The role of corticospinal tract damage in chronic motor recovery and neurorehabilitation: a pilot study

Background. With diffusion-tensor imaging (DTi) it is possible to estimate the structural characteristics of fiber bundles in vivo. This study used DTi to infer damage to the corticospinal tract (CST) and relates this parameter to (a) the level of residual motor ability at least 1 year poststroke and (b) the outcome of intensive motor rehabilitation with constraint-induced movement therapy (CIMT). Objective. To explore the role of CST damage in recovery and CIMT efficacy. Methods. Ten patients with low-functioning hemiparesis were scanned and tested at baseline, before and after CIMT. Lesion overlap with the CST was indexed as reduced anisotropy compared with a CST variability map derived from 26 controls. Residual motor ability was measured through the Wolf Motor Function Test (WMFT) and the Motor Activity Log (MAL) acquired at baseline. CIMT benefit was assessed through the pre—post treatment comparison of WMFT and MAL performance. Results. Lesion overlap with the CST correlated with residual motor ability at baseline, with greater deficits observed in patients with more extended CST damage. Infarct volume showed no systematic association with residual motor ability. CIMT led to significant improvements in motor function but outcome was not associated with the extent of CST damage or infarct volume. Conclusion. The study gives in vivo support for the proposition that structural CST damage, not infarct volume, is a major predictor for residual functional ability in the chronic state. The results provide initial evidence for positive effects of CIMT in patients with varying, including more severe, CST damage.

Corticospinal tract integrity and lesion volume play different roles in chronic hemiparesis and its improvement through motor practice

Background. Initial evidence suggests that the integrity of the ipsilesional corticospinal tract (CST) after stroke is strongly related to motor function in the chronic state but not the treatment gain induced by motor rehabilitation. Objective. We examined the association of motor status and treatment benefit by testing patients with a wide range of severity of hemiparesis of the left and right upper extremity. Method. Diffusion tensor imaging was performed in 22 patients beyond 12 months after onset of stroke with severe to moderate hemiparesis. Motor function was tested before and after 2 weeks of modified constraint-induced movement therapy. Results. CST integrity, but not lesion volume, correlated with the motor ability measures of the Wolf Motor Function Test and the Motor Activity Log. No differences were found between left and right hemiparesis. Motor performance improved significantly with the treatment regime, and did so equally for patients with left and right arm paresis. However, treatment benefit was not associated with either CST integrity or lesion volume. Conclusion. CST integrity correlated best in this small trial with chronic long-term status but not treatment-induced improvements. The CST may play a different role in the mechanisms mediating long-term outcome compared to those underlying practice-induced gains after a chronic plateau in motor function.

Making 'dirty' nations look clean? The nation state and the problem of selecting and weighting indices as tools for measuring progress towards sustainability

Pressing global environmental problems highlight the need to develop tools to measure progress towards "sustainability." However, some argue that any such attempt inevitably reflects the views of those creating such tools and only produce highly contested notions of "reality." To explore this tension, we critically assesses the Environmental Sustainability Index (ESI), a well-publicized product of the World Economic Forum that is designed to measure 'sustainability' by ranking nations on league tables based on extensive databases of environmental indicators. By recreating this index, and then using statistical tools (principal components analysis) to test relations between various components of the index, we challenge ways in which countries are ranked in the ESI. Based on this analysis, we suggest (1) that the approach taken to aggregate, interpret and present the ESI creates a misleading impression that Western countries are more sustainable than the developing world; (2) that unaccounted methodological biases allowed the authors of the ESI to over-generalize the relative 'sustainability' of different countries; and, (3) that this has resulted in simplistic conclusions on the relation between economic growth and environmental sustainability. This criticism should not be interpreted as a call for the abandonment of efforts to create standardized comparable data. Instead, this paper proposes that indicator selection and data collection should draw on a range of voices, including local stakeholders as well as international experts. We also propose that aggregating data into final league ranking tables is too prone to error and creates the illusion of absolute and categorical interpretations. (c) 2004 Elsevier Ltd. All rights reserved.

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.

Sparse kernel density construction using orthogonal forward regression with leave-one-out test score and local regularization

This paper presents an efficient construction algorithm for obtaining sparse kernel density estimates based on a regression approach that directly optimizes model generalization capability. Computational efficiency of the density construction is ensured using an orthogonal forward regression, and the algorithm incrementally minimizes the leave-one-out test score. A local regularization method is incorporated naturally into the density construction process to further enforce sparsity. An additional advantage of the proposed algorithm is that it is fully automatic and the user is not required to specify any criterion to terminate the density construction procedure. This is in contrast to an existing state-of-art kernel density estimation method using the support vector machine (SVM), where the user is required to specify some critical algorithm parameter. Several examples are included to demonstrate the ability of the proposed algorithm to effectively construct a very sparse kernel density estimate with comparable accuracy to that of the full sample optimized Parzen window density estimate. Our experimental results also demonstrate that the proposed algorithm compares favorably with the SVM method, in terms of both test accuracy and sparsity, for constructing kernel density estimates.

Colon extended physiologically based extraction test (CE-PBET) increases bioaccessibility of soil-bound PAH

Assessment of the risk to human health posed by contaminated land may be seriously overestimated if reliant on total pollutant concentration. In vitro extraction tests, such as the physiologically based extraction test (PBET), imitate the physicochemical conditions of the human gastro-intestinal tract and offer a more practicable alternative for routine testing purposes. However, even though passage through the colon accounts for approximately 80% of the transit time through the human digestive tract and the typical contents of the colon in vivo are a carbohydrate-rich aqueous medium with the potential to promote desorption of organic pollutants, PBET comprises stomach and small intestine compartments only. Through addition of an eight-hour colon compartment to PBET and use of a carbohydrate-rich fed-state medium we demonstrated that colon-extended PBET (CE-PBET) in- creased assessments of soil-bound PAH bioaccessibility by up to 50% in laboratory soils and a factor of 4 in field soils. We attribute this increased bioaccessibility to a combination of the additional extraction time and the presence of carbohydrates in the colon compartment, both of which favor PAH desorption from soil. We propose that future assessments of the bioaccessibility of organic pollutants in soils using physiologically based extraction tests should have a colon compartment as in CE-PBET.

State estimation using model order reduction for unstable systems

The problem of state estimation occurs in many applications of fluid flow. For example, to produce a reliable weather forecast it is essential to find the best possible estimate of the true state of the atmosphere. To find this best estimate a nonlinear least squares problem has to be solved subject to dynamical system constraints. Usually this is solved iteratively by an approximate Gauss–Newton method where the underlying discrete linear system is in general unstable. In this paper we propose a new method for deriving low order approximations to the problem based on a recently developed model reduction method for unstable systems. To illustrate the theoretical results, numerical experiments are performed using a two-dimensional Eady model – a simple model of baroclinic instability, which is the dominant mechanism for the growth of storms at mid-latitudes. It is a suitable test model to show the benefit that may be obtained by using model reduction techniques to approximate unstable systems within the state estimation problem.

State estimation using the particle filter with mode tracking

A particle filter is a data assimilation scheme that employs a fully nonlinear, non-Gaussian analysis step. Unfortunately as the size of the state grows the number of ensemble members required for the particle filter to converge to the true solution increases exponentially. To overcome this Vaswani [Vaswani N. 2008. IEEE Trans Signal Process 56:4583–97] proposed a new method known as mode tracking to improve the efficiency of the particle filter. When mode tracking, the state is split into two subspaces. One subspace is forecast using the particle filter, the other is treated so that its values are set equal to the mode of the marginal pdf. There are many ways to split the state. One hypothesis is that the best results should be obtained from the particle filter with mode tracking when we mode track the maximum number of unimodal dimensions. The aim of this paper is to test this hypothesis using the three dimensional stochastic Lorenz equations with direct observations. It is found that mode tracking the maximum number of unimodal dimensions does not always provide the best result. The best choice of states to mode track depends on the number of particles used and the accuracy and frequency of the observations.

An item response analysis of the motor and behavioral subscales of the unified Huntington's disease rating scale in huntington disease gene expansion carriers

Although the Unified Huntington's Disease Rating Scale (UHDRS) is widely used in the assessment of Huntington disease (HD), the ability of individual items to discriminate individual differences in motor or behavioral manifestations has not been extensively studied in HD gene expansion carriers without a motor-defined clinical diagnosis (ie, prodromal-HD or prHD). To elucidate the relationship between scores on individual motor and behavioral UHDRS items and total score for each subscale, a nonparametric item response analysis was performed on retrospective data from 2 multicenter longitudinal studies. Motor and behavioral assessments were supplied for 737 prHD individuals with data from 2114 visits (PREDICT-HD) and 686 HD individuals with data from 1482 visits (REGISTRY). Option characteristic curves were generated for UHDRS subscale items in relation to their subscale score. In prHD, overall severity of motor signs was low, and participants had scores of 2 or above on very few items. In HD, motor items that assessed ocular pursuit, saccade initiation, finger tapping, tandem walking, and to a lesser extent, saccade velocity, dysarthria, tongue protrusion, pronation/supination, Luria, bradykinesia, choreas, gait, and balance on the retropulsion test were found to discriminate individual differences across a broad range of motor severity. In prHD, depressed mood, anxiety, and irritable behavior demonstrated good discriminative properties. In HD, depressed mood demonstrated a good relationship with the overall behavioral score. These data suggest that at least some UHDRS items appear to have utility across a broad range of severity, although many items demonstrate problematic features.

An experimental manipulation of responsibility in children: a test of the inflated responsibility model of obsessive-compulsive disorder

The objective of this study was to investigate whether Salkovskis (1985) inflated responsibility model of obsessive-compulsive disorder (OCD) applied to children. In an experimental design, 81 children aged 9– 12 years were randomly allocated to three conditions: an inflated responsibility group, a moderate responsibility group, and a reduced responsibility group. In all groups children were asked to sort sweets according to whether or not they contained nuts. At baseline the groups did not differ on children’s self reported anxiety, depression, obsessive-compulsive symptoms or on inflated responsibility beliefs. The experimental manipulation successfully changed children’s perceptions of responsibility. During the sorting task time taken to complete the task, checking behaviours, hesitations, and anxiety were recorded. There was a significant effect of responsibility level on the behavioural variables of time taken, hesitations and check; as perceived responsibility increased children took longer to complete the task and checked and hesitated more often. There was no between-group difference in children’s self reported state anxiety. The results offer preliminary support for the link between inflated responsibility and increased checking behaviours in children and add to the small but growing literature suggesting that cognitive models of OCD may apply to children.

Advances in sequential data assimilation and numerical weather forecasting: an Ensemble Transform Kalman-Bucy Filter, a study on clustering in deterministic Ensemble Square Root Filters, and a test of a new time stepping scheme in an atmospheric model

This dissertation deals with aspects of sequential data assimilation (in particular ensemble Kalman filtering) and numerical weather forecasting. In the first part, the recently formulated Ensemble Kalman-Bucy (EnKBF) filter is revisited. It is shown that the previously used numerical integration scheme fails when the magnitude of the background error covariance grows beyond that of the observational error covariance in the forecast window. Therefore, we present a suitable integration scheme that handles the stiffening of the differential equations involved and doesn’t represent further computational expense. Moreover, a transform-based alternative to the EnKBF is developed: under this scheme, the operations are performed in the ensemble space instead of in the state space. Advantages of this formulation are explained. For the first time, the EnKBF is implemented in an atmospheric model. The second part of this work deals with ensemble clustering, a phenomenon that arises when performing data assimilation using of deterministic ensemble square root filters in highly nonlinear forecast models. Namely, an M-member ensemble detaches into an outlier and a cluster of M-1 members. Previous works may suggest that this issue represents a failure of EnSRFs; this work dispels that notion. It is shown that ensemble clustering can be reverted also due to nonlinear processes, in particular the alternation between nonlinear expansion and compression of the ensemble for different regions of the attractor. Some EnSRFs that use random rotations have been developed to overcome this issue; these formulations are analyzed and their advantages and disadvantages with respect to common EnSRFs are discussed. The third and last part contains the implementation of the Robert-Asselin-Williams (RAW) filter in an atmospheric model. The RAW filter is an improvement to the widely popular Robert-Asselin filter that successfully suppresses spurious computational waves while avoiding any distortion in the mean value of the function. Using statistical significance tests both at the local and field level, it is shown that the climatology of the SPEEDY model is not modified by the changed time stepping scheme; hence, no retuning of the parameterizations is required. It is found the accuracy of the medium-term forecasts is increased by using the RAW filter.

Analysis of functional networks involved in motor execution and motor imagery using combined hierarchical clustering analysis and independent component analysis

Cognitive experiments involving motor execution (ME) and motor imagery (MI) have been intensively studied using functional magnetic resonance imaging (fMRI). However, the functional networks of a multitask paradigm which include ME and MI were not widely explored. In this article, we aimed to investigate the functional networks involved in MI and ME using a method combining the hierarchical clustering analysis (HCA) and the independent component analysis (ICA). Ten right-handed subjects were recruited to participate a multitask experiment with conditions such as visual cue, MI, ME and rest. The results showed that four activation clusters were found including parts of the visual network, ME network, the MI network and parts of the resting state network. Furthermore, the integration among these functional networks was also revealed. The findings further demonstrated that the combined HCA with ICA approach was an effective method to analyze the fMRI data of multitasks.

The plasticity of the mirror system: how reward learning modulates cortical motor simulation of others

Cortical motor simulation supports the understanding of others' actions and intentions. This mechanism is thought to rely on the mirror neuron system (MNS), a brain network that is active both during action execution and observation. Indirect evidence suggests that alpha/beta suppression, an electroencephalographic (EEG) index of MNS activity, is modulated by reward. In this study we aimed to test the plasticity of the MNS by directly investigating the link between alpha/beta suppression and reward. 40 individuals from a general population sample took part in an evaluative conditioning experiment, where different neutral faces were associated with high or low reward values. In the test phase, EEG was recorded while participants viewed videoclips of happy expressions made by the conditioned faces. Alpha/beta suppression (identified using event-related desynchronisation of specific independent components) in response to rewarding faces was found to be greater than for non-rewarding faces. This result provides a mechanistic insight into the plasticity of the MNS and, more generally, into the role of reward in modulating physiological responses linked to empathy.

Memo test: standardisation of computerised assessment of auditory verbal short-term memory

Short-term memory (STM) impairments are prevalent in adults with acquired brain injuries. While there are several published tests to assess these impairments, the majority require speech production, e.g. digit span (Wechsler, 1987). This feature may make them unsuitable for people with aphasia and motor speech disorders because of word finding difficulties and speech demands respectively. If patients perceive the speech demands of the test to be high, the may not engage with testing. Furthermore, existing STM tests are mainly ‘pen-and-paper’ tests, which can jeopardise accuracy. To address these shortcomings, we designed and standardised a novel computerised test that does not require speech output and because of the computerised delivery it would enable clinicians identify STM impairments with greater precision than current tests. The matching listening span tasks, similar to the non-normed PALPA 13 (Kay, Lesser & Coltheart, 1992) is used to test short-term memory for serial order of spoken items. Sequences of digits are presented in pairs. The person hears the first sequence, followed by the second sequence and s/he decides whether the two sequences are the same or different. In the computerised test, the sequences are presented in live voice recordings on a portable computer through a software application (Molero Martin, Laird, Hwang & Salis 2013). We collected normative data from healthy older adults (N=22-24) using digits, real words (one- and two-syllables) and non-words (one- and two- syllables). Their performance was scored following two systems. The Highest Span system was the highest span length (e.g. 2-8) at which a participant correctly responded to over 7 out of 10 trials at the highest sequence length. Test re-test reliability was also tested in a subgroup of participants. The test will be available as free of charge for clinicians and researchers to use.

Visual processing of optic flow and motor control in the human posterior cingulate sulcus

Previous studies have shown that the human posterior cingulate contains a visual processing area selective for optic flow (CSv). However, other studies performed in both humans and monkeys have identified a somatotopic motor region at the same location (CMA). Taken together, these findings suggested the possibility that the posterior cingulate contains a single visuomotor integration region. To test this idea we used fMRI to identify both visual and motor areas of the posterior cingulate in the same brains and to test the activity of those regions during a visuomotor task. Results indicated that rather than a single visuomotor region the posterior cingulate contains adjacent but separate motor and visual regions. CSv lies in the fundus of the cingulate sulcus, while CMA lies in the dorsal bank of the sulcus, slightly superior in terms of stereotaxic coordinates. A surprising and novel finding was that activity in CSv was suppressed during the visuomotor task, despite the visual stimulus being identical to that used to localize the region. This may provide an important clue to the specific role played by this region in the utilization of optic flow to control self-motion.