Wade Thomas Rogers

Quantitation of cellular resolution in situ hybridization histochemistry in brain by image analysis

A new method for relative quantitation of mRNA levels with single neuron resolution is described. Hybridized tissue sections are emulsion dipped, exposed, and developed. The resulting silver grains are visualized using dark-field microscopy at high magnification. The method relies on computer-based image analysis of sequentially located, high resolution, small fields containing the cell images, each of which is analyzed for mRNA content. Maps of cell distributions are constructed, with cell marks color-coded for relative mRNA levels, yielding previously unavailable information on regional distribution of quantitative cellular expression of specific mRNA in brain.

The ventrolateral medulla as a source of synaptic drive to rhythmically firing neurons in the cardiovascular nucleus tractus solitarius of the rat

We sought to determine whether the caudal ventrolateral medulla (cVLM), at the level of area postrema, influences the rhythmically beating neurons found within the dorsomedial NTS in rat brainstem slices. Intra- or extracellular recordings of neurons firing rhythmically at around 5 Hz were characterized as either auto-active (i.e. pacemaker; AA) or synaptically driven (SD) by pharmacological interventions. The nature of inputs evoked from the ipsilateral cVLM were orthodromic and the majority were excitatory (latency 3-20 ms). Further, this excitatory influence was found to be tonically active in 25/47 cells studied since inactivating the ipsilateral cVLM by localized cooling reduced the firing rate by 0.5-3.0 Hz (23% on average). Neuronal characterization showed that the most consistent and pronounced effect occurred on SD rather than AA cells. Control experiments that cooled other areas of the slice closer to the recording site proved ineffective. Additional studies showed that most rhythmically firing cells in the NTS received an excitatory synaptic input from the solitary tract (ts; latency 3-30 ms). This input was reduced or blocked by inactivating the cVLM in neurons in which the ts latency of activation was greater than 8 ms in half of the neurons tested. Subsequent pharmacological tests revealed that these neurons were predominantly SD. Identified AA neurons received an input from the ts at a shorter latency, typically less than 8 ms, and this was unperturbed by cooling the cVLM in all cases. Further, there was no obvious difference in the baseline discharge rates between cells in the hemi-slice and those recorded in an intact slice. In a hemi-coronal slice cooling the cVLM also produced a 20% decrease in firing rate in identified SD neurons but no consistent change in AA cells. We conclude that (1) the ipsilateral cVLM contributes principally tonic excitatory drive to rhythmically active neurons in the dorsomedial NTS in vitro and this preferentially effects SD neurons; (2) other excitatory drives other than those from the ipsilateral cVLM impinge upon SD cells, the origin of which are relatively local and likely to be in the NTS; (3) in the slice the projection from the cVLM to the NTS appears to be present but the reciprocal connection is absent.

Quantitation and digital representation of in situ hybridization histochemistry

Publisher Summary In situ hybridization histochemistry has frequently been used as a qualitative technique to detect and localize specific nucleic acid sequences in an anatomical context, without particular respect to the abundance of the detected sequence. Quantitative analysis is necessary for evaluating changes in gene expression with in situ hybridization histochemistry. The structural and functional complexity of the brain requires that this analysis be represented in an anatomical context to be meaningful. With autoradiographic film analysis, this process is efficiently carried out by the computerized densitometry and pseudocolor representation of the film images of the hybridization signal. In contrast, a quantitative analysis of autoradiographic grain density at the cellular level is more difficult. However, the high degree of anatomical specificity and resolution obtained with emulsion autoradiography should facilitate any study of the distribution and regulation of messenger RNA (mRNA) levels in heterogeneous tissues, such as the brain.

Computer-aided mapping of brain tissue.

A computer-microscope system is described for use in capturing accurate, quantitative schematic (map) information from anatomical tissue sections. The system provides a rapid and convenient environment for acquisition and analysis of complex structures spread over large 3-D regions of the tissue. As a consequence of the complexity and subtlety of tissue analysis, most of the data acquisition functions of the system involve tight coupling between the hardware and the microscopist to preserve access to human judgment and intelligence. The instrument profoundly affects the ease and accuracy of neurobiological data analysis, making it practical to address previously inaccessible problems. Examples of data analyzed using the system are shown.

Dynamic model-based controller in the brain

The authors present a model of the neuronal network that performs adaptive control of the vertebrate cardiovascular system. The model incorporates new data on the cell groups and connections of the circuit, on the synaptic activity and discharge properties of cardiovascular neurons in the brainstem, and on the modulation of their excitability by nonsynaptic intrinsic membrane properties. Some of these data have been represented in a computational model, thus allowing simulations to generate hypotheses regarding design principles of the control system.<<ETX>>

Reconstructing computational principles in a vertebrate adaptive reflex system

This research is based on the premise that computational principles evolved by biological systems are applicable to engineering devices, that an interaction of ongoing neurobiological experiments with computer simulation will be productive in extracting computational principles, and that tools for the analysis of neurobiological systems and for their modeling and simulation have evolved to the point where success is probable. The approach is based on neuroanatomical experiments to establish the connectional circuit. However, it is found that knowledge of network architecture (connectivity) is not enough. The biophysics of neurons leads to important diversity of intrinsic properties among constituents of a network. Consequently, neurons have dynamical response properties that can sensitively affect, or even completely alter, the functioning of a distributed network. Experimentally determined facts of both connection and biophysics must inform computational models in order to capture network dynamics/performance. Simulation results in turn generate hypotheses which drive further testing in biological experiments