scholarly journals Reaching and grasping with the tongue: Shared motor planning between hand actions and articulatory gestures

2018 ◽  
Vol 71 (10) ◽  
pp. 2129-2141 ◽  
Author(s):  
Lari Vainio ◽  
Kaisa Tiippana ◽  
Mikko Tiainen ◽  
Aleksi Rantala ◽  
Martti Vainio
Keyword(s):  
Hand Movement ◽  
Precision Grip ◽  
Motor Planning ◽  
Action Planning ◽  
Hand Movements ◽  
Vowel Production ◽  
Power Grip ◽  
Production Processes ◽  
Manual Responses ◽  
Planning Processes

Research has shown connections between articulatory mouth actions and manual actions. This study investigates whether forward–backward hand movements could be associated with vowel production processes that programme tongue fronting/backing, lip rounding/spreading (Experiment 1), and/or consonant production processes that programme tongue tip and tongue dorsum actions (Experiment 2). The participants had to perform either forward or backward hand movement and simultaneously pronounce different vowels or consonants. The results revealed a response benefit, measured in vocal and manual reaction times, when the responses consisted of front vowels and forward hand movements. Conversely, back vowels were associated with backward hand movements. Articulation of rounded versus unrounded vowels or coronal versus dorsal consonants did not produce the effect. In contrast, when the manual responses of forward–backward hand movements were replaced by precision and power grip responses, the coronal consonants [t] and [r] were associated with the precision grip, whereas the dorsal consonant [k] was associated with the power grip. We propose that the movements of the tongue body, operating mainly for vowel production, share the directional action planning processes with the hand movements. Conversely, the tongue articulators related to tongue tip and dorsum movements, operating mainly for consonant production, share the action planning processes with the precision and power grip, respectively.

Context-dependent relationship in high-resolution micro-ECoG studies during finger movements

2020 ◽  
Vol 132 (5) ◽  
pp. 1358-1366
Author(s):  
Chao-Hung Kuo ◽  
Timothy M. Blakely ◽  
Jeremiah D. Wander ◽  
Devapratim Sarma ◽  
Jing Wu ◽  
...  
Keyword(s):  
High Resolution ◽  
Sensorimotor Cortex ◽  
Index Finger ◽  
Hand Movement ◽  
Cortical Activation ◽  
Hand Movements ◽  
Finger Movements ◽  
Thumb Movement ◽  
Neurosurgical Patients ◽  
The Relationship

OBJECTIVEThe activation of the sensorimotor cortex as measured by electrocorticographic (ECoG) signals has been correlated with contralateral hand movements in humans, as precisely as the level of individual digits. However, the relationship between individual and multiple synergistic finger movements and the neural signal as detected by ECoG has not been fully explored. The authors used intraoperative high-resolution micro-ECoG (µECoG) on the sensorimotor cortex to link neural signals to finger movements across several context-specific motor tasks.METHODSThree neurosurgical patients with cortical lesions over eloquent regions participated. During awake craniotomy, a sensorimotor cortex area of hand movement was localized by high-frequency responses measured by an 8 × 8 µECoG grid of 3-mm interelectrode spacing. Patients performed a flexion movement of the thumb or index finger, or a pinch movement of both, based on a visual cue. High-gamma (HG; 70–230 Hz) filtered µECoG was used to identify dominant electrodes associated with thumb and index movement. Hand movements were recorded by a dataglove simultaneously with µECoG recording.RESULTSIn all 3 patients, the electrodes controlling thumb and index finger movements were identifiable approximately 3–6-mm apart by the HG-filtered µECoG signal. For HG power of cortical activation measured with µECoG, the thumb and index signals in the pinch movement were similar to those observed during thumb-only and index-only movement, respectively (all p > 0.05). Index finger movements, measured by the dataglove joint angles, were similar in both the index-only and pinch movements (p > 0.05). However, despite similar activation across the conditions, markedly decreased thumb movement was observed in pinch relative to independent thumb-only movement (all p < 0.05).CONCLUSIONSHG-filtered µECoG signals effectively identify dominant regions associated with thumb and index finger movement. For pinch, the µECoG signal comprises a combination of the signals from individual thumb and index movements. However, while the relationship between the index finger joint angle and HG-filtered signal remains consistent between conditions, there is not a fixed relationship for thumb movement. Although the HG-filtered µECoG signal is similar in both thumb-only and pinch conditions, the actual thumb movement is markedly smaller in the pinch condition than in the thumb-only condition. This implies a nonlinear relationship between the cortical signal and the motor output for some, but importantly not all, movement types. This analysis provides insight into the tuning of the motor cortex toward specific types of motor behaviors.

scholarly journals Spectrum of power laws for curved hand movements

2015 ◽  
Vol 112 (29) ◽  
pp. E3950-E3958 ◽  
Author(s):  
Dongsung Huh ◽  
Terrence J. Sejnowski
Keyword(s):  
Optimal Control ◽  
Motor Planning ◽  
Power Laws ◽  
Angular Frequency ◽  
Control Model ◽  
Hand Movements ◽  
Local Curvature ◽  
Scale Invariant ◽  
The Past ◽  
Invariant Features

In a planar free-hand drawing of an ellipse, the speed of movement is proportional to the −1/3 power of the local curvature, which is widely thought to hold for general curved shapes. We investigated this phenomenon for general curved hand movements by analyzing an optimal control model that maximizes a smoothness cost and exhibits the −1/3 power for ellipses. For the analysis, we introduced a new representation for curved movements based on a moving reference frame and a dimensionless angle coordinate that revealed scale-invariant features of curved movements. The analysis confirmed the power law for drawing ellipses but also predicted a spectrum of power laws with exponents ranging between 0 and −2/3 for simple movements that can be characterized by a single angular frequency. Moreover, it predicted mixtures of power laws for more complex, multifrequency movements that were confirmed with human drawing experiments. The speed profiles of arbitrary doodling movements that exhibit broadband curvature profiles were accurately predicted as well. These findings have implications for motor planning and predict that movements only depend on one radian of angle coordinate in the past and only need to be planned one radian ahead.

Hand Movements and Nondominant Fluency in Bilinguals

1979 ◽  
Vol 48 (1) ◽  
pp. 207-214 ◽  
Author(s):  
Luis R. Marcos
Keyword(s):  
Cognitive Processes ◽  
Motor Behavior ◽  
Hand Movement ◽  
Movement Behavior ◽  
Hand Movements ◽  
Language Fluency ◽  
Movement Activity

16 subordinate bilingual subjects produced 5-min. monologues in their nondominant languages, i.e., English or Spanish. Hand-movement activity manifested during the videotape monologues was scored and related to measures of fluency in the nondominant language. The hand-movement behavior categorized as Groping Movement was significantly related to all of the nondominant-language fluency measures. These correlations support the assumption that Groping Movement may have a function in the process of verbal encoding. The results are discussed in terms of the possibility of monitoring central cognitive processes through the study of “visible” motor behavior.

scholarly journals Eye movements do not play an important role in the adaptation of hand tracking to a visuomotor rotation

2019 ◽  
Vol 121 (5) ◽  
pp. 1967-1976 ◽  
Author(s):  
Niels Gouirand ◽  
James Mathew ◽  
Eli Brenner ◽  
Frederic R. Danion
Keyword(s):  
Eye Movements ◽  
Time Course ◽  
Motor Behavior ◽  
Hand Movement ◽  
Visuomotor Adaptation ◽  
Online Control ◽  
Hand Movements ◽  
Hand Tracking ◽  
Gaze Fixation ◽  
The Gaze

Adapting hand movements to changes in our body or the environment is essential for skilled motor behavior. Although eye movements are known to assist hand movement control, how eye movements might contribute to the adaptation of hand movements remains largely unexplored. To determine to what extent eye movements contribute to visuomotor adaptation of hand tracking, participants were asked to track a visual target that followed an unpredictable trajectory with a cursor using a joystick. During blocks of trials, participants were either allowed to look wherever they liked or required to fixate a cross at the center of the screen. Eye movements were tracked to ensure gaze fixation as well as to examine free gaze behavior. The cursor initially responded normally to the joystick, but after several trials, the direction in which it responded was rotated by 90°. Although fixating the eyes had a detrimental influence on hand tracking performance, participants exhibited a rather similar time course of adaptation to rotated visual feedback in the gaze-fixed and gaze-free conditions. More importantly, there was extensive transfer of adaptation between the gaze-fixed and gaze-free conditions. We conclude that although eye movements are relevant for the online control of hand tracking, they do not play an important role in the visuomotor adaptation of such tracking. These results suggest that participants do not adapt by changing the mapping between eye and hand movements, but rather by changing the mapping between hand movements and the cursor’s motion independently of eye movements. NEW & NOTEWORTHY Eye movements assist hand movements in everyday activities, but their contribution to visuomotor adaptation remains largely unknown. We compared adaptation of hand tracking under free gaze and fixed gaze. Although our results confirm that following the target with the eyes increases the accuracy of hand movements, they unexpectedly demonstrate that gaze fixation does not hinder adaptation. These results suggest that eye movements have distinct contributions for online control and visuomotor adaptation of hand movements.

Hand Movement Training in Braille Reading

1981 ◽  
Vol 75 (8) ◽  
pp. 327-331 ◽  
Author(s):  
Diane P. Wormsley
Keyword(s):  
Character Recognition ◽  
Hand Movement ◽  
Movement Pattern ◽  
Hand Movements ◽  
Dramatic Decrease ◽  
Movement Training ◽  
Perceptual Ability ◽  
Tracking Movements

Twenty-one children ages 6 though 13 were taught to use their hands independently when reading braille to determine how this pattern of hand movements affected reading variables, excluding character recognition. Although all the children learned this pattern of hand movements during the 20 days scheduled for training, only nine children exhibited a dramatic decrease in inefficient tracking movements such as pauses and scrubbing motions. Because these children were younger and more intelligent than the others, read braille more slowly, and had received less training in braille at school, the results strongly suggested that skill in tracking and use of an efficient hand movement pattern is closely tied to perceptual ability. Thus when teaching children to read braille, the motor aspects of the task should be combined with the perceptual aspects from the beginning.

scholarly journals Distinct neuronal organizations of the caudal cingulate motor area and supplementary motor area in monkeys for ipsilateral and contralateral hand movements

2015 ◽  
Vol 113 (7) ◽  
pp. 2845-2858 ◽  
Author(s):  
Yoshihisa Nakayama ◽  
Osamu Yokoyama ◽  
Eiji Hoshi
Keyword(s):  
Neuronal Activity ◽  
Supplementary Motor Area ◽  
Functional Organization ◽  
Hand Movement ◽  
Motor Area ◽  
Hand Movements ◽  
Button Press ◽  
Cingulate Motor Area ◽  
Contralateral Hand ◽  
Hand Preferences

The caudal cingulate motor area (CMAc) and the supplementary motor area (SMA) play important roles in movement execution. The present study aimed to characterize the functional organization of these regions during movement by investigating laterality representations in the CMAc and SMA of monkeys via an examination of neuronal activity during a button press movement with either the right or left hand. Three types of movement-related neuronal activity were observed: 1) with only the contralateral hand, 2) with only the ipsilateral hand, and 3) with either hand. Neurons in the CMAc represented contralateral and ipsilateral hand movements to the same degree, whereas neuronal representations in the SMA were biased toward contralateral hand movement. Furthermore, recording neuronal activities using a linear-array multicontact electrode with 24 contacts spaced 150 μm apart allowed us to analyze the spatial distribution of neurons exhibiting particular hand preferences at the submillimeter scale. The CMAc and SMA displayed distinct microarchitectural organizations. The contralateral, ipsilateral, and bilateral CMAc neurons were distributed homogeneously, whereas SMA neurons exhibiting identical hand preferences tended to cluster. These findings indicate that the CMAc, which is functionally organized in a less structured manner than the SMA is, controls contralateral and ipsilateral hand movements in a counterbalanced fashion, whereas the SMA, which is more structured, preferentially controls contralateral hand movements.

The coactivation of antagonist muscles

1981 ◽  
Vol 59 (7) ◽  
pp. 733-747 ◽  
Author(s):  
Allan M. Smith
Keyword(s):  
Purkinje Cells ◽  
Cerebellar Cortex ◽  
Precision Grip ◽  
Reciprocal Inhibition ◽  
Inhibitory Neurons ◽  
Voluntary Movements ◽  
Renshaw Cells ◽  
Power Grip ◽  
Antagonist Muscles ◽  
Antagonist Coactivation

Since Sherrington's convincing demonstration of the reciprocal innervation of opposing muscles, it has generally been thought that antagonist muscles are inactive during most voluntary movements. However, more recent evidence suggests that excitation of Renshaw cells may facilitate antagonist coactivation whereas excitation of Ia inhibitory neurons can induce reciprocal inhibition. A body of evidence has accumulated to indicate some of the circumstances which particularly favour the co-contraction of antagonist muscles. Isometric prehension, either in the precision grip or the power grip, can be shown to be one of the most important examples of antagonist coactivation. Studies of the discharge of single Purkinje cells of the intermediate cerebellar cortex in awake monkeys during performance of a maintained grip revealed that the majority of these neurons are deactivated during antagonist co-contraction. In contrast, other, unidentified neurons of the cerebellar cortex were as a group activated during grasping. It is suggested that the Purkinje cells act to inhibit antagonist muscles during reciprocal inhibition but are themselves inhibited during antagonist coactivation. These results support a suggestion made by Tilney and Pike in 1925 that the cerebellum plays an important role in switching between the coactivation and reciprocal inhibition of antagonist muscles.

The Role of Hand Movement in Spatial Serial Order Memory

2020 ◽  
Vol 33 (3) ◽  
pp. 313-335
Author(s):  
Yangke Zhao ◽  
Chuansheng Chen ◽  
Xiuying Qian
Keyword(s):  
Hand Movement ◽  
Serial Order ◽  
Hand Movements ◽  
Facilitation Effect ◽  
Serial Memory ◽  
Backward Recall ◽  
Passive Viewing ◽  
Memory Experiment ◽  
Serial Order Memory

Abstract Research on serial order memory has traditionally used tasks where participants passively view the items. A few studies that included hand movement showed that such movement interfered with serial order memory. In the present study of three experiments, we investigated whether and how hand movements improved spatial serial order memory. Experiment 1 showed that manual tracing (i.e., hand movements that traced the presentation of stimuli on the modified eCorsi block tapping task) improved the performance of backward recall as compared to no manual tracing (the control condition). Experiment 2 showed that the facilitation effect resulted from voluntary hand movements and could not be achieved via passive viewing of another person’s manual tracing. Experiment 3 showed that it was the temporal, not the spatial, signal within manual tracing that facilitated spatial serial memory.

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