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Manuel Zimmer

One of the prime goals pursued by current neuroscientists is to gain a comprehensive understanding of how networks of neurons operate as a single brain to produce sensations, thoughts, and behaviour. This is a challenging endeavour because of the sheer complexity of mammalian nervous systems. To address this problem, we study at our lab the nematode C. elegans which is equipped with a simple and anatomically well-defined nervous system of just 302 neurons. Specifically, we combine worm genetics, quantitative behavioural assays, novel functional imaging techniques, and theoretical modelling to elucidate the neural circuits that control locomotion and chemosensory behaviours.

The neural basis of behaviour

Brain-wide calcium imaging in C. elegans

Figure 1: WF-TeFo imaging of the head region of a worm with pan-neuronal NLS-GCaMP5K expression. (A) Maximum intensity projection of 14 z-planes. Dashed lines outline the locations of head ganglia as shown in (D). Scale bar represents 10 μm. Arrows indicate the positions of y-z and x-z cross-sections shown in (B) and (C), respectively. (D) Schematic diagram of the left anterior head ganglia for comparison with (A).

A better understanding of how neural circuits in the brain process information and generate behaviour requires detailed knowledge of both anatomical neuronal wiring, as well as the dynamic rules governing the activity of neurons and their connections. The complete connectome of the C. elegans nervous system was reported more than 25 years ago. However, this has not been sufficient to explain how behaviours arise. The major impediment is the dense interconnectedness of neurons, with the consequence that there are no obvious anatomically identifiable pathways from sensory input down to motor output.

These and other findings in different animals led to the current view among neuroscientists that many sensory functions and behavioural states of animals are represented in a flexible and distributed fashion across neuronal networks. The current challenge in systems neuroscience is to identify the nature of, and decipher the mechanisms responsible for, the computations and algorithms that are performed by these neural networks.

Figure 2: In vivo characterization of NLS-GCaMP5K. (A) Schematic diagram of NLS-GCaMP5K. (B-F) Calcium imaging of oxygen-sensing BAG neurons by epifluorescence microscopy. (B-C) NLS-GCaMP5K fluorescence in stimulated BAG neurons. (B) Baseline (21% oxygen) fluorescence levels. (C) Oxygen downshift evoked response in BAG. (D-E) Averaged calcium transients in BAG expressing cytoplasmic (D) or nuclear (E) G-GAMP5K, and quantification of mean peak responses (F). Scale bars represent 10 μm.

Research in C. elegans focuses largely on isolated neurons and small circuits. This is mainly because of technical limitations in electrophysiology and functional imaging: C. elegans neurons are small and densely packed into head and tail ganglia and are closely surrounded by neuropil, which makes them inaccessible to multi-electrode arrays and hard to track with image segmentation methods when pan-neuronally expressed genetically encoded calcium indicators are used.

To overcome these limitations, the Vaziri lab developed wide-field temporal focusing (WF-TeFo), a 2-photon excitation-based, high-resolution imaging technique which is capable of unbiased and fast volumetric imaging of neurons. In addition, we designed a novel genetically encoded calcium reporter which is localized to the cell nucleus (NLS-GCaMP5K). In combination, the approaches allowed unambiguous anatomical identification of neurons and their temporal calcium signals (Figure 1). We confirmed that NLS-GCaMP5K reliably reports neural activity by comparing nuclear with cytoplasmic calcium responses in oxygen-sensing neurons (Figure 2).

Figure 3: Activity of the C. elegans brain. (A) Activity of 99 neurons from the same worm as in Figure 1, imaged volumetrically at 5 Hz for 200 s. Each row shows a heat plot of the NLS-GCaMP5K fluorescence time series. (B) Matrix showing the correlation coefficient (R) calculated from all-time-series shown in (A). Color indicates the degree of correlation. The data in A-B are grouped by agglomerative hierarchical clustering. (C) Selected traces of neurons. Purple: pre-motor interneurons. Green: head motor neurons.

Using WF-TeFo microscopy, we were able to capture calcium signals from most of the neurons in the worm’s brain at a volume acquisition rate of 5 volumes per second. Figure 3 shows the result of a typical recording. We found that at least 50% of neurons in the brain are active under our experimental conditions. Correlation analysis revealed a cluster of up to 20 neurons engaged in highly correlated activity, which is also anti-correlated to other smaller clusters of neurons (Figure 3C).

In nematodes, cell positions and identities are stereotypic. This enables us to identify, on our images, a subset of neurons with prominent activity patterns. The large cluster of correlated neurons is represented by pre-motor interneuron classes which have previously been implicated in decision-making during C. elegans locomotion. When foraging, the animals explore the environment by occasionally changing the direction of locomotion. The initiation of these manoeuvres is reported to be associated with enhanced activity of pre-motor interneurons such as AVA and RIM. These activities are shown in Figure 3C. Smaller clusters of neurons that appear anti-correlated with pre-motor interneurons were identified as head motor neurons. These are believed to control the undulatory motion of the worm.

Our results reveal unexpected system-wide synchrony and antagonistic complexes in the pre-motor circuits of the C. elegans brain. Our data suggest that decision-making, i.e. the initiation of locomotion manoeuvres, can be represented by transitions between network attractors. We are currently testing this hypothesis by combining our novel imaging approach with genetics, behavioural analysis, and theoretical modelling.

Selected Publications

  • Hums, I., Riedl, J., Mende, F., Kato, S., Kaplan, HS., Latham, R., Sonntag, M., Traunmüller, L., Zimmer, M. (2016). Regulation of two motor patterns enables the gradual adjustment of locomotion strategy in Caenorhabditis elegans. Elife. 5
  • Kato, S., Kaplan, HS., Schrödel, T., Skora, S., Lindsay, TH., Yemini, E., Lockery, S., Zimmer, M. (2015). Global Brain Dynamics Embed the Motor Command Sequence of Caenorhabditis elegans. Cell. 163(3):656-69
  • Schrödel, T., Prevedel, R., Aumayr, K., Zimmer, M., Vaziri, A. (2013). Brain-wide 3D imaging of neuronal activity in Caenorhabditis elegans with sculpted light. Nat Methods. 10(10):1013-20
  • Zimmer, M., Gray, JM., Pokala, N., Chang, AJ., Karow, DS., Marletta, MA., Hudson, ML., Morton, DB., Chronis, N., Bargmann, CI. (2009). Neurons detect increases and decreases in oxygen levels using distinct guanylate cyclases. Neuron. 61(6):865-79 
  • Chronis, N., Zimmer, M., Bargmann, CI. (2007). Microfluidics for in vivo imaging of neuronal and behavioral activity in Caenorhabditis elegans. Nat Methods. 4(9):727-31

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