Biomedical subjects

G Strangman

Publications and source records attributed to G Strangman.

5 recordsLinked to original sources

PubMed2003

Can the cerebral metabolic rate of oxygen be estimated with near-infrared spectroscopy?

We have measured the changes in oxy-haemoglobin and deoxy-haemoglobin in the adult human brain during a brief finger tapping exercise using near-infrared spectroscopy (NIRS). The cerebral metabolic rate of oxygen (CMRO2) can be estimated from these NIRS data provided certain model assumptions. The change in CMRO2 is related to changes in the total haemoglobin concentration, deoxy-haemoglobin concentration and blood flow. As NIRS does not provide a measure of dynamic changes in blood flow during brain activation, we relied on a Windkessel model that relates dynamic blood volume and flow changes, which has been used previously for estimating CMRO2 from functional magnetic resonance imaging (fMRI) data. Because of the partial volume effect we are unable to quantify the absolute changes in the local brain haemoglobin concentrations with NIRS and thus are unable to obtain an estimate of the absolute CMRO2 change. An absolute estimate is also confounded by uncertainty in the flow-volume relationship. However, the ratio of the flow change to the CMRO2 change is relatively insensitive to these uncertainties. For the linger tapping task, we estimate a most probable flow-consumption ratio ranging from 1.5 to 3 in agreement with previous findings presented in the literature, although we cannot exclude the possibility that there is no CMRO2 change. The large range in the ratio arises from the large number of model parameters that must be estimated from the data. A more precise estimate of the flow-consumption ratio will require better estimates of the model parameters or flow information, as can be provided by combining NIRS with fMRI.

Adult↗

PubMed2003

Differences in the hemodynamic response to event-related motor and visual paradigms as measured by near-infrared spectroscopy.

Several current brain imaging techniques rest on the assumption of a tight coupling between neural activity and hemodynamic response. The nature of this neurovascular coupling, however, is not completely understood. There is some evidence for a decoupling of these processes at the onset of neural activity, which manifests itself as a momentary increase in the relative concentration of deoxyhemoglobin (HbR). The existence of this early component of the hemodynamic response function, however, is controversial, as it is inconsistently found. Near infrared spectroscopy (NIRS) allows quantification of levels of oxyhemoglobin (HbO(2)) and HbR during task performance in humans. We acquired NIRS data during performance of simple motor and visual tasks, using rapid-presentation event-related paradigms. Our results demonstrate that rapid, event-related NIRS can provide robust estimates of the hemodynamic response without artifacts due to low-frequency signal components, unlike data from blocked designs. In both the motor and visual data the onset of the increase in HbO(2) occurs before HbR decreases, and there is a poststimulus undershoot. Our results also show that total blood volume (HbT) drops before HbO(2) and undershoots baseline, raising a new issue for neurovascular models. We did not find early deoxygenation in the motor data using physiologically plausible values for the differential pathlength factor, but did find one in the visual data. We suggest that this difference, which is consistent with functional magnetic resonance imaging (fMRI) data, may be attributable to different capillary transit times in these cortices.

Adult↗

PubMed2001

The accuracy of near infrared spectroscopy and imaging during focal changes in cerebral hemodynamics.

Near infrared spectroscopy (NIRS) can detect changes in the concentrations of oxy-hemoglobin ([HbO]) and deoxy-hemoglobin ([Hb]) in tissue based upon differential absorption at multiple wavelengths. The common analysis of NIRS data uses the modified Beer-Lambert law, which is an empirical formulation that assumes global concentration changes. We used simulations to examine the errors that result when this analysis is applied to focal hemodynamic changes, and we performed simultaneous NIRS measurements during a motor task in adult humans and a neonate to evaluate the dependence of the measured changes on detector-probe geometry. For both simulations and in vivo measurements, the wide range of NIRS results was compared to an imaging analysis, diffuse optical tomography (DOT). The results demonstrate that relative changes in [HbO] and [Hb] cannot, in general, be quantified with NIRS. In contrast to that method, DOT analysis was shown to accurately quantify simulated changes in chromophore concentrations. These results and the general principles suggest that DOT can accurately measure changes in [Hb] and [HbO], but NIRS cannot accurately determine even relative focal changes in these chromophore concentrations. For the standard NIRS analysis to become more accurate for focal changes, it must account for the position of the focal change relative to the source and detector as well as the wavelength dependent optical properties of the medium.

Adult↗

PubMed1997

Detecting synchronous cell assemblies with limited data and overlapping assemblies.

Two statistical methods-cross-correlation (Moore et al. 1966) and gravity clustering (Gerstein et al. 1985)-were evaluated for their ability to detect synchronous cell assemblies from simulated spike train data. The two methods were first analyzed for their temporal sensitivity to synchronous cell assemblies. The presented approach places a lower bound on the amount of data required to detect a synchronous assembly. On average, both methods required the same minimum amount of recording time to detect significant pairwise correlations, but the gravity method exhibited less variance in the recording time. The precise length of recording depends on the consistency with which a neuron fires synchronously with the assembly but was independent of the assembly firing rate. Next, the statistical methods were tested with respect to their ability to differentiate two distinct assemblies that overlapped in time and space. Both statistics could adequately differentiate two overlapping synchronous assemblies. For cross-correlation, this ability deteriorates quickly when considering three or more simultaneously active, overlapping assemblies, whereas the gravity method should be more flexible in this regard. The work demonstrates the difficulty of detecting assembly phenomena from simultaneous neuronal recordings. Other statistical methods and the detection of other types of assemblies are also discussed.

Action Potentials↗

PubMed1996

Searching for cell assemblies: how many electrodes do I need?

Two methods were derived to estimate the probability of recording cell assemblies using multiple simultaneous electrode recordings. The derivations are independent of the definition of a cell assembly, and require only a statistic for evaluating cell assembly membership from spike train data. The resulting equations are functions of 1) the size of the search area, 2) the smallest expected assembly size, 3) the number of recorded neurons, and 4) the predicted spatial distribution of assembly neurons. The equations can be used to estimate the following three quantities. First, the equations directly calculate the probability of detecting i or more cells of an hypothesized assembly. Second, by making several such calculations, one can estimate when sufficient sampling has been performed to claim, at any desired confidence level, that a posited type of cell assembly does not exist. Third, the probability of detecting one out of several active assemblies can be calculated, given assumptions about assembly-assembly interactions.

Cell Division↗