The Interplay of Architecture and Correlated Variability in Neuronal Networks

This much is certain: neurons are coupled, and they exhibit covariations in their output. The extent of each does not have a single answer. Moreover, the strength of neuronal correlations, in particular, has been a subject of hot debate within the neuroscience community over the past decade, as advancing recording techniques have made available a lot of new, sometimes seemingly conflicting, datasets. The impact of connectivity and the resulting correlations on the ability of animals to perform necessary tasks is even less well understood. In order to answer relevant questions in these categories, novel approaches must be developed. This work focuses on three somewhat distinct, but inseparably coupled, crucial avenues of research within the broader field of computational neuroscience. First, there is a need for tools which can be applied, both by experimentalists and theorists, to understand how networks transform their inputs. In turn, these tools will allow neuroscientists to tease apart the structure which underlies network activity. The Generalized Thinning and Shift framework, presented in Chapter 4, addresses this need. Next, taking for granted a general understanding of network architecture as well as some grasp of the behavior of its individual units, we must be able to reverse the activity to structure relationship, and understand instead how network structure determines dynamics. We achieve this in Chapters 5 through 7 where we present an application of linear response theory yielding an explicit approximation of correlations in integrate--and--fire neuronal networks. This approximation reveals the explicit relationship between correlations, structure, and marginal dynamics. Finally, we must strive to understand the functional impact of network dynamics and architecture on the tasks that a neural network performs. This need motivates our analysis of a biophysically detailed model of the blow fly visual system in Chapter 8. Our hope is that the work presented here represents significant advances in multiple directions within the field of computational neuroscience.Mathematics, Department o

Pooling and Correlated Neural Activity

Correlations between spike trains can strongly modulate neuronal activity and affect the ability of neurons to encode information. Neurons integrate inputs from thousands of afferents. Similarly, a number of experimental techniques are designed to record pooled cell activity. We review and generalize a number of previous results that show how correlations between cells in a population can be amplified and distorted in signals that reflect their collective activity. The structure of the underlying neuronal response can significantly impact correlations between such pooled signals. Therefore care needs to be taken when interpreting pooled recordings, or modeling networks of cells that receive inputs from large presynaptic populations. We also show that the frequently observed runaway synchrony in feedforward chains is primarily due to the pooling of correlated inputs

Motif Statistics and Spike Correlations in Neuronal Networks

Motifs are patterns of subgraphs of complex networks. We studied the impact of such patterns of connectivity on the level of correlated, or synchronized, spiking activity among pairs of cells in a recurrent network model of integrate and fire neurons. For a range of network architectures, we find that the pairwise correlation coefficients, averaged across the network, can be closely approximated using only three statistics of network connectivity. These are the overall network connection probability and the frequencies of two second-order motifs: diverging motifs, in which one cell provides input to two others, and chain motifs, in which two cells are connected via a third intermediary cell. Specifically, the prevalence of diverging and chain motifs tends to increase correlation. Our method is based on linear response theory, which enables us to express spiking statistics using linear algebra, and a resumming technique, which extrapolates from second order motifs to predict the overall effect of coupling on network correlation. Our motif-based results seek to isolate the effect of network architecture perturbatively from a known network state

The uses and abuses of power: teaching school leadership through children's literature

There are relatively few studies of how representations of teachers, schools and educational administrators in popular films and television might be, and are, used in leadership preparation. This paper seeks to add to this small body of work; it reports on an exploratory study of the representation of headteachers in contemporary children's fiction. Thirty-one texts are analysed to ascertain key themes and the major characterisations. The paper draws on children's literature scholars to argue that both the historical school story and its contemporary counterpart focus heavily on the power of the head to control the micro-world of the school. Because these fictional accounts deal with issues of power and justice more openly than many mainstream educational administration texts, this makes them particularly useful in the preparation of potential school leaders

Impact of network structure and cellular response on spike time correlations

Novel experimental techniques reveal the simultaneous activity of larger and larger numbers of neurons. As a result there is increasing interest in the structure of cooperative -- or correlated -- activity in neural populations, and in the possible impact of such correlations on the neural code. A fundamental theoretical challenge is to understand how the architecture of network connectivity along with the dynamical properties of single cells shape the magnitude and timescale of correlations. We provide a general approach to this problem by extending prior techniques based on linear response theory. We consider networks of general integrate-and-fire cells with arbitrary architecture, and provide explicit expressions for the approximate cross-correlation between constituent cells. These correlations depend strongly on the operating point (input mean and variance) of the neurons, even when connectivity is fixed. Moreover, the approximations admit an expansion in powers of the matrices that describe the network architecture. This expansion can be readily interpreted in terms of paths between different cells. We apply our results to large excitatory-inhibitory networks, and demonstrate first how precise balance --- or lack thereof --- between the strengths and timescales of excitatory and inhibitory synapses is reflected in the overall correlation structure of the network. We then derive explicit expressions for the average correlation structure in randomly connected networks. These expressions help to identify the important factors that shape coordinated neural activity in such networks

Sustainable tourism planning with multiple objective decision analysis: a case study of the Guimaras farm tourism pilot

There is widespread recognition that tourism, one of one of the world's largest and fastest growing industries, must move towards sustainability by embracing a more balanced planning approach. This is especially true in developing countries where tourism is being aggressively promoted, often with limited attention given to the overarching socioeconomic, institutional and biophysical parameters. This thesis uses an innovative and promising approach for sustainable tourism planning based on multiple objective decision analysis (MODA). After reviewing contemporary challenges in tourism planning and identifying MODA's potential contributions, practical application of MOD A is tested in a case study of The Philippine Cooperative Farm Tourism Project: The Guimaras Pilot Project. MODA is a planning and decision method that draws from many disciplines including economics, psychology, operations research, negotiation theory and statistical decision theory. It is based on six fundamental steps: (1) defining the decision problem effectively; (2) establishing the planning context; (3) identifying relevant stakeholders; (4) eliciting and structuring a comprehensive set of objectives; (5) creating alternatives to achieve the stated objectives; and, (6) evaluating the alternatives against the objectives. This 'people based' approach seeks to clarify inherent value tradeoffs while promoting the development of alternatives that are more likely to appeal to stakeholder interests. The insight gained from the MODA process allows decision makers to make better informed and more defensible choices — choices that can responsibly address the difficult issues of sustainable tourism and are more likely to result in successful project implementation. Sub-methods are easily couched in the conceptual structure provided by MODA. One technique used extensively during field research in the Philippines was the elicitation and organization of objectives into a hierarchy, ranging from national policy to local values. By focusing on objectives, the analysis was able to identify, and begin to address, critical gaps in available information (i.e., local market conditions were established using market research techniques and capture rate theory). Field work was also supported by interviews (semistructured, open and informal) and participatory observation. These efforts laid the foundation for a 'farm tourism' planning workshop. The workshop participants, representing key stakeholder groups, infused critical local knowledge into the process and helped establish realistic planning constraints. Using the objectives hierarchy, the participants also undertook a qualitative and quantitative examination of objectives that provided a chance to reflect on community values and direct the focus of the Guimaras Farm Tourism Pilot Project (fortified later by statistical analysis). The insights gained were then used by the workshop participants to create and clarify a range of alternatives that culminated in a grassroots vision of 'farm tourism'. MODA systematically promoted an open, participatory process and established a framework for multi-sectoral integration; The resulting group-efforts overcame entrenched positions (e.g., the farm estate concept) while nurturing a sense of commitment necessary for effective project implementation. A five year period would allow for a staggered phasing of three alternatives: (1) Excursion Farm Tourism; (2) Barangay (Village) Farm Tourism; and, (2) Estate Farm Tourism. These alternatives would all be based on education, interpretation and host/guest interaction. All of the alternatives would benefit from the creation of exhibits, events, tours and festivals. These activities would be immediately initiated and evolve over the life of the project. Close monitoring and ongoing evaluation would be needed to adjust the project to changing needs of local communities. Although some of MODA's more technical aspects (e.g., statistical analysis of objectives) will probably not become a planning standard on Guimaras, many of MODA's core principals (e.g., relevant stakeholder inclusion) will continue to be an important part of the Guimaras Farm Tourism planning process. The success of this planning and decision making method on the rural island of Guimaras suggests that it is widely applicable, and therefore capable of contributing to sustainable tourism initiates in many planning contexts.Applied Science, Faculty ofCommunity and Regional Planning (SCARP), School ofGraduat