Identifying rate-limiting nodes in large-scale cortical networks for visuospatial processing: an illustration using fMRI

With the advent of functional neuroimaging techniques, in particular functional magnetic resonance imaging (fMRI), we have gained greater insight into the neural correlates of visuospatial function. However, it may not always be easy to identify the cerebral regions most specifically associated with performance on a given task. One approach is to examine the quantitative relationships between regional activation and behavioral performance measures. In the present study, we investigated the functional neuroanatomy of two different visuospatial processing tasks, judgement of line orientation and mental rotation. Twenty-four normal participants were scanned with fMRI using blocked periodic designs for experimental task presentation. Accuracy and reaction time (RT) to each trial of both activation and baseline conditions in each experiment was recorded. Both experiments activated dorsal and ventral visual cortical areas as well as dorsolateral prefrontal cortex. More regionally specific associations with task performance were identified by estimating the association between (sinusoidal) power of functional response and mean RT to the activation condition; a permutation test based on spatial statistics was used for inference. There was significant behavioral-physiological association in right ventral extrastriate cortex for the line orientation task and in bilateral (predominantly right) superior parietal lobule for the mental rotation task. Comparable associations were not found between power of response and RT to the baseline conditions of the tasks. These data suggest that one region in a neurocognitive network may be most strongly associated with behavioral performance and this may be regarded as the computationally least efficient or rate-limiting node of the network.

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. (C) 2003 Elsevier Science B.V. All rights reserved.

Tracking the states of a nonlinear and nonstationary system in the weight-space of artificial neural networks

We propose a novel interpretation and usage of Neural Network (NN) in modeling physiological signals, which are allowed to be nonlinear and/or nonstationary. The method consists of training a NN for the k-step prediction of a physiological signal, and then examining the connection-weight-space (CWS) of the NN to extract information about the signal generator mechanism. We de. ne a novel feature, Normalized Vector Separation (gamma(ij)), to measure the separation of two arbitrary states i and j in the CWS and use it to track the state changes of the generating system. The performance of the method is examined via synthetic signals and clinical EEG. Synthetic data indicates that gamma(ij) can track the system down to a SNR of 3.5 dB. Clinical data obtained from three patients undergoing carotid endarterectomy of the brain showed that EEG could be modeled (within a root-means-squared-error of 0.01) by the proposed method, and the blood perfusion state of the brain could be monitored via gamma(ij), with small NNs having no more than 21 connection weight altogether.

Measurement of functional ability following traumatic brain injury using the Clinical Outcomes Variable Scale: A reliability study

This study determined the inter-tester and intra-tester reliability of physiotherapists measuring functional motor ability of traumatic brain injury clients using the Clinical Outcomes Variable Scale (COVS). To test inter-tester reliability, 14 physiotherapists scored the ability of 16 videotaped patients to execute the items that comprise the COVS. Intra-tester reliability was determined by four physiotherapists repeating their assessments after one week, and three months later. The intra-class correlation coefficients (ICC) were very high for both inter-tester reliability (ICC > 0.97 for total COVS scores, ICC > 0.93 for individual COVS items) and intra-tester reliability (ICC > 0.97). This study demonstrates that physiotherapists are reliable in the administration of the COVS.

A fast cross-entropy method for estimating buffer overflows in queuing networks

In this paper, we propose a fast adaptive importance sampling method for the efficient simulation of buffer overflow probabilities in queueing networks. The method comprises three stages. First, we estimate the minimum cross-entropy tilting parameter for a small buffer level; next, we use this as a starting value for the estimation of the optimal tilting parameter for the actual (large) buffer level. Finally, the tilting parameter just found is used to estimate the overflow probability of interest. We study various properties of the method in more detail for the M/M/1 queue and conjecture that similar properties also hold for quite general queueing networks. Numerical results support this conjecture and demonstrate the high efficiency of the proposed algorithm.

A hybrid planning method for transmission networks in a deregulated environment

The reconstruction of power industries has brought fundamental changes to both power system operation and planning. This paper presents a new planning method using multi-objective optimization (MOOP) technique, as well as human knowledge, to expand the transmission network in open access schemes. The method starts with a candidate pool of feasible expansion plans. Consequent selection of the best candidates is carried out through a MOOP approach, of which multiple objectives are tackled simultaneously, aiming at integrating the market operation and planning as one unified process in context of deregulated system. Human knowledge has been applied in both stages to ensure the selection with practical engineering and management concerns. The expansion plan from MOOP is assessed by reliability criteria before it is finalized. The proposed method has been tested with the IEEE 14-bus system and relevant analyses and discussions have been presented.

Ethanol inhibition of brain ornithine decarboxylase activity in the postnatal rat

The purpose of this study was to determine the relationship between ornithine decarboxylase activity (ODC; a marker for perturbed cell development), the blood alcohol level, and alcohol-induced microencephaly in the developing rat brain after binge treatment with ethanol vapour. By manipulating ethanol flow we were able to adjust vapour concentrations (24-65 mg ethanol/l air) such that an acute exposure of ethanol vapour for 3 h resulted in a range of blood alcohol levels (2.3-5.5 mg/ml). Acute studies showed that ethanol dose-dependently inhibited rat hippocampal and cerebellar ODC activity at PND4-PND10. There was a significant correlation between the blood alcohol level and degree of inhibition at all ages tested. Chronic treatment from PND4 to PND9 caused a significant decrease in both brain to body weight ratio and in hippocampal and cerebellar ODC activities at PND10. These results indicate that ethanol-induced disruption in ODC could play a significant role in ethanol's teratogenic effects during early postnatal development. (C) 1998 Elsevier Science Inc.

Chondroitin sulfates modulate axon guidance in embryonic Xenopus brain

Chondroitin sulfate proteoglycans display both inhibitory and stimulatory effects on cell adhesion and neurite outgrowth in vitro. The functional activity of these proteoglycans appears to be context specific and dependent on the presence of different chondroitin sulfate-binding molecules. Little is known about the role of chondroitin sulfate proteoglycans in the growth and guidance of axons in vivo. To address this question, we examined the effects of exogenous soluble chondroitin sulfates on the growth and guidance of axons arising from a subpopulation of neurons in the vertebrate brain which express NOC-2, a novel glycoform of the neural cell adhesion molecule N-CAM. Intact brains of stage 28 Xenopus embryos were unilaterally exposed to medium containing soluble exogenous chondroitin sulfates. When exposed to chondroitin sulfate, NOC-2(+) axons within the tract of the postoptic commissure failed to follow their normal trajectory across the ventral midline via the ventral commissure in the midbrain. Instead, these axons either stalled or grew into the dorsal midbrain or continued growing longitudinally within the ventral longitudinal tract. These findings suggest that chondroitin sulfate proteoglycans indirectly modulate the growth and guidance of a subpopulation of forebrain axons by regulating either matrix-bound or cell surface cues at specific choice points within the developing vertebrate brain. (C) 1998 Academic Press.

A longitudinal study of self-awareness: Functional deficits underestimated by persons with brain injury

A longitudinal study of 55 adults with severe traumatic brain injury (TBI) investigated the areas of function for which they lacked self-awareness of their level of competency. Data were collected at 3 and 12 months post-injury using the Patient Competency Rating Scale. Self-awareness was measured by comparing patient self-ratings with the ratings of an infor mant. The results were consistent with previous studies, indicating that self-awareness was most impaired for activities with a large cognitive and socioemotional component, and least impaired for basic activities of daily living, memory activities, and overt emotional responses. For most areas of function that were overestimated at 3 months post-injury, self-awareness subsequently improved during the first year after injury.

Cluster analysis of self-awareness levels in adults with traumatic brain injury and relationship to outcome

The purpose of this study was to investigate the relationship between self-awareness, emotional distress, motivation, and outcome in adults with severe traumatic brain injury. A sample of 55 patients were selected from 120 consecutive patients with severe traumatic brain injury admitted to the rehabilitation unit of a large metropolitan public hospital. Subjects received multidisciplinary inpatient rehabilitation and different types of outpatient rehabilitation and community-based services according to availability and need, Measures used in the cluster analysis were the Patient Competency Rating Scale, Self-Awareness of Deficits Interview, Head Injury Behavior Scale, Change Assessment Questionnaire, the Beck Depression Inventory, and Beck Anxiety Inventory; outcome measures were the Disability Rating Scale, Community Integration Questionnaire, and Sickness Impact Profile. A three-cluster solution was selected, with groups labeled as high self-awareness (n = 23), low self-awareness (n = 23), and good recovery (n = 8). The high self-awareness cluster had significantly higher levels of self-awareness, motivation, and emotional distress than the low self-awareness cluster but did not differ significantly in outcome. Self-awareness after brain injury is associated with greater motivation to change behavior and higher levels of depression and anxiety; however, it was not clear that this heightened motivation actually led to any improvement in outcome. Rehabilitation timing and approach may need to be tailored to match the individual's level of self-awareness, motivation, and emotional distress.

Increased expression of mitochondrial genes in human alcoholic brain revealed by differential display

Polymerase chain reaction (PCR)-based differential display was used to screen for alterations in gene expression in the mesolimbic system of the human alcoholic brain. Total RNA was extracted from the nucleus accumbens of five alcoholic and five control brains. A selected subpopulation of mRNA was reverse-transcribed to cDNA and amplified by PCR. A differentially expressed cDNA fragment was recovered, cloned, and sequenced. Full sequence analysis of this 467 bp fragment revealed 98.2% homology with the human mitochondrial 12S rRNA gene. Dot-blot analysis showed increased expression of this gem in nucleus accumbens and hippocampus, but not in the superior frontal cortex, primary motor cortex, caudate, and pallidus/putamen In a total of eight human alcoholic brains, compared with seven control brains. A similar increased expression was observed by dot-blot analysis, using RNA from the cerebral cortex of rats chronically treated with alcohol vapor. Hybridization of a 16S rRNA oligonucleotide probe indicated that the expression of both rRNAs genes was significantly increased in nucleus accumbens. These results indicate that chronic alcohol consumption induces alteration in expression of mitochondrial genes in selected brain regions. The altered gene expression may reflect mitochondrial dysfunction In the alcohol-affected brain.

A reproducible method for automated extraction of brain volumes from 3D human head MR images

An automated method for extracting brain volumes from three commonly acquired three-dimensional (3D) MR images (proton density, T1 weighted, and T2-weighted) of the human head is described. The procedure is divided into four levels: preprocessing, segmentation, scalp removal, and postprocessing. A user-provided reference point is the sole operator-dependent input required, The method's parameters were first optimized and then fixed and applied to 30 repeat data sets from 15 normal older adult subjects to investigate its reproducibility. Percent differences between total brain volumes (TBVs) for the subjects' repeated data sets ranged from .5% to 2.2%. We conclude that the method is both robust and reproducible and has the potential for wide application.