Dr. Pulkit Grover Profile

Dr. Pulkit Grover

at Carnegie Mellon Univ

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Publications (2)

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Proceedings Article | 4 March 2022 Presentation + Paper

Optimized optode placement strategy for diffuse optical tomography

Jiaming Cao, Pulkit Grover, Jana Kainerstorfer

Proceedings Volume 11945, 1194505 (2022) https://doi.org/10.1117/12.2610184

KEYWORDS: Sensors, Brain, Diffuse optical tomography, Head, Image resolution, Optimization (mathematics), Neuroimaging, Computer simulations

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Diffuse optical tomography (DOT) is a widely used optical method for functional neuroimaging. When a dense grid of optodes is used, DOT can produce functional brain imaging maps that are comparable with fMRI in terms of spatial resolution. However, when the available number of sources and detectors are limited, it is important to understand where to place them to image a region of interest (ROI) with optimal coverage and sensitivity to the brain. Conventionally, the optode configuration is heuristically determined by the experimenter. Recently, a total sensitivity maximizing algorithm was proposed to answer the question as an optimization problem. However, in larger ROIs and complex geometries, optodes tend to crowd over only a small portion of the ROI and have therefore unsatisfactory coverage of the ROI. ArrayDesigner was proposed as an attempt to address these limitations by adding a coverage term, so that the algorithm can balance between sensitivity and coverage of the ROI. In this work, we demonstrate that such modification still may not suffice in certain geometries, and the inherent nature of sensitivity maximization can limit the uniformity of imaging. We propose a resolution- based optimization algorithm Grid Resolution with Optimized Uniformity Placement (GROUP)" that aims to provide high-resolution, uniform DOT imaging. We show simulated data using a realistic head model that GROUP can provide better uniformity of resolution and has the flexibility to tune the focus to voxels of different depths.

SPIE Journal Paper | 1 January 2021 Open Access

Enhanced spatiotemporal resolution imaging of neuronal activity using joint electroencephalography and diffuse optical tomography

Jiaming Cao, Theodore Huppert, Pulkit Grover, Jana Kainerstorfer

NPh, Vol. 8, Issue 01, 015002, (January 2021) https://doi.org/10.1117/12.10.1117/1.NPh.8.1.015002

KEYWORDS: Electroencephalography, Reconstruction algorithms, Resolution enhancement technologies, Electrodes, Brain, Image resolution, Spatial resolution, Sensors, Hemodynamics, Neurophotonics

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Significance: Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) are both commonly used methodologies for neuronal source reconstruction. While EEG has high temporal resolution (millisecond-scale), its spatial resolution is on the order of centimeters. On the other hand, in comparison to EEG, fNIRS, or diffuse optical tomography (DOT), when used for source reconstruction, can achieve relatively high spatial resolution (millimeter-scale), but its temporal resolution is poor because the hemodynamics that it measures evolve on the order of several seconds. This has important neuroscientific implications: e.g., if two spatially close neuronal sources are activated sequentially with only a small temporal separation, single-modal measurements using either EEG or DOT alone would fail to resolve them correctly. Aim: We attempt to address this issue by performing joint EEG and DOT neuronal source reconstruction. Approach: We propose an algorithm that utilizes DOT reconstruction as the spatial prior of EEG reconstruction, and demonstrate the improvements using simulations based on the ICBM152 brain atlas. Results: We show that neuronal sources can be reconstructed with higher spatiotemporal resolution using our algorithm than using either modality individually. Further, we study how the performance of the proposed algorithm can be affected by the locations of the neuronal sources, and how the performance can be enhanced by improving the placement of EEG electrodes and DOT optodes. Conclusions: We demonstrate using simulations that two sources separated by 2.3-3.3 cm and 50 ms can be recovered accurately using the proposed algorithm by suitably combining EEG and DOT, but not by either in isolation. We also show that the performance can be enhanced by optimizing the electrode and optode placement according to the locations of the neuronal sources.

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