Quantification of functional recovery in a larval zebrafish model of spinal cord injury.

Human spinal cord injury (SCI) is characterized by permanent loss of damaged axons, resulting in chronic disability. In contrast, zebrafish can regenerate axonal projections following central nervous system injury and re-establish synaptic contacts with distant targets; elucidation of the underlying molecular events is an important goal with translational potential for improving outcomes in SCI patients. We generated transgenic zebrafish with GFP-labeled axons and transected their spinal cords at 10 days post-fertilization. Intravital confocal microscopy revealed robust axonal regeneration following the procedure, with abundant axons bridging the transection site by 48 h post-injury. In order to analyze neurological function in this model, we developed and validated new open-source software to measure zebrafish lateral trunk curvature during propulsive and turning movements at high temporal resolution. Immediately following spinal cord transection, axial movements were dramatically decreased caudal to the lesion site, but preserved rostral to the injury, suggesting the induction of motor paralysis below the transection level. Over the subsequent 96 h, the magnitude of movements caudal to the lesion recovered to baseline, but the rate of change of truncal curvature did not fully recover, suggesting incomplete restoration of caudal strength over this time course. Quantification of both morphological and functional recovery following SCI will be important for the analysis of axonal regeneration and downstream events necessary for restoration of motor function. An extensive array of genetic and pharmacological interventions can be deployed in the larval zebrafish model to investigate the underlying molecular mechanisms.

Mechanism of Pacemaker Activity in Zebrafish DC2/4 Dopaminergic Neurons.

Zebrafish models are used increasingly to study the molecular pathogenesis of Parkinson's disease (PD), owing to the extensive array of techniques available for their experimental manipulation and analysis. The ascending dopaminergic projection from the posterior tuberculum (TPp; diencephalic populations DC2 and DC4) to the subpallium is considered the zebrafish correlate of the mammalian nigrostriatal projection, but little is known about the neurophysiology of zebrafish DC2/4 neurons. This is an important knowledge gap, because autonomous activity in mammalian substantia nigra (SNc) dopaminergic neurons contributes to their vulnerability in PD models. Using a new transgenic zebrafish line to label living dopaminergic neurons, and a novel brain slice preparation, we conducted whole-cell patch clamp recordings of DC2/4 neurons from adult zebrafish of both sexes. Zebrafish DC2/4 neurons share many physiological properties with mammalian dopaminergic neurons, including the cell-autonomous generation of action potentials. However, in contrast to mammalian dopaminergic neurons, the pacemaker driving intrinsic rhythmic activity in zebrafish DC2/4 neurons does not involve calcium conductances, hyperpolarization-activated cyclic nucleotide-gated (HCN) channels, or sodium leak currents. Instead, voltage clamp recordings and computational models show that interactions between three components - a small, predominantly potassium, leak conductance, voltage-gated sodium channels, and voltage-gated potassium channels - are sufficient for pacemaker activity in zebrafish DC2/4 neurons. These results contribute to understanding the comparative physiology of the dopaminergic system and provide a conceptual basis for interpreting data derived from zebrafish PD models. The findings further suggest new experimental opportunities to address the role of dopaminergic pacemaker activity in the pathogenesis of PD.SIGNIFICANCE STATEMENT Posterior tuberculum (TPp) DC2/4 dopaminergic neurons are considered the zebrafish correlate of mammalian substantia nigra (SNc) neurons, whose degeneration causes the motor signs of Parkinson's disease (PD). Our study shows that DC2/4 and SNc neurons share a number of electrophysiological properties, including depolarized membrane potential, high input resistance, and continual, cell-autonomous pacemaker activity, that strengthen the basis for the increasing use of zebrafish models to study the molecular pathogenesis of PD. The mechanisms driving pacemaker activity differ between DC2/4 and SNc neurons, providing: (1) experimental opportunities to dissociate the contributions of intrinsic activity and underlying pacemaker currents to pathogenesis; and (2) essential information for the design and interpretation of studies using zebrafish PD models.

Chemoptogenetic ablation of neuronal mitochondria in vivo with spatiotemporal precision and controllable severity.

Mitochondrial dysfunction is implicated in the pathogenesis of multiple neurological diseases, but elucidation of underlying mechanisms is limited experimentally by the inability to damage specific mitochondria in defined neuronal groups. We developed a precision chemoptogenetic approach to target neuronal mitochondria in the intact nervous system in vivo. MG2I, a chemical fluorogen, produces singlet oxygen when bound to the fluorogen-activating protein dL5** and exposed to far-red light. Transgenic zebrafish expressing dL5** within neuronal mitochondria showed dramatic MG2I- and light-dependent neurobehavioral deficits, caused by neuronal bioenergetic crisis and acute neuronal depolarization. These abnormalities resulted from loss of neuronal respiration, associated with mitochondrial fragmentation, swelling and elimination of cristae. Remaining cellular ultrastructure was preserved initially, but cellular pathology downstream of mitochondrial damage eventually culminated in neuronal death. Our work provides powerful new chemoptogenetic tools for investigating mitochondrial homeostasis and pathophysiology and shows a direct relationship between mitochondrial function, neuronal biogenetics and whole-animal behavior.

Most life processes require the energy produced by small cellular compartments called mitochondria. Many internal and external factors can harm these miniature powerhouses, potentially leading to cell death. For instance, in patients with Parkinson's or Alzheimer's disease, dying neurons often show mitochondrial damage. However, it is unclear exactly how injured mitochondria trigger the demise of these cells. Gaining a better understanding of this process requires studying the impact of mitochondrial damage in live neurons, something that is still difficult to do. As a response to this challenge, Xie, Jiao, Bai, Ilin et al. designed a new tool that can specifically injure mitochondria in the neurons of live zebrafish larvae at will, and fine-tune the amount of damage inflicted. The zebrafish are genetically engineered so that the mitochondria in their neurons carry a protein which can bind to a chemical compound called MG2I. When attached to each other, MG2I and the protein respond to far-red light by locally creating highly damaging chemicals. This means that whenever far-red light is shone onto the larvae, mitochondria in their neurons are harmed ­ the brighter the light, the stronger the damage. Zebrafish larvae exposed to these conditions immediately stopped swimming: mitochondria in their neurons could not produce enough energy and these cells could therefore no longer communicate properly. The neurons then started to die about 24 hours after exposure to the light, suggesting that the mitochondrial damage triggered other downstream processes that culminated in cell death. This new light-controlled tool could help to understand the consequences of mitochondrial damage, potentially revealing new ways to rescue impaired neurons in patients with Parkinson's or Alzheimer's disease. In the future, the method could be adapted to work in any type of cell and deactivate other cell compartments, so that it can be used to study many types of diseases.

Distinct Heterosynaptic Plasticity in Fast Spiking and Non-Fast-Spiking Inhibitory Neurons in Rat Visual Cortex.

Inhibition in neuronal networks of the neocortex serves a multitude of functions, such as balancing excitation and structuring neuronal activity in space and time. Plasticity of inhibition is mediated by changes at both inhibitory synapses, as well as excitatory synapses on inhibitory neurons. Using slices from visual cortex of young male rats, we describe a novel form of plasticity of excitatory synapses on inhibitory neurons, weight-dependent heterosynaptic plasticity. Recordings from connected pyramid-to-interneuron pairs confirm that postsynaptic activity alone can induce long-term changes at synapses that were not presynaptically active during the induction, i.e., heterosynaptic plasticity. Moreover, heterosynaptic changes can accompany homosynaptic plasticity induced in inhibitory neurons by conventional spike-timing-dependent plasticity protocols. In both fast-spiking (FS) and non-FS neurons, heterosynaptic changes were weight-dependent, because they correlated with initial paired-pulse ratio (PPR), indicative of initial strength of a synapse. Synapses with initially high PPR, indicative of low release probability ("weak" synapses), had the tendency to be potentiated, while synapses with low initial PPR ("strong" synapses) tended to depress or did not change. Interestingly, the net outcome of heterosynaptic changes was different in FS and non-FS neurons. FS neurons expressed balanced changes, with gross average (n = 142) not different from control. Non-FS neurons (n = 66) exhibited net potentiation. This difference could be because of higher initial PPR in the non-FS neurons. We propose that weight-dependent heterosynaptic plasticity may counteract runaway dynamics of excitatory inputs imposed by Hebbian-type learning rules and contribute to fine-tuning of distinct aspects of inhibitory function mediated by FS and non-FS neurons in neocortical networks.SIGNIFICANCE STATEMENT Dynamic balance of excitation and inhibition is fundamental for operation of neuronal networks. Fine-tuning of such balance requires synaptic plasticity. Knowledge about diverse forms of plasticity operating in excitatory and inhibitory neurons is necessary for understanding normal function and causes of dysfunction of the nervous system. Here we show that excitatory inputs to major archetypal classes of neocortical inhibitory neurons, fast-spiking (FS) and non-fast-spiking (non-FS), express a novel type of plasticity, weight-dependent heterosynaptic plasticity, which accompanies the induction of Hebbian-type changes. This novel form of plasticity may counteract runaway dynamics at excitatory synapses to inhibitory neurons imposed by Hebbian-type learning rules and contribute to fine-tuning of diverse aspects of inhibitory function mediated by FS and non-FS neurons in neocortical networks.

Partial Breakdown of Input Specificity of STDP at Individual Synapses Promotes New Learning.

UNLABELLED: Hebbian-type learning rules, which underlie learning and refinement of neuronal connectivity, postulate input specificity of synaptic changes. However, theoretical analyses have long appreciated that additional mechanisms, not restricted to activated synapses, are needed to counteract positive feedback imposed by Hebbian-type rules on synaptic weight changes and to achieve stable operation of learning systems. The biological basis of such mechanisms has remained elusive. Here we show that, in layer 2/3 pyramidal neurons from slices of visual cortex of rats, synaptic changes induced at individual synapses by spike timing-dependent plasticity do not strictly follow the input specificity rule. Spike timing-dependent plasticity is accompanied by changes in unpaired synapses: heterosynaptic plasticity. The direction of heterosynaptic changes is weight-dependent, with balanced potentiation and depression, so that the total synaptic input to a cell remains preserved despite potentiation or depression of individual synapses. Importantly, this form of heterosynaptic plasticity is induced at unpaired synapses by the same pattern of postsynaptic activity that induces homosynaptic changes at paired synapses. In computer simulations, we show that experimentally observed heterosynaptic plasticity can indeed serve the theoretically predicted role of robustly preventing runaway dynamics of synaptic weights and activity. Moreover, it endows model neurons and networks with essential computational features: enhancement of synaptic competition, facilitation of the development of specific intrinsic connectivity, and the ability for relearning. We conclude that heterosynaptic plasticity is an inherent property of plastic synapses, crucial for normal operation of learning systems. SIGNIFICANCE STATEMENT: We show that spike timing-dependent plasticity in L2/L3 pyramids from rat visual cortex is accompanied by plastic changes in unpaired synapses. These heterosynaptic changes are weight-dependent and balanced: individual synapses expressed significant LTP or LTD, but the average over all synapses did not change. Thus, the rule of input specificity breaks down at individual synapses but holds for responses averaged over many inputs. In model neurons and networks, this experimentally characterized form of heterosynaptic plasticity prevents runaway dynamics of synaptic weights and activity, enhances synaptic competition, facilitates development of specific intrinsic connectivity, and enables relearning. This new form of heterosynaptic plasticity represents the cellular basis of a theoretically postulated mechanism, which is additional to Hebbian-type rules, and is necessary for stable operation of learning systems.

Live imaging of mitochondrial dynamics in CNS dopaminergic neurons in vivo demonstrates early reversal of mitochondrial transport following MPP(+) exposure.

Extensive convergent evidence collectively suggests that mitochondrial dysfunction is central to the pathogenesis of Parkinson's disease (PD). Recently, changes in the dynamic properties of mitochondria have been increasingly implicated as a key proximate mechanism underlying neurodegeneration. However, studies have been limited by the lack of a model in which mitochondria can be imaged directly and dynamically in dopaminergic neurons of the intact vertebrate CNS. We generated transgenic zebrafish in which mitochondria of dopaminergic neurons are labeled with a fluorescent reporter, and optimized methods allowing direct intravital imaging of CNS dopaminergic axons and measurement of mitochondrial transport in vivo. The proportion of mitochondria undergoing axonal transport in dopaminergic neurons decreased overall during development between 2days post-fertilization (dpf) and 5dpf, at which point the major period of growth and synaptogenesis of the relevant axonal projections is complete. Exposure to 0.5-1.0mM MPP(+) between 4 and 5dpf did not compromise zebrafish viability or cause detectable changes in the number or morphology of dopaminergic neurons, motor function or monoaminergic neurochemistry. However, 0.5mM MPP(+) caused a 300% increase in retrograde mitochondrial transport and a 30% decrease in anterograde transport. In contrast, exposure to higher concentrations of MPP(+) caused an overall reduction in mitochondrial transport. This is the first time mitochondrial transport has been observed directly in CNS dopaminergic neurons of a living vertebrate and quantified in a PD model in vivo. Our findings are compatible with a model in which damage at presynaptic dopaminergic terminals causes an early compensatory increase in retrograde transport of compromised mitochondria for degradation in the cell body. These data are important because manipulation of early pathogenic mechanisms might be a valid therapeutic approach to PD. The novel transgenic lines and methods we developed will be useful for future studies on mitochondrial dynamics in health and disease.

Identifying and tracking simulated synaptic inputs from neuronal firing: insights from in vitro experiments.

Accurately describing synaptic interactions between neurons and how interactions change over time are key challenges for systems neuroscience. Although intracellular electrophysiology is a powerful tool for studying synaptic integration and plasticity, it is limited by the small number of neurons that can be recorded simultaneously in vitro and by the technical difficulty of intracellular recording in vivo. One way around these difficulties may be to use large-scale extracellular recording of spike trains and apply statistical methods to model and infer functional connections between neurons. These techniques have the potential to reveal large-scale connectivity structure based on the spike timing alone. However, the interpretation of functional connectivity is often approximate, since only a small fraction of presynaptic inputs are typically observed. Here we use in vitro current injection in layer 2/3 pyramidal neurons to validate methods for inferring functional connectivity in a setting where input to the neuron is controlled. In experiments with partially-defined input, we inject a single simulated input with known amplitude on a background of fluctuating noise. In a fully-defined input paradigm, we then control the synaptic weights and timing of many simulated presynaptic neurons. By analyzing the firing of neurons in response to these artificial inputs, we ask 1) How does functional connectivity inferred from spikes relate to simulated synaptic input? and 2) What are the limitations of connectivity inference? We find that individual current-based synaptic inputs are detectable over a broad range of amplitudes and conditions. Detectability depends on input amplitude and output firing rate, and excitatory inputs are detected more readily than inhibitory. Moreover, as we model increasing numbers of presynaptic inputs, we are able to estimate connection strengths more accurately and detect the presence of connections more quickly. These results illustrate the possibilities and outline the limits of inferring synaptic input from spikes.

Adenosine effects on inhibitory synaptic transmission and excitation-inhibition balance in the rat neocortex.

KEY POINTS: Adenosine might be the most widespread neuromodulator in the brain, but its effects on inhibitory transmission in the neocortex are not understood. Here we report that adenosine suppresses inhibitory transmission to layer 2/3 pyramidal neurons via activation of presynaptic A1 receptors. We present evidence for functional A2A receptors, which have a weak modulatory effect on the A1-mediated suppression, at about 50% of inhibitory synapses at pyramidal neurons. Adenosine suppresses excitatory and inhibitory transmission to a different extent, and can change the excitation-inhibition balance at a set of synapses bidirectionally, but on average the balance was maintained during application of adenosine. These results suggest that changes of adenosine concentration may lead to differential modulation of excitatory-inhibitory balance in pyramidal neurons, and thus redistribution of local spotlights of activity in neocortical circuits, while preserving the balanced state of the whole network. ABSTRACT: Adenosine might be the most widespread neuromodulator in the brain: as a metabolite of ATP it is present in every neuron and glial cell. However, how adenosine affects operation of neurons and networks in the neocortex is poorly understood, mostly because modulation of inhibitory transmission by adenosine has been so little studied. To clarify adenosine's role at inhibitory synapses, and in excitation-inhibition balance in pyramidal neurons, we recorded pharmacologically isolated inhibitory responses, compound excitatory-inhibitory responses and spontaneous events in layer 2/3 pyramidal neurons in slices from rat visual cortex. We show that adenosine (1-150 µm) suppresses inhibitory transmission to these neurons in a concentration-dependent and reversible manner. The suppression was mediated by presynaptic A1 receptors (A1Rs) because it was blocked by a selective A1 antagonist, DPCPX, and associated with changes of release indices: paired-pulse ratio, inverse coefficient of variation and frequency of miniature events. At some synapses (12 out of 24) we found evidence for A2ARs: their blockade led to a small but significant increase of the magnitude of adenosine-mediated suppression. This effect of A2AR blockade was not observed when A1Rs were blocked, suggesting that A2ARs do not have their own effect on transmission, but can modulate the A1R-mediated suppression. At both excitatory and inhibitory synapses, the magnitude of A1R-mediated suppression and A2AR-A1R interaction expressed high variability, suggesting high heterogeneity of synapses in the sensitivity to adenosine. Adenosine could change the balance between excitation and inhibition at a set of inputs to a neuron bidirectionally, towards excitation or towards inhibition. On average, however, these bidirectional changes cancelled each other, and the overall balance of excitation and inhibition was maintained during application of adenosine. These results suggest that changes of adenosine concentration may lead to differential modulation of excitatory-inhibitory balance in pyramidal neurons, and thus redistribution of local spotlights of activity in neocortical circuits, while preserving the balanced state of the whole network.

Injection of fully-defined signal mixtures: a novel high-throughput tool to study neuronal encoding and computations.

Understanding of how neurons transform fluctuations of membrane potential, reflecting input activity, into spike responses, which communicate the ultimate results of single-neuron computation, is one of the central challenges for cellular and computational neuroscience. To study this transformation under controlled conditions, previous work has used a signal immersed in noise paradigm where neurons are injected with a current consisting of fluctuating noise that mimics on-going synaptic activity and a systematic signal whose transmission is studied. One limitation of this established paradigm is that it is designed to examine the encoding of only one signal under a specific, repeated condition. As a result, characterizing how encoding depends on neuronal properties, signal parameters, and the interaction of multiple inputs is cumbersome. Here we introduce a novel fully-defined signal mixture paradigm, which allows us to overcome these problems. In this paradigm, current for injection is synthetized as a sum of artificial postsynaptic currents (PSCs) resulting from the activity of a large population of model presynaptic neurons. PSCs from any presynaptic neuron(s) can be now considered as "signal", while the sum of all other inputs is considered as "noise". This allows us to study the encoding of a large number of different signals in a single experiment, thus dramatically increasing the throughput of data acquisition. Using this novel paradigm, we characterize the detection of excitatory and inhibitory PSCs from neuronal spike responses over a wide range of amplitudes and firing-rates. We show, that for moderately-sized neuronal populations the detectability of individual inputs is higher for excitatory than for inhibitory inputs during the 2-5 ms following PSC onset, but becomes comparable after 7-8 ms. This transient imbalance of sensitivity in favor of excitation may enhance propagation of balanced signals through neuronal networks. Finally, we discuss several open questions that this novel high-throughput paradigm may address.

Fast computations in cortical ensembles require rapid initiation of action potentials.

The abilities of neuronal populations to encode rapidly varying stimuli and respond quickly to abrupt input changes are crucial for basic neuronal computations, such as coincidence detection, grouping by synchrony, and spike-timing-dependent plasticity, as well as for the processing speed of neuronal networks. Theoretical analyses have linked these abilities to the fast-onset dynamics of action potentials (APs). Using a combination of whole-cell recordings from rat neocortical neurons and computer simulations, we provide the first experimental evidence for this conjecture and prove its validity for the case of distal AP initiation in the axon initial segment (AIS), typical for cortical neurons. Neocortical neurons with fast-onset APs in the soma can phase-lock their population firing to signal frequencies up to ∼300-400 Hz and respond within 1-2 ms to subtle changes of input current. The ability to encode high frequencies and response speed were dramatically reduced when AP onset was slowed by experimental manipulations or was intrinsically slow due to immature AP generation mechanisms. Multicompartment conductance-based models reproducing the initiation of spikes in the AIS could encode high frequencies only if AP onset was fast at the initiation site (e.g., attributable to cooperative gating of a fraction of sodium channels) but not when fast onset of somatic AP was produced solely by backpropagation. We conclude that fast-onset dynamics is a genuine property of cortical AP generators. It enables fast computations in cortical circuits that are rich in recurrent connections both within each region and across the hierarchy of areas.