Limb immobilization and nonuse are well-known causes of corticomotor depression. While physical training can drive the recovery from nonuse-dependent corticomotor effects, it remains unclear if it is ...possible to gain access to motor cortex in alternative ways, such as through motor imagery (MI) or action observation (AO). Transcranial magnetic stimulation was used to study the excitability of the hand left motor cortex in normal subjects immediately before and after 10 h of right arm immobilization. During immobilization, subjects were requested either to imagine to act with their constrained limb or to observe hand actions performed by other individuals. A third group of control subjects watched a nature documentary presented on a computer screen. Hand corticomotor maps and recruitment curves reliably showed that AO, but not MI, prevented the corticomotor depression induced by immobilization. Our results demonstrate the existence of a visuomotor mechanism in humans that links AO and execution which is able to effect cortical plasticity in a beneficial way. This facilitation was not related to the action simulation, because it was not induced by explicit MI.
In the human brain, homologous regions of the primary motor cortices (M1s) are connected through transcallosal fibers. Interhemispheric communication between the two M1s plays a major role in the ...control of unimanual hand movements, and the strength of this connection seems to be dependent on arm activity. For instance, a lesion in the M1 can induce an increase in the excitability of the intact M1 and an abnormal high inhibitory influence onto the damaged M1. This can be attributable to either the disuse of the affected limb or the overuse of the unaffected one. Here, to directly investigate cortical modifications induced by an abnormal asymmetric use of the two limbs, we studied both the excitability of the two M1s and transcallosal interaction between them in healthy subjects whose right hand was immobilized for 10 h. The left "not-immobilized" arm was completely free to move in one group of participants (G1) and limited in the other one (G2). We found that the non-use reduced the excitability of the left M1 and decreased the inhibitory influence onto the right hemisphere in the two groups. However, an increase in the excitability of right M1 and a deeper inhibitory interaction onto the left hemisphere were evident only in G1. Thus, modifications in the right M1 were not directly produced by the non-use but would depend on the overuse of the "not-immobilized" arm. Our findings suggest that the balance between the two M1s is strongly use dependent.
Complex motor tasks are learned through training which results in lasting improvement in sensorimotor performance and accuracy. Learning a motor skill is commonly attained via physical execution. ...However, research has shown that cognitive training, such as motor imagery (MI), effectively facilitates skill learning. Neurophysiological findings suggest that learning-induced plasticity in the human motor cortex, subserving consolidation and retention of motor skills, is stronger after movement execution (ME) than after MI training. Here, we designed an experimental task able to test for the fast and slow learning phases and for retention of motor skills for both MI and ME. We hypothesize that differences between MI and ME training would emerge in terms of reduced consolidation and retention of motor skills. Twenty-four young healthy subjects were divided into two groups, performing MI or ME training. Participants wore sensor-engineered gloves and their sensorimotor performance was assessed over a period of 15 days with 4-days training. We analysed the touch duration (TD), the inter-tapping interval (ITI), movement rate and accuracy. Results showed that (i) during the first phase of acquisition of motor skills, sensorimotor performance improved similarly in MI and ME groups; (ii) during the second learning phase movement rate increased more in ME than MI group and this difference was mainly driven by differences in the duration of TD; (iii) consolidation deficits with MI training reflected in impaired retention of the acquired skills, as TD and ITI were larger and movement rate was lower in the MI group with respect to the ME, till to 10 days after the last training session. Explicit component of motor learning, accuracy, was maintained in retention phase in both groups. Following our hypothesis, our findings show that MI training is as effective as ME within the first learning phase, but consolidation and retention of motor skills are less effective following MI training. This study highlights MI limitations and suggests option to enhance MI, as by providing an external sensory feedback.
•Motor imagery (MI) is as effective as actual training within the 1st learning phase.•Learning processes are less efficient in the 2nd learning phase with MI training.•Consolidation deficits reflect in impaired retention of motor skills with MI training.
Key points
The combination of action observation (AO) and a peripheral nerve stimulation has been shown to induce plasticity in the primary motor cortex (M1). However, using peripheral nerve ...stimulation little is known about the specificity of the sensory inputs.
The current study, using muscle tendon vibration to stimulate muscle spindles and transcranial magnetic stimulation to assess M1 excitability, investigated whether a proprioceptive stimulation leading to a kinaesthetic illusion of movement (KI) was able to evoke M1 plasticity when combined with AO.
M1 excitability increased immediately and up to 60 min after AO‐KI stimulation as a function of the vividness of the perceived illusion, and only when the movement directions of AO and KI were congruent.
Tactile stimulation coupled with AO and KI alone were not sufficient to induce M1 plasticity.
This methodology might be proposed to subjects during a period of immobilization to promote M1 activity without requiring any voluntary movement.
Physical practice is crucial to evoke cortical plasticity, but motor cognition techniques, such as action observation (AO), have shown their potentiality in promoting it when associated with peripheral afferent inputs, without the need of performing a movement. Here we investigated whether the combination of AO and a proprioceptive stimulation, able to evoke a kinaesthetic illusion of movement (KI), induced plasticity in the primary motor cortex (M1). In the main experiment, the role of congruency between the observed action and the illusory movement was explored together with the importance of the specificity of the sensory input modality (proprioceptive vs. tactile stimulation) to induce plasticity in M1. Further, a control experiment was carried out to assess the role of the mere kinaesthetic illusion on M1 excitability. Results showed that the combination of AO and KI evoked plasticity in M1, with an increase of the excitability immediately and up to 60 min after the conditioning protocol (P always <0.05). Notably, a significant increase in M1 excitability occurred only when the directions of the observed and illusory movements were congruent. Further, a significant positive linear relationship was found between the amount of M1 excitability increase and the vividness of the perceived illusion (P = 0.03). Finally, the tactile stimulation coupled with AO was not sufficient to induce changes in M1 excitability as well as the KI alone. All these findings indicate the importance of combining different sensory input signals to induce plasticity in M1, and that proprioception is the most suitable sensory modality to allow it.
Key points
The combination of action observation (AO) and a peripheral nerve stimulation has been shown to induce plasticity in the primary motor cortex (M1). However, using peripheral nerve stimulation little is known about the specificity of the sensory inputs.
The current study, using muscle tendon vibration to stimulate muscle spindles and transcranial magnetic stimulation to assess M1 excitability, investigated whether a proprioceptive stimulation leading to a kinaesthetic illusion of movement (KI) was able to evoke M1 plasticity when combined with AO.
M1 excitability increased immediately and up to 60 min after AO‐KI stimulation as a function of the vividness of the perceived illusion, and only when the movement directions of AO and KI were congruent.
Tactile stimulation coupled with AO and KI alone were not sufficient to induce M1 plasticity.
This methodology might be proposed to subjects during a period of immobilization to promote M1 activity without requiring any voluntary movement.
Motor learning via physical practice leads to long-term potentiation (LTP)-like plasticity in motor cortex (M1) and temporary occlusion of additional LTP-like plasticity. Motor learning can be ...achieved through simulation of movement, namely motor imagery (MI). When combined with electrical stimulation, MI influenced M1 excitability to a larger extent than MI itself. We explored whether a training based on the combination of MI and peripheral nerve stimulation (ESMI) modulates M1 LTP-like plasticity inducing retention of a new acquired skill. Twelve subjects mentally performed thumb-index movements, with synchronous electrical nerve stimulation, following an acoustic cue, in order to increase movement speed. Two control groups physically performed or imagined the same number of finger movements following the acoustic cue. After each training session, M1 LTP-like plasticity was assessed by using PAS25 (paired associative stimulation) technique. Performance was tested before and after training and 24 hours after training. Results showed that physical practice and ESMI training similarly increased movement speed, prevented the subsequent PAS25-induced LTP-like plasticity, and induced retention of motor skill the following day. Training with MI had significant, but minor effects. These findings suggest that a training combining MI with somatosensory input influences motor performance through M1 plasticity similarly to motor execution.
•Nine-Hole peg test was compared with a new task involving the sensorimotor domain.•Sensorimotor and prefrontal activity during manual dexterity was assessed by fNIRS.•Right BA10 and BA11 are the ...substrate for cognitive planning in manual dexterity.•BA10 activity correlates with increased time to perform the nine-hole peg test.•Cognitive domain should be considered when manual dexterity is investigated.
Manual dexterity is referred to as the skill to perform fine motor movements and it has been assumed to be associated to the cognitive domain, as well as the sensorimotor one. In this work, we investigated with functional near-infrared spectroscopy the cortical activations elicited by the execution of the 9-HPT, i.e., a standard test evaluating manual dexterity in which nine pegs were taken, placed into and then removed from nine holes on a board as quickly as possible. For comparison, we proposed a new active control task mainly involving the sensorimotor domain, in which the pegs must be placed and removed using the same single hole (1-HPT). Behaviorally, we found two distinct groups based on the difference between the execution time of the 9-HPT and the 1-HPT (ΔHPT). Cortical areas belonging to the network controlling reaching and grasping movements were active in both groups; however, participants showing a large ΔHPT presented significantly higher activation in prefrontal cortical areas (right BA10 and BA11) during 9-HPT and 1-HPT performance with respect to the participants with a small ΔHPT, who showed a deactivation in BA10. Unexpectedly, we observed a significant linear relationship between ΔHPT and right BA10 activity. This suggested that participants performing the 9-HPT more slowly than the 1-HPT recruited prefrontal areas implicitly exploiting the cognitive skills of planning, perhaps in search of a motor strategy to solve the test activating attentional and cognitive control processes, but this resulted not efficient and instead increased the time to accomplish a manual dexterity task.
Brainstem dysfunctions are very common in Multiple Sclerosis (MS) and are a critical predictive factor for future disability. Brainstem functionality can be explored with blink reflexes, subcortical ...responses consisting in a blink following a peripheral stimulation. Some reflexes are already employed in clinical practice, such as Trigeminal Blink Reflex (TBR). Here we propose for the first time in MS the exploration of Hand Blink Reflex (HBR), which size is modulated by the proximity of the stimulated hand to the face, reflecting the extension of the peripersonal space. The aim of this work is to test whether Machine Learning (ML) techniques could be used in combination with neurophysiological measurements such as TBR and HBR to improve their clinical information and potentially favour the early detection of brainstem dysfunctionality. HBR and TBR were recorded from a group of People with MS (PwMS) with Relapsing-Remitting form and from a healthy control group. Two AdaBoost classifiers were trained with TBR and HBR features each, for a binary classification task between PwMS and Controls. Both classifiers were able to identify PwMS with an accuracy comparable and even higher than clinicians. Our results indicate that ML techniques could represent a tool for clinicians for investigating brainstem functionality in MS. Also, HBR could be promising when applied in clinical practice, providing additional information about the integrity of brainstem circuits potentially favouring early diagnosis.
The present study was designed to explore the changes in motor performance and motor resonance after multiple sessions of action observation (AO) training. Subjects were exposed to the observation of ...a video showing finger tapping movements executed at 3Hz, a frequency higher than the spontaneous one (2Hz) for four consecutive days. Motor performance and motor resonance were tested before the AO training on the first day, and on the last day. Results showed that multiple sessions of AO training induced a shift of the speed of execution of finger tapping movements toward the observed one and a change in motor resonance. Before the 3Hz-AO training cortical excitability was highest during the observation of the 2Hz video. This motor resonance effect was lost after one single session of 3Hz-AO training whereas after multiple sessions of 3Hz-AO training cortical excitability was highest during the observation of the 3Hz video. Our study shows for the first time that multiple sessions of AO training are able not only to induce performance gains but also to change the way by which the observer's motor system recognizes a certain movement as belonging to the individual motor repertoire. These results may encourage the development of novel rehabilitative protocols based on multiple sessions of action observation aimed to regain a correct movement when its spontaneous speed is modified by pathologies or to modify the innate temporal properties of certain movements.
•M1 excitability resonated with the spontaneous tempo (SMT) of the observed movement.•Multiple sessions of action observation (AO-training) induced SMT changes.•After AO-training M1 excitability resonated with the tempo of the trained motor act.•This work adds new evidence on the neurophysiological basis of AO-training.
In vitro cultured neuronal networks coupled to microelectrode arrays (MEAs) constitute a valuable experimental model for studying changes in the neuronal dynamics at different stages of development. ...After a few days in culture, neurons start to connect each other with functionally active synapses, forming a random network and displaying spontaneous electrophysiological activity. The patterns of collective rhythmic activity change in time spontaneously during in vitro development. Such activity-dependent modifications play a key role in the maturation of the network and reflect changes in the synaptic efficacy, fact widely recognized as a cellular basis of learning, memory and developmental plasticity. Getting advantage from the possibilities offered by the MEAs, the aim of our study is to analyze and characterize the natural changes in dynamics of the electrophysiological activity at different ages of the culture, identifying peculiar steps of the spontaneous evolution of the network. The main finding is that between the second and the third week of culture, the network completely changes its electrophysiological patterns, both in terms of spiking and bursting activity and in terms of cross-correlation between pairs of active channels. Then the maturation process can be characterized by two main phases: modulation and shaping in the synaptic functional connectivity of the network (within the first and second week) and general moderate correlated activity, spread over the entire network, with connections properly formed and stabilized (within the fourth and fifth week).
The investigation of how humans perceive and respond to emotional signals conveyed by the human body has been for a long time secondary compared with the investigation of facial expressions and ...emotional scenes recognition. The aims of this behavioral study were to assess the ability to process emotional body postures and to test whether motor response is mainly driven by the emotional content of the picture or if it is influenced by motor resonance. Emotional body postures and scenes (IAPS) divided into three clusters (fear, happiness, and neutral) were shown to 25 healthy subjects (13 males, mean age ± SD: 22.3 ± 1.8 years) in a three-alternative forced choice task. Subjects were asked to recognize the emotional content of the pictures by pressing one of three keys as fast as possible in order to estimate response times (RTs). The rating of valence and arousal was also performed. We found shorter RTs for fearful body postures as compared with happy and neutral postures. In contrast, no differences across emotional categories were found for the IAPS stimuli. Analysis on valence and arousal and the subsequent item analysis showed an excellent reliability of the two sets of images used in the experiment. Our results show that fearful body postures are rapidly recognized and processed, probably thanks to the automatic activation of a series of central nervous system structures orchestrating the defensive threat reactions, strengthening and supporting previous neurophysiological and behavioral findings in body language processing.
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