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Mapping motor representations with positron emission tomography
Abstract
Brain activity was mapped in normal subjects during passive observation of the movements of an 'alien' hand and while imagining grasping objects with their own hand. None of the tasks required actual movement. Shifting from one mental task to the other greatly changed the pattern of brain activation. During observation of hand movements, activation was mainly found in visual cortical areas, but also in subcortical areas involved in motor behaviour, such as the basal ganglia and the cerebellum. During motor imagery, cortical and subcortical areas related to motor preparation and programming were strongly activated. These data support the notion that motor learning during observation of movements and mental practice involves rehearsal of neural pathways related to cognitive stages of motor control.
... Kavanagh and colleagues (2005) proposed that specific brain regions are activated when experiencing desires or cravings, similar to those activated during sensory imagery within the same sensory category. Indeed, the intention to initiate a movement leads to the activation of motion-related areas, such as the premotor cortex, or the parietal lobe and cerebellum (Decety et al. 1990(Decety et al. , 1994. In the same vein, the desire for music might lead to activation of brain regions associated with music imagery, i.e., the prefrontal cortex, the inferior frontal gyrus, or the superior temporal gyrus (Herholz et al. 2012). ...
... This notion is supported, among others, by research using imaging techniques that show that brain regions involved in action execution are also activated during mental imagery (Hardwick et al. 2018). In fact, the premotor cortex (PMC), supplementary motor areas (Gerardin et al. 2000;Johnson et al. 2002;Kuhtz-Buschbeck et al. 2003;Oostra et al. 2016;Orlandi et al. 2020), parietal regions (Decety et al. 1994;Sirigu et al. 1996;Pelgrims et al. 2009), cerebellum and basal ganglia (Decety et al. 1994;Grealy and Lee 2011;Heremans et al. 2011;Oostra et al. 2016) have been found active in various motor imagery tasks. The PMC and parietal areas would share a functional neural circuitry in the distributed Fronto-Parietal Network (dFPN) (Hétu et al. 2013;Ptak et al. 2017), enabling emulation. ...
... This notion is supported, among others, by research using imaging techniques that show that brain regions involved in action execution are also activated during mental imagery (Hardwick et al. 2018). In fact, the premotor cortex (PMC), supplementary motor areas (Gerardin et al. 2000;Johnson et al. 2002;Kuhtz-Buschbeck et al. 2003;Oostra et al. 2016;Orlandi et al. 2020), parietal regions (Decety et al. 1994;Sirigu et al. 1996;Pelgrims et al. 2009), cerebellum and basal ganglia (Decety et al. 1994;Grealy and Lee 2011;Heremans et al. 2011;Oostra et al. 2016) have been found active in various motor imagery tasks. The PMC and parietal areas would share a functional neural circuitry in the distributed Fronto-Parietal Network (dFPN) (Hétu et al. 2013;Ptak et al. 2017), enabling emulation. ...
The literature has demonstrated the potential for detecting accurate electrical signals that correspond to the will or intention to move, as well as decoding the thoughts of individuals who imagine houses, faces or objects. This investigation examines the presence of precise neural markers of imagined motivational states through the combining of electrophysiological and neuroimaging methods. 20 participants were instructed to vividly imagine the desire to move, listen to music or engage in social activities. Their EEG was recorded from 128 scalp sites and analysed using individual standardized Low-Resolution Brain Electromagnetic Tomographies (LORETAs) in the N400 time window (400–600 ms). The activation of 1056 voxels was examined in relation to the 3 motivational states. The most active dipoles were grouped in eight regions of interest (ROI), including Occipital, Temporal, Fusiform, Premotor, Frontal, OBF/IF, Parietal, and Limbic areas. The statistical analysis revealed that all motivational imaginary states engaged the right hemisphere more than the left hemisphere. Distinct markers were identified for the three motivational states. Specifically, the right temporal area was more relevant for “Social Play”, the orbitofrontal/inferior frontal cortex for listening to music, and the left premotor cortex for the “Movement” desire. This outcome is encouraging in terms of the potential use of neural indicators in the realm of brain-computer interface, for interpreting the thoughts and desires of individuals with locked-in syndrome.
... The study of human brain activity during motor imagery (MI) plays an important role in clinical neurology and neuroscience and for this reason the neuronal representation of MI and motor execution has been studied intensively for years using brain imaging techniques such as functional magnetic resonance [39], EEG [40]- [42] and positron emission tomography [43]. It is well established that adults present 8-12 Hz (i.e. ) and 16-26 Hz (i.e. ) rhythms in the EEG recorded from the scalp over the primary sensorimotor cortex. ...
The evaluation of time and frequency domain measures of coupling and causality relies on the parametric representation of linear multivariate processes. The study of temporal dependencies among time series is based on the identification of a Vector Autoregressive model. This procedure is pursued through the definition of a regression problem solved by means of Ordinary Least Squares (OLS) estimator. However, its accuracy is strongly influenced by the lack of data points and a stable solution is not always guaranteed. To overcome this issue, it is possible to use penalized regression techniques. The aim of this work is to compare the behavior of OLS with different penalized regression methods used for a connectivity analysis in different experimental conditions. Bias, accuracy in the reconstruction of network structure and computational time were used for this purpose. Different penalized regressions were tested by means of simulated data implementing different ground-truth networks under different amounts of data samples available. Then, the approaches were applied to real electroencephalographic signals (EEG) recorded from a healthy volunteer performing a motor imagery task. Penalized regressions outperform OLS in simulation settings when few data samples are available. The application on real EEG data showed how it is possible to use features extracted from brain networks for discriminating between two tasks even in conditions of data paucity. Penalized regression techniques can be used for brain connectivity estimation and can be exploited for the computation of all the connectivity estimators based on linearity assumption overcoming the limitations imposed by the classical OLS.
... However, in the present case an inanimate device was used that only mimicked the spatiotemporal movements of a hand, and did not look or otherwise act human. The results of Meltzoff (1995) dovetail with the finding that there are certain neural systems activated by human actions and not similar movements produced by a mechanical device (Decety et al. 1994;Perani et al. 2001;Castiello et al. 2002), and the demonstration that infants process animate body parts differently from inanimate objects (e.g. Brooks & Meltzoff 2002). ...
Humans, like other primates, are intensely social creatures. One of the main functions of our brains is to enable us to be as skilful in social interactions as we are in our interactions with the physical world. Any differences between human brains and those of our nearest relatives, the great apes, are likely to be linked to our unique achievements in social interaction and communication rather than our motor or perceptual skills. Unique to humans is the ability to mentalise (or mind read), that is to perceive and communicate mental states, such as beliefs and desires. A key problem facing neuroscience is to uncover the biological mechanisms underlying our ability to read other minds and to show how these mechanisms evolved. To solve this problem we need to do experiments in which people (or animals) interact with one another rather than behaving in isolation. Such experiments are now being conducted in increasing numbers and many of the leading exponents of such experiments have contributed to this volume. ‘The Neuroscience of Social Interactions’ will be an important step in uncovering the biological mechanisms underlying social interactions - undoubtedly one of the major programmes for neuroscience in the twenty-first century.
... Indeed, all these findings align with those studies examining cerebral activation related to observed or imagined prehension movements. These studies have consistently reported activation in areas such as the intraparietal sulcus, as well as the inferior and superior parietal lobules (Binkofski et al., 1998;Buccino et al., 2001;Decety et al., 1994;Grafton et al., 1996;Grèzes et al., 2003;Grèzes and Decety, 2002;Vingerhoets et al., 2009Vingerhoets et al., , 2010. Additional evidence from the SPL comes from monkey studies that show the involvement of this part of the brain in the encoding of object affordance. ...
... Motor imagery (MI) is a mental simulation or rehearsal of a movement without any motor output [1]. Previous research suggests that during MI, neural activity is similar to that during actual movements [2,3], and studies using transcranial magnetic stimulation (TMS) have shown that during MI, corticospinal excitability in the muscles involved in that movement is enhanced (e.g., Kasai et al. 1997, Fadiga et al., 1999 [4,5]. ...
... Indeed, the intention to initiate a movement leads to the activation of motion-related areas, such as the premotor cortex, or the parietal lobe and cerebellum (Decety et al., 1990(Decety et al., , 1994. In the same vein, the desire for music might lead to activation of brain regions associated with music imagery, i.e., the prefrontal cortex, the inferior frontal gyrus, or the superior temporal gyrus (Herholz et al., 2012). ...
The literature has demonstrated the potential for detecting accurate electrical signals that correspond to the will or intention to move, as well as decoding the thoughts of individuals who imagine houses, faces or objects. This investigation examines the presence of precise neural markers of imagined motivational states through the combining of electrophysiological and neuroimaging methods. 20 participants were instructed to vividly imagine the desire to move, listen to music or engage in social activities. Their EEG was recorded from 128 scalp sites and analysed using individual standardized Low-Resolution Brain Electromagnetic Tomographies (LORETAs) in the N400 time window (400–600 ms). The activation of 1056 voxels was examined in relation to the 3 motivational states. The most active dipoles were grouped in eight regions of interest (ROI), including Occipital, Temporal, Fusiform, Premotor, Frontal, OBF/IF, Parietal, and Limbic areas. The statistical analysis revealed that all motivational imaginary states engaged the right hemisphere more than the left hemisphere. Distinct markers were identified for the three motivational states. Specifically, the right temporal area was more relevant for "Social Play", the orbitofrontal/inferior frontal cortex for listening to music, and the left premotor cortex for the "Movement" desire. This outcome is encouraging in terms of the potential use of neural indicators in the realm of brain-computer interface, for interpreting the thoughts and desires of individuals with locked-in syndrome.
... The ability to mentally recall a motor act without any overt movement is called motor imagery (MI) (Kosslyn et al. 1995). The movement simulation that occurs on a cognitive level can be seen as a way in which we express the mental representation of the body in action (Decety et al. 1994;Decety and Jeannerod 1996;Gentilucci et al. 1998;Parsons 1987;Sekiyama 1982). MI tasks can be used as a proxy for the exploration of the mental representations of the body (e.g. ...
The mental representation of the body in action can be explored using motor imagery (MI) tasks. MI tasks can be allocated along a continuum going from more implicit to more explicit tasks, where the discriminant is the degree of action monitoring required to solve the tasks (which is the awareness of using the mental representation of our own body to monitor our motor imagery). Tasks based on laterality judgments, such as the Hand Laterality Task (HLT) and the Foot Laterality Task (FLT), provide an example of more implicit tasks (i.e., less action monitoring is required). While, an example of a more explicit task is the Mental Motor Chronometry task (MMC) for hands and feet, where individuals are asked to perform or imagine performing movements with their limbs (i.e., more action monitoring is required). In our study, we directly compared hands and feet at all these tasks for the first time, as these body districts have different physical features as well as functions. Fifty-five participants were asked to complete an online version of the HLT and FLT (more implicit measure), and an online version of the MMC task for hands and feet (more explicit measure). The mental representation of hands and feet in action differed only when the degree of action monitoring decreased (HLT ≠ FLT); we observed the presence of biomechanical constraints only for hands. Differently, when the degree of action monitoring increased hands and feet did not show any difference (MMC hands = MMC feet). Our results show the presence of a difference in the mental representation of hands and feet in action that specifically depends on the degree of action monitoring.
Background: Motor imagery (MI) involves visualizing a task rather than physically executing it, and its effectiveness may depend on duration. The optimal dose of MI for enhancing motor performance has not yet been determined.
Objectives: To compare the effects of different MI doses and physical practices on motor performance enhancement.
Methods: A pilot study was conducted with 27 healthy participants of both sexes aged 18-35 from Concordia University Wisconsin. The participants were divided into three groups: a control group with no MI, a low-dose MI group (6 minutes of MI practice per session), and a high-dose MI group (12 minutes of MI practice per session). Over three weeks, the participants completed nine sessions of a timed mirror tracing task, and their performance was measured by completion time and error count.
Results: The study involved 23 participants, with 8 in the control group, 9 in the low-dose group, and 6 in the high-dose group. Initial assessments revealed no significant differences in age or baseline performance among the groups. The control group experienced a notable decrease in task completion time in sessions three and six compared to the first session. The low-dose MI group demonstrated substantial improvement in all sessions, with noticeable differences observed between sessions two and three, as well as between sessions three and four. Conversely, the high-dose MI group did not show any significant improvement. There were no significant differences in performance between the groups across sessions.
Conclusion: Both MI and physical practice were found to enhance motor performance in novice tasks, with low-dose MI proving to be more effective than no MI. Interestingly, high-dose MI did not consistently lead to better performance. These findings highlight the importance of conducting additional research to determine the optimal MI dosage for different tasks and populations.
Trial Registration: ClinicalTrials.gov NCT06299345. Retrospectively registered on March 2024.
Afazi Tanımlama ve Sınıflandırma Özgül AKIN ŞENKAL Afazi ve Diğer İletişim Bozuklukları Tuğçe Gül ÇAĞLAR Afazide Semptomlar Şule MIDIK, Sebahattin TUNCER Afazide Nörolojik ve Nöropsikolojik Ek Bulgular Şule ÇEKİÇ Hata Analizi Şule MIDIK Afazide Sendrom Yaklaşımı ve Kognitif Yaklaşımlar Bünyamin ÇILDIR Dil ve Beyin Berna Deniz AYDIN, Tuğçe Gül ÇAĞLAR Afazi Sebepleri ve Prognoz Tuğçe Gül ÇAĞLAR, Şuayp KÜÇÜK, Fatma Men KILINÇ, Serpil DEMİR Afazide Linguistik Temeller Berkay ARSLAN İşitsel İşlemleme Basamakları Meral Didem TÜRKYILMAZ, Tuğçe Gül ÇAĞLAR, Berna Deniz AYDIN Normal ve Afazik İşlemleme Şuayp KÜÇÜK, Banu ERGÜNAL KÖSE Afazide Üretim Problemleri Tuğba EMEKCİ, Özgül AKIN ŞENKAL Afazide Davranışsal Değerlendirme Hale HANÇER, Emine DEMİREL AKSOY Afazide Teknoloji Kullanımı Hale HANÇER Afazide Anlaşılırlık ve Bilişsel Fonksiyonların Değerlendirilmesi Müge Müzeyyen ÇİYİLTEPE İnme ve Yutma Müge Müzeyyen ÇİYİLTEPE Afazi ve Ergoterapi Tuğba EMEKCİ Afazi için Terapi Yaklaşımları Müge Müzeyyen ÇİYİLTEPE
1. This study addressed potential neural mechanisms of the strength increase that occur before muscle hypertrophy. In particular we examined whether such strength increases may result from training-induced changes in voluntary motor programs. We compared the maximal voluntary force production after a training program of repetitive maximal isometric muscle contractions with force output after a training program that did not involve repetitive activation of muscle; that is, after mental training. 2. Subjects trained their left hypothenar muscles for 4 wk, five sessions per week. One group produced repeated maximal isometric contractions of the abductor muscles of the fifth digit's metacarpophalangeal joint. A second group imagined producing these same, effortful isometric contractions. A third group did not train their fifth digit. Maximal abduction force, flexion/extension force and electrically evoked twitch force (abduction) of the fifth digit were measured along with maximal integrated electromyograms (EMG) of the hypothenar muscles from both hands before and after training. 3. Average abduction force of the left fifth digit increased 22% for the Imagining group and 30% for the Contraction group. The mean increase for the Control group was 3.7%. 4. The maximal abduction force of the right (untrained) fifth digit increased significantly in both the Imagining and Contraction groups after training (10 and 14%, respectively), but not in the Control group (2.3%). These results are consistent with previous studies of training effects on contralateral limbs. 5. The abduction twitch force evoked by supramaximal electrical stimulations of the ulnar nerve was unchanged in all three groups after training, consistent with an absence of muscle hypertrophy. The maximal force of the left great toe extensors for individual subjects remained unchanged after training, which argues against strength increases due to general increases in effort level. 6. Increases in abduction and flexion forces of the fifth digit were poorly correlated in subjects of both training groups. The fifth finger abduction force and the hypothenar integrated EMG increases were not well correlated in these subjects either. Together these results indicate that training-induced changes of synergist and antagonist muscle activation patterns may have contributed to force increases in some of the subjects. 7. Strength increases can be achieved without repeated muscle activation. These force gains appear to result from practice effects on central motor programming/planning. The results of these experiments add to existing evidence for the neural origin of strength increases that occur before muscle hypertrophy.
We used positron emission tomography to contrast changes in cerebral blood flow associated with willed and routine acts. In the six tasks used, volunteers had to make a series of responses to a sequence of stimuli. For the routine acts, each response was completely specified by the stimulus. For the willed acts, the response was open-ended and therefore volunteers had to make a deliberate choice. Willed acts in the two response modalities studied (speaking a word, or lifting a finger) were associated with increased blood flow in the dorsolateral prefrontal cortex (Brodmann area 46). Willed acts were also associated with decreases in blood flow, but the location of these decreases was modality dependent.
1. Single-cell activity was recorded from three different motor areas in the cerebral cortex: the primary motor cortex (MI), supplementary motor area (SMA), and premotor cortex (PM). 2. Three monkeys (Macaca fuscata) were trained to perform a sequential motor task in two different conditions. In one condition (visually triggered task, VT), they reached to and touched three pads placed in a front panel by following lights illuminated individually from behind the pads. In the other condition (internally guided task, IT), they had to remember a predetermined sequence and press the three pads without visual guidance. In a transitional phase between the two conditions, the animals learned to memorize the correct sequence. Auditory instruction signals (tones of different frequencies) told the animal which mode it was in. After the instruction signals, the animals waited for a visual signal that triggered the first movement. 3. Neuronal activity was analyzed during three defined periods: delay period, premovement period, and movement period. Statistical comparisons were made to detect differences between the two behavioral modes with respect to the activity in each period. 4. Most, if not all, of MI neurons exhibited similar activity during the delay, premovement, and movement periods, regardless of whether the sequential motor task was visually guided or internally determined. 5. More than one-half of the SMA neurons were preferentially or exclusively active in relation to IT during both the premovement (55%) and movement (65%) periods. In contrast, PM neurons were more active (55% and 64% during the premovement and movement periods) in VT. 6. During the instructed-delay period, a majority of SMA neurons exhibited preferential or exclusive relation to IT whereas the activity in PM neurons was observed equally in different modes. 7. Two types of neurons exhibiting properties of special interest were observed. Sequence-specific neurons (active in a particular sequence only) were more common in SMA, whereas transition-specific neurons (active only at the transitional phase) were more common in PM. 8. Although a strict functional dichotomy is not acceptable, these observations support a hypothesis that the SMA is more related to IT, whereas PM is more involved in VT. 9. Some indications pointing to a functional subdivision of PM are obtained.
Measurement of cardiac and respiratory activity during mental simulation of locomotion at increasing speed revealed a covariation of heart rate and pulmonary ventilation with the degree of imagined effort. The degree of vegetative activation of a subject mentally running at 12 km/h was comparable to that of a subject actually walking at 5 km/h. This effect cannot be explained by an increase in peripheral (e.g. muscular) metabolic demands. Indeed, oxygen uptake decreased during motor imagery. This finding is suggestive of a commonality of neural structures responsible for mental imagery of movement and those responsible for programming actual movement. In addition, it provides an quantifiable way of testing mental imagery in relation to movement by using easily accessible biological markers.
Statistical parametric maps (SPMs) are potentially powerful ways of localizing differences in regional cerebral activity. This potential is limited by uncertainties in assessing the significance of these maps. In this report, we describe an approach that may partially resolve this issue. A distinction is made between using SPMs as images of change significance and using them to identify foci of significant change. In the first case, the SPM can be reported nonselectively as a single mathematical object with its omnibus significance. Alternatively, the SPM constitutes a large number of repeated measures over the brain. To reject the null hypothesis, that no change has occurred at a specific location, a threshold adjustment must be made that accounts for the large number of comparisons made. This adjustment is shown to depend on the SPM's smoothness. Smoothness can be determined empirically and be used to calculate a threshold required to identify significant foci. The approach models the SPM as a stationary stochastic process. The theory and applications are illustrated using uniform phantom images and data from a verbal fluency activation study of four normal subjects.
Regional cerebral blood flow, an index of local neuronal activity, was measured using positron emission tomography (PET) during the performance of the classic Stroop color/word task in eight healthy right-handed subjects. In the first condition of this paradigm, subjects name the color of the words presented on a video monitor. All the words are the color names congruent to the color presented (e.g., the noun "red" displayed in red color). In the second condition, subjects also name the color of the words presented on the monitor. However, during these trials all words are color names incongruent to the color presented (e.g., the noun "red" displayed in green color). The difference in brain activity between these two conditions (i.e., incongruent minus congruent) could reveal brain systems involved in the attentionally mediated resolution of the conflict between the habitual response of reading words vs. the task demands of naming the color of the words--i.e., the Stroop interference effect. The most robust responses occurred in the anterior cingulate cortex. Other responses noted were in the left premotor cortex, left postcentral cortex, left putamen, supplementary motor area, right superior temporal gyrus, and bilateral peristriate cortices. These data provide support for the role of the anterior cingulate cortex in attentional processing through the selection and recruitment of processing centers appropriate for task execution. Furthermore, the extensive distributed network of activated regions suggests that the Stroop interference effect cannot be explained simply in terms of stimulus encoding or response interference.
A study of some of the basic physical performance characteristics of an advanced commercial positron-emission tomograph (PET) is reported. It consists of eight rings of BGO (bismuth germanate) detectors (512/ring) with removable interring septa and retractable transmission ring sources for each ring. The (transaxial) detector width is 5.6 mm, and the lower limit of the spatial resolution in the reconstructed image is about 5 mm. Investigations were carried out of count-rate linearity, image count recovery with object size, the effect of attenuation correction on quantitation, and scatter fraction.
This paper concerns how motor actions are neurally represented and coded. Action planning and motor preparation can be studied using a specific type of representational activity, motor imagery. A close functional equivalence between motor imagery and motor preparation is suggested by the positive effects of imagining movements on motor learning, the similarity between the neural structures involved, and the similar physiological correlates observed in both imaging and preparing. The content of motor representations can be inferred from motor images at a macroscopic level, based on global aspects of the action (the duration and amount of effort involved) and the motor rules and constraints which predict the spatial path and kinematics of movements. A more microscopic neural account calls for a representation of object-oriented action. Object attributes are processed in different neural pathways depending on the kind of task the subject is performing. During object-oriented action, a pragmatic representation is activated in which object affordances are transformed into specific motor schemas (independently of other tasks such as object recognition). Animal as well as human clinical data implicate the posterior parietal and premotor cortical areas in schema instantiation. A mechanism is proposed that is able to encode the desired goal of the action and is applicable to different levels of representational organization.
A computer algorithm for the three-dimensional (3D) alignment of PET images is described. To align two images, the algorithm calculates the ratio of one image to the other on a voxel-by-voxel basis and then iteratively moves the images relative to one another to minimize the variance of this ratio across voxels. Since the method relies on anatomic information in the images rather than on external fiducial markers, it can be applied retrospectively. Validation studies using a 3D brain phantom show that the algorithm aligns images acquired at a wide variety of positions with maximum positional errors that are usually less than the width of a voxel (1.745 mm). Simulated cortical activation sites do not interfere with alignment. Global errors in quantitation from realignment are less than 2%. Regional errors due to partial volume effects are largest when the gantry is rotated by large angles or when the bed is translated axially by one-half the interplane distance. To minimize such partial volume effects, the algorithm can be used prospectively, during acquisition, to reposition the scanner gantry and bed to match an earlier study. Computation requires 3-6 min on a Sun SPARCstation 2.