Fast, automated implementation of temporally precise blind deconvolution of multiphasic excitatory postsynaptic currents.

Records of excitatory postsynaptic currents (EPSCs) are often complex, with overlapping signals that display a large range of amplitudes. Statistical analysis of the kinetics and amplitudes of such complex EPSCs is nonetheless essential to the understanding of transmitter release. We therefore developed a maximum-likelihood blind deconvolution algorithm to detect exocytotic events in complex EPSC records. The algorithm is capable of characterizing the kinetics of the prototypical EPSC as well as delineating individual release events at higher temporal resolution than other extant methods. The approach also accommodates data with low signal-to-noise ratios and those with substantial overlaps between events. We demonstrated the algorithm's efficacy on paired whole-cell electrode recordings and synthetic data of high complexity. Using the algorithm to align EPSCs, we characterized their kinetics in a parameter-free way. Combining this approach with maximum-entropy deconvolution, we were able to identify independent release events in complex records at a temporal resolution of less than 250 µs. We determined that the increase in total postsynaptic current associated with depolarization of the presynaptic cell stems primarily from an increase in the rate of EPSCs rather than an increase in their amplitude. Finally, we found that fluctuations owing to postsynaptic receptor kinetics and experimental noise, as well as the model dependence of the deconvolution process, explain our inability to observe quantized peaks in histograms of EPSC amplitudes from physiological recordings.

Anomalous Brownian motion discloses viscoelasticity in the ear's mechanoelectrical-transduction apparatus.

The ear detects sounds so faint that they produce only atomic-scale displacements in the mechanoelectrical transducer, yet thermal noise causes fluctuations larger by an order of magnitude. Explaining how hearing can operate when the magnitude of the noise greatly exceeds that of the signal requires an understanding both of the transducer's micromechanics and of the associated noise. Using microrheology, we characterize the statistics of this noise; exploiting the fluctuation-dissipation theorem, we determine the associated micromechanics. The statistics reveal unusual Brownian motion in which the mean square displacement increases as a fractional power of time, indicating that the mechanisms governing energy dissipation are related to those of energy storage. This anomalous scaling contradicts the canonical model of mechanoelectrical transduction, but the results can be explained if the micromechanics incorporates viscoelasticity, a salient characteristic of biopolymers. We amend the canonical model and demonstrate several consequences of viscoelasticity for sensory coding.

Modeling the resonant release of synaptic transmitter by hair cells as an example of biological oscillators with cooperative steps.

The initial synapses of the auditory system, which connect hair cells to afferent nerve fibers, display two unusual features. First, synaptic transmission occurs in a multiquantal fashion: the contents of multiple synaptic vesicles are discharged simultaneously. Second, synaptic transmission may be tuned to specific frequencies of stimulation. We developed a minimal theoretical model to explore the possibility that hair-cell synapses achieve both multiquantal release and frequency selectivity through a cooperative mechanism for the exocytotic release of neurotransmitter. We first characterized vesicle release as a four-step cycle at each release site, then generalized the result to an arbitrary number of steps. The cyclic process itself induces some degree of resonance, and may display a stable, underdamped fixed point of the release dynamics associated with a pair of complex eigenvalues. Cooperativity greatly enhances the frequency selectivity by moving the eigenvalues toward the imaginary axis; spontaneously oscillatory release can arise beyond a Hopf bifurcation. These phenomena occur both in the macroscopic limit, when the number of release sites involved is very large, and in the more realistic stochastic regime, when only a limited number of release sites participate at each synapse. It is thus possible to connect multiquantal release with frequency selectivity through the mechanism of cooperativity.

Activity-independent specification of synaptic targets in the posterior lateral line of the larval zebrafish.

The development of functional neural circuits requires that connections between neurons be established in a precise manner. The mechanisms by which complex nervous systems perform this daunting task remain largely unknown. In the posterior lateral line of larval zebrafish, each afferent neuron forms synaptic contacts with hair cells of a common hair-bundle polarity. We investigated whether afferent neurons distinguish hair-cell polarities by analyzing differences in the synaptic signaling between oppositely polarized hair cells. By examining two mutant zebrafish lines with defects in mechanoelectrical transduction, and by blocking transduction during the development of wild-type fish, we found that afferent neurons could form specific synapses in the absence of stimulus-evoked patterns of synaptic release. Asking next whether this specificity arises through intrinsically generated patterns of synaptic release, we found that the polarity preference persisted in two mutant lines lacking essential synaptic proteins. These results indicate that lateral-line afferent neurons do not require synaptic activity to distinguish hair-cell polarities and suggest that molecular labels of hair-cell polarity guide prepatterned afferents to form the appropriate synapses.

The unitary event underlying multiquantal EPSCs at a hair cell's ribbon synapse.

EPSCs at the synapses of sensory receptors and of some CNS neurons include large events thought to represent the synchronous release of the neurotransmitter contained in several synaptic vesicles by a process known as multiquantal release. However, determination of the unitary, quantal size underlying such putatively multiquantal events has proven difficult at hair cell synapses, hindering confirmation that large EPSCs are in fact multiquantal. Here, we address this issue by performing presynaptic membrane capacitance measurements together with paired recordings at the ribbon synapses of adult hair cells. These simultaneous presynaptic and postsynaptic assays of exocytosis, together with electron microscopic estimates of single vesicle capacitance, allow us to estimate a single vesicle EPSC charge of approximately -45 fC, a value in close agreement with the mean postsynaptic charge transfer of uniformly small EPSCs recorded during periods of presynaptic hyperpolarization. By thus establishing the magnitude of the fundamental quantal event at this peripheral sensory synapse, we provide evidence that the majority of spontaneous and evoked EPSCs are multiquantal. Furthermore, we show that the prevalence of uniquantal versus multiquantal events is Ca2+ dependent. Paired recordings also reveal a tight correlation between membrane capacitance increase and evoked EPSC charge, indicating that glutamate release during prolonged hair cell depolarization does not significantly saturate or desensitize postsynaptic AMPA receptors. We propose that the large EPSCs reflect the highly synchronized release of multiple vesicles at single presynaptic ribbon-type active zones through a compound or coordinated vesicle fusion mechanism.

Specificity of afferent synapses onto plane-polarized hair cells in the posterior lateral line of the zebrafish.

The proper wiring of the vertebrate brain represents an extraordinary developmental challenge, requiring billions of neurons to select their appropriate synaptic targets. In view of this complexity, simple vertebrate systems provide necessary models for understanding how synaptic specificity arises. The posterior lateral-line organ of larval zebrafish consists of polarized hair cells organized in discrete clusters known as neuromasts. Here we show that each afferent neuron of the posterior lateral line establishes specific contacts with hair cells of the same hair-bundle polarity. We quantify this specificity by modeling the neuron as a biased selector of hair-cell polarity and find evidence for bias from as early as 2.5 d after fertilization. More than half of the neurons form contacts on multiple neuromasts, but the innervated organs are spatially consecutive and the polarity preference is consistent. Using a novel reagent for correlative electron microscopy, HRP-mCherry, we show that these contacts are indeed afferent synapses bearing vesicle-loaded synaptic ribbons. Moreover, afferent neurons reassume their biased innervation pattern after hair-cell ablation and regeneration. By documenting specificity in the pattern of neuronal connectivity during development and in the context of organ regeneration, these results establish the posterior lateral-line organ as a vertebrate system for the in vivo study of synaptic target selection.