pao plants accumulated less H₂O₂ and exhibited less programmed cell death (PCD) than did wild-type plants, in contrast with S-pao and samdc downregulating plants. Induction of either stress-responsive genes or PCD was dependent on the level of Spd-derived apoplastic H₂O₂. Thus, in wild-type and A-pao plants, stress-responsive genes were efficiently induced, although in the latter at a lower rate, while S-pao plants, with higher H₂O₂ levels, failed to accumulate stress-responsive mRNAs, inducing PCD instead. Furthermore, decreasing intracellular PAs, while keeping normal apoplastic Spd oxidation, as in samdc downregulating transgenic plants, caused enhanced salinity-induced PCD. These results reveal that salinity induces the exodus of Spd into the apoplast, where it is catabolized by PAO, producing H₂O₂. The accumulated H₂O₂ results in the induction of either tolerance responses or PCD, depending also on the levels of intracellular PAs.

Glutamate dehydrogenase (GDH) may be a stress-responsive enzyme, as GDH exhibits considerable thermal stability, and de novo synthesis of the α-GDH subunit is induced by exogenous ammonium and senescence. NaCl treatment induces reactive oxygen species (ROS), intracellular ammonia, expression of tobacco (Nicotiana tabacum cv Xanthi) gdh-NAD;A1 encoding the α-subunit of GDH, increase in immunoreactive α-polypeptide, assembly of the anionic isoenzymes, and in vitro GDH aminating activity in tissues from hypergeous plant organs. In vivo aminating GDH activity was confirmed by gas chromatorgraphy-mass spectrometry monitoring of^{15}\\text{N}-\\text{Glu}$,^{15}\\text{N}-\\text{Gln}$, and^{15}\\text{N}-\\text{Pro}$in the presence of methionine sulfoximine and amino oxyacetic acid, inhibitors of Gln synthetase and transaminases, respectively. Along with upregulation of α-GDH by NaCl, isocitrate dehydrogenase genes, which provide 2-oxoglutarate, are also induced. Treatment with menadione also elicits a severalfold increase in ROS and immunoreactive α-polypeptide and GDH activity. This suggests that ROS participate in the signaling pathway for GDH expression and protease activation, which contribute to intracellular hyperammonia. Ammonium ions also mimic the effects of salinity in induction of gdh-NAD;A1 expression. These results, confirmed in tobacco and grape (Vitis vinifera cv Sultanina) tissues, support the hypothesis that the salinity-generated ROS signal induces α-GDH subunit expression, and the anionic iso-GDHs assimilate ammonia, acting as antistress enzymes in ammonia detoxification and production of Glu for Pro synthesis.