A generalization of Ramsey theory for graphs /

Bibliography: p. 16.

Studies in graph algorithms : generation and labeling problems /

Thesis--Illinois.

A graph-structure transformation model for picture parsing,

"COO-2118-0031."

A switching theory for bilateral nets of threshold elements.

Issued also as thesis, University of Illinois.

A generalization of Ramsey theory for graphs /

Includes bibliographical references.

Cerebellar language and cognitive functions in childhood: A comparative review of the clinical research

Background: Recent research addressing evidence from functional neuroimaging studies, neurophysiological research, and new advances in neuropsychology together with traditional cerebellar lesion studies have recently implicated the cerebellum in adult language and cognitive functions. However, more limited information is currently available in describing the functional connectivity present in the paediatric population. Aims: It is the purpose of this paper to review recent clinical research pertaining to paediatric populations, outlining the impact of site of lesion and specific associated clinical changes in children with cerebellar disturbances. Main contribution: The specific contribution of the right cerebellar hemisphere to language function is identified to also exist in the paediatric population, highlighting the existence of functional connections between this region of the brain and left frontal cortical areas early in development. Conclusions: Implications for future research in paediatric populations are extensive, as a greater awareness and an understanding of the recently acknowledged involvement of the cerebellum in cognition and nonmotor linguistic function is anticipated to also add new dimension and direction to the analysis of childhood language outcomes associated with the cerebellum.

Impact of social group processes and functional diversity on communication in networked organizations

This study examines the role of social group processes in perceptions of effective communication in Australian Cooperative Research Centres (CRCs). Communication professionals in 25 CRCs discussed the barriers and opportunities for communication in their diverse networked organizations. Thematic analysis of the transcripts highlighted the contribution of social group processes to both barriers and opportunities. Communication challenges implicated the social identity of organizational members, many of which were associated with distinct structural aspects of these organizations. Opportunities for communication frequently involved features that implicated social identity, including taking advantage of existing organizational or industry identities, preventing conflicting identities from becoming salient, and promoting a collective CRC identity.

Graphical modelling for brain connectivity via partial coherence

Spectral and coherence methodologies are ubiquitous for the analysis of multiple time series. Partial coherence analysis may be used to try to determine graphical models for brain functional connectivity. The outcome of such an analysis may be considerably influenced by factors such as the degree of spectral smoothing, line and interference removal, matrix inversion stabilization and the suppression of effects caused by side-lobe leakage, the combination of results from different epochs and people, and multiple hypothesis testing. This paper examines each of these steps in turn and provides a possible path which produces relatively ‘clean’ connectivity plots. In particular we show how spectral matrix diagonal up-weighting can simultaneously stabilize spectral matrix inversion and reduce effects caused by side-lobe leakage, and use the stepdown multiple hypothesis test procedure to help formulate an interaction strength.

Functional interconnectivity between the globus pallidus and the subthalamic nucleus in the mouse brain slice

In accordance with its central role in basal ganglia circuitry, changes in the rate of action potential firing and pattern of activity in the globus pallidus (GP)-subthalamic nucleus (STN) network are apparent in movement disorders. In this study we have developed a mouse brain slice preparation that maintains the functional connectivity between the GP and STN in order to assess its role in shaping and modulating bursting activity promoted by pharmacological manipulations. Fibre-tract tracing studies indicated that a parasagittal slice cut 20 deg to the midline best preserved connectivity between the GP and the STN. IPSCs and EPSCs elicited by electrical stimulation confirmed connectivity from GP to STN in 44/59 slices and from STN to GP in 22/33 slices, respectively. In control slices, 74/76 (97%) of STN cells fired tonically at a rate of 10.3 ± 1.3 Hz. This rate and pattern of single spiking activity was unaffected by bath application of the GABAA antagonist picrotoxin (50 μM, n = 9) or the glutamate receptor antagonist (6-cyano-7-nitroquinoxaline-2, 3-dione (CNQX) 10 μM, n = 8). Bursting activity in STN neurones could be induced pharmacologically by application of NMDA alone (20 μM, 3/18 cells, 17%) but was more robust if NMDA was applied in conjunction with apamin (20-100 nM, 34/77 cells, 44%). Once again, neither picrotoxin (50 μM, n = 5) nor CNQX (10 μM, n = 5) had any effect on the frequency or pattern of the STN neurone activity while paired STN and GP recordings of tonic and bursting activity show no evidence of coherent activity. Thus, in a mouse brain slice preparation where functional GP-STN connectivity is preserved, no regenerative synaptically mediated activity indicative of a dynamic network is evident, either in the resting state or when neuronal bursting in both the GP and STN is generated by application of NMDA/apamin. This difference from the brain in Parkinson's disease may be attributed either to insufficient preservation of cortico-striato-pallidal or cortico-subthalamic circuitry, and/or an essential requirement for adaptive changes resulting from dopamine depletion for the expression of network activity within this tissue complex. © The Physiological Society 2005.

Brain connectivity in positive and negative syndrome schizophrenia

If, as is widely believed, schizophrenia is characterized by abnormalities of brain functional connectivity, then it seems reasonable to expect that different subtypes of schizophrenia could be discriminated in the same way. However, evidence for differences in functional connectivity between the subtypes of schizophrenia is largely lacking and, where it exists, it could be accounted for by clinical differences between the patients (e.g. medication) or by the limitations of the measures used. In this study, we measured EEG functional connectivity in unmedicated male patients diagnosed with either positive or negative syndrome schizophrenia and compared them with age and sex matched healthy controls. Using new methodology (Medkour et al., 2009) based on partial coherence, brain connectivity plots were constructed for positive and negative syndrome patients and controls. Reliable differences in the pattern of functional connectivity were found with both syndromes showing not only an absence of some of the connections that were seen in controls but also the presence of connections that the controls did not show. Comparing connectivity graphs using the Hamming distance, the negative-syndrome patients were found to be more distant from the controls than were the positive syndrome patients. Bootstrap distributions of these distances were created which showed a significant difference in the mean distances that was consistent with the observation that negative-syndrome diagnosis is associated with a more severe form of schizophrenia. We conclude that schizophrenia is characterized by widespread changes in functional connectivity with negative syndrome patients showing a more extreme pattern of abnormality than positive syndrome patients.

Gene network and proteomic analyses of cardiac responses to pathological and physiological stress

Background—The molecular mechanisms underlying similarities and differences between physiological and pathological left ventricular hypertrophy (LVH) are of intense interest. Most previous work involved targeted analysis of individual signaling pathways or screening of transcriptomic profiles. We developed a network biology approach using genomic and proteomic data to study the molecular patterns that distinguish pathological and physiological LVH. Methods and Results—A network-based analysis using graph theory methods was undertaken on 127 genome-wide expression arrays of in vivo murine LVH. This revealed phenotype-specific pathological and physiological gene coexpression networks. Despite >1650 common genes in the 2 networks, network structure is significantly different. This is largely because of rewiring of genes that are differentially coexpressed in the 2 networks; this novel concept of differential wiring was further validated experimentally. Functional analysis of the rewired network revealed several distinct cellular pathways and gene sets. Deeper exploration was undertaken by targeted proteomic analysis of mitochondrial, myofilament, and extracellular subproteomes in pathological LVH. A notable finding was that mRNA–protein correlation was greater at the cellular pathway level than for individual loci. Conclusions—This first combined gene network and proteomic analysis of LVH reveals novel insights into the integrated pathomechanisms that distinguish pathological versus physiological phenotypes. In particular, we identify differential gene wiring as a major distinguishing feature of these phenotypes. This approach provides a platform for the investigation of potentially novel pathways in LVH and offers a freely accessible protocol (http://sites.google.com/site/cardionetworks) for similar analyses in other cardiovascular diseases.

Resting state morphology predicts the effect of theta burst stimulation in false belief reasoning:ventrolateral prefrontal cortex in false belief reasoning

When required to represent a perspective that conflicts with one's own, functional magnetic resonance imaging (fMRI) suggests that the right ventrolateral prefrontal cortex (rvlPFC) supports the inhibition of that conflicting self-perspective. The present task dissociated inhibition of self-perspective from other executive control processes by contrasting belief reasoning-a cognitive state where the presence of conflicting perspectives was manipulated-with a conative desire state wherein no systematic conflict existed. Linear modeling was used to examine the effect of continuous theta burst stimulation (cTBS) to rvlPFC on participants' reaction times in belief and desire reasoning. It was anticipated that cTBS applied to rvlPFC would affect belief but not desire reasoning, by modulating activity in the Ventral Attention System (VAS). We further anticipated that this effect would be mediated by functional connectivity within this network, which was identified using resting state fMRI and an unbiased model-free approach. Simple reaction-time analysis failed to detect an effect of cTBS. However, by additionally modeling individual measures from within the stimulated network, the hypothesized effect of cTBS to belief (but, importantly, not desire) reasoning was demonstrated. Structural morphology within the stimulated region, rvlPFC, and right temporoparietal junction were demonstrated to underlie this effect. These data provide evidence that inconsistencies found with cTBS can be mediated by the composition of the functional network that is being stimulated. We suggest that the common claim that this network constitutes the VAS explains the effect of cTBS to this network on false belief reasoning. Hum Brain Mapp, 2016. © 2016 Wiley Periodicals, Inc.

Principal component analysis and assessment of language network activation patterns in pediatric epilepsy

This dissertation establishes a novel data-driven method to identify language network activation patterns in pediatric epilepsy through the use of the Principal Component Analysis (PCA) on functional magnetic resonance imaging (fMRI). A total of 122 subjects’ data sets from five different hospitals were included in the study through a web-based repository site designed here at FIU. Research was conducted to evaluate different classification and clustering techniques in identifying hidden activation patterns and their associations with meaningful clinical variables. The results were assessed through agreement analysis with the conventional methods of lateralization index (LI) and visual rating. What is unique in this approach is the new mechanism designed for projecting language network patterns in the PCA-based decisional space. Synthetic activation maps were randomly generated from real data sets to uniquely establish nonlinear decision functions (NDF) which are then used to classify any new fMRI activation map into typical or atypical. The best nonlinear classifier was obtained on a 4D space with a complexity (nonlinearity) degree of 7. Based on the significant association of language dominance and intensities with the top eigenvectors of the PCA decisional space, a new algorithm was deployed to delineate primary cluster members without intensity normalization. In this case, three distinct activations patterns (groups) were identified (averaged kappa with rating 0.65, with LI 0.76) and were characterized by the regions of: (1) the left inferior frontal Gyrus (IFG) and left superior temporal gyrus (STG), considered typical for the language task; (2) the IFG, left mesial frontal lobe, right cerebellum regions, representing a variant left dominant pattern by higher activation; and (3) the right homologues of the first pattern in Broca's and Wernicke's language areas. Interestingly, group 2 was found to reflect a different language compensation mechanism than reorganization. Its high intensity activation suggests a possible remote effect on the right hemisphere focus on traditionally left-lateralized functions. In retrospect, this data-driven method provides new insights into mechanisms for brain compensation/reorganization and neural plasticity in pediatric epilepsy.