The neural connectome has been a subject of increasing research interest since the creation of the BRAIN initiative. Many research and engineering development devoted towards probing functional and structural connections between different regions of the brain are increasingly constantly being made. Optical technologies are no exception to this, facilitating study of the connectome down to the single-cell level. These technologies also realize the investigation of numerous types of electrical and metabolic phenomena, such as calcium signaling, phase changes associated with membrane movement, birefringence changes in cells associated with action potentials, and signaling of NADH and FAD, among other molecules. All of these can be tracked optically, which promotes investigations of how these cells communicate with one another through each of these mechanisms, but more interestingly, how these work together collectively. Optical coherence tomography (OCT), fluorescence lifetime imaging microscopy (FLIM), and multiphoton microscopy (MPM) allow for the simultaneous measurement of all these dynamics. With such rich sources of metabolic information, sophisticated analysis techniques must also be developed to investigate how the collective nature of these dynamics ultimately promotes survival and transfer of information in neural signals. In the Biophotonics Imaging Laboratory, we continue to make advances on each of these fronts with the goal of developing robust combinations of tools to help researchers investigate the complex mechanisms of brain function in healthy and diseased states.
- C. Renteria, et al., “Dynamic tracking algorithm for time-varying neuronal network 635 connectivity using wide-field optical image video sequences,” Scientific Reports,vol. 10, 636 no. 1, pp. 2540, February 2020.
- Y.Z. Liu et al., “Simultaneous two-photon activation and imaging of neural activity based on spectral-temporal modulation of supercontinuum light,” Neurophotonics.
As the volumes of data collected from neural tissue with optical imaging increases, and as the use of integrated optical systems becomes more ubiquitous, there is an added need for more sophisticated system analysis tools. To study the transient dynamics of cellular connectivity, we developed a time-varying connectivity algorithm for optical imaging data. The data in particular was acquired from neural cultures with GCaMP6s, and the connectivity between cells was inferred from their calcium dynamics. A time-varying window for the Pearson’s correlation coefficient was used to determine the linear connectivity between cells, and more concretely, the wavelet transform of the data was used to acquire the frequency-time information exchanged at different instances of cellular activity. Notably, wavelet coherence can be used to also identify the strength of neural connectivity at any point in time, the frequencies at which this is most prominent, and the phase information at these instances between cells, which provides relevant information about the directionality of signal exchange. Coupled to optical imaging, this technique provides a robust method for comprehensively characterizing the communication mechanisms from optical information exchange between cells.
- Renteria C, Liu Y-Z, Chaney EJ, Barkalifa R, Sengupta P, Boppart SA. Dynamic tracking algorithm for time-varying neuronal network connectivity using wide-field optical image video sequences. Scientific Reports, 10:2540, doi:10.1038/s41598-020-59227-5, 2020.
Top: Connectivity workflow for calcium imaging videos, highlighting the different types of data acquired for connectivity analysis. Bottom: Representative calcium imaging plots of cellular activation for multiple cells in a culture (top), the overall connectivity weights acquired between cells (middle), and the time-varying connectivity plots between pairs of cells (bottom).