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Title: Relationship between simultaneously recorded spiking activity and fluorescence signal in GCaMP6 transgenic mice}
Article:
Abstract:
Fluorescent calcium indicators are often used to investigate neural dynamics, but the relationship between fluorescence and action potentials( APs) remains unclear. Most APs can be detected when the soma almost fills the microscope’s field of view, but calcium indicators are used to image populations of neurons, necessitating a large field of view, generating fewer photons per neuron, and compromising AP detection. Here, we characterized the AP-fluorescence transfer function in vivo for 48 layer 2/3 pyramidal neurons in primary visual cortex, with simultaneous calcium imaging and cell-attached recordings from transgenic mice expressing GCaMP6s or GCaMP6f. While most APs were detected under optimal conditions, under conditions typical of population imaging studies, only a minority of 1 AP and 2 AP events were detected( often <10% and ~20–30%, respectively), emphasizing the limits of AP detection under more realistic imaging conditions.
Introduction:
Genetically encoded calcium indicators( GECIs) are widely used with two-photon laser scanning microscopy to report neuronal activity within local populations in vivo( Luo et al., 2018). This optical approach is minimally invasive and enables simultaneous measurement of activity from hundreds or even thousands of neurons at single-cell resolution, over multiple sessions. Using a contemporary GECI such as GCaMP6s, fluorescence changes associated with isolated spikes( action potentials, APs) in vivo can be detected when imaged at sufficiently high spatiotemporal resolution( Chen et al., 2013)( http://dx. doi. org/10. 6080/K02R3PMN). Yet undetected APs are common in population imaging experiments( Theis et al., 2016; Berens et al., 2018). Inferring the underlying AP train or firing rate from calcium imaging remains challenging for several reasons. First, population imaging studies necessarily employ a large field of view containing many neurons. In contrast, the AP to calcium-dependent fluorescence transfer function is typically characterized with a soma filling the field of view of the microscope, to maximize photon flux from the soma and thereby signal-to-noise ratio. Second, there is no ground truth spiking information available for most neurons in a population. Spiking information, often from a cell-attached recording, can be used to refine the spike inference model and thereby optimize AP detection. Third, the AP to calcium-dependent fluorescence transfer function may be different for each neuron due to various intrinsic and extrinsic factors, such as neuron-to-neuron differences in indicator expression. Compared to viral expression, transgenic mouse lines offer convenience( e. g. bypassing virus injection and associated procedures) and achieve more uniform GECI expression in genetically defined neuronal populations( Madisen et al., 2015; Daigle et al., 2018). Using our intersectional transgenic mouse lines that enable Cre recombinase-dependent expression of GCaMP6s or GCaMP6f, we simultaneously characterized the spiking activity and fluorescence of individual GECI-expressing pyramidal neurons in layer 2/3 of mouse primary visual cortex( V1). We then tested the performance of several spike inference models, detecting APs under optimal conditions( models refined using the spiking information, with the soma filling the field of view) and under the less optimal conditions typical of population imaging experiments. Our results provide insight into the relationship between spiking activity in vivo and fluorescence signals and will aid the interpretation of existing and future calcium imaging datasets.
Discussion:
Calcium imaging is widely used to report neuronal spiking activity in vivo. However, accurate spike inference from calcium imaging remains a challenge, and there are relatively few ground truth datasets with simultaneous calcium imaging and electrophysiology to aid the development of more accurate spike inference algorithms. In a recent challenge, ~40 algorithms were trained and tested on datasets consisting of 37 GCaMP6-expressing neurons, underscoring the need for additional GCaMP6 calibration data( Berens et al., 2018). In addition to supporting efforts toward spike inference, an improved understanding of the relationship between spiking and observed fluorescence signals is necessary to further broaden the utility and impact of calcium imaging. To these ends, we contribute a ground truth dataset consisting of 48 V1 L2/3 excitatory neurons recorded at single-cell resolution( available at https://portal. brain-map. org/explore/circuits/oephys) and characterized their AP-to-calcium fluorescence transfer function. Complementing existing datasets with viral GECI expression( Chen et al., 2013; Theis et al., 2016; Dana et al., 2016), our work facilitates interpretation of existing and future calcium imaging studies using mainstream transgenic mouse lines, such as the Allen Institute’s Brain Observatory Visual Coding dataset( http://observatory. brain-map. org/visualcoding)( de Vries et al., 2020). Previous studies have established that most APs can be detected with GCaMP6 indicators under near-optimal conditions( Chen et al., 2013). Yet undetected APs are common in population imaging experiments( Theis et al., 2016; Berens et al., 2018). To investigate why APs are often missed during population imaging, we compared event detection in 250 ms time windows with a neuronal soma occupying most of the image, near-optimal conditions for AP event detection, and event detection when the soma occupies just a small percentage of the field of view, less ideal conditions that are common in population imaging studies. Importantly, we downsampled images to simulate population imaging conditions, enabling comparison for the same APs under different imaging conditions. Our results indicate that, in GCaMP6 transgenic mice, most APs can be detected under near-optimal conditions, while detection is less effective during population imaging. These conclusions are similar to those of previous studies with viral GCaMP6 expression, but our results also reveal two reasons for the difference in detection. Unsurprisingly, the reduced signal-to-noise ratio of population imaging, relative to single soma imaging, results in less effective event detection. However, a high signal-to-noise ratio, achieved by imaging one soma, was no guarantee of effective event detection. Effective detection also required optimization of detection for the neuron of interest, using known AP times to identify events with different AP numbers and so generate kernels of the appropriate amplitude and time course. Parameter tuning in the absence of known AP times, with the MLspike autocalibration routine, improved event detection but not to the high standard of ground truth-optimized detection. Unfortunately, measuring AP times for every neuron with electrophysiology is rarely feasible, severely limiting the percentage of events one might reasonably expect to detect with GCaMP6 in most imaging experiments. Our results point to several practices that might be adopted to maximize spike detection. First, minimize the field of view, hence maximizing photon flux per neuron. Second, tune the spike inference model for each neuron independently, where possible. Third, compare the results of several spike inference models. The three models employed here produced similar AP detection rates, whether applied to high-resolution or to downsampled images. Similarly, Pachitariu et al., 2018 observed that the L0 constraint failed to improve performance of the NND model. Nonetheless, each model has strengths and weaknesses. For example, a model may detect more APs than another but at the cost of a greater false positive rate. As a result, model performance may diverge for some AP rates and patterns. In the worst case, comparing models provides some protection from errors in implementation. Fourth, ensure that traces are sampled( or upsampled) at a sufficiently high rate when employing NND and use autocalibration with MLspike; both make a substantial difference to model performance. Finally, exercise caution when interpreting the inferred spike rates. Commonly, many APs are not detected using even the most accurate spike inference models. In summary, in this study we present a ground truth dataset from anesthetized mice with simultaneous electrophysiology and calcium imaging. Analysis of this dataset revealed that only a small fraction of isolated APs were detected under typical population imaging conditions and with existing spike inference algorithms. By making our data freely available, we hope that it will serve the community as a further resource to better understand the quantitative link between calcium-evoked fluorescent imaging signals and spiking activity.
Neurons , the cells that make up the nervous system , transmit information using electrical signals known as action potentials or spikes . Studying the spiking patterns of neurons in the brain is essential to understand perception , memory , thought , and behaviour . One way to do that is by recording electrical activity with microelectrodes . Another way to study neuronal activity is by using molecules that change how they interact with light when calcium binds to them , since changes in calcium concentration can be indicative of neuronal spiking . That change can be observed with specialized microscopes know as two-photon fluorescence microscopes . Using calcium indicators , it is possible to simultaneously record hundreds or even thousands of neurons . However , calcium fluorescence and spikes do not translate one-to-one . In order to interpret fluorescence data , it is important to understand the relationship between the fluorescence signals and the spikes associated with individual neurons . The only way to directly measure this relationship is by using calcium imaging and electrical recording simultaneously to record activity from the same neuron . However , this is extremely challenging experimentally , so this type of data is rare . To shed some light on this , Huang , Ledochowitsch et al . used mice that had been genetically modified to produce a calcium indicator in neurons of the visual cortex and simultaneously obtained both fluorescence measurements and electrical recordings from these neurons . These experiments revealed that , while the majority of time periods containing multi-spike neural activity could be identified using calcium imaging microscopy , on average , less than 10% of isolated single spikes were detectable . This is an important caveat that researchers need to take into consideration when interpreting calcium imaging results . These findings are intended to serve as a guide for interpreting calcium imaging studies that look at neurons in the mammalian brain at the population level . In addition , the data provided will be useful as a reference for the development of activity sensors , and to benchmark and improve computational approaches for detecting and predicting spikes .