Method to reconstruct neuronal action potential train from two-photon calcium imaging

Differential Covariance: A New Class of Methods to Estimate Sparse Connectivity from Neural Recordings

With our ability to record more neurons simultaneously, making sense of these data is a challenge. Functional connectivity is one popular way to study the relationship of multiple neural signals. Correlation-based methods are a set of currently well-used techniques for functional connectivity estimation. However, due to explaining away and unobserved common inputs (Stevenson, Rebesco, Miller, & Körding, 2008 ), they produce spurious connections. The general linear model (GLM), which models spike trains as Poisson processes (Okatan, Wilson, & Brown, 2005 ; Truccolo, Eden, Fellows, Donoghue, & Brown, 2005 ; Pillow et al., 2008 ), avoids these confounds. We develop here a new class of methods by using differential signals based on simulated intracellular voltage recordings. It is equivalent to a regularized AR(2) model. We also expand the method to simulated local field potential recordings and calcium imaging. In all of our simulated data, the differential covariance-based methods achieved performance better than or similar to the GLM method and required fewer data samples. This new class of methods provides alternative ways to analyze neural signals.

Reconstruction of burst activity from calcium imaging of neuronal population via Lq minimization and interval screening

Calcium imaging is becoming an increasingly popular technology to indirectly measure activity patterns in local neuronal networks. Based on the dependence of calcium fluorescence on neuronal spiking, two-photon calcium imaging affords single-cell resolution of neuronal population activity. However, it is still difficult to reconstruct neuronal activity from complex calcium fluorescence traces, particularly for traces contaminated by noise. Here, we describe a robust and efficient neuronal-activity reconstruction method that utilizes Lq minimization and interval screening (IS), which we refer to as LqIS. The simulation results show that LqIS performs satisfactorily in terms of both accuracy and speed of reconstruction. Reconstruction of simulation and experimental data also shows that LqIS has advantages in terms of the recall rate, precision rate, and timing error. Finally, LqIS is demonstrated to effectively reconstruct neuronal burst activity from calcium fluorescence traces recorded from large-size neuronal population.

NeuroCa: integrated framework for systematic analysis of spatiotemporal neuronal activity patterns from large-scale optical recording data

Optical recording facilitates monitoring the activity of a large neural network at the cellular scale, but the analysis and interpretation of the collected data remain challenging. Here, we present a MATLAB-based toolbox, named NeuroCa, for the automated processing and quantitative analysis of large-scale calcium imaging data. Our tool includes several computational algorithms to extract the calcium spike trains of individual neurons from the calcium imaging data in an automatic fashion. Two algorithms were developed to decompose the imaging data into the activity of individual cells and subsequently detect calcium spikes from each neuronal signal. Applying our method to dense networks in dissociated cultures, we were able to obtain the calcium spike trains of [Formula: see text] neurons in a few minutes. Further analyses using these data permitted the quantification of neuronal responses to chemical stimuli as well as functional mapping of spatiotemporal patterns in neuronal firing within the spontaneous, synchronous activity of a large network. These results demonstrate that our method not only automates time-consuming, labor-intensive tasks in the analysis of neural data obtained using optical recording techniques but also provides a systematic way to visualize and quantify the collective dynamics of a network in terms of its cellular elements.

Error estimation for reconstruction of neuronal spike firing from fast calcium imaging

Calcium imaging is becoming an increasingly popular technology to indirectly measure activity patterns in local neuronal networks. Calcium transients reflect neuronal spike patterns allowing for spike train reconstructed from calcium traces. The key to judging spiking train authenticity is error estimation. However, due to the lack of an appropriate mathematical model to adequately describe this spike-calcium relationship, little attention has been paid to quantifying error ranges of the reconstructed spike results. By turning attention to the data characteristics close to the reconstruction rather than to a complex mathematic model, we have provided an error estimation method for the reconstructed neuronal spiking from calcium imaging. Real false-negative and false-positive rates of 10 experimental Ca(2+) traces were within the estimated error ranges and confirmed that this evaluation method was effective. Estimation performance of the reconstruction of spikes from calcium transients within a neuronal population demonstrated a reasonable evaluation of the reconstructed spikes without having real electrical signals. These results suggest that our method might be valuable for the quantification of research based on reconstructed neuronal activity, such as to affirm communication between different neurons.

Two-photon imaging of neural population activity in zebrafish

Rapidly developing imaging technologies including two-photon microscopy and genetically encoded calcium indicators have opened up new possibilities for recording neural population activity in awake, behaving animals. In the small, transparent zebrafish, it is even becoming possible to image the entire brain of a behaving animal with single-cell resolution, creating brain-wide functional maps. In this chapter, we comprehensively review past functional imaging studies in zebrafish, and the insights that they provide into the functional organization of neural circuits. We further offer a basic primer on state-of-the-art methods for in vivo calcium imaging in the zebrafish, including building a low-cost two-photon microscope and highlight possible challenges and technical considerations.