Biomedical subjects

Monica K Chawla

Publications and source records attributed to Monica K Chawla.

6 recordsLinked to original sources

PubMed2006

Advanced imaging of multiple mRNAs in brain tissue using a custom hyperspectral imager and multivariate curve resolution.

Simultaneous imaging of multiple cellular components is of tremendous importance in the study of complex biological systems, but the inability to use probes with similar emission spectra and the time consuming nature of collecting images on a confocal microscope are prohibitive. Hyperspectral imaging technology, originally developed for remote sensing applications, has been adapted to measure multiple genes in complex biological tissues. A spectral imaging microscope was used to acquire overlapping fluorescence emissions from specific mRNAs in brain tissue by scanning the samples using a single fluorescence excitation wavelength. The underlying component spectra obtained from the samples are then separated into their respective spectral signatures using multivariate analyses, enabling the simultaneous quantitative measurement of multiple genes either at regional or cellular levels.

Animals↗

PubMed2006

Recent behavioral history modifies coupling between cell activity and Arc gene transcription in hippocampal CA1 neurons.

The ability of neurons to alter their transcriptional programs in response to synaptic input is of fundamental importance to the neuroplastic mechanisms underlying learning and memory. Because of technical limitations of conventional gene detection methods, the current view of activity-dependent neural transcription derives from experiments in which neurons are assumed quiescent until a signaling stimulus is given. The present study was designed to move beyond this static model by examining how earlier episodes of neural activity influence transcription of the immediate-early gene Arc. Using a sensitive FISH method that detects primary transcript at genomic alleles, the proportion of hippocampal CA1 neurons that activate transcription of Arc RNA was constant at approximately 40% in response to both a single novel exploration session and daily sessions repeated over 9 days. This proportion is similar to the percentage of active neurons defined electrophysiologically. However, this close correspondence was disrupted in rats exposed briefly, but repeatedly, to the same environment within a single day. Arc transcription in CA1 neurons declined dramatically after as few as four 5-min sessions, despite stable electrophysiological activity during all sessions. Additional experiments indicate that the decrement in Arc transcription occurred at the cellular, rather than synaptic level, and was not simply linked to habituation to novelty. Thus, the neural genomic response is governed by recent, but not remote, cell firing history in the behaving animal. This state-dependence of neuronal transcriptional coupling provides a mechanism of metaplasticity and may regulate capacity for synaptic modification in neural networks.

Alleles↗

PubMed2005

Differential encoding of behavior and spatial context in deep and superficial layers of the neocortex.

Rodent hippocampal activity is correlated with spatial and behavioral context, but how context affects coding in association neocortex is not well understood. The cellular distribution of the neural activity-regulated immediate-early gene Arc was used to monitor the activity history of cells in CA1, and in deep and superficial layers of posterior parietal and gustatory cortices (which encode movement and taste, respectively), during two behavioral epochs in which spatial and behavioral context were independently manipulated while gustatory input was held constant. Under conditions in which the hippocampus strongly differentiated behavioral and spatial contexts, deep parietal and gustatory layers did not discriminate between spatial contexts, whereas superficial layers in both neocortical regions discriminated well. Deep parietal cells discriminated behavioral context, whereas deep gustatory cortex neurons encoded the two conditions identically. Increased context sensitivity of superficial neocortical layers, which receive more hippocampal outflow, may reflect a general principle of neocortical organization for memory retrieval.

Animals↗

PubMed2005

Hierarchical, model-based merging of multiple fragments for improved three-dimensional segmentation of nuclei.

BACKGROUND: Automated segmentation of fluorescently labeled cell nuclei in three-dimensional confocal images is essential for numerous studies, e.g., spatiotemporal fluorescence in situ hybridization quantification of immediate early gene transcription. High accuracy and automation levels are required in high-throughput and large-scale studies. Common sources of segmentation error include tight clustering and fragmentation of nuclei. Previous region-based methods are limited because they perform merging of two nuclear fragments at a time. To achieve higher accuracy without sacrificing scale, more sophisticated yet computationally efficient algorithms are needed. METHODS: A recursive tree-based algorithm that can consider multiple object fragments simultaneously is described. Starting with oversegmented data, it searches efficiently for the optimal merging pattern guided by a quantitative scoring criterion based on object modeling. Computation is bounded by limiting the depth of the merging tree. RESULTS: The proposed method was found to perform consistently better, achieving merging accuracy in the range of 92% to 100% compared with our previous algorithm, which varied in the range of 75% to 97%, even with a modest merging tree depth of 3. The overall average accuracy improved from 90% to 96%, with roughly the same computational cost for a set of representative images drawn from the CA1, CA3, and parietal cortex regions of the rat hippocampus. CONCLUSION: Hierarchical tree model-based algorithms significantly improve the accuracy of automated nuclear segmentation without sacrificing speed.

Algorithms↗

PubMed2004

3D-catFISH: a system for automated quantitative three-dimensional compartmental analysis of temporal gene transcription activity imaged by fluorescence in situ hybridization.

Fluorescence in situ hybridization (FISH) of neural activity-regulated, immediate-early gene (IEG) expression provides a method of functional brain imaging with cellular resolution. This enables the identification, in one brain, of which specific principal neurons were active during each of two distinct behavioral epochs. The unprecedented potential of this differential method for large-scale analysis of functional neural circuits is limited, however, by the time-intensive nature of manual image analysis. A comprehensive software tool for processing three-dimensional, multi-spectral confocal image stacks is described which supports the automation of this analysis. Nuclei counterstained with conventional DNA dyes and FISH signals indicating the sub-cellular distribution of specific, IEG RNA species are imaged using different spectral channels. The DNA channel data are segmented into individual nuclei by a three-dimensional multi-step algorithm that corrects for depth-dependent attenuation, non-isotropic voxels, and imaging noise. Intra-nuclear and cytoplasmic FISH signals are associated spatially with the nuclear segmentation results to generate a detailed tabular/database and graphic representation. Here we present a comprehensive validation of data generated by the automated software against manual quantification by human experts on hippocampal and parietal cortical regions (96.5% concordance with multi-expert consensus). The high degree of reliability and accuracy suggests that the software will generalize well to multiple brain areas and eventually to large-scale brain analysis.

Algorithms↗

PubMed2004

Imaging correlates of brain function in monkeys and rats isolates a hippocampal subregion differentially vulnerable to aging.

The hippocampal formation contains a distinct population of neurons organized into separate anatomical subregions. Each hippocampal subregion expresses a unique molecular profile accounting for their differential vulnerability to mechanisms of memory dysfunction. Nevertheless, it remains unclear which hippocampal subregion is most sensitive to the effects of advancing age. Here we investigate this question by using separate imaging techniques, each assessing different correlates of neuronal function. First, we used MRI to map cerebral blood volume, an established correlate of basal metabolism, in the hippocampal subregions of young and old rhesus monkeys. Second, we used in situ hybridization to map Arc expression in the hippocampal subregions of young and old rats. Arc is an immediate early gene that is activated in a behavior-dependent manner and is correlated with spike activity. Results show that the dentate gyrus is the hippocampal subregion most sensitive to the effects of advancing age, which together with prior studies establishes a cross-species consensus. This pattern isolates the locus of age-related hippocampal dysfunction and differentiates normal aging from Alzheimer's disease.

Aging↗