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Dizaji, A. S.

Publications and source records attributed to Dizaji, A. S..

2 recordsLinked to original sources

Neuronal tracing and analysis by multispectral tracing in densely labeled mouse brain

Accurate and complete neuronal wiring diagrams are necessary for understanding brain function at many scales from long-range interregional projections to microcircuits. Traditionally, light microscopy-based anatomical reconstructions use monochromatic labeling and therefore necessitate sparse labeling to eliminate tracing ambiguity between intermingled neurons. Consequently, our knowledge of neuronal morphology has largely been based on averaged estimations across many samples. Recently developed second-generation Brainbow tools promise to circumvent this limitation by revealing fine anatomical details of many unambiguously identifiable neurons in densely labeled samples. Yet, a means to quantify and analyze the information is currently lacking. Therefore, we developed nTracer, an ImageJ plugin capable of rapidly and accurately reconstructing whole-cell morphology of large neuronal populations in densely labeled brains.

neuroscience

A Change-point Analysis Method for Single-trial Study of Simultaneous EEG-fMRI of Auditory/Visual Oddball Task

Simultaneous EEG-fMRI has been vastly used to investigate functional networks of brain combining high spatial resolution (millimeter) of fMRI with high temporal resolution (millisecond) of EEG. However, to extract the most relevant information from the acquired data, it is necessary to develop analysis methods with less ad hoc assumptions. To this end, brain rhythms are often used which are the specific frequency-bands of EEG signal and assumed to represent diverse sub-second cognitive processes at different parts of the cortex. Furthermore, single-trial analysis of EEG is believed to show more realistic picture of ongoing and event-related activities of brain. Here, we present a nonparametric multiple change-point detection and estimation method for the single-trial analysis of simultaneous EEG-fMRI experiment recorded during auditory and visual oddball tasks. In a simple attention task like oddball, the frontal cortex of brain is responsible to distinguish and respond appropriately to target versus standard events. By using EEG signal at the frontal cortex, we show that the -band activity changes according to \"inhibition timing\" hypothesis and the {beta}-band activity is in line with \"maintaining the status quo\" hypothesis. Furthermore, using these activities to build regressors in the GLM analysis of fMRI, we localize active brain regions with high spatial and temporal resolutions and elaborate further on the coordination of attentional networks across brain.

neuroscience