The preparation and readiness for voluntary movement: a high-field event-related fMRI study of the Bereitschafts-BOLD response

Activity within motor areas of the cortex begins to increase 1 to 2 s prior to voluntary self-initiated movement (termed the Bereitschaftspotential or readiness potential). There has been much speculation and debate over the precise source of this early premovement activity as it is important for understanding the roles of higher order motor areas in the preparation and readiness for voluntary movement. In this study, we use high-field (3-T) event-related fMRI with high temporal sampling (partial brain volumes every 250 ms) to specifically examine hemodynamic response time courses during the preparation, readiness, and execution of purely self-initiated voluntary movement. Five right-handed healthy volunteers performed a rapid sequential finger-to-thumb movement performed at self-determined times (12-15 trials). Functional images for each trial were temporally aligned and the averaged time series for each subject was iteratively correlated with a canonical hemodynamic response function progressively shifted in time. This analysis method identified areas of activation without constraining hemodynamic response timing. All subjects showed activation within frontal mesial areas, including supplementary motor area (SMA) and cingulate motor areas, as well as activation in left primary sensorimotor areas. The time courses of hemodynamic responses showed a great deal of variability in shape and timing between subjects; however, four subjects clearly showed earlier relative hemodynamic responses within SMA/cingulate motor areas compared with left primary motor areas. These results provide further evidence that the SMA and cingulate motor areas are major contributors to early stage premovement activity and play an important role in the preparation and readiness for voluntary movement. (C) 2003 Elsevier Inc. All rights reserved.

Predicting energy requirements in the clinical setting: Are current methods evidence based?

Estimating energy requirements is necessary in clinical practice when indirect calorimetry is impractical. This paper systematically reviews current methods for estimating energy requirements. Conclusions include: there is discrepancy between the characteristics of populations upon which predictive equations are based and current populations; tools are not well understood, and patient care can be compromised by inappropriate application of the tools. Data comparing tools and methods are presented and issues for practitioners are discussed. (C) 2003 International Life Sciences Institute.

Formal methods within a totally functional approach to programming

Taking functional programming to its extremities in search of simplicity still requires integration with other development (e.g. formal) methods. Induction is the key to deriving and verifying functional programs, but can be simplified through packaging proofs with functions, particularly folds, on data (structures). Totally Functional Programming avoids the complexities of interpretation by directly representing data (structures) as platonic combinators - the functions characteristic to the data. The link between the two simplifications is that platonic combinators are a kind of partially-applied fold, which means that platonic combinators inherit fold-theoretic properties, but with some apparent simplifications due to the platonic combinator representation. However, despite observable behaviour within functional programming that suggests that TFP is widely-applicable, significant work remains before TFP as such could be widely adopted.

Assessing cost-effectiveness - Mental health: introduction to the study and methods

Objective: The Assessing Cost-Effectiveness - Mental Health (ACE-MH) study aims to assess from a health sector perspective, whether there are options for change that could improve the effectiveness and efficiency of Australia's current mental health services by directing available resources toward 'best practice' cost-effective services. Method: The use of standardized evaluation methods addresses the reservations expressed by many economists about the simplistic use of League Tables based on economic studies confounded by differences in methods, context and setting. The cost-effectiveness ratio for each intervention is calculated using economic and epidemiological data. This includes systematic reviews and randomised controlled trials for efficacy, the Australian Surveys of Mental Health and Wellbeing for current practice and a combination of trials and longitudinal studies for adherence. The cost-effectiveness ratios are presented as cost (A$) per disability-adjusted life year (DALY) saved with a 95% uncertainty interval based on Monte Carlo simulation modelling. An assessment of interventions on 'second filter' criteria ('equity', 'strength of evidence', 'feasibility' and 'acceptability to stakeholders') allows broader concepts of 'benefit' to be taken into account, as well as factors that might influence policy judgements in addition to cost-effectiveness ratios. Conclusions: The main limitation of the study is in the translation of the effect size from trials into a change in the DALY disability weight, which required the use of newly developed methods. While comparisons within disorders are valid, comparisons across disorders should be made with caution. A series of articles is planned to present the results.

Computational methods for prediction of T-cell epitopes - a framework for modelling, testing, and applications

Computational models complement laboratory experimentation for efficient identification of MHC-binding peptides and T-cell epitopes. Methods for prediction of MHC-binding peptides include binding motifs, quantitative matrices, artificial neural networks, hidden Markov models, and molecular modelling. Models derived by these methods have been successfully used for prediction of T-cell epitopes in cancer, autoimmunity, infectious disease, and allergy. For maximum benefit, the use of computer models must be treated as experiments analogous to standard laboratory procedures and performed according to strict standards. This requires careful selection of data for model building, and adequate testing and validation. A range of web-based databases and MHC-binding prediction programs are available. Although some available prediction programs for particular MHC alleles have reasonable accuracy, there is no guarantee that all models produce good quality predictions. In this article, we present and discuss a framework for modelling, testing, and applications of computational methods used in predictions of T-cell epitopes. (C) 2004 Elsevier Inc. All rights reserved.

Premovement activity of the pre-supplementary motor area and the readiness for action: Studies of time-resolved event-related functional MRI

The supplementary motor area (SMA) is thought to play in important role in the preparation and organisation of voluntary movement. It has long been known that cortical activity begins to increase up to 2 s prior to voluntary self-initiated movement. This increasing premovement activity measured in EEG is known as the Bereitschaftspotential or readiness potential. Modern functional brain imaging methods, using event-related and time-resolved functional MRI techniques, are beginning to reveal the role of the SMA, and in particular the more anterior pre-SMA, in premovement activity associated with the readiness for action. In this paper we review recent studies using event-related time-resolved fMRI methods to examine the time-course of activation changes within the SMA throughout the preparation, readiness and execution of action. These studies suggest that the preSMA plays a common role in encoding or representing actions prior to our own voluntary self-initiated movements, during motor imagery, and from the observation of others' actions. We suggest that the pre-SMA generates and encodes motor representations which are then maintained in readiness for action. (c) 2005 Elsevier B.V. All rights reserved.

Special issue on methods and learning in functional MRI: Introductory remarks

This special issue represents a further exploration of some issues raised at a symposium entitled “Functional magnetic resonance imaging: From methods to madness” presented during the 15th annual Theoretical and Experimental Neuropsychology (TENNET XV) meeting in Montreal, Canada in June, 2004. The special issue’s theme is methods and learning in functional magnetic resonance imaging (fMRI), and it comprises 6 articles (3 reviews and 3 empirical studies). The first (Amaro and Barker) provides a beginners guide to fMRI and the BOLD effect (perhaps an alternative title might have been “fMRI for dummies”). While fMRI is now commonplace, there are still researchers who have yet to employ it as an experimental method and need some basic questions answered before they venture into new territory. This article should serve them well. A key issue of interest at the symposium was how fMRI could be used to elucidate cerebral mechanisms responsible for new learning. The next 4 articles address this directly, with the first (Little and Thulborn) an overview of data from fMRI studies of category-learning, and the second from the same laboratory (Little, Shin, Siscol, and Thulborn) an empirical investigation of changes in brain activity occurring across different stages of learning. While a role for medial temporal lobe (MTL) structures in episodic memory encoding has been acknowledged for some time, the different experimental tasks and stimuli employed across neuroimaging studies have not surprisingly produced conflicting data in terms of the precise subregion(s) involved. The next paper (Parsons, Haut, Lemieux, Moran, and Leach) addresses this by examining effects of stimulus modality during verbal memory encoding. Typically, BOLD fMRI studies of learning are conducted over short time scales, however, the fourth paper in this series (Olson, Rao, Moore, Wang, Detre, and Aguirre) describes an empirical investigation of learning occurring over a longer than usual period, achieving this by employing a relatively novel technique called perfusion fMRI. This technique shows considerable promise for future studies. The final article in this special issue (de Zubicaray) represents a departure from the more familiar cognitive neuroscience applications of fMRI, instead describing how neuroimaging studies might be conducted to both inform and constrain information processing models of cognition.