Seizures initiate in zones of relative hyperexcitation in a zebrafish epilepsy model.

Seizures are thought to arise from an imbalance of excitatory and inhibitory neuronal activity. While most classical studies suggest excessive excitatory neural activity plays a generative role, some recent findings challenge this view and instead argue that excessive activity in inhibitory neurons initiates seizures. We investigated this question of imbalance in a zebrafish seizure model with two-photon imaging of excitatory and inhibitory neuronal activity throughout the brain using a nuclear-localized calcium sensor. We found that seizures consistently initiated in circumscribed zones of the midbrain before propagating to other brain regions. Excitatory neurons were both more prevalent and more likely to be recruited than inhibitory neurons in initiation as compared with propagation zones. These findings support a mechanistic picture whereby seizures initiate in a region of hyperexcitation, then propagate more broadly once inhibitory restraint in the surround is overcome.

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.

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 STATEMENTDscaml1 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.

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.

A Lyapunov theory demonstrating a fundamental limit on the speed of systems consolidation.

The nervous system reorganizes memories from an early site to a late site, a commonly observed feature of learning and memory systems known as systems consolidation. Previous work has suggested learning rules by which consolidation may occur. Here, we provide conditions under which such rules are guaranteed to lead to stable convergence of learning and consolidation. We use the theory of Lyapunov functions, which enforces stability by requiring learning rules to decrease an energy-like (Lyapunov) function. We present the theory in the context of a simple circuit architecture motivated by classic models of learning in systems consolidation mediated by the cerebellum. Stability is only guaranteed if the learning rate in the late stage is not faster than the learning rate in the early stage. Further, the slower the learning rate at the late stage, the larger the perturbation the system can tolerate with a guarantee of stability. We provide intuition for this result by mapping the consolidation model to a damped driven oscillator system, and showing that the ratio of early-to late-stage learning rates in the consolidation model can be directly identified with the (square of the) oscillator's damping ratio. This work suggests the power of the Lyapunov approach to provide constraints on nervous system function.

Cyclic structure with cellular precision in a vertebrate sensorimotor neural circuit.

Neuronal wiring diagrams reconstructed by electron microscopy1,2,3,4,5 pose new questions about the organization of nervous systems following the time-honored tradition of cross-species comparisons.6,7 The C. elegans connectome has been conceptualized as a sensorimotor circuit that is approximately feedforward,8,9,10,11 starting from sensory neurons proceeding to interneurons and ending with motor neurons. Overrepresentation of a 3-cell motif often known as the "feedforward loop" has provided further evidence for feedforwardness.10,12 Here, we contrast with another sensorimotor wiring diagram that was recently reconstructed from a larval zebrafish brainstem.13 We show that the 3-cycle, another 3-cell motif, is highly overrepresented in the oculomotor module of this wiring diagram. This is a first for any neuronal wiring diagram reconstructed by electron microscopy, whether invertebrate12,14 or mammalian.15,16,17 The 3-cycle of cells is "aligned" with a 3-cycle of neuronal groups in a stochastic block model (SBM)18 of the oculomotor module. However, the cellular cycles exhibit more specificity than can be explained by the group cycles-recurrence to the same neuron is surprisingly common. Cyclic structure could be relevant for theories of oculomotor function that depend on recurrent connectivity. The cyclic structure coexists with the classic vestibulo-ocular reflex arc for horizontal eye movements,19 and could be relevant for recurrent network models of temporal integration by the oculomotor system.20,21.

Regression-based identification of behavior-encoding neurons during large-scale optical imaging of neural activity at cellular resolution.

The advent of methods for optical imaging of large-scale neural activity at cellular resolution in behaving animals presents the problem of identifying behavior-encoding cells within the resulting image time series. Rapid and precise identification of cells with particular neural encoding would facilitate targeted activity measurements and perturbations useful in characterizing the operating principles of neural circuits. Here we report a regression-based approach to semiautomatically identify neurons that is based on the correlation of fluorescence time series with quantitative measurements of behavior. The approach is illustrated with a novel preparation allowing synchronous eye tracking and two-photon laser scanning fluorescence imaging of calcium changes in populations of hindbrain neurons during spontaneous eye movement in the larval zebrafish. Putative velocity-to-position oculomotor integrator neurons were identified that showed a broad spatial distribution and diversity of encoding. Optical identification of integrator neurons was confirmed with targeted loose-patch electrical recording and laser ablation. The general regression-based approach we demonstrate should be widely applicable to calcium imaging time series in behaving animals.

Functional dissection of circuitry in a neural integrator.

In neural integrators, transient inputs are accumulated into persistent firing rates that are a neural correlate of short-term memory. Integrators often contain two opposing cell populations that increase and decrease sustained firing as a stored parameter value rises. A leading hypothesis for the mechanism of persistence is positive feedback through mutual inhibition between these opposing populations. We tested predictions of this hypothesis in the goldfish oculomotor velocity-to-position integrator by measuring the eye position and firing rates of one population, while pharmacologically silencing the opposing one. In complementary experiments, we measured responses in a partially silenced single population. Contrary to predictions, induced drifts in neural firing were limited to half of the oculomotor range. We built network models with synaptic-input thresholds to demonstrate a new hypothesis suggested by these data: mutual inhibition between the populations does not provide positive feedback in support of integration, but rather coordinates persistent activity intrinsic to each population.

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.

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.

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.

Correlated discharge among cell pairs within the oculomotor horizontal velocity-to-position integrator.

In the oculomotor system, temporal integration of velocity commands into position signals may depend on synaptic feedback among neurons of a bilateral brainstem cell assembly known as the "neural integrator." Both ipsilateral excitatory and contralateral inhibitory projections between eye position-related integrator cells are hypothesized as a substrate for positive feedback supporting integration. Presence of feedback interactions should be evident in cross-correlation functions of neuron pairs. Here, unilateral and bilateral paired recordings were obtained during fixation behavior from neurons in goldfish brainstem area I, a key element of the integrator. During fixations, discharge of most unilateral pairs, composed of cells with eye position sensitivities of the same sign, was positively correlated with lag of 0-10 msec (n = 11 of 14 significant). Typically, a very narrow peak (mean half-width <4 msec) near zero lag was observed. Discharge of bilateral pairs, composed of cells with position sensitivities of the opposite sign, was either negatively correlated with lag of 0-10 msec (n = 5 of 13 significant) or not correlated. Troughs in negative correlations always had minima between 3 and 5 msec lag. These results are consistent with the feedback hypothesis of temporal integration, highlighting excitation unilaterally and inhibition bilaterally. Absence of visual input did not weaken correlations, but other sources of correlated input extrinsic to area I were not ruled out. Triplet recordings revealed that unilateral pairwise correlations were primarily independent. Correlation between unilateral pairs systematically decreased with increasing eye position, demonstrating that synchrony is not necessary for persistent activity at high firing rates.

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

A short-term memory can be evoked by different inputs and control separate targets in different behavioral contexts. To address the circuit mechanisms underlying context-dependent memory function, we determined through optical imaging how memory is encoded at the whole-network level in two behavioral settings. Persistent neural activity maintaining a memory of desired eye position was imaged throughout the oculomotor integrator after saccadic or optokinetic stimulation. While eye position was encoded by the amplitude of network activity, the spatial patterns of firing were context dependent: cells located caudally generally were most persistent following saccadic input, whereas cells located rostrally were most persistent following optokinetic input. To explain these data, we computationally identified four independent modes of network activity and found these were differentially accessed by saccadic and optokinetic inputs. These results show how a circuit can simultaneously encode memory value and behavioral context, respectively, in its amplitude and spatial pattern of persistent firing.

A modeling framework for deriving the structural and functional architecture of a short-term memory microcircuit.

Although many studies have identified neural correlates of memory, relatively little is known about the circuit properties connecting single-neuron physiology to behavior. Here we developed a modeling framework to bridge this gap and identify circuit interactions capable of maintaining short-term memory. Unlike typical studies that construct a phenomenological model and test whether it reproduces select aspects of neuronal data, we directly fit the synaptic connectivity of an oculomotor memory circuit to a broad range of anatomical, electrophysiological, and behavioral data. Simultaneous fits to all data, combined with sensitivity analyses, revealed complementary roles of synaptic and neuronal recruitment thresholds in providing the nonlinear interactions required to generate the observed circuit behavior. This work provides a methodology for identifying the cellular and synaptic mechanisms underlying short-term memory and demonstrates how the anatomical structure of a circuit may belie its functional organization.

Computational modeling reveals dendritic origins of GABA(A)-mediated excitation in CA1 pyramidal neurons.

GABA is the key inhibitory neurotransmitter in the adult central nervous system, but in some circumstances can lead to a paradoxical excitation that has been causally implicated in diverse pathologies from endocrine stress responses to diseases of excitability including neuropathic pain and temporal lobe epilepsy. We undertook a computational modeling approach to determine plausible ionic mechanisms of GABA(A)-dependent excitation in isolated post-synaptic CA1 hippocampal neurons because it may constitute a trigger for pathological synchronous epileptiform discharge. In particular, the interplay intracellular chloride accumulation via the GABA(A) receptor and extracellular potassium accumulation via the K/Cl co-transporter KCC2 in promoting GABA(A)-mediated excitation is complex. Experimentally it is difficult to determine the ionic mechanisms of depolarizing current since potassium transients are challenging to isolate pharmacologically and much GABA signaling occurs in small, difficult to measure, dendritic compartments. To address this problem and determine plausible ionic mechanisms of GABA(A)-mediated excitation, we built a detailed biophysically realistic model of the CA1 pyramidal neuron that includes processes critical for ion homeostasis. Our results suggest that in dendritic compartments, but not in the somatic compartments, chloride buildup is sufficient to cause dramatic depolarization of the GABA(A) reversal potential and dominating bicarbonate currents that provide a substantial current source to drive whole-cell depolarization. The model simulations predict that extracellular K(+) transients can augment GABA(A)-mediated excitation, but not cause it. Our model also suggests the potential for GABA(A)-mediated excitation to promote network synchrony depending on interneuron synapse location - excitatory positive-feedback can occur when interneurons synapse onto distal dendritic compartments, while interneurons projecting to the perisomatic region will cause inhibition.

Spatial gradients and multidimensional dynamics in a neural integrator circuit.

In a neural integrator, the variability and topographical organization of neuronal firing-rate persistence can provide information about the circuit's functional architecture. We used optical recording to measure the time constant of decay of persistent firing (persistence time) across a population of neurons comprising the larval zebrafish oculomotor velocity-to-position neural integrator. We found extensive persistence time variation (tenfold; coefficients of variation = 0.58-1.20) across cells in individual larvae. We also found that the similarity in firing between two neurons decreased as the distance between them increased and that a gradient in persistence time was mapped along the rostrocaudal and dorsoventral axes. This topography is consistent with the emergence of persistence time heterogeneity from a circuit architecture in which nearby neurons are more strongly interconnected than distant ones. Integrator circuit models characterized by multiple dimensions of slow firing-rate dynamics can account for our results.

Plasticity and tuning of the time course of analog persistent firing in a neural integrator.

In a companion paper, we reported that the goldfish oculomotor neural integrator could be trained to instability or leak by rotating the visual surround with a velocity proportional to +/- horizontal eye position, respectively. Here we analyze changes in the firing rate behavior of neurons in area I in the caudal brainstem, a central component of the oculomotor neural integrator. Persistent firing could be detuned to instability and leak, respectively, along with fixation behavior. Prolonged training could reduce the time constant of persistent firing of some cells by more than an order of magnitude, to <1 s. Normal visual feedback gradually retuned persistent firing of integrator neurons toward stability, along with fixation behavior. In animals with unstable fixations, approximately half of the eye position-related cells had upward or unstable firing rate drift. In animals with leaky fixations, two-thirds of the eye position-related cells showed leaky firing drift. The remaining eye position-related cells, generally those with lower eye position thresholds, showed a more complex pattern of history-dependent/predictive firing rate drift in relation to eye drift. These complex drift cells often showed a drop in maximum persistent firing rate after training to leak. Despite this diversity, firing drift and the degree of instability or leak in firing rates were broadly correlated with fixation performance. The presence, strength, and reversibility of this plasticity demonstrate that, in this system, visual feedback plays a vital role in gradually tuning the time course of persistent neural firing.

Plasticity and tuning by visual feedback of the stability of a neural integrator.

Persistent neural firing is of fundamental importance to working memory and other brain functions because it allows information to be held "online" following an input and to be integrated over time. Many models of persistent activity rely on some kind of positive feedback internal to the neural circuit concerned; however, too much feedback causes runaway firing (instability), and too little results in loss of persistence (leak). This parameter sensitivity leads to the hypothesis that the brain uses an error signal (external feedback) to tune the stability of persistent firing by adjusting the amount of internal feedback. We test this hypothesis by manipulating external visual feedback, a putative sensory error signal, in a model system for persistent firing, the goldfish oculomotor neural integrator. Over tens of minutes to hours, electronically controlled visual feedback consistent with a leaky or unstable integrator can drive the integrator progressively more unstable or leaky, respectively. Eye fixation time constants can be reduced >100-fold to <1 s. Normal visual feedback gradually retunes the integrator back to stability. Changes in the phase of the sinusoidal vestibulo-ocular response are consistent with integrator detuning, as are changes in ocular drift following eye position shifts compensating for brief passive head movements during fixations. Corresponding changes in persistent firing of integrator neurons are presented in the accompanying article. The presence, strength, and reversibility of the plasticity demonstrate that, in this system, external visual feedback plays a vital role in gradually tuning the stability of the neural integrator.

In vivo mammalian brain imaging using one- and two-photon fluorescence microendoscopy.

One of the major limitations in the current set of techniques available to neuroscientists is a dearth of methods for imaging individual cells deep within the brains of live animals. To overcome this limitation, we developed two forms of minimally invasive fluorescence microendoscopy and tested their abilities to image cells in vivo. Both one- and two-photon fluorescence microendoscopy are based on compound gradient refractive index (GRIN) lenses that are 350-1,000 microm in diameter and provide micron-scale resolution. One-photon microendoscopy allows full-frame images to be viewed by eye or with a camera, and is well suited to fast frame-rate imaging. Two-photon microendoscopy is a laser-scanning modality that provides optical sectioning deep within tissue. Using in vivo microendoscopy we acquired video-rate movies of thalamic and CA1 hippocampal red blood cell dynamics and still-frame images of CA1 neurons and dendrites in anesthetized rats and mice. Microendoscopy will help meet the growing demand for in vivo cellular imaging created by the rapid emergence of new synthetic and genetically encoded fluorophores that can be used to label specific brain areas or cell classes.