Modelling of large-scale brain network dynamics

Like many systems in nature, the brain is a highly organised unit of interacting components. A natural way to study such systems is through the lens of mathematics, from which we may attempt to delineate the mechanisms that underlie seemingly unfathomable brain functionality using prescribed parameters and equations. In this thesis, we use large-scale neural mass network models of the human cortex to simulate brain activity. Moreover, we utilise techniques from graph, linear and weakly-coupled oscillator theory to describe the network states that are exhibited by such models. In particular, we focus on how the emergent patterns of synchrony (which are thought to be fundamental to the function of brain), or so-called functional connectivity, are dependent on the structural connectivity, which is the anatomical substrate for brain dynamics. Through large-scale network simulations and linear analysis we find that the structure--function relationship is highly dependent on-- and indeed, predictable from-- the dynamical state of individual nodes in the network, highlighting the role of dynamics in facilitating emergent functional connectivity. We take this further to consider how network states are modulated by external simulation and conduction delays, especially in relation to the influence of transcranial magnetic stimulation (TMS) on the brain's dynamics and, more generally, its role as a neuromodulator. We describe a computational framework using a recently developed next-generation neural mass model, by which trains of simulated pulses are employed to drive network dynamics into different states, which we believe may be adapted to be used to study the efficacy of TMS and to test in silico different stimulation protocols that can be used to treat neurological conditions. We then analyse more specific applications to potential effects of TMS: neural entrainment and conduction delays (which may be altered via TMS-induced plasticity). We use the theory of Lyapunov exponents to study entrainment via external stimulation and use linear analysis, as well as structural eigenmodes, to predict emergent network states due to conduction delays across long-range white matter projections

Ultrasonic spectrometry and modelling that verifies shear-wave reconversion in micro- and nano-fluids

Ultrasonic spectrometry and modelling that verifies shear-wave reconversion in micro- and nano-fluid

Alternative Transcript Initiation and Splicing as a Response to DNA Damage

Humans are exposed to the DNA damaging agent, ionizing radiation (IR), from background radiation, medical treatments, occupational and accidental exposures. IR causes changes in transcription, but little is known about alternative transcription in response to IR on a genome-wide basis. These investigations examine the response to IR at the exon level in human cells, using exon arrays to comprehensively characterize radiation-induced transcriptional expression products. Previously uncharacterized alternative transcripts that preferentially occur following IR exposure have been discovered. A large number of genes showed alternative transcription initiation as a response to IR. Dose-response and time course kinetics have also been characterized. Interestingly, most genes showing alternative transcript induction maintained these isoforms over the dose range and times tested. Finally, clusters of co-ordinately up- and down-regulated radiation response genes were identified at specific chromosomal loci. These data provide the first genome-wide view of the transcriptional response to ionizing radiation at the exon level. This study provides novel insights into alternative transcripts as a mechanism for response to DNA damage and cell stress responses in general

Structure-function clustering in weighted brain networks

Abstract: Functional networks, which typically describe patterns of activity taking place across the cerebral cortex, are widely studied in neuroscience. The dynamical features of these networks, and in particular their deviation from the relatively static structural network, are thought to be key to higher brain function. The interactions between such structural networks and emergent function, and the multimodal neuroimaging approaches and common analysis according to frequency band motivate a multilayer network approach. However, many such investigations rely on arbitrary threshold choices that convert dense, weighted networks to sparse, binary structures. Here, we generalise a measure of multiplex clustering to describe weighted multiplexes with arbitrarily-many layers. Moreover, we extend a recently-developed measure of structure-function clustering (that describes the disparity between anatomical connectivity and functional networks) to the weighted case. To demonstrate its utility we combine human connectome data with simulated neural activity and bifurcation analysis. Our results indicate that this new measure can extract neurologically relevant features not readily apparent in analogous single-layer analyses. In particular, we are able to deduce dynamical regimes under which multistable patterns of neural activity emerge. Importantly, these findings suggest a role for brain operation just beyond criticality to promote cognitive flexibility

Safety, the Preface Paradox and Possible Worlds Semantics

This paper contains an argument to the effect that possible worlds semantics renders semantic knowledge impossible, no matter what ontological interpretation is given to possible worlds. The essential contention made is that possible worlds semantic knowledge is unsafe and this is shown by a parallel with the preface paradox

Limitations of fasting indices in the measurement of insulin sensitivity in Afro-Caribbean adults

In young Afro-Caribbean adults, HOMA-IR compared poorly with other measures of insulin sensitivity. It remains important to determine whether similar findings occur in a more insulin resistant population. However, HOMA-IR correlated with clinical measures of insulin sensitivity (i.e. adiposity), so it may still be useful in epidemiological studies

994-99 Can Late Saphenous Vein Graft Closure Be Predicted by Quantitative Angiographic Analysis Before the Clinical Event?

Angiographic parameters predicting the likelihood of late occlusion of saphenous vein grafts (SVG) have been infrequently described. The Post-CABG Study, a 5-year trial aimed at reducing SVG closure in minimally symptomatic patients 1–11 years Post-CABG, offers a unique view into this event since this study requires an angiogram to document baseline graft patency. In this preliminary study we performed quantitative angiographic analysis (QAA Reiber) comparing the baseline Post-CABG study angiogram to an unscheduled “clinically driven” angiogram. Of 1253 enrolled patients with at least one patent SVG, 35 developed MI or unstable angina associated angiographically with a changed SVG lesion and either total or subtotal occlusion. Average patient age was 58±2 (SEM)years; 97% were male. Years since SVG placement to baseline angiogram averaged 6.5±0.4 (range 2–14). Time from the baseline to the unscheduled angiogram was 22±2 mo (range 3–47). In 28 patients the involved graft was single and in 7 sequential. The SVG insertion segments involved the LCX in 17, RCA in 15 and LAD in 10.ResultsThe initial lesion diameter at the site of the subsequent inciting lesion for all 35 patients averaged 2.58±0.17 mm, or 29.5±3.6% diam. stenosis. (This was defined as the most severe stenosis in any part of the graft in patients with subsequent total graft occlusion, and the exactly matched graft site in those with subtotal occlusion.) In 8 patients the baseline SVG was entirely normal. The initial lesion was >50% stenosis in only 4 patients. At the time of the clinical event, the lesion had progressed to 87±2.6% diam stenosis (N=35). In 16 patients the causal lesion was subtotal, while in 19 the SVG was totally occluded. The mean native vessel — responsible graft anastomotic diameter was 2.33±0.12mm.ConclusionQAA of SVG in asymptomatic patients may not predict subsequent graft closure associated with acute coronary syndromes. The initial site of the lesion is typically of mild-moderate severity, and only later exhibits rapid progression to occlusion

Developmental contributions to macronutrient selection: A randomized controlled trial in adult survivors of malnutrition

Background and objectives: Birthweight differences between kwashiorkor and marasmus suggest that intrauterine factors influence the development of these syndromes of malnutrition and may modulate risk of obesity through dietary intake. We tested the hypotheses that the target protein intake in adulthood is associated with birthweight, and that protein leveraging to maintain this target protein intake would influence energy intake (EI) and body weight in adult survivors of malnutrition.Methodology: Sixty-three adult survivors of marasmus and kwashiorkor could freely compose a diet from foods containing 10, 15 and 25 percentage energy from protein (percentage of energy derived from protein (PEP); Phase 1) for 3 days. Participants were then randomized in Phase 2 (5 days) to diets with PEP fixed at 10%, 15% or 25%.Results: Self-selected PEP was similar in both groups. In the groups combined, selected PEP was 14.7, which differed significantly (P < 0.0001) from the null expectation (16.7%) of no selection. Self-selected PEP was inversely related to birthweight, the effect disappearing after adjusting for sex and current body weight. In Phase 2, PEP correlated inversely with EI (P = 0.002) and weight change from Phase 1 to 2 (P = 0.002). Protein intake increased with increasing PEP, but to a lesser extent than energy increased with decreasing PEP.Conclusions and implications: Macronutrient intakes were not independently related to birthweight or diagnosis. In a free-choice situation (Phase 1), subjects selected a dietary PEP significantly lower than random. Lower PEP diets induce increased energy and decreased protein intake, and are associated with weight gain

Stretch goals and the distribution of organizational performance

Many academics, consultants, and managers advocate stretch goals to attain superior organizational performance. However, existing theory speculates that, although stretch goals may benefit some organizations, they are not a “rule for riches” for all organizations. To address this speculation, we use two experimental studies to explore the effects on the mean, median, variance, and skewness of performance of stretch compared with moderate goals. Participants were assigned moderate or stretch goals to manage a widely used business simulation. Compared with moderate goals, stretch goals improve performance for a few participants, but many abandon the stretch goals in favor of lower self-set goals, or adopt a survival goal when faced with the threat of bankruptcy. Consequently, stretch goals generate higher performance variance across organizations and a right-skewed performance distribution. Contrary to conventional wisdom, we find no positive stretch goal main effect on performance. Instead, stretch goals compared with moderate goals generate large attainment discrepancies that increase willingness to take risks, undermine goal commitment, and generate lower risk-adjusted performance. The results provide a richer theoretical and empirical appreciation of how stretch goals influence performance