bioRxiv Science⌕ Search

bioRxiv · 10.1101/676312

NeuroPAL: A Neuronal Polychromatic Atlas of Landmarks for Whole-Brain Imaging in C. elegans

Abstract

Comprehensively resolving single neurons and their cellular identities from whole-brain fluorescent images is a major challenge. We achieve this in C. elegans through the engineering and use of a multicolor transgene called NeuroPAL (a Neuronal Polychromatic Atlas of Landmarks). NeuroPAL worms share a stereotypical multicolor fluorescence map for the entire hermaphrodite nervous system that allows comprehensive determination of neuronal identities. Neurons labeled with NeuroPAL do not exhibit fluorescence in the green, cyan, or yellow emission channels, allowing the transgene to be used with numerous reporters of gene expression or neuronal dynamics. Here we showcase three studies that leverage NeuroPAL for nervous-system-wide neuronal identification. First, we determine the brainwide expression patterns of all metabotropic receptors for acetylcholine, GABA, and glutamate, completing a map of this communication network. Second, we uncover novel changes in cell fate caused by transcription factor mutations. Third, we record brainwide activity in response to attractive and repulsive chemosensory cues, characterizing multimodal coding and novel neuronal asymmetries for these stimuli. We present a software package that enables semi-automated determination of all neuronal identities based on color and positional information. The NeuroPAL framework and software provide a means to design landmark atlases for other tissues and organisms. In conclusion, we expect NeuroPAL to serve as an invaluable tool for gene expression analysis, neuronal fate studies, and for mapping whole-brain activity patterns.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Yemini, E., Lin, A., Nejatbakhsh, A., Varol, E., Sun, R., Mena, G. E., Samuel, A. D., Paninski, L., Venkatachalam, V., Hobert, O.. 2019-06-20. NeuroPAL: A Neuronal Polychromatic Atlas of Landmarks for Whole-Brain Imaging in C. elegans. https://doi.org/10.1101/676312

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Simple, static, spiking nonlinearities can account for seemingly complex interactions between visual, motor and cognitive variables in the visual cortex.

Neural activity in the visual cortex is driven by the stimulus and modulated by multiple task-related variables, including spatial attention, eye movements, and perceptual decisions. These multiple influences are each typically described as nonlinear interactions such as gain or normalization, raising the question of how these diverse signals can be combined through cellular or circuit mechanisms. Here we address this problem by examining neuronal responses in macaque visual areas V2 and V3 during a visual discrimination task that dissociates spatial attention from motor planning and microsaccadic eye movements. Using a statistical modeling framework, we show that attentional, microsaccade-related, and choice-related influences on neural activity are best explained by a simple additive stimulus-independent input modulation, which manifests as a gain via a spiking nonlinearity. In addition to explaining how interactions between variables might be accomplished mechanistically, this framework also resolves a controversy about the relationship between microsaccades and spatial attention. We find that neither microsaccade direction nor microsaccade-related neural activity accounts for attentional modulation, although these variables are often correlated, leading to apparent interactions. Thus, visual cortex can integrate sensory, motor-related, and cognitive signals through a parsimonious mechanism that preserves stable stimulus representations while supporting flexible, context-dependent modulation.

neuroscience↗

40 Hz visual stimulation increases gamma-band functional connectivity between visual, parietal and frontal regions

Visual stimulation at 40 Hz is being investigated as a non-invasive intervention for Alzheimer's disease. Its neural responses have been reported in regions beyond the visual cortex, and concurrent cognitive tasks have been shown to increase their spatial extent. However, it is unclear whether these responses reflect increased functional connectivity between regions or a common response to the stimulus, and whether a concurrent task changes this connectivity. We recorded EEG from 29 healthy young adults during Regular 40 Hz flicker and Irregular 30-50 Hz flicker, each with and without a target-counting task (2 x 2 within-participant design). Source-space connectivity between visual, parietal, and frontal regions was estimated with the debiased squared weighted phase-lag index (dWPLI). Regular stimulation increased 38-42 Hz connectivity for all three region pairs, with the largest increase between visual and parietal regions (increase in all 29 participants). The increase was specific to the stimulation frequency and was observed with two source reconstruction methods and in sensor space. The visual-parietal increase remained significant after correction for source leakage (spatial mixing between reconstructed sources) and after removal of the estimated stimulus-locked component, whereas the increases in visual-frontal and parietal-frontal connectivity did not. The concurrent task did not modulate the visual-parietal effect. For visual-frontal and parietal-frontal connectivity, the stimulation-by-ask interaction was not significant. These results show that 40 Hz visual stimulation increases gamma-band connectivity beyond the visual cortex, and much of this increase reflects a common stimulus-locked response, and connectivity beyond this response was observed mainly between visual and parietal regions.

neuroscience↗

Feedback Valence, Prediction Error, and the Limits of Computational Attribution in Symptom-Related EEG

Feedback-locked electroencephalography (EEG) responses are often interpreted using model-derived prediction errors (PEs), although signed PE can be strongly coupled to feedback valence in binary-outcome tasks. We revisited a published anxiety-related EEG association using two open probabilistic-learning datasets to examine measurement reliability, predictor separability, and participant-level recovery. In the primary dataset, greater trait anxiety was associated with a larger negative-minus-positive FCz theta response among 46 participants with elevated depressive symptoms after adjustment for depression severity. The association also differed between the sampled depression-symptom groups. The feedback contrast showed useful within-session reliability, but matched delta and P3-minus-N2 analyses did not establish theta specificity. Within participants, feedback valence and signed PE were highly correlated (r = -0.964). Exact-design simulations showed that population-level model discrimination could succeed despite poor recovery of individual neural slopes. Participant-specific learning-model refits recovered overall signed PE more consistently than the within-valence variation needed to distinguish it from feedback valence. An independent dataset reproduced the FCz feedback contrast in untreated and placebo cohorts but lacked trait-anxiety scores. Adding signed PE to valence yielded a small held-out predictive improvement under one reinforcement-learning specification, with limited support across sessions and no comparable support under the dual-rate model or in placebo. Together, these findings support a symptom-related feedback EEG association while constraining its theta-specific and participant-level computational interpretation.

neuroscience↗