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Schaper, C.

Publications and source records attributed to Schaper, C..

2 recordsLinked to original sources

Analytic Model of fMRI BOLD Signals for Separable Metrics of Neural and Metabolic Activity

The applications of fMRI (functional magnetic resonance imaging) are broad covering diagnostic and clinical extents of brain function, which involves the analysis of BOLD (blood oxygen level-dependent) contrast signals. The BOLD signals are sourced from both neural and metabolic functions, and thus to enable a detailed examination of fMRI studies, methods are sought to separate the neural and metabolic functions, such that the neural component, which is often the metric of interest, can be independently examined, especially in relation to neural connectivity. In this work, a modeling approach is developed that separates the neural and metabolic functions from the overall BOLD signal. The newly developed model is initially developed within a linear framework and demonstrates excellent comparison in data fit at 97.4% to the three Gamma function, which has been widely used to characterize fMRI BOLD experimental data. The neural component of the model formulation is comprised of a proper transfer function of two poles and two zeros, and characterizes the salient features of the BOLD signal, including the initial dip, peak, undershoot, and stabilization period. The linear model is extended to characterize nonlinear fMRI BOLD signal responses through the integration of saturation functions to both the leading and trailing edges of the signal. The nonlinear model representation not only explains the muted response in amplitude and oscillations, but also explains nuanced oscillations during the hold and settling phases of fMRI BOLD responses as exemplified in comparison to published data of sensorimotor responses. Further, the newly developed decomposition is derived within a framework for modeling neurovascular coupling environments, and thus lends credibility to the modeling framework. In developing the decomposition of the neural and metabolic transfer functions, it is a conclusion that the BOLD signal correlates very well with the fast dynamics associated with neural response to external stimuli.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=155 SRC=\"FIGDIR/small/573006_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (17K):\norg.highwire.dtl.DTLVardef@1171945org.highwire.dtl.DTLVardef@17c3c0aorg.highwire.dtl.DTLVardef@149eebborg.highwire.dtl.DTLVardef@d840e1_HPS_FORMAT_FIGEXP M_FIG C_FIG The normalized impulse response of the BOLD signal and the corresponding neural activity according to the newly developed model. There is a correspondence of the critical points for the oscillatory response of the neural function and metabolic reactivity, including the initial dip, peak and subsequent undershoot. Thus, the BOLD signal is a correlated representation of the underlying neural response.

neuroscience

Dynamics and Internal Control of Body Temperature in Response to Infectious Agents and other Causal Factors

Thermoregulation is crucial to homeostasis, but the mechanisms of its dysfunction are still largely mysterious, including fever, which is generally the most disconcerting sign of a serious infection or disease. Theories on body temperature dynamics that aim to explain a fever, such as changes in an internal setpoint, have been proposed, but none can identify the fundamental molecular pathways that produce a fever. Here, potential molecular pathways resultant in fever are identified, modeled, and compared to experimental temperature response data. Based on recent developments made by this lab, which has shown that the pyrogen prostaglandin E2 (PGE2) possesses similar binding affinity as the hormone cortisol (CORT) at the critical ligand binding domain (LBD) of glucocorticoid receptors (GR); molecular modeling, mathematical modeling and a case study for validation is used to indicate that competitive inhibition of CORT by PGE2 as a fundamental reason for dysfunctional dynamics of body temperature, including fever. Comprised of a superposition of proportional and derivative terms of signals representing temperature receptors, CORT concentration, and PGE2 concentration, the internal temperature control model characterizes dynamics associated with the cardiovascular, immune, and neural systems in response to infectious agents, triggering events, and other causal factors. The model is validated by examination of the transient and spectral characteristics of a three-day case history involving temperature trajectories after physical activity protocols in response to a standard vaccination of pneumococcal and influenza species.

physiology