Disrupted Modularity and Local Connectivity of Brain Functional Networks in Childhood-Onset Schizophrenia

Modularity is a fundamental concept in systems neuroscience, referring to the formation of local cliques or modules of densely intra-connected nodes that are sparsely inter-connected with nodes in other modules. Topological modularity of brain functional networks can quantify theoretically anticipated abnormality of brain network community structure – so-called dysmodularity – in developmental disorders such as childhood-onset schizophrenia (COS). We used graph theory to investigate topology of networks derived from resting-state fMRI data on 13 COS patients and 19 healthy volunteers. We measured functional connectivity between each pair of 100 regional nodes, focusing on wavelet correlation in the frequency interval 0.05–0.1 Hz, then applied global and local thresholding rules to construct graphs from each individual association matrix over the full range of possible connection densities. We show how local thresholding based on the minimum spanning tree facilitates group comparisons of networks by forcing the connectedness of sparse graphs. Threshold-dependent graph theoretical results are compatible with the results of a k-means unsupervised learning algorithm and a multi-resolution (spin glass) approach to modularity, both of which also find community structure but do not require thresholding of the association matrix. In general modularity of brain functional networks was significantly reduced in COS, due to a relatively reduced density of intra-modular connections between neighboring regions. Other network measures of local organization such as clustering were also decreased, while complementary measures of global efficiency and robustness were increased, in the COS group. The group differences in complex network properties were mirrored by differences in simpler statistical properties of the data, such as the variability of the global time series and the internal homogeneity of the time series within anatomical regions of interest

Formation of Structure in Cortical Networks through Spike Timing-Dependent Plasticity

The connectivity of mammalian brains exhibits structure at a wide variety of spatial scales, from the broad (which brain areas connect to which) to the extremely fine (where synapses form on the morphology of individual neurons). Two striking features of the neuron-to- neuron connectivity are 1) the strong over-representation of multi-synapse connectivity pat- terns compared to simple random-network models and 2) a strong relationship between neurons’ local connectivity and their stimulus preferences, so that local network structure plays a large role in the computations neurons perform. A central question in systems neu- roscience is how such structures emerge. Answers to this question are confounded by the mutual interactions of neuronal activity and neural network structure. Patterns of synaptic connectivity influence neurons’ joint activity, while the synapses between neurons are plastic and strengthen or weaken depending on the activity of the pre- and postsynaptic neurons. In this thesis, I develop a self-consistent framework for the coevolution of network struc- ture and spiking activity. Subsequent chapters leverage this to develop low-dimensional sets of equations that directly describe the plasticity of connectivity patterns in large spiking networks. I examine plasticity during spontaneous activity and then how the structure of external stimuli can shape network structure and subsequent spontaneous plasticity. These studies provide a step towards understanding how the structure of neuronal networks and neurons’ joint activity interact to allow network computations

Annual Report of the University, 1999-2000, Volumes 1-4

The Robert O. Anderson School and Graduate School of Management at The University of New Mexico Period of Report: July 1, 1999 to June 30, 2000 Submitted by Howard L. Smith, Dean The Anderson Schools of Management is divided into four distinct divisions- the Department of Accounting; the Department of Finance, International and Technology Management; the Department of Marketing, Information and Decision Sciences; and the Department of Organizational Studies. This structure provides an opportunity for The Anderson Schools to develop four distinct areas of excellence, proven by results reported here. I. Significant Developments During the Academic Year The Anderson Schools of Management • As a result of the multi-year gift from the Ford Motor Company, completed renovation of The Schools\u27 Advisement and Placement Center, as well as all student organization offices. • The Ford gift also provided for $100,000 to support faculty research, case studies and course development. • The Schools revised the MBA curriculum to meet the changing needs of professional, advanced business education. • The Schools updated computer laboratory facilities, with the addition of a 45-unit cluster for teaching and student work. • The faculty and staff of The Schools furthered outreach in economic development activities by participating directly as committee members and leaders in the cluster workgroups of the Next Generation Economy Initiative. • The faculty, staff and students of The Schools contributed to the development of the Ethics in Business Awards; particularly exciting was the fact that all nominee packages were developed by student teams from The Anderson Schools. • The Schools continue to generate more credit hours per faculty member than any other division of the UNM community. The Accounting Department • Preparation and presentation of a progress report to accrediting body, the AACSB. The Department of Finance, International and Technology Management • The Department continued to focus on expansion of the Management of Technology program as a strategic strength of The Schools. The Department of Marketing. Information and Decision Sciences • Generated 9022 credit hours, with a student enrollment of 3070. The Department of Organizational Studies • Coordinated the 9th UNM Universidad de Guanajuato (UG) Mexico Student Exchange

Annual Report of the University, 2000-2001, Volumes 1-4

Message from the President Thank you for joining me in this look back over the past year at the University of New Mexico. It was a year filled with activity, accomplishment and challenge, and this is our opportunity to reflect back on that year. In 2000-2001 we engaged in a University-wide strategic planning process that called on the energies and talents of hundreds of individuals- faculty, staff, students and members of our broader community. The plan, which will be completed in Fall 2001, will serve as our roadmap for the future and will guide our efforts to capitalize on the opportunities and to meet the challenges of the next several years. This process has encouraged us to examine closely our mission and our values, who we are and what we aspire to become. It has given us reason to be proud of our past and cause to think seriously about how we must change in the future. While this was a year for looking ahead, it was also a year of significant accomplishment. For example, we launched a comprehensive set of programs designed to enrich the academic and social experiences of our undergraduate students. We began the implementation of Freshman Learning Communities where small cohorts of students study and learn together in a common set of courses under the guidance of a senior faculty scholar. We reorganized our advisement systems, we undertook the construction or renovation of student-centered facilities on campus, and we created new support systems to enhance student academic success. It was a year in which our support of faculty, staff and students was our highest priority. Through the support of the New Mexico Legislature, faculty and staff received significant salary increases. A new health benefits plan for graduate assistants was implemented. Our Staff as Students program enabled more than 40 staff members to obtain UNM degrees. And, a Center for Scholarship in Teaching and Learning was established to assist faculty in their efforts to develop more effective teaching skills. Finally, this was a year in which UNM dramatically expanded its role in the local community and throughout the state. Never before has the University been as active or as visible in meeting its public responsibility as it was in 2000-2001. From its active participation in economic development initiatives, to its involvement in K-12 educational improvement efforts, to its significant leadership role in health care delivery, UNM demonstrated its ability to help the state meet its most pressing social challenges. And, as UNM took on a more visible role in supporting the state\\u27s citizens, the support for UNM was returned in kind. This year, annual giving to the University rose to a record 35.3 million dollars, a 40% increase over just two years ago. All told, it has been a gratifying and successful year. However, we cannot allow our past accomplishments to mask the continued challenges facing this University. Neither will we allow these challenges to dominate our thinking and diminish out pride in what the University has achieved. So we will savor our successes and continue to move forward. As always, we thank you for sharing our dreams and for supporting the University of New Mexico. Sincerely, William C. Gordon, Presiden

Principles of regional covariance in brain structure

The human brain varies between individuals in both shape and size. These variations are not unique for each brain region. This causes grey matter density between regions to covary, a phenomenon known as “structural brain covariance”. The reasons for this structural covariance, and its possible relations to functional connectivity, remain poorly understood. In order to study this morphological variation, a standard brain atlas – also called a brain template – is commonly used to enable consolidation of information across individuals. In the early days of computerised brain research, this was done by creating an average of a large number of brain images from young adults resampled into a common stereotaxic space known as the “MNI space”, which is still widely used today. However, this space is less ideal for ageing studies since the brain changes structurally with age. The aim of this thesis was to provide a deeper understanding of the principles governing structural covariance across the age span. In Study I, the need of a computerised brain atlas in ageing was addressed by constructing a standard non-linear brain template from 314 older individuals (average age 75 years) together with a regional atlas and corresponding tissue probability maps. This template was constructed to be linearly mapped to MNI space while forming its own non-linear ageing space. The tissue probability maps also allowed us to construct a non-linear transformation to other spaces and warp the regional atlas to other study cohorts. This approach was used in Study II-IV. In Study II, the nature of structural covariance in ageing was investigated by calculating for each grey matter voxel (data point) its number of significant correlations with all the other grey matter voxels in the brain, in a large sample of 960 healthy individuals (age range 68-83 years). Voxels with many significant correlations (known as “hubs”) were found in the basal ganglia, the thalamus, the brainstem, and the cerebellum. No significant difference in the covariance structure could be found between relatively younger (68-75 years) and older (76-83 years) individuals or between men and women, suggesting that the hubs represent a fundamental property of structural brain variation that is relatively unaffected by the ageing process. Study III investigated if the subcortical hub regions from Study II would also be present as hubs with a high level of covariation in a study cohort of 138 young adults between 18-35 years. Secondly, we explored if the observed patterns of structural covariation were related to patterns of functional connectivity during resting state. We replicated the finding from Study II that the basal ganglia, the thalamus, and the brainstem were structural hub regions, further strengthening the support that these hubs are not caused by old age. Comparisons of structural covariance patterns and patterns of functional connectivity during rest demonstrated only limited overlap, suggesting that functional connectivity does not cause structural covariance as a general principle. In the final study (Study IV), a dimensionality reduced latent space representation of the cohort from Study III was examined using a convolutional variational autoencoder. The results revealed that only four dimensions – or latent factors – were required to reconstruct most of the structural covariance, including the hubs. Regions with low overall structural covariability typically showed an inconsistent pattern of intercorrelations with other regions in their scores on different factors (e.g. significantly correlated on one factor, but not on other factors). In contrast, hub regions tended to covary across the whole latent space. The factors that correlated positively with the subcortical hubs were also positively related to an increase in functional connectivity during resting state in wide-spread cortical regions. In summary, these results show that subcortical hubs in human brains are robust across the age span and that structural covariance only shows weak relations to patterns of functional connectivity. Further studies in genetically informative samples would be required to investigate the genetic basis of structural covariation in the human brain