To enable intuitive operation of powered artificial legs, an interface between user and prosthesis that can recognize the user's movement intent is desired. A novel neural-machine interface (NMI) based on neuromuscular-mechanical fusion developed in our previous study has demonstrated a great potential to accurately identify the intended movement of transfemoral amputees. However, this interface has not yet been integrated with a powered prosthetic leg for true neural control. This study aimed to report (1) a flexible platform to implement and optimize neural control of powered lower limb prosthesis and (2) an experimental setup and protocol to evaluate neural prosthesis control on patients with lower limb amputations. First a platform based on a PC and a visual programming environment were developed to implement the prosthesis control algorithms, including NMI training algorithm, NMI online testing algorithm, and intrinsic control algorithm. To demonstrate the function of this platform, in this study the NMI based on neuromuscular-mechanical fusion was hierarchically integrated with intrinsic control of a prototypical transfemoral prosthesis. One patient with a unilateral transfemoral amputation was recruited to evaluate our implemented neural controller when performing activities, such as standing, level-ground walking, ramp ascent, and ramp descent continuously in the laboratory. A novel experimental setup and protocol were developed in order to test the new prosthesis control safely and efficiently. The presented proof-of-concept platform and experimental setup and protocol could aid the future development and application of neurally-controlled powered artificial legs.
17 Related JoVE Articles!
Oscillation and Reaction Board Techniques for Estimating Inertial Properties of a Below-knee Prosthesis
Institutions: University of Northern Colorado, Arizona State University, Iowa State University.
The purpose of this study was two-fold: 1) demonstrate a technique that can be used to directly estimate the inertial properties of a below-knee prosthesis, and 2) contrast the effects of the proposed technique and that of using intact limb inertial properties on joint kinetic estimates during walking in unilateral, transtibial amputees. An oscillation and reaction board system was validated and shown to be reliable when measuring inertial properties of known geometrical solids. When direct measurements of inertial properties of the prosthesis were used in inverse dynamics modeling of the lower extremity compared with inertial estimates based on an intact shank and foot, joint kinetics at the hip and knee were significantly lower during the swing phase of walking. Differences in joint kinetics during stance, however, were smaller than those observed during swing. Therefore, researchers focusing on the swing phase of walking should consider the impact of prosthesis inertia property estimates on study outcomes. For stance, either one of the two inertial models investigated in our study would likely lead to similar outcomes with an inverse dynamics assessment.
Bioengineering, Issue 87, prosthesis inertia, amputee locomotion, below-knee prosthesis, transtibial amputee
Movement Retraining using Real-time Feedback of Performance
Institutions: University of British Columbia .
Any modification of movement - especially movement patterns that have been honed over a number of years - requires re-organization of the neuromuscular patterns responsible for governing the movement performance. This motor learning can be enhanced through a number of methods that are utilized in research and clinical settings alike. In general, verbal feedback of performance in real-time or knowledge of results following movement is commonly used clinically as a preliminary means of instilling motor learning. Depending on patient preference and learning style, visual feedback (e.g.
through use of a mirror or different types of video) or proprioceptive guidance utilizing therapist touch, are used to supplement verbal instructions from the therapist. Indeed, a combination of these forms of feedback is commonplace in the clinical setting to facilitate motor learning and optimize outcomes.
Laboratory-based, quantitative motion analysis has been a mainstay in research settings to provide accurate and objective analysis of a variety of movements in healthy and injured populations. While the actual mechanisms of capturing the movements may differ, all current motion analysis systems rely on the ability to track the movement of body segments and joints and to use established equations of motion to quantify key movement patterns. Due to limitations in acquisition and processing speed, analysis and description of the movements has traditionally occurred offline after completion of a given testing session.
This paper will highlight a new supplement to standard motion analysis techniques that relies on the near instantaneous assessment and quantification of movement patterns and the display of specific movement characteristics to the patient during
a movement analysis session. As a result, this novel technique can provide a new method of feedback delivery that has advantages over currently used feedback methods.
Medicine, Issue 71, Biophysics, Anatomy, Physiology, Physics, Biomedical Engineering, Behavior, Psychology, Kinesiology, Physical Therapy, Musculoskeletal System, Biofeedback, biomechanics, gait, movement, walking, rehabilitation, clinical, training
A Novel Application of Musculoskeletal Ultrasound Imaging
Institutions: George Mason University, George Mason University, George Mason University, George Mason University.
Ultrasound is an attractive modality for imaging muscle and tendon motion during dynamic tasks and can provide a complementary methodological approach for biomechanical studies in a clinical or laboratory setting. Towards this goal, methods for quantification of muscle kinematics from ultrasound imagery are being developed based on image processing. The temporal resolution of these methods is typically not sufficient for highly dynamic tasks, such as drop-landing. We propose a new approach that utilizes a Doppler method for quantifying muscle kinematics. We have developed a novel vector tissue Doppler imaging (vTDI) technique that can be used to measure musculoskeletal contraction velocity, strain and strain rate with sub-millisecond temporal resolution during dynamic activities using ultrasound. The goal of this preliminary study was to investigate the repeatability and potential applicability of the vTDI technique in measuring musculoskeletal velocities during a drop-landing task, in healthy subjects. The vTDI measurements can be performed concurrently with other biomechanical techniques, such as 3D motion capture for joint kinematics and kinetics, electromyography for timing of muscle activation and force plates for ground reaction force. Integration of these complementary techniques could lead to a better understanding of dynamic muscle function and dysfunction underlying the pathogenesis and pathophysiology of musculoskeletal disorders.
Medicine, Issue 79, Anatomy, Physiology, Joint Diseases, Diagnostic Imaging, Muscle Contraction, ultrasonic applications, Doppler effect (acoustics), Musculoskeletal System, biomechanics, musculoskeletal kinematics, dynamic function, ultrasound imaging, vector Doppler, strain, strain rate
Quantification of Orofacial Phenotypes in Xenopus
Institutions: Virginia Commonwealth University.
has become an important tool for dissecting the mechanisms governing craniofacial development and defects. A method to quantify orofacial development will allow for more rigorous analysis of orofacial phenotypes upon abrogation with substances that can genetically or molecularly manipulate gene expression or protein function. Using two dimensional images of the embryonic heads, traditional size dimensions-such as orofacial width, height and area- are measured. In addition, a roundness measure of the embryonic mouth opening is used to describe the shape of the mouth. Geometric morphometrics of these two dimensional images is also performed to provide a more sophisticated view of changes in the shape of the orofacial region. Landmarks are assigned to specific points in the orofacial region and coordinates are created. A principle component analysis is used to reduce landmark coordinates to principle components that then discriminate the treatment groups. These results are displayed as a scatter plot in which individuals with similar orofacial shapes cluster together. It is also useful to perform a discriminant function analysis, which statistically compares the positions of the landmarks between two treatment groups. This analysis is displayed on a transformation grid where changes in landmark position are viewed as vectors. A grid is superimposed on these vectors so that a warping pattern is displayed to show where significant landmark positions have changed. Shape changes in the discriminant function analysis are based on a statistical measure, and therefore can be evaluated by a p-value. This analysis is simple and accessible, requiring only a stereoscope and freeware software, and thus will be a valuable research and teaching resource.
Developmental Biology, Issue 93, Orofacial quantification, geometric morphometrics, Xenopus, orofacial development, orofacial defects, shape changes, facial dimensions
Clinical Assessment of Spatiotemporal Gait Parameters in Patients and Older Adults
Institutions: Schulthess Clinic.
Spatial and temporal characteristics of human walking are frequently evaluated to identify possible gait impairments, mainly in orthopedic and neurological patients1-4
, but also in healthy older adults5,6
. The quantitative gait analysis described in this protocol is performed with a recently-introduced photoelectric system (see Materials table) which has the potential to be used in the clinic because it is portable, easy to set up (no subject preparation is required before a test), and does not require maintenance and sensor calibration. The photoelectric system consists of series of high-density floor-based photoelectric cells with light-emitting and light-receiving diodes that are placed parallel to each other to create a corridor, and are oriented perpendicular to the line of progression7
. The system simply detects interruptions in light signal, for instance due to the presence of feet within the recording area. Temporal gait parameters and 1D spatial coordinates of consecutive steps are subsequently calculated to provide common gait parameters such as step length, single limb support and walking velocity8
, whose validity against a criterion instrument has recently been demonstrated7,9
. The measurement procedures are very straightforward; a single patient can be tested in less than 5 min and a comprehensive report can be generated in less than 1 min.
Medicine, Issue 93, gait analysis, walking, floor-based photocells, spatiotemporal, elderly, orthopedic patients, neurological patients
Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction
Institutions: Rutgers University, Koç University, New York University, Fairfield University.
We describe a high-throughput, high-volume, fully automated, live-in 24/7 behavioral testing system for assessing the effects of genetic and pharmacological manipulations on basic mechanisms of cognition and learning in mice. A standard polypropylene mouse housing tub is connected through an acrylic tube to a standard commercial mouse test box. The test box has 3 hoppers, 2 of which are connected to pellet feeders. All are internally illuminable with an LED and monitored for head entries by infrared (IR) beams. Mice live in the environment, which eliminates handling during screening. They obtain their food during two or more daily feeding periods by performing in operant (instrumental) and Pavlovian (classical) protocols, for which we have written protocol-control software and quasi-real-time data analysis and graphing software. The data analysis and graphing routines are written in a MATLAB-based language created to simplify greatly the analysis of large time-stamped behavioral and physiological event records and to preserve a full data trail from raw data through all intermediate analyses to the published graphs and statistics within a single data structure. The data-analysis code harvests the data several times a day and subjects it to statistical and graphical analyses, which are automatically stored in the "cloud" and on in-lab computers. Thus, the progress of individual mice is visualized and quantified daily. The data-analysis code talks to the protocol-control code, permitting the automated advance from protocol to protocol of individual subjects. The behavioral protocols implemented are matching, autoshaping, timed hopper-switching, risk assessment in timed hopper-switching, impulsivity measurement, and the circadian anticipation of food availability. Open-source protocol-control and data-analysis code makes the addition of new protocols simple. Eight test environments fit in a 48 in x 24 in x 78 in cabinet; two such cabinets (16 environments) may be controlled by one computer.
Behavior, Issue 84, genetics, cognitive mechanisms, behavioral screening, learning, memory, timing
Establishment of a Surgically-induced Model in Mice to Investigate the Protective Role of Progranulin in Osteoarthritis
Institutions: NYU Hospital for Joint Diseases, New York University Medical Center.
Destabilization of medial meniscus (DMM) model is an important tool for studying the pathophysiological roles of numerous arthritis associated molecules in the pathogenesis of osteoarthritis (OA) in vivo
. However, the detailed, especially the visualized protocol for establishing this complicated model in mice, is not available. Herein we took advantage of wildtype and progranulin (PGRN)-/- mice as examples to introduce a protocol for inducing DMM model in mice, and compared the onset of OA following establishment of this surgically induced model. The operations performed on mice were either sham operation, which just opened joint capsule, or DMM operation, which cut the menisco-tibial ligament and caused destabilization of medial meniscus. Osteoarthritis severity was evaluated using histological assay (e.g.
Safranin O staining), expressions of OA-associated genes, degradation of cartilage extracellular matrix molecules, and osteophyte formation. DMM operation successfully induced OA initiation and progression in both wildtype and PGRN-/- mice, and loss of PGNR growth factor led to a more severe OA phenotype in this surgically induced model.
Bioengineering, Issue 84, Mouse, Cartilage, Surgery, Osteoarthritis, degenerative arthritis, progranulin, destabilization of medial meniscus (DMM)
Simultaneous Scalp Electroencephalography (EEG), Electromyography (EMG), and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
Institutions: National Institutes of Health, University of Houston, University of Houston, University of Houston, University of Houston.
Recent studies support the involvement of supraspinal networks in control of bipedal human walking. Part of this evidence encompasses studies, including our previous work, demonstrating that gait kinematics and limb coordination during treadmill walking can be inferred from the scalp electroencephalogram (EEG) with reasonably high decoding accuracies. These results provide impetus for development of non-invasive brain-machine-interface (BMI) systems for use in restoration and/or augmentation of gait- a primary goal of rehabilitation research. To date, studies examining EEG decoding of activity during gait have been limited to treadmill walking in a controlled environment. However, to be practically viable a BMI system must be applicable for use in everyday locomotor tasks such as over ground walking and turning. Here, we present a novel protocol for non-invasive collection of brain activity (EEG), muscle activity (electromyography (EMG)), and whole-body kinematic data (head, torso, and limb trajectories) during both treadmill and over ground walking tasks. By collecting these data in the uncontrolled environment insight can be gained regarding the feasibility of decoding unconstrained gait and surface EMG from scalp EEG.
Behavior, Issue 77, Neuroscience, Neurobiology, Medicine, Anatomy, Physiology, Biomedical Engineering, Molecular Biology, Electroencephalography, EEG, Electromyography, EMG, electroencephalograph, gait, brain-computer interface, brain machine interface, neural decoding, over-ground walking, robotic gait, brain, imaging, clinical techniques
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Institutions: University of Ulm.
Diffusion tensor imaging (DTI) techniques provide information on the microstructural processes of the cerebral white matter (WM) in vivo
. The present applications are designed to investigate differences of WM involvement patterns in different brain diseases, especially neurodegenerative disorders, by use of different DTI analyses in comparison with matched controls.
DTI data analysis is performed in a variate fashion, i.e.
voxelwise comparison of regional diffusion direction-based metrics such as fractional anisotropy (FA), together with fiber tracking (FT) accompanied by tractwise fractional anisotropy statistics (TFAS) at the group level in order to identify differences in FA along WM structures, aiming at the definition of regional patterns of WM alterations at the group level. Transformation into a stereotaxic standard space is a prerequisite for group studies and requires thorough data processing to preserve directional inter-dependencies. The present applications show optimized technical approaches for this preservation of quantitative and directional information during spatial normalization in data analyses at the group level. On this basis, FT techniques can be applied to group averaged data in order to quantify metrics information as defined by FT. Additionally, application of DTI methods, i.e.
differences in FA-maps after stereotaxic alignment, in a longitudinal analysis at an individual subject basis reveal information about the progression of neurological disorders. Further quality improvement of DTI based results can be obtained during preprocessing by application of a controlled elimination of gradient directions with high noise levels.
In summary, DTI is used to define a distinct WM pathoanatomy of different brain diseases by the combination of whole brain-based and tract-based DTI analysis.
Medicine, Issue 77, Neuroscience, Neurobiology, Molecular Biology, Biomedical Engineering, Anatomy, Physiology, Neurodegenerative Diseases, nuclear magnetic resonance, NMR, MR, MRI, diffusion tensor imaging, fiber tracking, group level comparison, neurodegenerative diseases, brain, imaging, clinical techniques
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Institutions: The Feinstein Institute for Medical Research.
The scaled subprofile model (SSM)1-4
is a multivariate PCA-based algorithm that identifies major sources of variation in patient and control group brain image data while rejecting lesser components (Figure 1
). Applied directly to voxel-by-voxel covariance data of steady-state multimodality images, an entire group image set can be reduced to a few significant linearly independent covariance patterns and corresponding subject scores. Each pattern, termed a group invariant subprofile (GIS), is an orthogonal principal component that represents a spatially distributed network of functionally interrelated brain regions. Large global mean scalar effects that can obscure smaller network-specific contributions are removed by the inherent logarithmic conversion and mean centering of the data2,5,6
. Subjects express each of these patterns to a variable degree represented by a simple scalar score that can correlate with independent clinical or psychometric descriptors7,8
. Using logistic regression analysis of subject scores (i.e.
pattern expression values), linear coefficients can be derived to combine multiple principal components into single disease-related spatial covariance patterns, i.e.
composite networks with improved discrimination of patients from healthy control subjects5,6
. Cross-validation within the derivation set can be performed using bootstrap resampling techniques9
. Forward validation is easily confirmed by direct score evaluation of the derived patterns in prospective datasets10
. Once validated, disease-related patterns can be used to score individual patients with respect to a fixed reference sample, often the set of healthy subjects that was used (with the disease group) in the original pattern derivation11
. These standardized values can in turn be used to assist in differential diagnosis12,13
and to assess disease progression and treatment effects at the network level7,14-16
. We present an example of the application of this methodology to FDG PET data of Parkinson's Disease patients and normal controls using our in-house software to derive a characteristic covariance pattern biomarker of disease.
Medicine, Issue 76, Neurobiology, Neuroscience, Anatomy, Physiology, Molecular Biology, Basal Ganglia Diseases, Parkinsonian Disorders, Parkinson Disease, Movement Disorders, Neurodegenerative Diseases, PCA, SSM, PET, imaging biomarkers, functional brain imaging, multivariate spatial covariance analysis, global normalization, differential diagnosis, PD, brain, imaging, clinical techniques
Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
When considering human neuroimaging data, an appreciation of signal variability represents a fundamental innovation in the way we think about brain signal. Typically, researchers represent the brain's response as the mean across repeated experimental trials and disregard signal fluctuations over time as "noise". However, it is becoming clear that brain signal variability conveys meaningful functional information about neural network dynamics. This article describes the novel method of multiscale entropy (MSE) for quantifying brain signal variability. MSE may be particularly informative of neural network dynamics because it shows timescale dependence and sensitivity to linear and nonlinear dynamics in the data.
Neuroscience, Issue 76, Neurobiology, Anatomy, Physiology, Medicine, Biomedical Engineering, Electroencephalography, EEG, electroencephalogram, Multiscale entropy, sample entropy, MEG, neuroimaging, variability, noise, timescale, non-linear, brain signal, information theory, brain, imaging
Treatment of Osteochondral Defects in the Rabbit's Knee Joint by Implantation of Allogeneic Mesenchymal Stem Cells in Fibrin Clots
Institutions: Klinikum rechts der Isar der Technischen Universität München, Klinikum rechts der Isar der Technischen Universität München, Klinikum rechts der Isar der Technischen Universität München, Uniklinik Köln.
The treatment of osteochondral articular defects has been challenging physicians for many years. The better understanding of interactions of articular cartilage and subchondral bone in recent years led to increased attention to restoration of the entire osteochondral unit. In comparison to chondral lesions the regeneration of osteochondral defects is much more complex and a far greater surgical and therapeutic challenge. The damaged tissue does not only include the superficial cartilage layer but also the subchondral bone. For deep, osteochondral damage, as it occurs for example with osteochondrosis dissecans, the full thickness of the defect needs to be replaced to restore the joint surface 1
. Eligible therapeutic procedures have to consider these two different tissues with their different intrinsic healing potential 2
. In the last decades, several surgical treatment options have emerged and have already been clinically established 3-6
Autologous or allogeneic osteochondral transplants consist of articular cartilage and subchondral bone and allow the replacement of the entire osteochondral unit. The defects are filled with cylindrical osteochondral grafts that aim to provide a congruent hyaline cartilage covered surface 3,7,8
. Disadvantages are the limited amount of available grafts, donor site morbidity (for autologous transplants) and the incongruence of the surface; thereby the application of this method is especially limited for large defects.
New approaches in the field of tissue engineering opened up promising possibilities for regenerative osteochondral therapy. The implantation of autologous chondrocytes marked the first cell based biological approach for the treatment of full-thickness cartilage lesions and is now worldwide established with good clinical results even 10 to 20 years after implantation 9,10
. However, to date, this technique is not suitable for the treatment of all types of lesions such as deep defects involving the subchondral bone 11
combines bone grafting with current approaches in Tissue Engineering 5,6
. This combination seems to be able to overcome the limitations seen in osteochondral grafts alone. After autologous bone grafting to the subchondral defect area, a membrane seeded with autologous chondrocytes is sutured above and facilitates to match the topology of the graft with the injured site. Of course, the previous bone reconstruction needs additional surgical time and often even an additional surgery. Moreover, to date, long-term data is missing 12
Tissue Engineering without additional bone grafting aims to restore the complex structure and properties of native articular cartilage by chondrogenic and osteogenic potential of the transplanted cells. However, again, it is usually only the cartilage tissue that is more or less regenerated. Additional osteochondral damage needs a specific further treatment. In order to achieve a regeneration of the multilayered structure of osteochondral defects, three-dimensional tissue engineered products seeded with autologous/allogeneic cells might provide a good regeneration capacity 11
Beside autologous chondrocytes, mesenchymal stem cells (MSC) seem to be an attractive alternative for the development of a full-thickness cartilage tissue. In numerous preclinical in vitro
and in vivo
studies, mesenchymal stem cells have displayed excellent tissue regeneration potential 13,14
. The important advantage of mesenchymal stem cells especially for the treatment of osteochondral defects is that they have the capacity to differentiate in osteocytes as well as chondrocytes. Therefore, they potentially allow a multilayered regeneration of the defect.
In recent years, several scaffolds with osteochondral regenerative potential have therefore been developed and evaluated with promising preliminary results 1,15-18
. Furthermore, fibrin glue as a cell carrier became one of the preferred techniques in experimental cartilage repair and has already successfully been used in several animal studies 19-21
and even first human trials 22
The following protocol will demonstrate an experimental technique for isolating mesenchymal stem cells from a rabbit's bone marrow, for subsequent proliferation in cell culture and for preparing a standardized in vitro
-model for fibrin-cell-clots. Finally, a technique for the implantation of pre-established fibrin-cell-clots into artificial osteochondral defects of the rabbit's knee joint will be described.
Biomedical Engineering, Issue 75, Medicine, Anatomy, Physiology, Cellular Biology, Molecular Biology, Stem Cell Biology, Tissue Engineering, Surgery, Mesenchymal stem cells, fibrin clot, cartilage, osteochondral defect, rabbit, experimental, subchondral bone, knee injury, bone grafting, regenerative therapy, chondrocytes, cell culture, isolation, transplantation, animal model
A 3D System for Culturing Human Articular Chondrocytes in Synovial Fluid
Institutions: Tufts University School of Medicine, Tufts Medical Center.
Cartilage destruction is a central pathological feature of osteoarthritis, a leading cause of disability in the US. Cartilage in the adult does not regenerate very efficiently in vivo
; and as a result, osteoarthritis leads to irreversible cartilage loss and is accompanied by chronic pain and immobility 1,2
. Cartilage tissue engineering offers promising potential to regenerate and restore tissue function. This technology typically involves seeding chondrocytes into natural or synthetic scaffolds and culturing the resulting 3D construct in a balanced medium over a period of time with a goal of engineering a biochemically and biomechanically mature tissue that can be transplanted into a defect site in vivo 3-6
. Achieving an optimal condition for chondrocyte growth and matrix deposition is essential for the success of cartilage tissue engineering.
In the native joint cavity, cartilage at the articular surface of the bone is bathed in synovial fluid. This clear and viscous fluid provides nutrients to the avascular articular cartilage and contains growth factors, cytokines and enzymes that are important for chondrocyte metabolism 7,8
. Furthermore, synovial fluid facilitates low-friction movement between cartilaginous surfaces mainly through secreting two key components, hyaluronan and lubricin 9 10
. In contrast, tissue engineered cartilage is most often cultured in artificial media. While these media are likely able to provide more defined conditions for studying chondrocyte metabolism, synovial fluid most accurately reflects the natural environment of which articular chondrocytes reside in.
Indeed, synovial fluid has the advantage of being easy to obtain and store, and can often be regularly replenished by the body. Several groups have supplemented the culture medium with synovial fluid in growing human, bovine, rabbit and dog chondrocytes, but mostly used only low levels of synovial fluid (below 20%) 11-25
. While chicken, horse and human chondrocytes have been cultured in the medium with higher percentage of synovial fluid, these culture systems were two-dimensional 26-28
. Here we present our method of culturing human articular chondrocytes in a 3D system with a high percentage of synovial fluid (up to 100%) over a period of 21 days. In doing so, we overcame a major hurdle presented by the high viscosity of the synovial fluid. This system provides the possibility of studying human chondrocytes in synovial fluid in a 3D setting, which can be further combined with two other important factors (oxygen tension and mechanical loading) 29,30
that constitute the natural environment for cartilage to mimic the natural milieu for cartilage growth. Furthermore, This system may also be used for assaying synovial fluid activity on chondrocytes and provide a platform for developing cartilage regeneration technologies and therapeutic options for arthritis.
Cellular Biology, Issue 59, Chondrocytes, articular, human, synovial fluid, alginate bead, 3D culture
Creating Objects and Object Categories for Studying Perception and Perceptual Learning
Institutions: Georgia Health Sciences University, Georgia Health Sciences University, Georgia Health Sciences University, Palo Alto Research Center, Palo Alto Research Center, University of Minnesota .
In order to quantitatively study object perception, be it perception by biological systems or by machines, one needs to create objects and object categories with precisely definable, preferably naturalistic, properties1
. Furthermore, for studies on perceptual learning, it is useful to create novel objects and object categories (or object classes
) with such properties2
Many innovative and useful methods currently exist for creating novel objects and object categories3-6
(also see refs. 7,8). However, generally speaking, the existing methods have three broad types of shortcomings.
First, shape variations are generally imposed by the experimenter5,9,10
, and may therefore be different from the variability in natural categories, and optimized for a particular recognition algorithm. It would be desirable to have the variations arise independently of the externally imposed constraints.
Second, the existing methods have difficulty capturing the shape complexity of natural objects11-13
. If the goal is to study natural object perception, it is desirable for objects and object categories to be naturalistic, so as to avoid possible confounds and special cases.
Third, it is generally hard to quantitatively measure the available information in the stimuli created by conventional methods. It would be desirable to create objects and object categories where the available information can be precisely measured and, where necessary, systematically manipulated (or 'tuned'). This allows one to formulate the underlying object recognition tasks in quantitative terms.
Here we describe a set of algorithms, or methods, that meet all three of the above criteria. Virtual morphogenesis (VM) creates novel, naturalistic virtual 3-D objects called 'digital embryos' by simulating the biological process of embryogenesis14
. Virtual phylogenesis (VP) creates novel, naturalistic object categories by simulating the evolutionary process of natural selection9,12,13
. Objects and object categories created by these simulations can be further manipulated by various morphing methods to generate systematic variations of shape characteristics15,16
. The VP and morphing methods can also be applied, in principle, to novel virtual objects other than digital embryos, or to virtual versions of real-world objects9,13
. Virtual objects created in this fashion can be rendered as visual images using a conventional graphical toolkit, with desired manipulations of surface texture, illumination, size, viewpoint and background. The virtual objects can also be 'printed' as haptic objects using a conventional 3-D prototyper.
We also describe some implementations of these computational algorithms to help illustrate the potential utility of the algorithms. It is important to distinguish the algorithms from their implementations. The implementations are demonstrations offered solely as a 'proof of principle' of the underlying algorithms. It is important to note that, in general, an implementation of a computational algorithm often has limitations that the algorithm itself does not have.
Together, these methods represent a set of powerful and flexible tools for studying object recognition and perceptual learning by biological and computational systems alike. With appropriate extensions, these methods may also prove useful in the study of morphogenesis and phylogenesis.
Neuroscience, Issue 69, machine learning, brain, classification, category learning, cross-modal perception, 3-D prototyping, inference
One Dimensional Turing-Like Handshake Test for Motor Intelligence
Institutions: Ben-Gurion University.
In the Turing test, a computer model is deemed to "think intelligently" if it can generate answers that are not distinguishable from those of a human. However, this test is limited to the linguistic aspects of machine intelligence. A salient function of the brain is the control of movement, and the movement of the human hand is a sophisticated demonstration of this function. Therefore, we propose a Turing-like handshake test, for machine motor intelligence. We administer the test through a telerobotic system in which the interrogator is engaged in a task of holding a robotic stylus and interacting with another party (human or artificial). Instead of asking the interrogator whether the other party is a person or a computer program, we employ a two-alternative forced choice method and ask which of two systems is more human-like. We extract a quantitative grade for each model according to its resemblance to the human handshake motion and name it "Model Human-Likeness Grade" (MHLG). We present three methods to estimate the MHLG. (i) By calculating the proportion of subjects' answers that the model is more human-like than the human; (ii) By comparing two weighted sums of human and model handshakes we fit a psychometric curve and extract the point of subjective equality (PSE); (iii) By comparing a given model with a weighted sum of human and random signal, we fit a psychometric curve to the answers of the interrogator and extract the PSE for the weight of the human in the weighted sum. Altogether, we provide a protocol to test computational models of the human handshake. We believe that building a model is a necessary step in understanding any phenomenon and, in this case, in understanding the neural mechanisms responsible for the generation of the human handshake.
Neuroscience, Issue 46, Turing test, Human Machine Interface, Haptics, Teleoperation, Motor Control, Motor Behavior, Diagnostics, Perception, handshake, telepresence
Methods to Quantify Pharmacologically Induced Alterations in Motor Function in Human Incomplete SCI
Institutions: Rehabilitation Institute of Chicago, University of Illinois at Chicago, University of Illinois at Chicago.
Spinal cord injury (SCI) is a debilitating disorder, which produces profound deficits in volitional motor control. Following medical stabilization, recovery from SCI typically involves long term rehabilitation. While recovery of walking ability is a primary goal in many patients early after injury, those with a motor incomplete SCI, indicating partial preservation of volitional control, may have the sufficient residual descending pathways necessary to attain this goal. However, despite physical interventions, motor impairments including weakness, and the manifestation of abnormal involuntary reflex activity, called spasticity or spasms, are thought to contribute to reduced walking recovery. Doctrinaire thought suggests that remediation of this abnormal motor reflexes associated with SCI will produce functional benefits to the patient. For example, physicians and therapists will provide specific pharmacological or physical interventions directed towards reducing spasticity or spasms, although there continues to be little empirical data suggesting that these strategies improve walking ability.
In the past few decades, accumulating data has suggested that specific neuromodulatory agents, including agents which mimic or facilitate the actions of the monoamines, including serotonin (5HT) and norepinephrine (NE), can initiate or augment walking behaviors in animal models of SCI. Interestingly, many of these agents, particularly 5HTergic agonists, can markedly increase spinal excitability, which in turn also increases reflex activity in these animals. Counterintuitive to traditional theories of recovery following human SCI, the empirical evidence from basic science experiments suggest that this reflex hyper excitability and generation of locomotor behaviors are driven in parallel by neuromodulatory inputs (5HT) and may be necessary for functional recovery following SCI.
The application of this novel concept derived from basic scientific studies to promote recovery following human SCI would appear to be seamless, although the direct translation of the findings can be extremely challenging. Specifically, in the animal models, an implanted catheter facilitates delivery of very specific 5HT agonist compounds directly onto the spinal circuitry. The translation of this technique to humans is hindered by the lack of specific surgical techniques or available pharmacological agents directed towards 5HT receptor subtypes that are safe and effective for human clinical trials. However, oral administration of commonly available 5HTergic agents, such as selective serotonin reuptake inhibitors (SSRIs), may be a viable option to increase central 5HT concentrations in order to facilitate walking recovery in humans. Systematic quantification of how these SSRIs modulate human motor behaviors following SCI, with a specific focus on strength, reflexes, and the recovery of walking ability, are missing.
This video demonstration is a progressive attempt to systematically and quantitatively assess the modulation of reflex activity, volitional strength and ambulation following the acute oral administration of an SSRI in human SCI. Agents are applied on single days to assess the immediate effects on motor function in this patient population, with long-term studies involving repeated drug administration combined with intensive physical interventions.
Medicine, Issue 50, spinal cord injury, spasticity, locomotion, strength, vector coding, biomechanics, reflex, serotonin, human, electromyography
Basics of Multivariate Analysis in Neuroimaging Data
Institutions: Columbia University.
Multivariate analysis techniques for neuroimaging data have recently received increasing attention as they have many attractive features that cannot be easily realized by the more commonly used univariate, voxel-wise, techniques1,5,6,7,8,9
. Multivariate approaches evaluate correlation/covariance of activation across brain regions, rather than proceeding on a voxel-by-voxel basis. Thus, their results can be more easily interpreted as a signature of neural networks. Univariate approaches, on the other hand, cannot directly address interregional correlation in the brain. Multivariate approaches can also result in greater statistical power when compared with univariate techniques, which are forced to employ very stringent corrections for voxel-wise multiple comparisons. Further, multivariate techniques also lend themselves much better to prospective application of results from the analysis of one dataset to entirely new datasets. Multivariate techniques are thus well placed to provide information about mean differences and correlations with behavior, similarly to univariate approaches, with potentially greater statistical power and better reproducibility checks. In contrast to these advantages is the high barrier of entry to the use of multivariate approaches, preventing more widespread application in the community. To the neuroscientist becoming familiar with multivariate analysis techniques, an initial survey of the field might present a bewildering variety of approaches that, although algorithmically similar, are presented with different emphases, typically by people with mathematics backgrounds. We believe that multivariate analysis techniques have sufficient potential to warrant better dissemination. Researchers should be able to employ them in an informed and accessible manner. The current article is an attempt at a didactic introduction of multivariate techniques for the novice. A conceptual introduction is followed with a very simple application to a diagnostic data set from the Alzheimer s Disease Neuroimaging Initiative (ADNI), clearly demonstrating the superior performance of the multivariate approach.
JoVE Neuroscience, Issue 41, fMRI, PET, multivariate analysis, cognitive neuroscience, clinical neuroscience