Hansen, K. R. | Search bioRxiv

bioRxiv2018

Automatic Cell Segmentation by Adaptive Thresholding (ACSAT) for large scale calcium imaging datasets

Advances in calcium imaging have made it possible to record from an increasingly larger number of neurons simultaneously. Neuroscientists can now routinely image hundreds to thousands of individual neurons. With the continued neurotechnology development effort, it is expected that millions of neurons could soon be simultaneously measured. An emerging technical challenge that parallels the advancement in imaging such a large number of individual neurons is the processing of correspondingly large datasets, an important step of which is the identification of individual neurons. Traditional methods rely mainly on manual or semi-manual inspection, which cannot be scaled to processing large datasets. To address this challenge, we have developed an automated cell segmentation method, which is referred to as Automated Cell Segmentation by Adaptive Thresholding (ACSAT). ACSAT includes an iterative procedure that automatically calculates global and local threshold values during each iteration based on image pixel intensities. As such, the algorithm is capable of handling morphological variations and dynamic changes in fluorescence intensities in different calcium imaging datasets. In addition, ACSAT computes adaptive threshold values based on a time-collapsed image that is representative of the image sequence, and thus ACSAT provides segmentation results at a fast speed. We tested the algorithm on wide-field calcium imaging datasets in the brain regions of hippocampus and striatum in mice. ACSAT achieved precision and recall rates of approximately 80% when compared to individual neurons that are verified by human inspection. Additionally, ACSAT successfully detected low-intensity neurons that were initially undetected by humans.\n\nSignificanceACSAT automatically segments cells in large scale wide-field calcium imaging datasets. It is based on adaptive thresholding at both global and local levels, implemented in an iterative process to identify individual neurons in a time-collapsed image from an image sequence. It is therefore capable of handling variation in cell morphology and dynamic changes between different calcium imaging datasets at a fast speed. Based on tests performed on two datasets from mouse hippocampus and striatum, ACSAT performed comparable to human referees and was even able to detect low-intensity neurons that were initially undetected by human referees.

neuroscience↗

bioRxiv2018

Inhalation frequency controls reformatting of mitral/tufted cell odor representations in the olfactory bulb

In mammals olfactory sensation depends on inhalation, which controls activation of sensory neurons and temporal patterning of central activity. Odor representations by mitral and tufted (MT) cells, the main output from the olfactory bulb (OB), reflect sensory input as well as excitation and inhibition from OB circuits, which may change as sniff frequency increases. To test the impact of sampling frequency on MT cell odor responses, we obtained whole-cell recordings from MT cells in anesthetized male and female mice while varying inhalation frequency via tracheotomy, allowing comparison of inhalation-linked responses across cells. We characterized frequency effects on MT cell responses during inhalation of air and odorants using inhalation pulses and also playback of sniffing recorded from awake mice. Inhalation-linked changes in membrane potential were well-predicted across frequency from linear convolution of 1 Hz responses and, as frequency increased, near-identical temporal responses could emerge from depolarizing, hyperpolarizing or multiphasic MT responses. However, net excitation was not well predicted from 1 Hz responses and varied substantially across MT cells, with some cells increasing and others decreasing in spike rate. As a result, sustained odorant sampling at higher frequencies led to increasing decorrelation of the MT cell population response pattern over time. Bulk activation of sensory inputs by optogenetic stimulation affected MT cells more uniformly across frequency, suggesting that frequency-dependent decorrelation emerges from odor-specific patterns of activity in the OB network. These results suggest that sampling behavior alone can reformat early sensory representations, possibly to optimize sensory perception during repeated sampling.\n\nSignificance statementOlfactory sensation in mammals depends on inhalation, which increases in frequency during active sampling of olfactory stimuli. We asked how inhalation frequency can shape the neural coding of odor information by recording from projection neurons of the olfactory bulb while artificially varying odor sampling frequency in the anesthetized mouse. We found that sampling an odor at higher frequencies led to diverse changes in net responsiveness, as measured by action potential output, that were not predicted from low-frequency responses. These changes led to a reorganization of the pattern of neural activity evoked by a given odorant that occurred preferentially during sustained, high-frequency inhalation. These results point to a novel mechanism for modulating early sensory representations solely as a function of sampling behavior.

neuroscience↗