Long-term optical monitoring of genetically encoded fluorescent indicators

Abstract

Over the past several decades, genetically encoded fluorescent indicators have revolutionized neuroscience by enabling cell-type-specific optical recording of neural activity. While most applications have focused on brain regions where stimulus-evoked activity correlates with behavior on the scale of seconds to minutes, many fundamental behavioral and physiological processes such as feeding, thermoregulation, and circadian timekeeping occur over hours to weeks. However, adapting optical recording techniques to these longer timescales presents unique challenges, particularly in accurately measuring and interpreting neural activity across extended recording durations. As a result, even studies using similar data have reached divergent conclusions, largely due to differences in data analysis and interpretation. This lack of standardization risks misinterpretation, miscommunication, and reduced reproducibility. In this article, we focus on in vivo fiber photometry calcium imaging in circadian neuroscience research as a case study. We review the current literature, outline theoretical, and practical challenges, and offer perspectives for optimizing experimental approaches and standardizing data interpretation. Importantly, the fundamental principles of long-term optical recording extend beyond circadian research and apply broadly to brain circuits that govern behavior and physiology over days to weeks.

Keywords: circadian rhythms; fiber photometry; genetically-encoded fluorescent indicators; long-term in vivo imaging; optical recording.

Fig. 1.

Coupling between tonic and phasic calcium signals varies across brain regions in long-term photometry recordings. A) Simulated calcium-dependent and isosbestic signals over 3 days, illustrating two representative recording scenarios. The top trace models a region with strong circadian rhythms in tonic calcium (e.g. SCN), while the bottom trace models a region with relatively stable tonic calcium (e.g. ARC). Numbered timepoints (1–4) correspond to magnified views in (B and C) Schematic decomposition of fluorescence signals at each timepoint. Signals are conceptually separated into four components: activity-driven calcium, baseline intracellular calcium, ligand-free fluorescence, and autofluorescence. This decomposition is conceptual, intended to illustrate major sources of the fluorescence signal, and is not derived from experimental data. In regions like the SCN (panels 1–2), both tonic baseline and phasic activity fluctuate over time, resulting in higher transients with an elevated baseline during the day and fewer transients with a lower baseline at night. In contrast, regions like the ARC (panels 3–4) show a similar circadian variation in phasic activity but maintain a stable tonic baseline. This distinction highlights the need to analyze tonic and phasic signal components as distinct but complementary features of long-term recordings.

Fig. 2.

Workflow for extracting tonic calcium signals from long-term photometry recordings. A) Raw calcium-dependent and isosbestic signals recorded from GCaMP7s-expressing SCN NMS neurons over 2 days. Data were acquired in 10 min sessions once per hour; 50 min “off-periods” are omitted for illustration. Inset: magnified view of a single 10 min session. B) The isosbestic trace is “globally fit” across the full 48 h recording to correct for photobleaching, changes in protein expression, and low-frequency motion artifacts. C) Within each session, ΔF/F₀ is computed as (signal—fitted isosbestic)/fitted isosbestic, using the portion of the global isosbestic fit corresponding to that session's time window. The tonic signal is then defined as the 2nd percentile of ΔF/F₀ values within each 10 min session. D) Tonic calcium and average fluorescence signals over time. While both signals show circadian variation, because the average fluorescence trace includes both tonic and phasic signal components, its peak time occurs later than that of the percentile-defined tonic signal. Inset: magnified view of the phase difference (triangles).

Fig. 3.

Workflow for extracting phasic calcium signals from long-term photometry recordings. A) Example 10-min session from the SCN recording shown in Fig. 2 illustrating phasic signal extraction following artifact correction. Left: the calcium-dependent signal and isosbestic reference share an “upward” artifact. Center: least-squares (LSQ) fitting, the most widely used method for isosbestic correction in fiber photometry, often fails to capture such transient artifacts, flattening the fitted isosbestic trace. Alternatives such as correlation-guided “dynamic” fitting adapt to local signal structure and preserve shared artifacts in the fitted isosbestic. Right: As a result, LSQ correction introduces a spurious upward deflection in the ΔF/F₀ trace, whereas dynamic fitting avoids this distortion. B) Stacked 10 min ΔF/F₀ traces recorded hourly across a full circadian cycle. ZT (zeitgeber time) indicates hours since lights-on in a 12h:12 h light:dark cycle, where ZT 0 is lights-on and ZT 12 is lights-off. C) Representative 10 min ΔF/F₀ traces depicting potential patterns of phasic activity. The shading indicates signal used to calculate integrated calcium levels; the triangles indicate detected peaks classified as calcium transients. While the top and bottom traces have similar peak counts, they differ substantially in integrated calcium levels due to differences in transient amplitude and shape. This divergence can occur in both directions: sessions with similar numbers of transients may yield different integrated calcium levels, and sessions with similar integrated calcium levels may differ in peak frequency. For accurate characterization, both metrics should be reported when feasible. D, E) Normalized calcium transient numbers (D) and integrated calcium fluorescence levels (E) measured from each 10 min ΔF/F₀ trace across 48 h. Note that both measures reveal circadian variations in phasic activity, but with distinct temporal profiles.

Fig. 4.

Signal decomposition framework and recommended practices for long-term photometry analysis. A) Conceptual pipeline for separating raw fluorescence signals into tonic and phasic signal components. Each branch highlights distinct steps for artifact correction, ΔF/F₀ calculation, and signal quantification, reflecting their different temporal dynamics and analysis needs. B) Recommended practices for acquisition, analysis, and visualization of long-term recordings. These guidelines support reproducibility and ensure proper interpretation of signal features in datasets recorded over extended timescales.