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Assessing functional performance using computer-based simulations of everyday activities.

ABSTRACT: Current functional capacity (FC) measures for patients with schizophrenia typically involve informant assessments or are in paper and pencil format, requiring in-person administration by a skilled assessor. This approach presents logistic problems and limits the possibilities for remote assessment, an important issue for these patients. This study evaluated the feasibility of using a computer-based assessment battery, including simulations of everyday activities. The battery was compared to in-person standard assessments of cognition and FC with respect to baseline convergence and sensitivity to group differences. The battery, administered on a touch screen computer, included measures of critical everyday activities, including: ATM Banking/Financial Management, Prescriptions Refill via Telephone/Voice Menu System, and Forms Completion (simulating a clinic and patient history form). The sample included 77 older adult patients with schizophrenia and 24 older adult healthy controls that were administered the battery at two time points. The results indicated that the battery was sensitive to group differences in FC. Performance on the battery was also moderately correlated with standard measures of cognitive abilities and showed convergence with standard measures of FC, while demonstrating good test-retest reliability. Our results show that it is feasible to use technology-based assessment protocols with older adults and patients with schizophrenia. The battery overcomes logistic constraints associated with current FC assessment protocols as the battery is computer-based, can be delivered remotely and does not require a healthcare professional for administration.

SUBMITTER: Czaja SJ

PROVIDER: S-EPMC5432393 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Assessing functional performance using computer-based simulations of everyday activities.

Czaja Sara J SJ Loewenstein David A DA Lee Chin Chin CC Fu Shih Hua SH Harvey Philip D PD

Schizophrenia research 20161130

Current functional capacity (FC) measures for patients with schizophrenia typically involve informant assessments or are in paper and pencil format, requiring in-person administration by a skilled assessor. This approach presents logistic problems and limits the possibilities for remote assessment, an important issue for these patients. This study evaluated the feasibility of using a computer-based assessment battery, including simulations of everyday activities. The battery was compared to in-p ...[more]

PMID: 27913159

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Project description:When researchers evaluate brain-computer interface (BCI) systems, we want quantitative answers to questions such as: How good is the system's performance? How good does it need to be? and: Is it capable of reaching the desired level in future? In response to the current lack of objective, quantitative, study-independent approaches, we introduce methods that help to address such questions. We identified three challenges: (I) the need for efficient measurement techniques that adapt rapidly and reliably to capture a wide range of performance levels; (II) the need to express results in a way that allows comparison between similar but non-identical tasks; (III) the need to measure the extent to which certain components of a BCI system (e.g. the signal processing pipeline) not only support BCI performance, but also potentially restrict the maximum level it can reach.For challenge (I), we developed an automatic staircase method that adjusted task difficulty adaptively along a single abstract axis. For challenge (II), we used the rate of information gain between two Bernoulli distributions: one reflecting the observed success rate, the other reflecting chance performance estimated by a matched random-walk method. This measure includes Wolpaw's information transfer rate as a special case, but addresses the latter's limitations including its restriction to item-selection tasks. To validate our approach and address challenge (III), we compared four healthy subjects' performance using an EEG-based BCI, a 'Direct Controller' (a high-performance hardware input device), and a 'Pseudo-BCI Controller' (the same input device, but with control signals processed by the BCI signal processing pipeline).Our results confirm the repeatability and validity of our measures, and indicate that our BCI signal processing pipeline reduced attainable performance by about 33% (21 bits min(-1)).Our approach provides a flexible basis for evaluating BCI performance and its limitations, across a wide range of tasks and task difficulties.

Project description:N-methyl-D-aspartate receptors (NMDARs)-i.e., transmembrane proteins expressed in neurons-play a central role in the molecular mechanisms of learning and memory formation. It is unclear how the known atomic structures of NMDARs determined by x-ray crystallography and electron cryomicroscopy (18 published Protein Data Bank entries) relate to the functional states of NMDARs inferred from electrophysiological recordings (multiple closed, open, preopen, etc. states). We address this problem by using molecular dynamics simulations at atomic resolution, a method successfully applied in the past to much smaller biomolecules. Our simulations predict that several conformations of NMDARs with experimentally determined geometries, including four "nonactive" electron cryomicroscopy structures, rapidly interconvert on submicrosecond timescales and therefore may correspond to the same functional state of the receptor (specifically, one of the closed states). This conclusion is not trivial because these conformational transitions involve changes in certain interatomic distances as large as tens of Å. The simulations also predict differences in the conformational dynamics of the apo and holo (i.e., agonist and coagonist bound) forms of the receptor on the microsecond timescale. To our knowledge, five new conformations of NMDARs, with geometries joining various features from different known experimental structures, are also predicted by the model. The main limitation of this work stems from its limited sampling (30 μs of aggregate length of molecular dynamics trajectories). Though this level significantly exceeds the sampling in previous simulations of parts of NMDARs, it is still much lower than the sampling recently achieved for smaller biomolecules (up to a few milliseconds), thus precluding, in particular, the observation of transitions between different functional states of NMDARs. Despite this limitation, such computational predictions may guide further experimental studies on the structure, dynamics, and function of NMDARs, for example by suggesting optimal locations of spectroscopic probes. Overall, atomic resolution simulations provide, to our knowledge, a novel perspective on the structure and dynamics of NMDARs, complementing information obtained by experimental methods.

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Assessing functional performance using computer-based simulations of everyday activities.

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Assessing functional performance using computer-based simulations of everyday activities.

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