Positive Technology Journal

Inducing a virtual hand ownership illusion through a brain-computer interface.

Neuroreport. 2009 Apr 22;20(6):589-594

Authors: Perez-Marcos D, Slater M, Sanchez-Vives MV

The apparently stable brain representation of our bodies is easily challenged. We have recently shown that the illusion of ownership of a three-dimensional virtual hand can be evoked through synchronous tactile stimulation of a person's hidden real hand and that of the virtual hand. This reproduces the well-known rubber-hand illusion, but in virtual reality. Here we show that some aspects of the illusion can also occur through motor imagery used to control movements of a virtual hand. When movements of the virtual hand followed motor imagery, the illusion of ownership of the virtual hand was evoked and muscle activity measured through electromyogram correlated with movements of the virtual arm. Using virtual bodies has a great potential in the fields of physical and neural rehabilitation, making the understanding of ownership of a virtual body highly relevant.

Driving dreams: cortical activations during imagined passive and active whole body movement.

Ann N Y Acad Sci. 2009 May;1164:372-5

Authors: Flanagin VL, Wutte M, Glasauer S, Jahn K

It is unclear how subjects perceive and process self-motion cues in virtual reality environments. Movement could be perceived as passive, akin to riding in a car, or active, such as walking down the street. These two very different types of self-motion were studied here using motor imagery in fMRI. In addition, the relative importance of visual and proprioceptive training cues was examined. Stronger activations were found during proprioceptive motor imagery compared with visual motor imagery, suggesting that proprioceptive signals are important for successful imagined movement. No significant activations were found during active movement with proprioceptive training. Passive locomotion, however, was correlated with activity in an occipital-parietal and parahippocampal cortical network, which are the same regions found during navigation with virtual reality stimuli.

Neurofeedback-based motor imagery training for brain-computer interface (BCI).

J Neurosci Methods. 2009 Apr 30;179(1):150-6

Authors: Hwang HJ, Kwon K, Im CH

In the present study, we propose a neurofeedback-based motor imagery training system for EEG-based brain-computer interface (BCI). The proposed system can help individuals get the feel of motor imagery by presenting them with real-time brain activation maps on their cortex. Ten healthy participants took part in our experiment, half of whom were trained by the suggested training system and the others did not use any training. All participants in the trained group succeeded in performing motor imagery after a series of trials to activate their motor cortex without any physical movements of their limbs. To confirm the effect of the suggested system, we recorded EEG signals for the trained group around sensorimotor cortex while they were imagining either left or right hand movements according to our experimental design, before and after the motor imagery training. For the control group, we also recorded EEG signals twice without any training sessions. The participants' intentions were then classified using a time-frequency analysis technique, and the results of the trained group showed significant differences in the sensorimotor rhythms between the signals recorded before and after training. Classification accuracy was also enhanced considerably in all participants after motor imagery training, compared to the accuracy before training. On the other hand, the analysis results for the control EEG data set did not show consistent increment in both the number of meaningful time-frequency combinations and the classification accuracy, demonstrating that the suggested system can be used as a tool for training motor imagery tasks in BCI applications. Further, we expect that the motor imagery training system will be useful not only for BCI applications, but for functional brain mapping studies that utilize motor imagery tasks as well.

A virtual reality-based system integrated with fmri to study neural mechanisms of action observation-execution: A proof of concept study.

Restor Neurol Neurosci. 2009;27(3):209-23

Authors: Adamovich SV, August K, Merians A, Tunik E

Purpose: Emerging evidence shows that interactive virtual environments (VEs) may be a promising tool for studying sensorimotor processes and for rehabilitation. However, the potential of VEs to recruit action observation-execution neural networks is largely unknown. For the first time, a functional MRI-compatible virtual reality system (VR) has been developed to provide a window into studying brain-behavior interactions. This system is capable of measuring the complex span of hand-finger movements and simultaneously streaming this kinematic data to control the motion of representations of human hands in virtual reality. Methods: In a blocked fMRI design, thirteen healthy subjects observed, with the intent to imitate (OTI), finger sequences performed by the virtual hand avatar seen in 1st person perspective and animated by pre-recorded kinematic data. Following this, subjects imitated the observed sequence while viewing the virtual hand avatar animated by their own movement in real-time. These blocks were interleaved with rest periods during which subjects viewed static virtual hand avatars and control trials in which the avatars were replaced with moving non-anthropomorphic objects. Results: We show three main findings. First, both observation with intent to imitate and imitation with real-time virtual avatar feedback, were associated with activation in a distributed frontoparietal network typically recruited for observation and execution of real-world actions. Second, we noted a time-variant increase in activation in the left insular cortex for observation with intent to imitate actions performed by the virtual avatar. Third, imitation with virtual avatar feedback (relative to the control condition) was associated with a localized recruitment of the angular gyrus, precuneus, and extrastriate body area, regions which are (along with insular cortex) associated with the sense of agency. Conclusions: Our data suggest that the virtual hand avatars may have served as disembodied training tools in the observation condition and as embodied "extensions" of the subject's own body (pseudo-tools) in the imitation. These data advance our understanding of the brain-behavior interactions when performing actions in VE and have implications in the development of observation- and imitation-based VR rehabilitation paradigms.

Neurofeedback-based motor imagery training for brain-computer interface (BCI).

J Neurosci Methods. 2009 Apr 30;179(1):150-6

Authors: Hwang HJ, Kwon K, Im CH

In the present study, we propose a neurofeedback-based motor imagery training system for EEG-based brain-computer interface (BCI). The proposed system can help individuals get the feel of motor imagery by presenting them with real-time brain activation maps on their cortex. Ten healthy participants took part in our experiment, half of whom were trained by the suggested training system and the others did not use any training. All participants in the trained group succeeded in performing motor imagery after a series of trials to activate their motor cortex without any physical movements of their limbs. To confirm the effect of the suggested system, we recorded EEG signals for the trained group around sensorimotor cortex while they were imagining either left or right hand movements according to our experimental design, before and after the motor imagery training. For the control group, we also recorded EEG signals twice without any training sessions. The participants' intentions were then classified using a time-frequency analysis technique, and the results of the trained group showed significant differences in the sensorimotor rhythms between the signals recorded before and after training. Classification accuracy was also enhanced considerably in all participants after motor imagery training, compared to the accuracy before training. On the other hand, the analysis results for the control EEG data set did not show consistent increment in both the number of meaningful time-frequency combinations and the classification accuracy, demonstrating that the suggested system can be used as a tool for training motor imagery tasks in BCI applications. Further, we expect that the motor imagery training system will be useful not only for BCI applications, but for functional brain mapping studies that utilize motor imagery tasks as well.

Effect of Motor Imagery in the Rehabilitation of Burn Patients.

J Burn Care Res. 2009 Jun 5;

Authors: Guillot A, Lebon F, Vernay M, Girbon JP, Doyon J, Collet C

Although there is ample evidence that motor imagery (MI) improves motor performance after CNS injury, it is still unknown whether MI may enhance motor recovery after peripheral injury and most especially in the rehabilitation of burn patients. This study aimed to investigate the effects of a 2-week MI training program combined with conventional rehabilitation on the recovery of motor functions in handed burn patients. Fourteen patients admitted to the Medical Burn Center were requested to take part in the study and were randomly assigned to the imagery or the control group. Behavioral data related to the ability to perform each successive step of three manual motor sequences were collected at five intervals during the medical procedure. The results provided evidence that MI may facilitate motor recovery, and the belief in the effectiveness of MI was strong in all patients. MI may substantially contribute to improve the efficacy of conventional rehabilitation programs. Hence, this technique should be considered as a reliable alternative method to help burn patients to recover motor functions.

How does visual thinking work in the mind of a person with autism? A personal account.

Philos Trans R Soc Lond B Biol Sci. 2009 May 27;364(1522):1437-42

Authors: Grandin T

My mind is similar to an Internet search engine that searches for photographs. I use language to narrate the photo-realistic pictures that pop up in my imagination. When I design equipment for the cattle industry, I can test run it in my imagination similar to a virtual reality computer program. All my thinking is associative and not linear. To form concepts, I sort pictures into categories similar to computer files. To form the concept of orange, I see many different orange objects, such as oranges, pumpkins, orange juice and marmalade. I have observed that there are three different specialized autistic/Asperger cognitive types. They are: (i) visual thinkers such as I who are often poor at algebra, (ii) pattern thinkers such as Daniel Tammet who excel in math and music but may have problems with reading or writing composition, and (iii) verbal specialists who are good at talking and writing but they lack visual skills.

Neurofeedback-based motor imagery training for brain-computer interface (BCI).

J Neurosci Methods. 2009 Apr 30;179(1):150-156

Authors: Hwang HJ, Kwon K, Im CH

In the present study, we propose a neurofeedback-based motor imagery training system for EEG-based brain-computer interface (BCI). The proposed system can help individuals get the feel of motor imagery by presenting them with real-time brain activation maps on their cortex. Ten healthy participants took part in our experiment, half of whom were trained by the suggested training system and the others did not use any training. All participants in the trained group succeeded in performing motor imagery after a series of trials to activate their motor cortex without any physical movements of their limbs. To confirm the effect of the suggested system, we recorded EEG signals for the trained group around sensorimotor cortex while they were imagining either left or right hand movements according to our experimental design, before and after the motor imagery training. For the control group, we also recorded EEG signals twice without any training sessions. The participants' intentions were then classified using a time-frequency analysis technique, and the results of the trained group showed significant differences in the sensorimotor rhythms between the signals recorded before and after training. Classification accuracy was also enhanced considerably in all participants after motor imagery training, compared to the accuracy before training. On the other hand, the analysis results for the control EEG data set did not show consistent increment in both the number of meaningful time-frequency combinations and the classification accuracy, demonstrating that the suggested system can be used as a tool for training motor imagery tasks in BCI applications. Further, we expect that the motor imagery training system will be useful not only for BCI applications, but for functional brain mapping studies that utilize motor imagery tasks as well.

Facilitation of motor imagery through movement-related cueing.

Brain Res. 2009 Apr 27;

Authors: Heremans E, Helsen WF, De Poel HJ, Alaerts K, Meyns P, Feys P

In the past few years, the use of motor imagery as an adjunct to other forms of training has been studied extensively. However, very little attention has been paid to how imagery could be used to greatest effect. It is well known that the provision of external cues has a beneficial effect on motor skill acquisition and performance during physical practice. Since physical execution and mental imagery share several common mechanisms, we hypothesized that motor imagery might be affected by external cues in a similar way. To examine this, we compared the motor imagery performance of three groups of 15 healthy participants who either physically performed or imagined performing a goal-directed cyclical wrist movement in the presence or the absence of visual and/or auditory external cues. As outcome measures, the participants' imagery vividness scores and eye movements were measured during all conditions. We found that visual movement-related cues improved the spatial accuracy of the participants' eye movements during imagery, while auditory cues specifically enhanced their temporal accuracy. Furthermore, both types of cues significantly improved the participants' imagery vividness. These findings indicate that subjects may imagine a movement in a better way when provided with external movement-related stimuli, which may possibly be useful with regard to the efficiency of mental practice in (clinical) training protocols.

Development of hierarchical structures for actions and motor imagery: a constructivist view from synthetic neuro-robotics study.

Psychol Res. 2009 Apr 8;

Authors: Nishimoto R, Tani J

The current paper shows a neuro-robotics experiment on developmental learning of goal-directed actions. The robot was trained to predict visuo-proprioceptive flow of achieving a set of goal-directed behaviors through iterative tutor training processes. The learning was conducted by employing a dynamic neural network model which is characterized by their multiple time-scale dynamics. The experimental results showed that functional hierarchical structures emerge through stages of developments where behavior primitives are generated in earlier stages and their sequences of achieving goals appear in later stages. It was also observed that motor imagery is generated in earlier stages compared to actual behaviors. Our claim that manipulatable inner representation should emerge through the sensory-motor interactions is corresponded to Piaget's constructivist view.