Spatial patterns of persistent neural activity vary with the behavioral context of short-term memory

Subsets of extraocular motoneurons produce kinematically distinct saccades during hunting and exploration

Animals construct diverse behavioral repertoires by moving a limited number of body parts with varied kinematics and patterns of coordination. There is evidence that distinct movements can be generated by changes in activity dynamics within a common pool of motoneurons or by selectively engaging specific subsets of motoneurons in a task-dependent manner. However, in most cases, we have an incomplete understanding of the patterns of motoneuron activity that generate distinct actions and of how upstream premotor circuits select and assemble such motor programs. In this study, we used two closely related but kinematically distinct types of saccadic eye movement in larval zebrafish as a model to examine circuit control of movement diversity. In contrast to the prevailing view of a final common pathway, we found that in the oculomotor nucleus, distinct subsets of motoneurons were engaged for each saccade type. This type-specific recruitment was topographically organized and aligned with ultrastructural differences in motoneuron morphology and afferent synaptic innervation. Medially located motoneurons were active for both saccade types, and circuit tracing revealed a type-agnostic premotor pathway that appears to control their recruitment. By contrast, a laterally located subset of motoneurons was specifically active for hunting-associated saccades and received premotor input from pretectal hunting command neurons. Our data support a model in which generalist and action-specific premotor pathways engage distinct subsets of motoneurons to elicit varied movements of the same body part that subserve distinct behavioral functions.

Predicting modular functions and neural coding of behavior from a synaptic wiring diagram

A long-standing goal in neuroscience is to understand how a circuit's form influences its function. Here, we reconstruct and analyze a synaptic wiring diagram of the larval zebrafish brainstem to predict key functional properties and validate them through comparison with physiological data. We identify modules of strongly connected neurons that turn out to be specialized for different behavioral functions, the control of eye and body movements. The eye movement module is further organized into two three-block cycles that support the positive feedback long hypothesized to underlie low-dimensional attractor dynamics in oculomotor control. We construct a neural network model based directly on the reconstructed wiring diagram that makes predictions for the cellular-resolution coding of eye position and neural dynamics. These predictions are verified statistically with calcium imaging-based neural activity recordings. This work demonstrates how connectome-based brain modeling can reveal previously unknown anatomical structure in a neural circuit and provide insights linking network form to function.

Zebrafish Optokinetic Reflex: Minimal Reporting Guidelines and Recommendations

Optokinetic reflex (OKR) assays in zebrafish models are a valuable tool for studying a diverse range of ophthalmological and neurological conditions. Despite its increasing popularity in recent years, there are no clear reporting guidelines for the assay. Following reporting guidelines in research enhances reproducibility, reduces bias, and mitigates underreporting and poor methodologies in published works. To better understand optimal reporting standards for an OKR assay in zebrafish, we performed a systematic literature review exploring the animal, environmental, and technical factors that should be considered. Using search criteria from three online databases, a total of 109 research papers were selected for review. Multiple crucial factors were identified, including larval characteristics, sample size, fixing method, OKR set-up, distance of stimulus, detailed stimulus parameters, eye recording, and eye movement analysis. The outcome of the literature analysis highlighted the insufficient information provided in past research papers and the lack of a systematic way to present the parameters related to each of the experimental factors. To circumvent any future errors and champion robust transparent research, we have created the zebrafish optokinetic (ZOK) reflex minimal reporting guideline.

Dimensionality reduction reveals separate translation and rotation populations in the zebrafish hindbrain

In many brain areas, neuronal activity is associated with a variety of behavioral and environmental variables. In particular, neuronal responses in the zebrafish hindbrain relate to oculomotor and swimming variables as well as sensory information. However, the precise functional organization of the neurons has been difficult to unravel because neuronal responses are heterogeneous. Here, we used dimensionality reduction methods on neuronal population data to reveal the role of the hindbrain in visually driven oculomotor behavior and swimming. We imaged neuronal activity in zebrafish expressing GCaMP6s in the nucleus of almost all neurons while monitoring the behavioral response to gratings that rotated with different speeds. We then used reduced-rank regression, a method that condenses the sensory and motor variables into a smaller number of "features," to predict the fluorescence traces of all ROIs (regions of interest). Despite the potential complexity of the visuo-motor transformation, our analysis revealed that a large fraction of the population activity can be explained by only two features. Based on the contribution of these features to each ROI's activity, ROIs formed three clusters. One cluster was related to vergent movements and swimming, whereas the other two clusters related to leftward and rightward rotation. Voxels corresponding to these clusters were segregated anatomically, with leftward and rightward rotation clusters located selectively to the left and right hemispheres, respectively. Just as described in many cortical areas, our analysis revealed that single-neuron complexity co-exists with a simpler population-level description, thereby providing insights into the organization of visuo-motor transformations in the hindbrain.

Feedforward amplification in recurrent networks underlies paradoxical neural coding

The activity of single neurons encodes behavioral variables, such as sensory stimuli (Hubel & Wiesel 1959) and behavioral choice (Britten et al. 1992; Guo et al. 2014), but their influence on behavior is often mysterious. We estimated the influence of a unit of neural activity on behavioral choice from recordings in anterior lateral motor cortex (ALM) in mice performing a memory-guided movement task (H. K. Inagaki et al. 2018). Choice selectivity grew as it flowed through a sequence of directions in activity space. Early directions carried little selectivity but were predicted to have a large behavioral influence, while late directions carried large selectivity and little behavioral influence. Consequently, estimated behavioral influence was only weakly correlated with choice selectivity; a large proportion of neurons selective for one choice were predicted to influence choice in the opposite direction. These results were consistent with models in which recurrent circuits produce feedforward amplification (Goldman 2009; Ganguli et al. 2008; Murphy & Miller 2009) so that small amplitude signals along early directions are amplified to produce low-dimensional choice selectivity along the late directions, and behavior. Targeted photostimulation experiments (Daie et al. 2021b) revealed that activity along the early directions triggered sequential activity along the later directions and caused predictable behavioral biases. These results demonstrate the existence of an amplifying feedforward dynamical motif in the motor cortex, explain paradoxical responses to perturbation experiments (Chettih & Harvey 2019; Daie et al. 2021b; Russell et al. 2019), and reveal behavioral relevance of small amplitude neural dynamics.

Dimensionality reduction of calcium-imaged neuronal population activity

Calcium imaging has been widely adopted for its ability to record from large neuronal populations. To summarize the time course of neural activity, dimensionality reduction methods, which have been applied extensively to population spiking activity, may be particularly useful. However, it is unclear if the dimensionality reduction methods applied to spiking activity are appropriate for calcium imaging. We thus carried out a systematic study of design choices based on standard dimensionality reduction methods. We also developed a method to perform deconvolution and dimensionality reduction simultaneously (Calcium Imaging Linear Dynamical System, CILDS). CILDS most accurately recovered the single-trial, low-dimensional time courses from simulated calcium imaging data. CILDS also outperformed the other methods on calcium imaging recordings from larval zebrafish and mice. More broadly, this study represents a foundation for summarizing calcium imaging recordings of large neuronal populations using dimensionality reduction in diverse experimental settings.

Motor cortical influence relies on task-specific activity covariation

During limb movement, spinal circuits facilitate the alternating activation of antagonistic flexor and extensor muscles. Yet antagonist cocontraction is often required to stabilize joints, like when loads are handled. Previous results suggest that these different muscle activation patterns are mediated by separate flexion- and extension-related motor cortical output populations, while others suggest recruitment of task-specific populations. To distinguish between hypotheses, we developed a paradigm in which mice toggle between forelimb tasks requiring antagonist alternation or cocontraction and measured activity in motor cortical layer 5b. Our results conform to neither hypothesis: consistent flexion- and extension-related activity is not observed across tasks, and no task-specific populations are observed. Instead, activity covariation among motor cortical neurons dramatically changes between tasks, thereby altering the relation between neural and muscle activity. This is also observed specifically for corticospinal neurons. Collectively, our findings indicate that motor cortex drives different muscle activation patterns via task-specific activity covariation.

Oculomotor plant and neural dynamics suggest gaze control requires integration on distributed timescales

A fundamental principle of biological motor control is that the neural commands driving movement must conform to the response properties of the motor plants they control. In the oculomotor system, characterizations of oculomotor plant dynamics traditionally supported models in which the plant responds to neural drive to extraocular muscles on exclusively short, subsecond timescales. These models predict that the stabilization of gaze during fixations between saccades requires neural drive that approximates eye position on longer timescales and is generated through the temporal integration of brief eye velocity-encoding signals that cause saccades. However, recent measurements of oculomotor plant behaviour have revealed responses on longer timescales. Furthermore, measurements of firing patterns in the oculomotor integrator have revealed a more complex encoding of eye movement dynamics. Yet, the link between these observations has remained unclear. Here we use measurements from the larval zebrafish to link dynamics in the oculomotor plant to dynamics in the neural integrator. The oculomotor plant in both anaesthetized and awake larval zebrafish was characterized by a broad distribution of response timescales, including those much longer than 1 s. Analysis of the firing patterns of oculomotor integrator neurons, which exhibited a broadly distributed range of decay time constants, demonstrates the sufficiency of this activity for stabilizing gaze given an oculomotor plant with distributed response timescales. This work suggests that leaky integration on multiple, distributed timescales by the oculomotor integrator reflects an inverse model for generating oculomotor commands, and that multi-timescale dynamics may be a general feature of motor circuitry. KEY POINTS: Recent observations of oculomotor plant response properties and neural activity across the oculomotor system have called into question classical formulations of both the oculomotor plant and the oculomotor integrator. Here we use measurements from new and published experiments in the larval zebrafish together with modelling to reconcile recent oculomotor plant observations with oculomotor integrator function. We developed computational techniques to characterize oculomotor plant responses over several seconds in awake animals, demonstrating that long timescale responses seen in anaesthetized animals extend to the awake state. Analysis of firing patterns of oculomotor integrator neurons demonstrates the sufficiency of this activity for stabilizing gaze given an oculomotor plant with multiple, distributed response timescales. Our results support a formulation of gaze stabilization by the oculomotor system in which commands for stabilizing gaze are generated through integration on multiple, distributed timescales.

Ramp-to-threshold dynamics in a hindbrain population controls the timing of spontaneous saccades

Organisms have the capacity to make decisions based solely on internal drives. However, it is unclear how neural circuits form decisions in the absence of sensory stimuli. Here we provide a comprehensive map of the activity patterns underlying the generation of saccades made in the absence of visual stimuli. We perform calcium imaging in the larval zebrafish to discover a range of responses surrounding spontaneous saccades, from cells that display tonic discharge only during fixations to neurons whose activity rises in advance of saccades by multiple seconds. When we lesion cells in these populations we find that ablation of neurons with pre-saccadic rise delays saccade initiation. We analyze spontaneous saccade initiation using a ramp-to-threshold model and are able to predict the times of upcoming saccades using pre-saccadic activity. These findings suggest that ramping of neuronal activity to a bound is a critical component of self-initiated saccadic movements.

Approaches to inferring multi-regional interactions from simultaneous population recordings: Inferring multi-regional interactions from simultaneous population recordings

Most past studies of neural representations and dynamics have focused on recordings from single brain areas. However, growing evidence of brain-wide, parallel representations of cognitive variables suggests that analyzing neural representations and dynamics in individual brain areas can benefit from understanding the context of multi-regional interactions that support them. Moreover, perturbation experiments revealed that the manner in which these parallel representations interact with each other can differ dramatically across different pairs of brain areas. Recent advances in recording technology offer a potentially powerful substrate to study how multi-regional interactions coordinate neural representations in individual brain areas and dictate behavior on a single-trial basis through simultaneous recordings of multiple brain areas. We review pragmatic approaches to studying multi-regional interactions and illustrate them in the concrete context of a rodent delayed response task paradigm.

Network structure of cascading neural systems predicts stimulus propagation and recovery

OBJECTIVE

Many neural systems display spontaneous, spatiotemporal patterns of neural activity that are crucial for information processing. While these cascading patterns presumably arise from the underlying network of synaptic connections between neurons, the precise contribution of the network's local and global connectivity to these patterns and information processing remains largely unknown.

APPROACH

Here, we demonstrate how network structure supports information processing through network dynamics in empirical and simulated spiking neurons using mathematical tools from linear systems theory, network control theory, and information theory.

MAIN RESULTS

In particular, we show that activity, and the information that it contains, travels through cycles in real and simulated networks.

SIGNIFICANCE

Broadly, our results demonstrate how cascading neural networks could contribute to cognitive faculties that require lasting activation of neuronal patterns, such as working memory or attention.

Persistent Firing and Adaptation in Optic-Flow-Sensitive Descending Neurons

A general principle of sensory systems is that they adapt to prolonged stimulation by reducing their response over time. Indeed, in many visual systems, including higher-order motion sensitive neurons in the fly optic lobes and the mammalian visual cortex, a reduction in neural activity following prolonged stimulation occurs. In contrast to this phenomenon, the response of the motor system controlling flight maneuvers persists following the offset of visual motion. It has been suggested that this gap is caused by a lingering calcium signal in the output synapses of fly optic lobe neurons. However, whether this directly affects the responses of the post-synaptic descending neurons, leading to the observed behavioral output, is not known. We use extracellular electrophysiology to record from optic-flow-sensitive descending neurons in response to prolonged wide-field stimulation. We find that, as opposed to most sensory and visual neurons, and in particular to the motion vision sensitive neurons in the brains of both flies and mammals, the descending neurons show little adaption during stimulus motion. In addition, we find that the optic-flow-sensitive descending neurons display persistent firing, or an after-effect, following the cessation of visual stimulation, consistent with the lingering calcium signal hypothesis. However, if the difference in after-effect is compensated for, subsequent presentation of stimuli in a test-adapt-test paradigm reveals adaptation to visual motion. Our results thus show a combination of adaptation and persistent firing in the neurons that project to the thoracic ganglia and thereby control behavioral output.

Anatomy and Connectivity of the Torus Longitudinalis of the Adult Zebrafish

This study describes the cytoarchitecture of the torus longitudinalis (TL) in adult zebrafish by using light and electron microscopy, as well as its main connections as revealed by DiI tract tracing. In addition, by using high resolution confocal imaging followed by digital tracing, we describe the morphology of tectal pyramidal cells (type I cells) that are GFP positive in the transgenic line Tg(1.4dlx5a-dlx6a:GFP)^ot1. The TL consists of numerous small and medium-sized neurons located in a longitudinal eminence attached to the medial optic tectum. A small proportion of these neurons are GABAergic. The neuropil shows three types of synaptic terminals and numerous dendrites. Tracing experiments revealed that the main efference of the TL is formed of parallel-like fibers that course within the marginal layer of the optic tectum. A toral projection to the thalamic nucleus rostrolateralis is also observed. Afferents to the TL come from visual and cerebellum-related nuclei in the pretectum, namely the central, intercalated and the paracommissural pretectal nuclei, as well as from the subvalvular nucleus in the isthmus. Additional afferents to the TL may come from the cerebellum but their origins could not be confirmed. The tectal afferent projection to the TL originates from cells similar to the type X cells described in other cyprinids. Tectal pyramidal neurons show round or piriform cell bodies, with spiny apical dendritic trees in the marginal layer. This anatomical study provides a basis for future functional and developmental studies focused on this cerebellum-like circuit in zebrafish.

Functional architecture underlying binocular coordination of eye position and velocity in the larval zebrafish hindbrain

BACKGROUND

The oculomotor integrator (OI) in the vertebrate hindbrain transforms eye velocity input into persistent position coding output, which plays a crucial role in retinal image stability. For a mechanistic understanding of the integrator function and eye position control, knowledge about the tuning of the OI and other oculomotor nuclei is needed. Zebrafish are increasingly used to study integrator function and sensorimotor circuits, yet the precise neuronal tuning to motor variables remains uncharacterized.

RESULTS

Here, we recorded cellular calcium signals while evoking monocular and binocular optokinetic eye movements at different slow-phase eye velocities. Our analysis reveals the anatomical distributions of motoneurons and internuclear neurons in the nucleus abducens as well as those of oculomotor neurons in caudally adjacent hindbrain volumes. Each neuron is tuned to eye position and/or velocity to variable extents and is only activated after surpassing particular eye position and velocity thresholds. While the abducens (rhombomeres 5/6) mainly codes for eye position, in rhombomeres 7/8, a velocity-to-position coding gradient exists along the rostro-caudal axis, which likely corresponds to the oculomotor structures storing velocity and position, and is in agreement with a feedforward mechanism of persistent activity generation. Position encoding neurons are recruited at eye position thresholds distributed across the behaviourally relevant dynamic range, while velocity-encoding neurons have more centred firing thresholds for velocity. In the abducens, neurons coding exclusively for one eye intermingle with neurons coding for both eyes. Many of these binocular neurons are preferentially active during conjugate eye movements and less active during monocular eye movements. This differential recruitment during monocular versus conjugate tasks represents a functional diversification in the final common motor pathway.

CONCLUSIONS

We localized and functionally characterized the repertoire of oculomotor neurons in the zebrafish hindbrain. Our findings provide evidence for a mixed but task-specific binocular code and suggest that generation of persistent activity is organized along the rostro-caudal axis in the hindbrain.

Evidence accumulation during a sensorimotor decision task revealed by whole-brain imaging

Although animals can accumulate sensory evidence over considerable time scales to appropriately select behavior, little is known about how the vertebrate brain as a whole accomplishes this. In this study, we developed a new sensorimotor decision-making assay in larval zebrafish based on whole-field visual motion. Fish responded by swimming in the direction of perceived motion, such that the latency to initiate swimming and the fraction of correct turns were modulated by motion strength. Using whole-brain functional imaging, we identified neural activity relevant to different stages of the decision-making process, including the momentary evaluation and accumulation of sensory evidence. This activity is distributed in functional clusters across different brain regions and is characterized by a wide range of time constants. In addition, we found that the caudal interpeduncular nucleus (IPN), a circular structure located ventrally on the midline of the brain, reliably encodes the left and right turning rates.

Zebrafish dscaml1 Deficiency Impairs Retinal Patterning and Oculomotor Function

Down syndrome cell adhesion molecules (dscam and dscaml1) are essential regulators of neural circuit assembly, but their roles in vertebrate neural circuit function are still mostly unexplored. We investigated the functional consequences of dscaml1 deficiency in the larval zebrafish (sexually undifferentiated) oculomotor system, where behavior, circuit function, and neuronal activity can be precisely quantified. Genetic perturbation of dscaml1 resulted in deficits in retinal patterning and light adaptation, consistent with its known roles in mammals. Oculomotor analyses revealed specific deficits related to the dscaml1 mutation, including severe fatigue during gaze stabilization, reduced saccade amplitude and velocity in the light, greater disconjugacy, and impaired fixation. Two-photon calcium imaging of abducens neurons in control and dscaml1 mutant animals confirmed deficits in saccade-command signals (indicative of an impairment in the saccadic premotor pathway), whereas abducens activation by the pretectum-vestibular pathway was not affected. Together, we show that loss of dscaml1 resulted in impairments in specific oculomotor circuits, providing a new animal model to investigate the development of oculomotor premotor pathways and their associated human ocular disorders.SIGNIFICANCE STATEMENT Dscaml1 is a neural developmental gene with unknown behavioral significance. Using the zebrafish model, this study shows that dscaml1 mutants have a host of oculomotor (eye movement) deficits. Notably, the oculomotor phenotypes in dscaml1 mutants are reminiscent of human ocular motor apraxia, a neurodevelopmental disorder characterized by reduced saccade amplitude and gaze stabilization deficits. Population-level recording of neuronal activity further revealed potential subcircuit-specific requirements for dscaml1 during oculomotor behavior. These findings underscore the importance of dscaml1 in the development of visuomotor function and characterize a new model to investigate potential circuit deficits underlying human oculomotor disorders.

The Zebrafish Visual System: From Circuits to Behavior

Visual stimuli can evoke complex behavioral responses, but the underlying streams of neural activity in mammalian brains are difficult to follow because of their size. Here, I review the visual system of zebrafish larvae, highlighting where recent experimental evidence has localized the functional steps of visuomotor transformations to specific brain areas. The retina of a larva encodes behaviorally relevant visual information in neural activity distributed across feature-selective ganglion cells such that signals representing distinct stimulus properties arrive in different areas or layers of the brain. Motor centers in the hindbrain encode motor variables that are precisely tuned to behavioral needs within a given stimulus setting. Owing to rapid technological progress, larval zebrafish provide unique opportunities for obtaining a comprehensive understanding of the intermediate processing steps occurring between visual and motor centers, revealing how visuomotor transformations are implemented in a vertebrate brain.

Bridging large-scale neuronal recordings and large-scale network models using dimensionality reduction

A long-standing goal in neuroscience has been to bring together neuronal recordings and neural network modeling to understand brain function. Neuronal recordings can inform the development of network models, and network models can in turn provide predictions for subsequent experiments. Traditionally, neuronal recordings and network models have been related using single-neuron and pairwise spike train statistics. We review here recent studies that have begun to relate neuronal recordings and network models based on the multi-dimensional structure of neuronal population activity, as identified using dimensionality reduction. This approach has been used to study working memory, decision making, motor control, and more. Dimensionality reduction has provided common ground for incisive comparisons and tight interplay between neuronal recordings and network models.

Neuronal, mathematical, and molecular bases of perceptual decision-making in C. elegans

Animals process sensory information from the environment to make behavioral decisions. Although environmental information may be ambiguous or gradually changing, animals can still choose one behavioral option among several through perceptual decision-making. Perceptual decision-making has been intensively studied in primates and rodents, and neural activity that accumulates sensory information has been shown to be crucial. However, it remains unclear how the accumulating neural activity is generated, and whether such activity is a conserved decision-making strategy across the animal kingdom. Here, we review the previous perceptual decision-making studies in vertebrates and invertebrates and our recent achievement in an invertebrate model animal, the nematode Caenorhabditis elegans. In the study, we analyzed temporal dynamics of neuronal activity during perceptual decision-making in navigational behavior of C. elegans. We identified neural activity that accumulates sensory information and elucidated the molecular mechanism for the accumulating activity, which may be relevant to decision-making across the animal kingdom.

A neural network model for the orbitofrontal cortex and task space acquisition during reinforcement learning

Reinforcement learning has been widely used in explaining animal behavior. In reinforcement learning, the agent learns the value of the states in the task, collectively constituting the task state space, and uses the knowledge to choose actions and acquire desired outcomes. It has been proposed that the orbitofrontal cortex (OFC) encodes the task state space during reinforcement learning. However, it is not well understood how the OFC acquires and stores task state information. Here, we propose a neural network model based on reservoir computing. Reservoir networks exhibit heterogeneous and dynamic activity patterns that are suitable to encode task states. The information can be extracted by a linear readout trained with reinforcement learning. We demonstrate how the network acquires and stores task structures. The network exhibits reinforcement learning behavior and its aspects resemble experimental findings of the OFC. Our study provides a theoretical explanation of how the OFC may contribute to reinforcement learning and a new approach to understanding the neural mechanism underlying reinforcement learning.

Population-scale organization of cerebellar granule neuron signaling during a visuomotor behavior

Granule cells at the input layer of the cerebellum comprise over half the neurons in the human brain and are thought to be critical for learning. However, little is known about granule neuron signaling at the population scale during behavior. We used calcium imaging in awake zebrafish during optokinetic behavior to record transgenically identified granule neurons throughout a cerebellar population. A significant fraction of the population was responsive at any given time. In contrast to core precerebellar populations, granule neuron responses were relatively heterogeneous, with variation in the degree of rectification and the balance of positive versus negative changes in activity. Functional correlations were strongest for nearby cells, with weak spatial gradients in the degree of rectification and the average sign of response. These data open a new window upon cerebellar function and suggest granule layer signals represent elementary building blocks under-represented in core sensorimotor pathways, thereby enabling the construction of novel patterns of activity for learning.

Sensorimotor computation underlying phototaxis in zebrafish

Animals continuously gather sensory cues to move towards favourable environments. Efficient goal-directed navigation requires sensory perception and motor commands to be intertwined in a feedback loop, yet the neural substrate underlying this sensorimotor task in the vertebrate brain remains elusive. Here, we combine virtual-reality behavioural assays, volumetric calcium imaging, optogenetic stimulation and circuit modelling to reveal the neural mechanisms through which a zebrafish performs phototaxis, i.e. actively orients towards a light source. Key to this process is a self-oscillating hindbrain population (HBO) that acts as a pacemaker for ocular saccades and controls the orientation of successive swim-bouts. It further integrates visual stimuli in a state-dependent manner, i.e. its response to visual inputs varies with the motor context, a mechanism that manifests itself in the phase-locked entrainment of the HBO by periodic stimuli. A rate model is developed that reproduces our observations and demonstrates how this sensorimotor processing eventually biases the animal trajectory towards bright regions.

Active locomotion requires closed-loop sensorimotor co ordination between perception and action. Here the authors show using behavioural, imaging and modelling approaches that gaze orientation during phototaxis behaviour in larval zebrafish is related to oscillatory dynamics of a neuronal population in the hindbrain.

Behaviorally Selective Engagement of Short-Latency Effector Pathways by Motor Cortex

Blocking motor cortical output with lesions or pharmacological inactivation has identified movements that require motor cortex. Yet, when and how motor cortex influences muscle activity during movement execution remains unresolved. We addressed this ambiguity using measurement and perturbation of motor cortical activity together with electromyography in mice during two forelimb movements that differ in their requirement for cortical involvement. Rapid optogenetic silencing and electrical stimulation indicated that short-latency pathways linking motor cortex with spinal motor neurons are selectively activated during one behavior. Analysis of motor cortical activity revealed a dramatic change between behaviors in the coordination of firing patterns across neurons that could account for this differential influence. Thus, our results suggest that changes in motor cortical output patterns enable a behaviorally selective engagement of short-latency effector pathways. The model of motor cortical influence implied by our findings helps reconcile previous observations on the function of motor cortex.

Electron Microscopic Reconstruction of Functionally Identified Cells in a Neural Integrator

Neural integrators are involved in a variety of sensorimotor and cognitive behaviors. The oculomotor system contains a simple example, a hindbrain neural circuit that takes velocity signals as inputs and temporally integrates them to control eye position. Here we investigated the structural underpinnings of temporal integration in the larval zebrafish by first identifying integrator neurons using two-photon calcium imaging and then reconstructing the same neurons through serial electron microscopic analysis. Integrator neurons were identified as those neurons with activities highly correlated with eye position during spontaneous eye movements. Three morphological classes of neurons were observed: ipsilaterally projecting neurons located medially, contralaterally projecting neurons located more laterally, and a population at the extreme lateral edge of the hindbrain for which we were not able to identify axons. Based on their somatic locations, we inferred that neurons with only ipsilaterally projecting axons are glutamatergic, whereas neurons with only contralaterally projecting axons are largely GABAergic. Dendritic and synaptic organization of the ipsilaterally projecting neurons suggests a broad sampling from inputs on the ipsilateral side. We also observed the first conclusive evidence of synapses between integrator neurons, which have long been hypothesized by recurrent network models of integration via positive feedback.

Stimulus-Driven Population Activity Patterns in Macaque Primary Visual Cortex

Dimensionality reduction has been applied in various brain areas to study the activity of populations of neurons. To interpret the outputs of dimensionality reduction, it is important to first understand its outputs for brain areas for which the relationship between the stimulus and neural response is well characterized. Here, we applied principal component analysis (PCA) to trial-averaged neural responses in macaque primary visual cortex (V1) to study two fundamental, population-level questions. First, we characterized how neural complexity relates to stimulus complexity, where complexity is measured using relative comparisons of dimensionality. Second, we assessed the extent to which responses to different stimuli occupy similar dimensions of the population activity space using a novel statistical method. For comparison, we performed the same dimensionality reduction analyses on the activity of a recently-proposed V1 receptive field model and a deep convolutional neural network. Our results show that the dimensionality of the population response changes systematically with alterations in the properties and complexity of the visual stimulus.

A central goal in systems neuroscience is to understand how large populations of neurons work together to enable us to sense, to reason, and to act. To go beyond single-neuron and pairwise analyses, recent studies have applied dimensionality reduction methods to neural population activity to reveal tantalizing evidence of neural mechanisms underlying a wide range of brain functions. To aid in interpreting the outputs of dimensionality reduction, it is important to vary the inputs to a brain area and ask whether the outputs of dimensionality reduction change in a sensible manner, which has not yet been shown. In this study, we recorded the activity of tens of neurons in the primary visual cortex (V1) of macaque monkeys while presenting different visual stimuli. We found that the dimensionality of the population activity grows with stimulus complexity, and that the population responses to different stimuli occupy similar dimensions of the population firing rate space, in accordance with the visual stimuli themselves. For comparison, we applied the same analysis methods to the activity of a recently-proposed V1 receptive field model and a deep convolutional neural network. Overall, we found dimensionality reduction to yield interpretable results, providing encouragement for the use of dimensionality reduction in other brain areas.

Spike Pattern Structure Influences Synaptic Efficacy Variability under STDP and Synaptic Homeostasis. II: Spike Shuffling Methods on LIF Networks

Synapses may undergo variable changes during plasticity because of the variability of spike patterns such as temporal stochasticity and spatial randomness. Here, we call the variability of synaptic weight changes during plasticity to be efficacy variability. In this paper, we investigate how four aspects of spike pattern statistics (i.e., synchronous firing, burstiness/regularity, heterogeneity of rates and heterogeneity of cross-correlations) influence the efficacy variability under pair-wise additive spike-timing dependent plasticity (STDP) and synaptic homeostasis (the mean strength of plastic synapses into a neuron is bounded), by implementing spike shuffling methods onto spike patterns self-organized by a network of excitatory and inhibitory leaky integrate-and-fire (LIF) neurons. With the increase of the decay time scale of the inhibitory synaptic currents, the LIF network undergoes a transition from asynchronous state to weak synchronous state and then to synchronous bursting state. We first shuffle these spike patterns using a variety of methods, each designed to evidently change a specific pattern statistics; and then investigate the change of efficacy variability of the synapses under STDP and synaptic homeostasis, when the neurons in the network fire according to the spike patterns before and after being treated by a shuffling method. In this way, we can understand how the change of pattern statistics may cause the change of efficacy variability. Our results are consistent with those of our previous study which implements spike-generating models on converging motifs. We also find that burstiness/regularity is important to determine the efficacy variability under asynchronous states, while heterogeneity of cross-correlations is the main factor to cause efficacy variability when the network moves into synchronous bursting states (the states observed in epilepsy).

Development of functional hindbrain oculomotor circuitry independent of both vascularization and neuronal activity in larval zebrafish

We investigated the contribution of blood vessel formation and neuronal excitability to the development of functional neural circuitry in larval zebrafish by analyzing oculomotor performance in response to visual and vestibular stimuli. To address the dependence of neuronal function on the presence of blood vessels, we compared wild type embryos to reck and cloche mutants that lacked intracerebral blood vessels. To test how neuronal excitability impacts neuronal development and intracerebral vascularization, we blocked neural activity using Tetraodotoxin (TTX) and Tricaine. In reck mutants, we found both slow phase horizontal tracking and fast phase resets with only a slightly reduced amplitude and bandwidth. Spontaneous saccades, eye position holding and vestibular gravitoinertial induced eye rotation were also present. All of these behaviors except for visual tracking were observed in cloche mutants that lacked any head vasculature. Thus, numerous oculomotor neuronal circuits spanning the forebrain, midbrain and hindbrain compartments, ending in motor innervations of the eye muscles, were correctly formed and generated appropriate oculomotor behaviors without blood vessels. However, our observations indicate that beginning at approximately six days, circulation was required for sustained behavioral performance. We further found that blocking neuronal excitability with either TTX or Tricaine up to 4-5 days post fertilization did not noticeably interfere with intracerebral blood vessel formation in wild type larvae. After removal of drug treatments, the oculomotor behaviors returned within hours. Thus, development of neuronal circuits that drive oculomotor performance does not require neuronal spiking or activity. Together these findings demonstrate that neither vascularization nor neuronal excitability are essential for the formation of numerous oculomotor nuclei with intricately designed connectivity and signal processing. We conclude that a genetic blueprint specifies early larval structural and physiological features, and this developmental strategy may be viewed as a unique adaptation required for early survival.

A structural and genotypic scaffold underlying temporal integration

The accumulation and storage of information over time, temporal integration, is key to numerous behaviors. Many oculomotor tasks depend on integration of eye-velocity signals to eye-position commands, a transformation achieved by a hindbrain cell group termed the velocity-to-position neural integrator (VPNI). Although the VPNI's coding properties have been well characterized, its mechanism of function remains poorly understood because few links exist between neuronal activity, structure, and genotypic identity. To fill this gap, we used calcium imaging and single-cell electroporation during oculomotor behaviors to map VPNI neural activity in zebrafish onto a hindbrain scaffold consisting of alternating excitatory and inhibitory parasagittal stripes. Three distinct classes of VPNI cells were identified. One glutamatergic class was medially located along a stripe associated with the alx transcription factor; these cells had ipsilateral projections terminating near abducens motoneurons and collateralized extensively within the ipsilateral VPNI in a manner consistent with integration through recurrent excitation. A second glutamatergic class was more laterally located along a stripe associated with transcription factor dbx1b; these glutamatergic cells had contralateral projections collateralizing near abducens motoneurons, consistent with a role in disconjugate eye movements. A third class, immunohistochemically suggested to be GABAergic, was located primarily in the dbx1b stripe and also had contralateral projections terminating near abducens motoneurons; these cells collateralized extensively in the dendritic field of contralateral VPNI neurons, consistent with a role in coordinating activity between functionally opposing populations. This mapping between VPNI activity, structure, and genotype may provide a blueprint for understanding the mechanisms governing temporal integration.

Neurons that Remember How We Got There

In this issue of Neuron, Daie et al. (2015) show that the eye velocity-to-position neural integrator not only encodes the position, but also how it was reached. Representing content and context in the same neuronal population may form a general coding principle.