Truncating Tau Reveals Different Pathophysiological Actions of Oligomers in Single Neurons

Tau protein is involved in maintaining the structural integrity of neurons. In tauopathies, including Alzheimer's disease, tau forms oligomers, which can modulate neuronal function. Previously the introduction of oligomeric full-length human tau (aa 1-441; FL-oTau) into pyramidal neurons decreased whole-cell conductance, increased excitability and changed the action potential (AP) waveform. Introducing N-terminally truncated tau (aa 124-441; CFRAG) removed the effects on the AP waveform and input resistance but the increase in excitability remained. A hyperpolarising shift in spike threshold underlies this increase in excitability. The N-terminal fragment (aa 1-123; NFRAG) markedly increased input resistance and changed the AP waveform. Lower concentrations of NFRAG only changed the AP waveform. Thus the two truncations can recapitulate the effects of FL-oTau. To investigate underlying mechanisms, we recorded sodium currents and found that FL-oTau lowers the activation voltage and reduced the maximal conductance, consistent with the lower spike threshold and reduction in AP amplitude.

Altered A-type potassium channel function impairs dendritic spike initiation and temporammonic long-term potentiation in Fragile X syndrome

Fragile X syndrome (FXS) is the leading monogenetic cause of cognitive impairment and autism spectrum disorder. Area CA1 of the hippocampus receives current information about the external world from the entorhinal cortex via the temporoammonic (TA) pathway. Given its role in learning and memory, it is surprising that little is known about TA long-term potentiation (TA-LTP) in FXS. We found that TA-LTP was impaired in fmr1 KO mice. Furthermore, dendritic Ca2+ influx was smaller and dendritic spike threshold was depolarized in fmr1 KO mice. Dendritic spike threshold and TA-LTP were restored by block of A-type K+ channels. The impairment of TA-LTP coupled with enhanced Schaffer collateral LTP may contribute to spatial memory alterations in FXS. Furthermore, as both of these LTP phenotypes are attributed to changes in A-type K+ channels in FXS, our findings provide a potential therapeutic target to treat cognitive impairments in FXS.

Neural excitability increases with axonal resistance between soma and axon initial segment

The position of the axon initial segment (AIS) is thought to play a critical role in neuronal excitability. In particular, empirical studies have found correlations between a distal shift in AIS position and a reduction of excitability. Yet, theoretical work has suggested that the neuron should become more excitable as the distance between soma and AIS is increased, because of increased electrical isolation. Specifically, resistive coupling theory predicts that the action potential (AP) threshold decreases with the logarithm of the axial resistance (Ra) between the middle of the AIS and the soma. However, no direct experimental evidence has been provided so far to support this theoretical prediction. We therefore examined how changes in Ra at the axon hillock impact the voltage threshold (Vth) of the somatic AP in L5 pyramidal neurons. Increasing Ra by mechanically pinching the axon between the soma and the AIS was found to lower the spike threshold by ~6 mV. Conversely, decreasing Ra by replacing a weakly mobile ion (gluconate) by a highly mobile ion (chloride) elevated the spike threshold. All Ra-dependent changes in spike threshold could be reproduced in a Hodgkin-Huxley compartmental model. We conclude that in L5 pyramidal neurons, excitability increases with axial resistance, and therefore with a distal shift of the AIS.

Adaptation with correlated noise predicts negative interval correlations in neuronal spike trains

Negative correlations in the sequential evolution of interspike intervals (ISIs) are a signature of memory in neuronal spike-trains. They provide coding benefits including firing-rate stabilization, improved detectability of weak sensory signals, and enhanced transmission of information by improving signal-to-noise ratio. Here we predict observed ISI serial correlations from primary electrosensory afferents of weakly electric fish using an adaptive threshold model with a noisy spike threshold. We derive a general relationship between serial correlation coefficients (SCCs) and the autocorrelation function of added noise. Observed afferent spike-trains fall into two categories based on the pattern of SCCs: non-bursting units have negative SCCs which remain negative but decay to zero with increasing lags (Type I SCCs), and bursting units have oscillatory (alternating sign) SCCs which damp to zero with increasing lags (Type II SCCs). Type I SCCs are generated by low-pass filtering white noise before adding it to the spike threshold, whereas Type II SCCs are generated by high-pass filtering white noise. Thus, a single parameter (the sign of the pole of the filter) generates both types of SCCs. The filter pole (equivalently time-constant) is estimated from the observed SCCs. The predicted SCCs are in geometric progression. The theory predicts that the limiting sum of SCCs is −0.5, and this is confirmed from the expressions for the two types of filters. Observed SCCs from afferents have a limiting sum that is slightly larger at −0.475 ±0.04 (mean ±s.d.). The theoretical limit of the sum of SCCs leads to a perfect DC block in the power spectrum of the spike-train, thereby maximizing signal-to-noise ratio during signal encoding. The experimentally observed sum of SCCs is just short of this limit. We conclude by discussing the results from the perspective of optimal coding.Author summaryMany neurons spontaneously emit spikes (impulses) with a random time interval between successive spikes (interspike interval or ISI). The spike generation mechanism can have memory so that successive ISIs are dependent on one another and exhibit correlations. An ISI which is longer than the mean ISI tends to be followed by an ISI which is shorter than the mean, and vice versa. Thus, adjacent ISIs are negatively correlated, and further these correlations can extend over multiple ISIs. A simple model describing negative correlations in ISIs is an adaptive threshold with noise added to the spike threshold. A neuron becomes more resistant (refractory) to spiking immediately after a spike is output, with refractoriness increasing as more spikes are spaced closer together. Refractoriness reduces as spikes are spaced further apart. We show that a neuron can generate experimentally observed patterns of correlations by relating it to the noise in the spike threshold. Two different types of filtered noise (low-pass and high-pass) generate the observed patterns of correlations. We show that the theoretical sum of the sequence of correlations has a limiting value which maximizes the information a neuron can transmit. The observed sum of correlations is close to this limit.

Synaptic and intrinsic mechanisms underlying development of cortical direction selectivity

Modifications of synaptic inputs and cell-intrinsic properties both contribute to neuronal plasticity and development. To better understand these mechanisms, we undertook an intracellular analysis of the development of direction selectivity in the ferret visual cortex, which occurs rapidly over a few days after eye opening. We found strong evidence of developmental changes in linear spatiotemporal receptive fields of simple cells, implying alterations in circuit inputs. Further, this receptive field plasticity was accompanied by increases in near-spike-threshold excitability and input-output gain that resulted in dramatically increased spiking responses in the experienced state. Increases in subthreshold membrane responses induced by the receptive field plasticity and the increased input-output spiking gain were both necessary to explain the elevated firing rates in experienced ferrets. These results demonstrate that cortical direction selectivity develops through a combination of plasticity in inputs and in cell-intrinsic properties.

Spike threshold adaptation diversifies neuronal operating modes in the auditory brain stem

Single neurons function along a spectrum of neuronal operating modes whose properties determine how the output firing activity is generated from synaptic input. The auditory brain stem contains a diversity of neurons, from pure coincidence detectors to pure integrators and those with intermediate properties. We investigated how intrinsic spike initiation mechanisms regulate neuronal operating mode in the avian cochlear nucleus. Although the neurons in one division of the avian cochlear nucleus, nucleus magnocellularis, have been studied in depth, the spike threshold dynamics of the tonically firing neurons of a second division of cochlear nucleus, nucleus angularis (NA), remained unexplained. The input-output functions of tonically firing NA neurons were interrogated with directly injected in vivo-like current stimuli during whole cell patch-clamp recordings in vitro. Increasing the amplitude of the noise fluctuations in the current stimulus enhanced the firing rates in one subset of tonically firing neurons (“differentiators”) but not another (“integrators”). We found that spike thresholds showed significantly greater adaptation and variability in the differentiator neurons. A leaky integrate-and-fire neuronal model with an adaptive spike initiation process derived from sodium channel dynamics was fit to the firing responses and could recapitulate >80% of the precise temporal firing across a range of fluctuation and mean current levels. Greater threshold adaptation explained the frequency-current curve changes due to a hyperpolarized shift in the effective adaptation voltage range and longer-lasting threshold adaptation in differentiators. The fine-tuning of the intrinsic properties of different NA neurons suggests they may have specialized roles in spectrotemporal processing. NEW & NOTEWORTHY Avian cochlear nucleus angularis (NA) neurons are responsible for encoding sound intensity for sound localization and spectrotemporal processing. An adaptive spike threshold mechanism fine-tunes a subset of repetitive-spiking neurons in NA to confer coincidence detector-like properties. A model based on sodium channel inactivation properties reproduced the activity via a hyperpolarized shift in adaptation conferring fluctuation sensitivity.

Adaptive integrate-and-fire model reproduces the dynamics of olfactory receptor neuron responses in a moth

In order to understand how olfactory stimuli are encoded and processed in the brain, it is important to build a computational model for olfactory receptor neurons (ORNs). Here, we present a simple and reliable mathematical model of a moth ORN generating spikes. The model incorporates a simplified description of the chemical kinetics leading to olfactory receptor activation and action potential generation. We show that an adaptive spike threshold regulated by prior spike history is an effective mechanism for reproducing the typical phasic–tonic time course of ORN responses. Our model reproduces the response dynamics of individual neurons to a fluctuating stimulus that approximates odorant fluctuations in nature. The parameters of the spike threshold are essential for reproducing the response heterogeneity in ORNs. The model provides a valuable tool for efficient simulations of olfactory circuits.

Axonal Na+ channels detect and transmit levels of input synchrony in local brain circuits

Sensory processing requires mechanisms of fast coincidence-detection to discriminate synchronous from asynchronous inputs. Spike-threshold adaptation enables such a discrimination but is ineffective in transmitting this information to the network. We show here that presynaptic axonal sodium channels read and transmit precise levels of input synchrony to the postsynaptic cell by modulating the presynaptic action potential (AP) amplitude. As a consequence, synaptic transmission is facilitated at cortical synapses when the presynaptic spike is produced by synchronous inputs. Using dual soma-axon recordings, imaging, and modeling, we show that this facilitation results from enhanced AP amplitude in the axon due to minimized inactivation of axonal sodium-channels. Quantifying local circuit activity and using network modeling, we found that spikes induced by synchronous inputs produced a larger effect on network activity than spikes induced by asynchronous inputs. Therefore, this input-synchrony dependent facilitation (ISF) may constitute a powerful mechanism regulating spike transmission.

Cellular and network mechanisms may generate sparse coding of sequential object encounters in hippocampal-like circuits

In mammals, the localization of distinct landmarks is performed by hippocampal neurons that sparsely encode an animal’s location relative to surrounding objects. Similarly, the dorsal lateral pallium (DL) is essential for spatial learning in teleost fish. The DL of weakly electric gymnotiform fish receives sensory inputs from the preglomerular nucleus (PG), which has been hypothesized to encode the temporal sequence of electrosensory or visual landmark/food encounters. Here, we show that DL neurons have a hyperpolarized resting membrane potential combined with a high and dynamic spike threshold that increases following each spike. Current-evoked spikes in DL cells are followed by a strong small-conductance calcium-activated potassium channel (SK) mediated after-hyperpolarizing potential (AHP). Together, these properties prevent high frequency and continuous spiking. The resulting sparseness of discharge and dynamic threshold suggest that DL neurons meet theoretical requirements for generating spatial memory engrams by decoding the landmark/food encounter sequences encoded by PG neurons.

Increased excitation-inhibition ratio stabilizes synapse and circuit excitability in four autism mouse models

SummaryDistinct genetic forms of autism are hypothesized to share a common increase in excitation-inhibition (E-I) ratio in cerebral cortex, causing hyperexcitability and excess spiking. We provide the first systematic test of this hypothesis across 4 mouse models (Fmr1−/y,Cntnap2−/-,16p11.2del/+,Tsc2+/-), focusing on somatosensory cortex. All autism mutants showed reduced feedforward inhibition in layer 2/3 coupled with more modest, variable reductions in feedforward excitation, driving a common increase in E-I conductance ratio. Despite this, feedforward spiking, synaptic depolarization and spontaneous spiking were essentially normal. Modeling revealed that E and I conductance changes in each mutant were quantitatively matched to yield stable, not increased, synaptic depolarization for cells near spike threshold. Correspondingly, whisker-evoked spiking was not increasedin vivo, despite detectably reduced inhibition. Thus, elevated E-I ratio is a common circuit phenotype, but appears to reflect homeostatic stabilization of synaptic drive, rather than driving network hyperexcitability in autism.