Clustered functional MRI of overt speech production

To investigate the neural network of overt speech production, eventrelated fMRI was performed in 9 young healthy adult volunteers. A clustered image acquisition technique was chosen to minimize speechrelated movement artifacts. Functional images were acquired during the production of oral movements and of speech of increasing complexity (isolated vowel as well as monosyllabic and trisyllabic utterances). This imaging technique and behavioral task enabled depiction of the articulo-phonologic network of speech production from the supplementary motor area at the cranial end to the red nucleus at the caudal end. Speaking a single vowel and performing simple oral movements involved very similar activation of the corticaland subcortical motor systems. More complex, polysyllabic utterances were associated with additional activation in the bilateral cerebellum,reflecting increased demand on speech motor control, and additional activation in the bilateral temporal cortex, reflecting the stronger involvement of phonologic processing.

Advances in upper limb stroke rehabilitation: a technology push

Strokes affect thousands of people worldwide leaving sufferers with severe disabilities affecting their daily activities. In recent years, new rehabilitation techniques have emerged such as constraint-induced therapy, biofeedback therapy and robot-aided therapy. In particular, robotic techniques allow precise recording of movements and application of forces to the affected limb, making it a valuable tool for motor rehabilitation. In addition, robot-aided therapy can utilise visual cues conveyed on a computer screen to convert repetitive movement practice into an engaging task such as a game. Visual cues can also be used to control the information sent to the patient about exercise performance and to potentially address psychosomatic variables influencing therapy. This paper overviews the current state-of-the-art on upper limb robot-mediated therapy with a focal point on the technical requirements of robotic therapy devices leading to the development of upper limb rehabilitation techniques that facilitate reach-to-touch, fine motor control, whole-arm movements and promote rehabilitation beyond hospital stay. The reviewed literature suggest that while there is evidence supporting the use of this technology to reduce functional impairment, besides the technological push, the challenge ahead lies on provision of effective assessment of outcome and modalities that have a stronger impact transferring functional gains into functional independence.

Speech-like and non-speech lip kinematics and coordination in aphasia

Background and aims: In addition to the well-known linguistic processing impairments in aphasia, oro-motor skills and articulatory implementation of speech segments are reported to be compromised to some degree in most types of aphasia. This study aimed to identify differences in the characteristics and coordination of lip movements in the production of a bilabial closure gesture between speech-like and nonspeech tasks in individuals with aphasia and healthy control subjects. Method and procedure: Upper and lower lip movement data were collected for a speech-like and a nonspeech task using an AG 100 EMMA system from five individuals with aphasia and five age and gender matched control subjects. Each task was produced at two rate conditions (normal and fast), and in a familiar and a less-familiar manner. Single articulator kinematic parameters (peak velocity, amplitude, duration, and cyclic spatio-temporal index) and multi-articulator coordination indices (average relative phase and variability of relative phase) were measured to characterize lip movements. Outcome and results: The results showed that when the two lips had similar task goals (bilabial closure) in speech-like versus nonspeech task, kinematic and coordination characteristics were not found to be different. However, when changes in rate were imposed on the bilabial gesture, only speech-like task showed functional adaptations, indicated by a greater decrease in amplitude and duration at fast rates. In terms of group differences, individuals with aphasia showed smaller amplitudes and longer movement durations for upper lip, higher spatio-temporal variability for both lips, and higher variability in lip coordination than the control speakers. Rate was an important factor in distinguishing the two groups, and individuals with aphasia were limited in implementing the rate changes. Conclusion and implications: The findings support the notion of subtle but robust differences in motor control characteristics between individuals with aphasia and the control participants, even in the context of producing bilabial closing gestures for a relatively simple speech-like task. The findings also highlight the functional differences between speech-like and nonspeech tasks, despite a common movement coordination goal for bilabial closure.

The neurological underpinnings of cluttering: some initial findings

Background Cluttering is a fluency disorder characterised by overly rapid or jerky speech patterns that compromise intelligibility. The neural correlates of cluttering are unknown but theoretical accounts implicate the basal ganglia and medial prefrontal cortex. Dysfunction in these brain areas would be consistent with difficulties in selection and control of speech motor programs that are characteristic of speech disfluencies in cluttering. There is a surprising lack of investigation into this disorder using modern imaging techniques. Here, we used functional MRI to investigate the neural correlates of cluttering. Method We scanned 17 adults who clutter and 17 normally fluent control speakers matched for age and sex. Brain activity was recorded using sparse-sampling functional MRI while participants viewed scenes and either (i) produced overt speech describing the scene or (ii) read out loud a sentence provided that described the scene. Speech was recorded and analysed off line. Differences in brain activity for each condition compared to a silent resting baseline and between conditions were analysed for each group separately (cluster-forming threshold Z > 3.1, extent p < 0.05, corrected) and then these differences were further compared between the two groups (voxel threshold p < 0.01, extent > 30 voxels, uncorrected). Results In both conditions, the patterns of activation in adults who clutter and control speakers were strikingly similar, particularly at the cortical level. Direct group comparisons revealed greater activity in adults who clutter compared to control speakers in the lateral premotor cortex bilaterally and, as predicted, on the medial surface (pre-supplementary motor area). Subcortically, adults who clutter showed greater activity than control speakers in the basal ganglia. Specifically, the caudate nucleus and putamen were overactive in adults who clutter for the comparison of picture description with sentence reading. In addition, adults who clutter had reduced activity relative to control speakers in the lateral anterior cerebellum bilaterally. Eleven of the 17 adults who clutter also stuttered. This comorbid diagnosis of stuttering was found to contribute to the abnormal overactivity seen in the group of adults who clutter in the right ventral premotor cortex and right anterior cingulate cortex. In the remaining areas of abnormal activity seen in adults who clutter compared to controls, the subgroup who clutter and stutter did not differ from the subgroup who clutter but do not stutter. Conclusions Our findings were in good agreement with theoretical predictions regarding the neural correlates of cluttering. We found evidence for abnormal function in the basal ganglia and their cortical output target, the medial prefrontal cortex. The findings are discussed in relation to models of cluttering that point to problems with motor control of speech.

Rapid evolution of the cerebellum in humans and other great apes

Humans’ unique cognitive abilities are usually attributed to a greatly expanded neocortex, which has been described as “the crowning achievement of evolution and the biological substrate of human mental prowess” [1]. The human cerebellum, however, contains four times more neurons than the neocortex [2] and is attracting increasing attention for its wide range of cognitive functions. Using a method for detecting evolutionary rate changes along the branches of phylogenetic trees, we show that the cerebellum underwent rapid size increase throughout the evolution of apes, including humans, expanding significantly faster than predicted by the change in neocortex size. As a result, humans and other apes deviated significantly from the general evolutionary trend for neocortex and cerebellum to change in tandem, having significantly larger cerebella relative to neocortex size than other anthropoid primates. These results suggest that cerebellar specialization was a far more important component of human brain evolution than hitherto recognized and that technical intelligence was likely to have been at least as important as social intelligence in human cognitive evolution. Given the role of the cerebellum in sensory-motor control and in learning complex action sequences, cerebellar specialization is likely to have underpinned the evolution of humans’ advanced technological capacities, which in turn may have been a preadaptation for language.

Neural systems in the visual control of steering

Visual control of locomotion is essential for most mammals and requires coordination between perceptual processes and action systems. Previous research on the neural systems engaged by self-motion has focused on heading perception, which is only one perceptual subcomponent. For effective steering, it is necessary to perceive an appropriate future path and then bring about the required change to heading. Using function magnetic resonance imaging in humans, we reveal a role for the parietal eye fields (PEFs) in directing spatially selective processes relating to future path information. A parietal area close to PEFs appears to be specialized for processing the future path information itself. Furthermore, a separate parietal area responds to visual position error signals, which occur when steering adjustments are imprecise. A network of three areas, the cerebellum, the supplementary eye fields, and dorsal premotor cortex, was found to be involved in generating appropriate motor responses for steering adjustments. This may reflect the demands of integrating visual inputs with the output response for the control device.

Determining feature relevance for the grouping of motor unit action potentials through generative topographic mapping

The study of motor unit action potential (MUAP) activity from electrornyographic signals is an important stage on neurological investigations that aim to understand the state of the neuromuscular system. In this context, the identification and clustering of MUAPs that exhibit common characteristics, and the assessment of which data features are most relevant for the definition of such cluster structure are central issues. In this paper, we propose the application of an unsupervised Feature Relevance Determination (FRD) method to the analysis of experimental MUAPs obtained from healthy human subjects. In contrast to approaches that require the knowledge of a priori information from the data, this FRD method is embedded on a constrained mixture model, known as Generative Topographic Mapping, which simultaneously performs clustering and visualization of MUAPs. The experimental results of the analysis of a data set consisting of MUAPs measured from the surface of the First Dorsal Interosseous, a hand muscle, indicate that the MUAP features corresponding to the hyperpolarization period in the physisiological process of generation of muscle fibre action potentials are consistently estimated as the most relevant and, therefore, as those that should be paid preferential attention for the interpretation of the MUAP groupings.

Architecture for neuronal cell control of a mobile robot

It is usually expected that the intelligent controlling mechanism of a robot is a computer system. Research is however now ongoing in which biological neural networks are being cultured and trained to act as the brain of an interactive real world robot - thereby either completely replacing or operating in a cooperative fashion with a computer system. Studying such neural systems can give a distinct insight into biological neural structures and therefore such research has immediate medical implications. In particular, the use of rodent primary dissociated cultured neuronal networks for the control of mobile `animals' (artificial animals, a contraction of animal and materials) is a novel approach to discovering the computational capabilities of networks of biological neurones. A dissociated culture of this nature requires appropriate embodiment in some form, to enable appropriate development in a controlled environment within which appropriate stimuli may be received via sensory data but ultimate influence over motor actions retained. The principal aims of the present research are to assess the computational and learning capacity of dissociated cultured neuronal networks with a view to advancing network level processing of artificial neural networks. This will be approached by the creation of an artificial hybrid system (animal) involving closed loop control of a mobile robot by a dissociated culture of rat neurons. This 'closed loop' interaction with the environment through both sensing and effecting will enable investigation of its learning capacity This paper details the components of the overall animat closed loop system and reports on the evaluation of the results from the experiments being carried out with regard to robot behaviour.

Impedance mismatch: some differences between the way humans and robots control interaction forces

In over forty years of research robots have made very little progress still largely confined to industrial manufacture and cute toys, yet in the same period computing has followed Moores Law where the capacity double roughly every two years. So why is there no Moores Law for robots? Two areas stand out as worthy of research to speedup progress. The first is to get a greater understanding of how human and animal brains control movement, the second to build a new generation of robots that have greater haptic sense, that is a better ability to adapt to the environment as it is encountered. A remarkable property of the cognitive-motor system in humans and animals is that it is slow. Recognising an object may take 250 mS, a reaction time of 150 mS is considered fast. Yet despite this slow system we are well designed to allow contact with the world in a variety of ways. We can anticipate an encounter, use the change of force as a means of communication and ignore sensory cues when they are not relevant. A better understanding of these process has allowed us to build haptic interfaces to mimic the interaction. Emerging from this understanding are new ways to control the contact between robots, the user and the environment. Rehabilitation robotics has all the elements in the subject to not only enable and change the lives of people with disabilities, but also to facilitate revolution change in classic robotics.

Generative topographic mapping applied to clustering and visualization of motor unit action potentials

The identification and visualization of clusters formed by motor unit action potentials (MUAPs) is an essential step in investigations seeking to explain the control of the neuromuscular system. This work introduces the generative topographic mapping (GTM), a novel machine learning tool, for clustering of MUAPs, and also it extends the GTM technique to provide a way of visualizing MUAPs. The performance of GTM was compared to that of three other clustering methods: the self-organizing map (SOM), a Gaussian mixture model (GMM), and the neural-gas network (NGN). The results, based on the study of experimental MUAPs, showed that the rate of success of both GTM and SOM outperformed that of GMM and NGN, and also that GTM may in practice be used as a principled alternative to the SOM in the study of MUAPs. A visualization tool, which we called GTM grid, was devised for visualization of MUAPs lying in a high-dimensional space. The visualization provided by the GTM grid was compared to that obtained from principal component analysis (PCA). (c) 2005 Elsevier Ireland Ltd. All rights reserved.

Upper limb robot mediated stroke therapy - GENTLE/s approach

Stroke is a leading cause of disability in particular affecting older people. Although the causes of stroke are well known and it is possible to reduce these risks, there is still a need to improve rehabilitation techniques. Early studies in the literature suggest that early intensive therapies can enhance a patient's recovery. According to physiotherapy literature, attention and motivation are key factors for motor relearning following stroke. Machine mediated therapy offers the potential to improve the outcome of stroke patients engaged on rehabilitation for upper limb motor impairment. Haptic interfaces are a particular group of robots that are attractive due to their ability to safely interact with humans. They can enhance traditional therapy tools, provide therapy "on demand" and can present accurate objective measurements of a patient's progression. Our recent studies suggest the use of tele-presence and VR-based systems can potentially motivate patients to exercise for longer periods of time. The creation of human-like trajectories is essential for retraining upper limb movements of people that have lost manipulation functions following stroke. By coupling models for human arm movement with haptic interfaces and VR technology it is possible to create a new class of robot mediated neuro rehabilitation tools. This paper provides an overview on different approaches to robot mediated therapy and describes a system based on haptics and virtual reality visualisation techniques, where particular emphasis is given to different control strategies for interaction derived from minimum jerk theory and the aid of virtual and mixed reality based exercises.

Thought communication and control: a first step using radiotelegraphy

A signalling procedure is described involving a connection, via the Internet, between the nervous system of an able-bodied individual and a robotic prosthesis, and between the nervous systems of two able-bodied human subjects. Neural implant technology is used to directly interface each nervous system with a computer. Neural motor unit and sensory receptor recordings are processed real-time and used as the communication basis. This is seen as a first step towards thought communication, in which the neural implants would be positioned in the central nervous systems of two individuals.

Investigation of language and motor skills in Serbian speaking children with specific language impairment and in typically developing children

Specific language impairment (SLI) is usually defined as a developmental language disorder which does not result from a hearing loss, autism, neurological and emotional difficulties, severe social deprivation, low non-verbal abilities. Children affected with SLI typically have difficulties with the acquisition of different aspects of language and by definition, their impairment is specific to language and no other skills are affected. However, there has been a growing body of literature to suggest that children with SLI also have non-linguistic deficits, including impaired motor abilities. The aim of the current study is to investigate language and motor abilities of a group of thirty children with SLI (aged between 4 and 7) in comparison to a group of 30 typically developing children matched for chronological age. The results showed that the group of children with SLI had significantly more difficulties on the language and motor assessments compared to the control group. The SLI group also showed delayed onset in the development of all motor skills under investigation in comparison to the typically developing group. More interestingly, the two groups differed with respect to which language abilities were correlated with motor abilities, however Imitation of Complex Movements was the unique skill which reliably predicted expressive vocabulary in both typically developing children and in children with SLI.

Speed sensorless vector control of induction machines

A novel rotor velocity estimation scheme applicable to vector controlled induction motors has been described. The proposed method will evaluate rotor velocity, ωr, on-line, does not require any extra transducers or injection of any signals, nor does it employ complicated algorithms such as MRAS or Kalman filters. Furthermore, the new scheme will operate at all velocities including zero with very little error. The procedure employs motor model equations, however all differential and integral terms have been eliminated giving a very fast, low-cost, effective and practical alternative to the current available methods. Simulation results verify the operation of the scheme under ideal and PWM conditions.