Theodore J Huppert | Search PubMed

PubMed2006

Diffuse optical tomography system to image brain activation with improved spatial resolution and validation with functional magnetic resonance imaging.

Although most current diffuse optical brain imaging systems use only nearest- neighbor measurement geometry, the spatial resolution and quantitative accuracy of the imaging can be improved through the collection of overlapping sets of measurements. A continuous-wave diffuse optical imaging system that combines frequency encoding with time-division multiplexing to facilitate overlapping measurements of brain activation is described. Phantom measurements to confirm the expected improvement in spatial resolution and quantitative accuracy are presented. Experimental results showing the application of this instrument for imaging human brain activation are also presented. The observed improvement in spatial resolution is confirmed by functional magnetic resonance imaging.

Brain↗

PubMed2005

Dynamic physiological modeling for functional diffuse optical tomography.

Diffuse optical tomography (DOT) is a noninvasive imaging technology that is sensitive to local concentration changes in oxy- and deoxyhemoglobin. When applied to functional neuroimaging, DOT measures hemodynamics in the scalp and brain that reflect competing metabolic demands and cardiovascular dynamics. The diffuse nature of near-infrared photon migration in tissue and the multitude of physiological systems that affect hemodynamics motivate the use of anatomical and physiological models to improve estimates of the functional hemodynamic response. In this paper, we present a linear state-space model for DOT analysis that models the physiological fluctuations present in the data with either static or dynamic estimation. We demonstrate the approach by using auxiliary measurements of blood pressure variability and heart rate variability as inputs to model the background physiology in DOT data. We evaluate the improvements accorded by modeling this physiology on ten human subjects with simulated functional hemodynamic responses added to the baseline physiology. Adding physiological modeling with a static estimator significantly improved estimates of the simulated functional response, and further significant improvements were achieved with a dynamic Kalman filter estimator (paired t tests, n=10, P<0.05). These results suggest that physiological modeling can improve DOT analysis. The further improvement with the Kalman filter encourages continued research into dynamic linear modeling of the physiology present in DOT. Cardiovascular dynamics also affect the blood-oxygen-dependent (BOLD) signal in functional magnetic resonance imaging (fMRI). This state-space approach to DOT analysis could be extended to BOLD fMRI analysis, multimodal studies and real-time analysis.

Blood Pressure↗

PubMed2005

Physiological system identification with the Kalman filter in diffuse optical tomography.

Diffuse optical tomography (DOT) is a noninvasive imaging technology that is sensitive to local concentration changes in oxy- and deoxyhemoglobin. When applied to functional neuroimaging, DOT measures hemodynamics in the scalp and brain that reflect competing metabolic demands and cardiovascular dynamics. Separating the effects of systemic cardiovascular regulation from the local dynamics is vitally important in DOT analysis. In this paper, we use auxiliary physiological measurements such as blood pressure and heart rate within a Kalman filter framework to model physiological components in DOT. We validate the method on data from a human subject with simulated local hemodynamic responses added to the baseline physiology. The proposed method significantly improved estimates of the local hemodynamics in this test case. Cardiovascular dynamics also affect the blood oxygen dependent (BOLD) signal in functional magnetic resonance imaging (fMRI). This Kalman filter framework for DOT may be adapted for BOLD fMRI analysis and multimodal studies.

Algorithms↗

PubMed2003

Chain length dependence of apomyoglobin folding: structural evolution from misfolded sheets to native helices.

Very little is known about how protein structure evolves during the polypeptide chain elongation that accompanies cotranslational protein folding. This in vitro model study is aimed at probing how conformational space evolves for purified N-terminal polypeptides of increasing length. These peptides are derived from the sequence of an all-alpha-helical single domain protein, Sperm whale apomyoglobin (apoMb). Even at short chain lengths, ordered structure is found. The nature of this structure is strongly chain length dependent. At relatively short lengths, a predominantly non-native beta-sheet conformation is present, and self-associated amyloid-like species are generated. As chain length increases, alpha-helix progressively takes over, and it replaces the beta-strand. The observed trends correlate with the specific fraction of solvent-accessible nonpolar surface area present at different chain lengths. The C-terminal portion of the chain plays an important role by promoting a large and cooperative overall increase in helical content and by consolidating the monomeric association state of the full-length protein. Thus, a native-like energy landscape develops late during apoMb chain elongation. This effect may provide an important driving force for chain expulsion from the ribosome and promote nearly-posttranslational folding of single domain proteins in the cell. Nature has been able to overcome the above intrinsic misfolding trends by modulating the composition of the intracellular environment. An imbalance or improper functioning by the above modulating factors during translation may play a role in misfolding-driven intracellular disorders.

Animals↗