Claridge-Chang Lab

New Paper: Getting over ANOVA

Adam Claridge-Chang — Fri, 07 Aug 2026 00:00:00 GMT

‘Getting over ANOVA’ is the title of our paper on multi-group data, out today in Nature Methods.

The break-up is overdue. ANOVA asks whether all the groups are the same—a question nobody wants answered—and then sends you off to a pile of post-hoc tests nobody wants either. So what replaces it? We need methods that answer what we actually want to know: which groups differ, in which direction, and by how much. And they should not just report it, but also show it.

The new paper describes a software package, DABEST 2.0, that brings estimation graphics to multi-group data: repeated measures, two-factor interactions via delta-delta effects, binary outcomes, and internal replicates via mini-meta. Some graphics can directly replace an ANOVA method. Each graphic shows the raw data, the effect size, and the uncertainty.

Building software to visualize multi-group effect sizes has been a collaborative effort by the DABEST team, and I’m proud of what we built. DABEST is open source and available in Python, R, and through a web app. Data analysis should be easy to practice, and give you direct answers to the questions your experiments were designed to ask.

Shout out to the team: Zinan Lu, Jonathan Anns, Yishan Mai, Rou Zhang, Kahseng Lian, Nicole Lee, Shan Hashir, Zhuoyu Wang, Yixuan Li, A. Rosa Castillo, Joses Ho, Hyungwon Choi, Sangyu Xu

Check the discussion on LinkedIn

Nicole Lee Graduates

Adam Claridge-Chang — Wed, 15 Jul 2026 00:00:00 GMT

I was delighted to celebrate Nicole Lee’s graduation!

Over her years in the lab she investigated valence neurons, built behavioral rigs, hacked analysis pipelines, contributed to open-source software, and developed new optogenetic toolkits. Beyond the science, she was the kind of labmate who makes everyone around them better.

Congratulations, Dr. Nicole, and this is just the beginning!

Check out her work here: https://lnkd.in/g9YateT2

Mini-Meta to Summarize All Internal Results

Yishan Mai — Thu, 25 Jun 2026 00:00:00 GMT

A difficult question I ran into early in my PhD was: When multiple experimenters do the same experiment but produce different results, what do you do?

Many would either cherry-pick the “best” replicate or blindly average results; the first conceals data while the second is statistically unsound. To solve this problem, we developed mini meta-analysis for DABEST 2.0, which lets you synthesize results from internally replicated experiments. It allows you to:

— Visualize effect sizes from each replicate

— Compute a weighted meta-analytic effect

— See the consistency (or heterogeneity) across your replicates

So next time you and your colleagues have the urge to argue on whose replicate is more “correct”, consider using mini meta-analysis to combine your data into a single, meaningful conclusion, while maintaining transparency in data reporting.

Preprint: https://doi.org/10.64898/2026.01.26.701654

Code: https://github.com/ACCLAB/DABEST-python

Work in collaboration with: Zinan Lu, Jonathan Anns, Sangyu Xu, Nicole Lee, Hyungwon Choi, Adam Claridge-Chang, and others.

Repeated Measures: A Better Way

Jonathan Anns — Thu, 21 May 2026 00:00:00 GMT

Why your repeated-measures data deserves better than a simple line

Whenever the same subjects are measured more than once, whether across timepoints, doses, or conditions, you have a repeated-measures design. It’s one of the most common frameworks in biomedical research. Yet research papers typically reduce these experiments into a mean line with error bars and P-values (Fig. 1A).

So, what’s missing? The individual trajectories. The sense of variability. The actual magnitude of change.

In addition, the typical analysis approach entails a combinatorial explosion of post-hoc tests computing every possible pairwise comparison (Fig. 1B), many of which are not relevant to your hypothesis and unnecessarily inflate your multiple comparisons burden. The questions that actually motivated the study (when does the effect begin?, how large does it grow?, and does it persist?) are obfuscated.

Our new software, DABEST 2.0, is designed around a different approach: keep the individuals, and draw the overall shape. Our repeated-measures figure has two panels doing two distinct jobs. The upper panel shows observed values and their dispersion, an attribute of the sample (Fig. 1C). The lower panel shows the bootstrap distribution of the effect at each timepoint, an inference of precision that sharpens as the sample grows (Fig. 1D).

With DABEST 2.0, you can:

— Visualise each subject’s individual trajectory alongside the means.

— Report the effect size with confidence intervals for the comparisons you care about.

— Show the full distribution of differences.

The result is a figure that more clearly quantifies (in a pretty way!) what changed, for whom, and by how much.

Preprint: https://doi.org/10.64898/2026.01.26.701654

Code: https://github.com/ACCLAB/DABEST-python

Work in collaboration with: Zinan Lu, Yishan Mai, Sangyu Xu, Nicole Lee, Hyungwon Choi, Adam Claridge-Chang, and others.

Preprint: Long-Stokes-Shift mScarlet3 as a Structural Marker for Two-Photon Imaging

Adam Claridge-Chang — Thu, 14 May 2026 00:00:00 GMT

Excited to share our new preprint! 🎉

We made a transgenic fly harbouring a long-Stokes-shift red fluorescent protein (LSSmScarlet3) that can be imaged alongside green GCaMP using a single 920 nm laser. No second laser needed.

This will let researchers do dual-channel functional and structural two-photon imaging more simply and affordably than before. We show the spectral properties, validate it in live fly (Drosophila) brains, and demonstrate minimal crosstalk with the green channel. In addition, we think this tool could be useful well beyond structural marking in applications like from co-imaging synaptic activity to tracking subcellular localization and protein levels in real time.

The transgenic line is validated and ready to use, we hope it’s useful to the fly imaging community.

Preprint: https://doi.org/10.64898/2026.04.12.718060

Work by Sangyu Xu, Xianyuan Zhang, King Yee Cheung, Yishan Mai and others.

Preprint: A Mushroom-Body Output Neuron That Mediates Octopamine-Driven and Hunger-Motivated Feeding in Drosophila

Adam Claridge-Chang — Wed, 13 May 2026 00:00:00 GMT

What if a single brain cell could make you hungry or ruin your appetite?

That’s essentially what we found in the vinegar fly (Drosophila). A neuron called MBON11 in the fly brain, can drive feeding behavior in both directions. Activate this cell with red light and flies eat more, even if they’re full. Silence this neuron with green light, and hungry flies eat much less.

Curiously, MBON11 is located in the mushroom body, which is the brain region flies use to learn and remember. We show that it also directly controls the drive to eat, drawing the picture that memory circuits are intimately involved in feeding decisions and, seemingly, hunger itself.

We found that two different chemical signals feed into this neuron. Adrenaline-like octopamine can increase feeding without being strictly necessary, while dopamine is required for hunger to translate into eating, but can’t override a full stomach on its own. MBON11 receives both of these types of signals.

A methodological note: we used a feeding assay that directly measures consumption, and instead of relying on a single feeding metric, we used multi-dimensional ‘phenovectors’, and contextualized them against natural hunger and satiety states. This gave us a richer, holistic picture of how different circuit manipulations affect feeding patterns overall.

Proud of Xianyuan Zhang and the whole team on this one. 🎉

Preprint out now: https://doi.org/10.64898/2026.03.13.711740

Xianyuan Zhang, Sangyu Xu, Joses Ho, James C. Stewart

Nicole Lee Defends Thesis

Adam Claridge-Chang — Wed, 15 Apr 2026 00:00:00 GMT

Thrilled to announce the successful thesis defense of lab member and doctoral student Nicole Lee! She grew from strength to strength, and has written an excellent thesis on the relationship between motor functions and valence, and developing new optogenetic tools to better silence neuronal circuits.

The examiners (Shawn Je, Hong-Wen Tang, Caroline Wee, and Joshua Gooley) posed some challenging questions that Nicole handled with aplomb.

Preprint: Getting over ANOVA

Adam Claridge-Chang — Thu, 12 Feb 2026 00:00:00 GMT

Here’s a dirty secret about ANOVA: it tests a null hypothesis that nobody cares about. When you run a one-way ANOVA, you’re testing whether “all group means are equal.” But even if you reject this hypothesis, you learn nothing about which groups differ, in which direction, or by how much.

So you embark on a second analytical step: multiple two-group comparisons. A modest six-group experiment suddenly requires testing 15 hypotheses. To manage this multiplicity, you apply corrections like Bonferroni, which undermine your statistical power. What you posed as a focused research question has sprawled into a complex web of subsidiary tests, forced by the ANOVA ritual.

Our new preprint, “Getting over ANOVA: Estimation graphics for multi-group comparisons,” makes the case for a better approach. Estimation statistics encourages you to compare each test group to a single control, focusing on the effect sizes that actually matter. A six-group experiment focuses attention on just five effect sizes with confidence intervals, showing magnitude and precision directly.

The preprint introduces estimation methods for a range of multi-group designs: repeated-measures experiments, 2×2 factorial designs, binary outcome data, and mini-meta analysis for internal replicates. Each can replace data-analysis practices used in thousands of studies every year.

Read our new preprint here: https://doi.org/10.64898/2026.01.26.701654

The Word That Wasn’t There

Adam Claridge-Chang — Mon, 26 Jan 2026 00:00:00 GMT

I was writing about serotonin-receiving neurons and reached for “serotonoceptive.” The word should exist, but it doesn’t.

We have “dopaminergic” for neurons that release dopamine, so why no equivalent for neurons that receive it? Instead, the literature is full of workarounds: “dopamine-sensitive neurons,” “neurons expressing dopamine receptors,” “dopamine target cells.”

A solution was hiding in plain sight: “nociceptive” and “proprioceptive” have been around since Sherrington. Recent papers already use “GABAceptive” and “dopaminoceptive.”

So I wrote a short paper proposing we generalize the ‘-ceptive’ suffix. Dopaminergic neurons release dopamine; dopaminoceptive neurons receive it. Simple, systematic, and searchable.

Read the editorial here: https://doi.org/10.5281/zenodo.18373728

First Image of the Actin Nucleus: The Seed That Grows the Cytoskeleton

Adam Claridge-Chang — Mon, 08 Dec 2025 00:00:00 GMT

For 50 years, biologists have known that cells build their internal scaffolding from actin filaments, but we’ve never actually seen how filament formation begins. I’m excited to share that our collaborative team has solved this basic mystery about the cytoskeleton.Using x-ray crystallography, the Robinson group captured the first atomic-resolution structure of an actin nucleus: the three-molecule complex that starts every actin filament. Their secret weapon? Villin protein fromParalvinella sulfincola, a remarkable worm that thrives in scalding deep-sea thermal vents. Collected by submarine, the worm’s naturally stable actin-binding protein proved perfect for crystallization.The three actin molecules in the nucleus aren’t identical: each adopts a different shape, representing different stages of the transformation from individual units to filament building blocks. They also discovered a molecular gate that dynamically opens and closes to allow new actin molecules to join the growing filament.The structure also illuminates how actin-binding proteins cut filaments: they exploit natural fluctuations to compete for binding sites and destabilize the structure. This principle likely applies to other actin-binding proteins relevant to disease and development, opening new avenues for intervention.This work was led by the Robinson group, with contributions from the Girguis (marine biology) and Copley (genomics) groups.Our paper is out now in Science Advances. https://doi.org/10.1126/sciadv.adw6915

Genome of a thermal-vent worm yields insight into animal heat tolerance

Adam Claridge-Chang — Thu, 04 Dec 2025 00:00:00 GMT

How do neurons keep working at the thermal limit of animal life?Our new chromosome-scale genome of the Pompeii worm starts to answer. It has a conservative genome but a finely tuned proteome: expanded globins, anaerobic enzymes, and new sulfur chemistry. These let the worm thrive while grazing on bacteria in hot, dark, oxygen-starved vents at the bottom of the Pacific Ocean.This new proteome now offers thermostable tools for biochemistry and a window into physiology at extremes.This amazing project was led bySami EL HILALIandRichard Copley, with contributions from the Robinson, Hoelz, Martín-Durán, and Jollivet groups.Read the paper in BMC Biologyhttps://doi.org/10.1186/s12915-025-02369-7

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Using a long-Stokes-shift dye for two-photon microscopy

Adam Claridge-Chang — Thu, 04 Dec 2025 00:00:00 GMT

Two colors from one laser: new preprint from my lab about a novel dye application.Motion artifacts and anatomical orientation can pose challenges to two-photon live imaging. A second color channel helps with both problems—but usually requires a second expensive laser. We found another way. The dye ATTO 490LS is a long-Stokes-shift fluorescent dye that’s been around for a decade, but its two-photon properties were unknown. We’ve now found that 490LS works beautifully with a 920 nm laser, the same wavelength used for GFP and GCaMP imaging. Excite with 920 nm, collect both green and red light with two detectors. One laser, two colors.Having a stable red marker like 490LS lets you find a region of interest and distinguish real calcium transients from motion-induced changes. We’re now working toward HaloTag and other conjugates for in vivo chemogenetic labeling, allowing calcium imaging with a stable reference. Please let us know if you’re interested in trying some.Preprint now on bioRxiv:https://www.biorxiv.org/content/10.1101/2025.11.21.689649v2.fullWork was led byKing Yee Cheung, with help fromXianyuan Zhang,Danesha Devini Suresh,Masahiro Fukuda, and the NUS Microscopy Core.

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Activation Drift in Kalium Channelrhodopsins

Adam Claridge-Chang — Tue, 11 Nov 2025 00:00:00 GMT

When KCRs were discovered in 2022, they promised to revolutionize neuronal silencing. Finally we had a light-gated potassium channel that could inhibit neurons in a similar way to endogenous K+ channels. The Spudich, Hegemann, and Deisseroth groups pioneered engineering variants with improved K+ selectivity (WiChR, KALI1, KALI2) each showing progressively better specificity and higher conductance.But something didn’t add up; a report from worms showed, under certain conditions, behavior consistent with undesirable activation. Now, our systematic evaluation in flies and worms shows why: during continuous illumination, many KCRs’ potassium selectivity declines. Indeed, as time wears on and sodium conductance rises, each can shift from acting as an inhibitor to becoming an activator.This suggests that KCRs have an Achilles heel—but for one exception. Among all variants tested, KCR1-C29D, a single point mutation made by the Hegemann group, outperformed the heavily engineered versions. Across light intensities and durations, C29D maintains stable inhibition, providing reliable silencing.The TL;DR of the paper:→ Ion selectivity stability matters more than absolute selectivity→ Light intensity and illumination duration affect KCR function→ Sometimes high conductance can be too much of a good thing→ Sometimes simpler mutations work better than complex engineeringThis work bridges the gap between biophysical characterization and applications in neural circuit analysis. It shows why systematic validation remains essential, especially when everyone is excited about a new tool.🔗 Read more atAdvanced Science:https://doi.org/10.1002/advs.202509180This work was done with collaborators from labs in Würzburg, Leipzig, and Frankfurt, includingShiqiang Gao, who led this important project. Congratulations also to Zhiyi Zhang, and StanislavOttfrom my group whose work established C29D as the best inhibitor.

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Parallel Function of Dopamine Neurons in Acute Behavior

Adam Claridge-Chang — Tue, 11 Nov 2025 00:00:00 GMT

Our lab identified a previously unknown parallel function of dopamine neurons involved in olfactory memory inDrosophila. While these neurons were known to be crucial for memory formation, we demonstrate they simultaneously drive immediate attraction and aversion behaviors, independent of their memory-related function.Through optogenetic manipulation, we found that sensory neurons essential for olfactory memory were not required for dopamine-driven immediate responses. We identified two key neuronal populations: a broad network of dopaminergic neurons that influenced behavior through dopamine, glutamate, and octopamine signaling, and a more specific cluster that drove attractive responses. Notably, inhibiting this latter group caused flies to display active avoidance, highlighting its role in ongoing behavioral control.This work reveals how dopaminergic systems can coherently guide both immediate responses and memory formation, advancing our understanding of the neural circuits underlying learning and behavior.The study was published inPLOS Biology.

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Synthetic memory inception

Adam Claridge-Chang — Tue, 11 Nov 2025 00:00:00 GMT

We successfully implanted entirely artificial memories by simultaneously activating sensory neurons and dopaminergic circuits using optogenetics. Even without any natural odors or reinforcements, we could implant new odor memories.We found that coincident activation of olfactory receptor neurons (ORNs) and dopamine neurons was sufficient to form both aversive and appetitive memories. Complex temporal patterns weren’t required: simple rectangular light pulses worked fine.This study demonstrates that basic co-activation of sensory and neuromodulatory pathways is enough to instruct associative learning.Our fully optogenetic approach opens new possibilities for dissecting memory mechanisms with unprecedented control over timing and cellular specificity.Grateful to my co-authorsTayfun Tümkaya, Ph.D.,Xianyuan Zhang.Yishan Mai, James Stewart, and the team at Duke-NUS Medical School & A*STAR Singapore.Read the full paper in iScience:https://doi.org/10.1016/j.isci.2025.113540

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Technical note: Fly KCR construct maps

Adam Claridge-Chang — Tue, 25 Mar 2025 00:00:00 GMT

We have uploaded the verified vector information for the publishedDrosophilaKCR constructs to Zenodo. Files can be assessed under:https://zenodo.org/records/15074206The file contains vector maps for the below constructs:pJFRC7_20xUAS_HcKCR1_AAA_YFPpJFRC7_20xUAS_HcKCR1_C29D_YFPpJFRC7_20xUAS_HcKCR1_ET_YFPpJFRC7_20xUAS_HcKCR1_GS_YFPpJFRC7_20xUAS_HcKCR2_AAA_YFPpJFRC7_20xUAS_HcKCR2_ET_YFPpJFRC7_20xUAS_HcKCR2_GS_YFPpJFRC7_20xUAS_WiChR_ET_YFPThesewere reported in:Ott, S., Xu, S., Lee, N.et al.Kalium channelrhodopsins effectively inhibit neurons.Nat Commun15, 3480 (2024). https://doi.org/10.1038/s41467-024-47203-wAlso:Kalium channelrhodopsins effectively inhibit neurons in the small model animalsStanislavOtt,SangyuXu,NicoleLee,Ivan Hee KeanHong,JonathanAnns,Danesha DeviniSuresh,ZhiyiZhang,XianyuanZhang,RaihanahHarion,WeiyingYe,VaishnaviChandramouli,SureshJesuthasan,YasunoriSaheki,AdamClaridge-ChangbioRxiv2024.01.14.575538;doi:https://doi.org/10.1101/2024.01.14.575538Fly constructs and geneticsUAS-KCR1-ET,UAS-KCR2-ET,UAS-KCR1-GSand UAS-WiChR transgenic lines were generated byde novosynthesis (Genscript) ofDrosophilacodon-optimized HcKCR insert sequences43(Genbank #MZ826861and #MZ826862) or the WiChR sequence[45](https://www.biorxiv.org/content/10.1101/2024.01.14.575538v1.full#ref-45)(Genbank #OP710241) as eYFP fusions. After Sanger sequencing verification (Genscript), the fragments were cloned into anpJFRC7-20XUAS-IVS-mCD8::GFPvector (Addgeneplasmid # 26220), replacing themCD8::GFPinsert via restriction enzyme digest (XhoI, Xba I). ForUAS-KCR1-GS, a 3×GGGGS sequence was used to link the opsin with the fluorophore. For the KCR-ET and WiChR constructs, an AAA linker sequence was used as the starting point, to which two modifications were made: (1) an FCYENEV motif was added to the C terminus of eYFP to boost protein export from the endoplasmic reticulum and prevent potential aggregate formation51; and (2) a KSRITSEGEYIPLDQIDINV trafficking signal from Kir 2.152was added to the linker at C terminus of the opsin to boost protein expression10. The KCR1-C29D variant45was obtained by site-directed mutagenesis of the KCR1-ET sequence, where the cysteine at position 29 was replaced by aspartic acid (Genscript). The synthesized constructs were injected into flies and targeted to attP1 or attP2 insertion sites on the second or third chromosomes respectively and the transgenic progeny were balanced either over CyO or TM6C (BestGene). Expression was verified by imaging of eYFP fluorescence with a Leica TCS SP8 STED confocal microscope. Opsin transgenic flies were crossed with relevant Gal4 driver lines to produce F1 offspring for use as test subjects. Driver Gal4 lines and UAS-opsin responder lines were each crossed with an otherwise wild-typew1118line and the F1 progeny (e.g.UAS-KCR1-ET/+orelav-Gal4/+) were used as control subjects.

New Study Reveals Parallel Function of Dopamine Neurons in Acute Behavior

Adam Claridge-Chang — Wed, 19 Feb 2025 00:00:00 GMT

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Our lab has identified a previously unknown parallel function of dopamine neurons involved in olfactory memory inDrosophila. While these neurons were known to be crucial for memory formation, we demonstrate they simultaneously drive immediate attraction and aversion behaviors, independent of their memory-related function.Through optogenetic manipulation, we found that sensory neurons essential for olfactory memory were not required for dopamine-driven immediate responses. We identified two key neuronal populations: a broad network of dopaminergic neurons that influenced behavior through dopamine, glutamate, and octopamine signaling, and a more specific cluster that drove attractive responses. Notably, inhibiting this latter group caused flies to display active avoidance, highlighting its role in ongoing behavioral control.This work reveals how dopaminergic systems can coherently guide both immediate responses and memory formation, advancing our understanding of the neural circuits underlying learning and behavior.The study was published inPLOS Biology.

Welcome to Our New Website

Adam Claridge-Chang — Fri, 10 Jan 2025 00:00:00 GMT

A Fresh Start

We’ve migrated our lab website to a new platform powered by Quarto and nbdev.

This gives us several new capabilities:

Executable code: Blog posts can include Python code that runs
Better reproducibility: Jupyter notebooks are tested automatically
Modern design: Clean, responsive layout

What’s Coming

Over the next few weeks, we’ll be migrating content from our old site.

Stay tuned for updates on our research in behavioral neuroscience, optogenetics, and statistical methods.

Sample Code Post

Adam Claridge-Chang — Fri, 10 Jan 2025 00:00:00 GMT

—title: “Sample Code Post”date: 2025-01-10description: “Demonstrating executable code in blog posts.”categories: [tutorial, code]author: “Adam Claridge-Chang”aliases: - /blog/posts/2025-01-10-code-example/index.html—

Executable Code in Blog Posts

This post demonstrates that code actually runs:

Code

Kalium channelrhodopsins in the small animal models

Adam Claridge-Chang — Tue, 16 Jan 2024 00:00:00 GMT

Update:Now published inNature Communications.The Claridge-Chang lab evaluated the utility of the new kalium channelrhodopsins to suppress behavior and inhibit neural activity inDrosophila,C. elegans, and zebrafish. In direct comparisons with ACR1, a variety of KCRs with enhanced plasma-membrane trafficking displayed excellent potency, and with improved properties that include reduced toxicity and superior efficacy in putative high-chloride cells.This comparative analysis of behavioral inhibition between chloride- and potassium-selective silencing tools establishes KCRs as next-generation optogenetic inhibitors forin vivocircuit analysis in behaving animals.Read morehere.

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