Germán Sumbre

Spontaneous Neuronal Network Dynamics Reveal Circuit’s Functional Adaptations for Behavior

Summary Spontaneous neuronal activity is spatiotemporally structured, influencing brain computations. Nevertheless, the neuronal interactions underlying these spontaneous activity patterns, and their biological relevance, remain elusive. Here, we addressed these questions using two-photon calcium imaging of intact zebrafish larvae to monitor the neuron-to-neuron spontaneous activity fine structure in the tectum, a region involved in visual spatial detection. Spontaneous activity was organized in topographically compact assemblies, grouping functionally similar neurons rather than merely neighboring ones, reflecting the tectal retinotopic map despite being independent of retinal drive. Assemblies represent all-or-none-like sub-networks shaped by competitive dynamics, mechanisms advantageous for visual detection in noisy natural environments. Notably, assemblies were tuned to the same angular sizes and spatial positions as prey-detection performance in behavioral assays, and their spontaneous activation predicted directional tail movements. Therefore, structured spontaneous activity represents “preferred” network states, tuned to behaviorally relevant features, emerging from the circuit’s intrinsic non-linear dynamics, adapted for its functional role.

The first mecp2-null zebrafish model shows altered motor behaviors

Rett syndrome (RTT) is an X-linked neurodevelopmental disorder and one of the most common causes of mental retardation in affected girls. Other symptoms include a rapid regression of motor and cognitive skills after an apparently early normal development. Sporadic mutations in the transcription factor MECP2 has been shown to be present in more than 90% of the patients and several models of MeCP2-deficient mice have been created to understand the role of this gene. These models have pointed toward alterations in the maintenance of the central nervous system rather than its development, in line with the late onset of the disease in humans. However, the exact functions of MeCP2 remain difficult to delineate and the animal models have yielded contradictory results. Here, we present the first mecp2-null allele mutation zebrafish model. Surprisingly and in contrast to MeCP2-null mouse models, mecp2-null zebrafish are viable and fertile. They present nonetheless clear behavioral alterations during their early development, including spontaneous and sensory-evoked motor anomalies, as well as defective thigmotaxis.

A microfluidic device to study neuronal and motor responses to acute chemical stimuli in zebrafish

Zebrafish larva is a unique model for whole-brain functional imaging and to study sensory-motor integration in the vertebrate brain. To take full advantage of this system, one needs to design sensory environments that can mimic the complex spatiotemporal stimulus patterns experienced by the animal in natural conditions. We report on a novel open-ended microfluidic device that delivers pulses of chemical stimuli to agarose-restrained larvae with near-millisecond switching rate and unprecedented spatial and concentration accuracy and reproducibility. In combination with two-photon calcium imaging and recordings of tail movements, we found that stimuli of opposite hedonic values induced different circuit activity patterns. Moreover, by precisely controlling the duration of the stimulus (50–500 ms), we found that the probability of generating a gustatory-induced behavior is encoded by the number of neurons activated. This device may open new ways to dissect the neural-circuit principles underlying chemosensory perception.

The Emergence of the Spatial Structure of Tectal Spontaneous Activity Is Independent of Visual Inputs

Summary The brain is spontaneously active, even in the absence of sensory stimulation. The functionally mature zebrafish optic tectum shows spontaneous activity patterns reflecting a functional connectivity adapted for the circuit’s functional role and predictive of behavior. However, neither the emergence of these patterns during development nor the role of retinal inputs in their maturation has been characterized. Using two-photon calcium imaging, we analyzed spontaneous activity in intact and enucleated zebrafish larvae throughout tectum development. At the onset of retinotectal connections, intact larvae showed major changes in the spatiotemporal structure of spontaneous activity. Although the absence of retinal inputs had a significant impact on the development of the temporal structure, the tectum was still capable of developing a spatial structure associated with the circuit’s functional roles and predictive of behavior. We conclude that neither visual experience nor intrinsic retinal activity is essential for the emergence of a spatially structured functional circuit.

Functional Interactions between Newborn and Mature Neurons Leading to Integration into Established Neuronal Circuits

Summary From development up to adulthood, the vertebrate brain is continuously supplied with newborn neurons that integrate into established mature circuits. However, how this process is coordinated during development remains unclear. Using two-photon imaging, GCaMP5 transgenic zebrafish larvae, and sparse electroporation in the larva’s optic tectum, we monitored spontaneous and induced activity of large neuronal populations containing newborn and functionally mature neurons. We observed that the maturation of newborn neurons is a 4-day process. Initially, newborn neurons showed undeveloped dendritic arbors, no neurotransmitter identity, and were unresponsive to visual stimulation, although they displayed spontaneous calcium transients. Later on, newborn-labeled neurons began to respond to visual stimuli but in a very variable manner. At the end of the maturation period, newborn-labeled neurons exhibited visual tuning curves (spatial receptive fields and direction selectivity) and spontaneous correlated activity with neighboring functionally mature neurons. At this developmental stage, newborn-labeled neurons presented complex dendritic arbors and neurotransmitter identity (excitatory or inhibitory). Removal of retinal inputs significantly perturbed the integration of newborn neurons into the functionally mature tectal network. Our results provide a comprehensive description of the maturation of newborn neurons during development and shed light on potential mechanisms underlying their integration into a functionally mature neuronal circuit.

Sustained Rhythmic Brain Activity Underlies Visual Motion Perception in Zebrafish

Summary Following moving visual stimuli (conditioning stimuli, CS), many organisms perceive, in the absence of physical stimuli, illusory motion in the opposite direction. This phenomenon is known as the motion aftereffect (MAE). Here, we use MAE as a tool to study the neuronal basis of visual motion perception in zebrafish larvae. Using zebrafish eye movements as an indicator of visual motion perception, we find that larvae perceive MAE. Blocking eye movements using optogenetics during CS presentation did not affect MAE, but tectal ablation significantly weakened it. Using two-photon calcium imaging of behaving GCaMP3 larvae, we find post-stimulation sustained rhythmic activity among direction-selective tectal neurons associated with the perception of MAE. In addition, tectal neurons tuned to the CS direction habituated, but neurons in the retina did not. Finally, a model based on competition between direction-selective neurons reproduced MAE, suggesting a neuronal circuit capable of generating perception of visual motion.

A computational toolbox and step-by-step tutorial for the analysis of neuronal population dynamics in calcium imaging data

The development of new imaging and optogenetics techniques to study the dynamics of large neuronal circuits is generating datasets of unprecedented volume and complexity, demanding the development of appropriate analysis tools. We present a tutorial for the use of a comprehensive computational toolbox for the analysis of neuronal population activity imaging. It consists of tools for image pre-processing and segmentation, estimation of significant single-neuron single-trial signals, mapping event-related neuronal responses, detection of activity-correlated neuronal clusters, exploration of population dynamics, and analysis of clusters’ features against surrogate control datasets. They are integrated in a modular and versatile processing pipeline, adaptable to different needs. The clustering module is capable of detecting flexible, dynamically activated neuronal assemblies, consistent with the distributed population coding of the brain. We demonstrate the suitability of the toolbox for a variety of calcium imaging datasets, and provide a case study to explain its implementation.

Automatic classification of behavior in zebrafish larvae

Zebrafish larvae navigate the environment by discrete episode of propulsion called bouts. We introduce a novel method for automatically classifying tail bouts. A supervised soft-clustering algorithm to categorize tail bouts into 5 categories of movements: Scoot, Asymmetrical Scoot, Routine Turn, C Bend and Burst. Tail bouts were correctly classified with 82% chance while errors in the classification occurred mostly between similar categories. Although previous studies have performed categorization of behavior in free-swimming conditions, our method does not rely on the analysis of the larva’s trajectory and is thus compatible with both free-swimming and functional imaging in head-fixed condition.

A 2D virtual reality system for visual goal-driven navigation in zebrafish larvae.

Animals continuously rely on sensory feedback to adjust motor commands. In order to study the role of visual feedback in goal-driven navigation, we developed a 2D visual virtual reality system for zebrafish larvae. The visual feedback can be set to be similar to what the animal experiences in natural conditions. Alternatively, modification of the visual feedback can be used to study how the brain adapts to perturbations. For this purpose, we first generated a library of free-swimming behaviors from which we learned the relationship between the trajectory of the larva and the shape of its tail. Then, we used this technique to infer the intended displacements of head-fixed larvae, and updated the visual environment accordingly. Under these conditions, larvae were capable of aligning and swimming in the direction of a whole-field moving stimulus and produced the fine changes in orientation and position required to capture virtual prey. We demonstrate the sensitivity of larvae to visual feedback by updating the visual world in real-time or only at the end of the discrete swimming episodes. This visual feedback perturbation caused impaired performance of prey-capture behavior, suggesting that larvae rely on continuous visual feedback during swimming.

Fast functional imaging of multiple brain regions in intact zebrafish larvae using Selective Plane Illumination Microscopy

The optical transparency and the small dimensions of zebrafish at the larval stage make it a vertebrate model of choice for brain-wide in-vivo functional imaging. However, current point-scanning imaging techniques, such as two-photon or confocal microscopy, impose a strong limit on acquisition speed which in turn sets the number of neurons that can be simultaneously recorded [1]. At 5 Hz, this number is of the order of one thousand, i.e. approximately 1-2% of the brain. We demonstrate that this limitation can be greatly overcome by using Selective-Plane Illumination Microscopy (SPIM) [2-4]. Zebrafish larvae expressing the genetically encoded calcium indicator GCaMP3 were illuminated with a scanned laser sheet and imaged with a camera whose optical axis was oriented orthogonally to the illumination plane. This optical sectioning approach was shown to permit functional imaging of most of the brain volume of 5-9 day old larvae with single-cell resolution. The spontaneous activity of up to 5000 neurons was recorded at 20 Hz for 20-60 min. By rapidly scanning the specimen in the axial direction, the activity of 25000 individual neurons from 5 different z-planes (approximately 30% of the entire brain) could be simultaneously monitored at 4 Hz. Compared to point-scanning techniques, this imaging strategy thus yields a ~20-fold increase in data throughput (number of recorded neurons times acquisition rate) without compromising the signal-to-noise ratio. The extended field of view offered by the SPIM method allowed us to directly identify large scale ensembles of neurons, spanning several brain regions (see Figure ​Figure1),1), that displayed correlated activity and were thus likely to participate in common neural processes. Figure 1 Image of the brain of a 6 day-old GCaMP3 zebrafish obtained by SPIM. Colored neurons indicate a set of neurons showing correlated activity.