Density center-based fast clustering of widefield fluorescence imaging of cortical mesoscale functional connectivity and relation to structural connectivity.

ABSTRACT: Spontaneous resting-state neural activity or hemodynamics has been used to reveal functional connectivity in the brain. However, most of the commonly used clustering algorithms for functional parcellation are time-consuming, especially for high-resolution imaging data. We propose a density center-based fast clustering (DCBFC) method that can rapidly perform the functional parcellation of isocortex. DCBFC was validated using both simulation data and the spontaneous calcium signals from widefield fluorescence imaging of excitatory neuron-expressing transgenic mice (Vglut2-GCaMP6s). Compared to commonly used clustering methods such as k-means, hierarchical, and spectral, DCBFC showed a higher adjusted Rand index when the signal-to-noise ratio was greater than - 8    dB for simulated data and

SUBMITTER: Li M 

PROVIDER: S-EPMC6917047 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature