An organizational perspective on goal setting in community-based brain injury rehabilitation

Purpose. To use a taxonomy of goal content, developed in community-based brain injury rehabilitation to examine and compare the content of goals set within two different service settings; and to further examine the potential of the taxonomy to be a reliable and comprehensive framework for classifying goals. Method. Qualitative analysis and categorization of 1492 goal statements extracted from a community-based brain injury rehabilitation service over two time periods (1996-97, 1998-99), and cross-organizational comparison of ratings of goal classifications using a random sample of 100 goal statements drawn from this data set and the original 1765 goal statements used in developing the taxonomy. Results. Application of the taxonomy beyond the original service setting in which it was developed indicated a strong inter-rater reliability, with a high test-retest agreement reported over time. For both services, a small number of categories accounted for a substantial proportion of goals set within the two time periods, while considerable change was evident in goals between the two periods for one service. Further, both placed emphasis on individually focused goals rather than relationship or family-related goals. Conclusion. The taxonomy provides a reliable means for classifying goals and is a useful tool for exploration of the multiple influences on goal setting. Further application of the taxonomy to examine the relative influence on goal setting of client factors versus a range of organizational factors would be beneficial.

Analysis of spatial patterns in histological sections of brain tissue using a method based on regression

A method of determining the spatial pattern of any histological feature in sections of brain tissue which can be measured quantitatively is described and compared with a previously described method. A measurement of a histological feature such as density, area, amount or load is obtained for a series of contiguous sample fields. The regression coefficient (β) is calculated from the measurements taken in pairs, first in pairs of adjacent samples and then in pairs of samples taken at increasing degrees of separation between them, i.e. separated by 2, 3, 4,..., n units. A plot of β versus the degree of separation between the pairs of sample fields reveals whether the histological feature is distributed randomly, uniformly or in clusters. If the feature is clustered, the analysis determines whether the clusters are randomly or regularly distributed, the mean size of the clusters and the spacing of the clusters. The method is simple to apply and interpret and is illustrated using simulated data and studies of the spatial patterns of blood vessels in the cerebral cortex of normal brain, the degree of vacuolation of the cortex in patients with Creutzfeldt-Jacob disease (CJD) and the characteristic lesions present in Alzheimer's disease (AD). Copyright (C) 2000 Elsevier Science B.V.

Which physiological components are more suitable for visual ERP based brain-computer interface?:A preliminary MEG/EEG study

We investigated which evoked response component occurring in the first 800 ms after stimulus presentation was most suitable to be used in a classical P300-based brain-computer interface speller protocol. Data was acquired from 275 Magnetoencephalographic sensors in two subjects and from 61 Electroencephalographic sensors in four. To better characterize the evoked physiological responses and minimize the effect of response overlap, a 1000 ms Inter Stimulus Interval was preferred to the short (

Suppression of phase synchronisation in network based on cat’s brain

We wish to acknowledge the support of the Brazilian agencies: CNPq, CAPES, and FAPESP (2015/07311-7 and 2011/19296-1).

Introduction of novel video-based tasks to clinical fMRI: Comparing traditional fMRI tasks with novel video-based tasks for mapping brain language areas

Recently, blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) has become a routine clinical procedure for localization of language and motor brain regions and has been replacing more invasive preoperative procedures. However, the fMRI results from these tasks are not always reproducible even from the same patient. Evaluating the reproducibility of language and speech mapping is especially complicated due to the complex brain circuitry that may become activated during the functional task. Non-language areas such as sensory, attention, decision-making, and motor brain regions may also be activated in addition to the specific language regions during a traditional sentence-completion task. In this study, I test a new approach, which utilizes 4-minute video-based tasks, to map language and speech brain regions for patients undergoing brain surgery. Results from 35 subjects have shown that the video-based task activates Wernicke’s area, as well as Broca’s area in most subjects. The computed laterality indices, which indicate the dominant hemisphere from that functional task, have indicated left dominance from the video-based tasks. This study has shown that the video-based task may be an alternative method for localization of language and speech brain regions for patients who are unable to complete the sentence-completion task.

Information-Based Approaches of Noninvasive Transcranial Brain Stimulation

Progress in cognitive neuroscience relies on methodological developments to increase the specificity of knowledge obtained regarding brain function. For example, in functional neuroimaging the current trend is to study the type of information carried by brain regions rather than simply compare activation levels induced by task manipulations. In this context noninvasive transcranial brain stimulation (NTBS) in the study of cognitive functions may appear coarse and old fashioned in its conventional uses. However, in their multitude of parameters, and by coupling them with behavioral manipulations, NTBS protocols can reach the specificity of imaging techniques. Here we review the different paradigms that have aimed to accomplish this in both basic science and clinical settings and follow the general philosophy of information-based approache

Fluorine-18-labeled estrogens, progestins and corticosteroids for receptor-based imaging of breast tumors and target areas of the brain

Estrogens can be labeled with the positron-emitting radionuclide fluorine-18 (t$\sb{1/2}$ = 110 min) by fluoride ion (n-Bu$\sb4$N$\sp{18}$F) displacement of a 16$\beta$-trifluoromethanesulfonate (triflate) derivative of the corresponding estrone 3-triflate, and purification by HPLC. That sequence has been used to synthesize the 11$\beta$-methoxy 1 and 11$\beta$-ethyl 2 analogues of the breast tumor imaging agent, 16$\alpha$-($\sp{18}$F) fluoro-17$\beta$-estradiol (FES). Tissue distribution studies of 1 and 2 in immature female rats show high selectivity for target tissue (T, uterus) vs non-target (NT, muscle and lung), with T/NT ratios being 43 and 17 at one hour after injection for 1 and 2, respectively. The parent estrogen FES has previously been shown to display an intermediate value for tissue selectivity.

Brain emotional learning based control of a SDOF structural system with a MR damper

This paper describes the application of a Brain Emotional Learning (BEL) controller to improve the response of a SDOF structural system under an earthquake excitation using a magnetorheological (MR) damper. The main goal is to study the performance of a BEL based semi-active control system to generate the control signal for a MR damper. The proposed approach consists of a two controllers: a primary controller based on a BEL algorithm that determines the desired damping force from the system response and a secondary controller that modifies the input current to the MR damper to generate a reference damping force. A parametric model of the damper is used to predict the damping force based on the piston motion and also the current input. A Simulink model of the structural system is developed to analyze the effectiveness of the semi-active controller. Finally, the numerical results are presented and discussed.

Human brain regions required for the dividing and switching of attention between two features of a single object

This combined PET and ERP study was designed to identify the brain regions activated in switching and divided attention between different features of a single object using matched sensory stimuli and motor response. The ERP data have previously been reported in this journal [64]. We now present the corresponding PET data. We identified partially overlapping neural networks with paradigms requiring the switching or dividing of attention between the elements of complex visual stimuli. Regions of activation were found in the prefrontal and temporal cortices and cerebellum. Each task resulted in different prefrontal cortical regions of activation lending support to the functional subspecialisation of the prefrontal and temporal cortices being based on the cognitive operations required rather than the stimuli themselves.