New biophysical methods for the characterization of signal transfer in neurons

Many neurons have extensive dendritic trees, and therefore somatic voltage clamp of dendritic synapses is often associated with substantial distortion and attenuation of the synaptic currents. A new method is presented which permits faithful extraction of the decay time constant of the synaptic conductance independent of dendritic geometry and the electrotonic location of the synapse. The decay time course of the synaptic conductance was recovered with high accuracy in all the tested geometries, even with high series resistances, low membrane resistances, and electrotonically remote, distributed synapses. The method also provides the time course of the voltage change at the synapse in response to a somatic voltage clamp step, and thus will be useful for constraining compartmental models and estimating the relative electrotonic distance of synapses. Action potential propagation in dendrites links information processing in different regions of the dendritic tree. In simulations using compartmental models with identical complements of voltage-gated channels, different dendritic branching patterns caused a range of backpropagation efficacies, similar to that observed experimentally. Dendritic geometry also determines the extent to which modulation of channel densities can affect propagation. Forward propagation of dendritically initiated action potentials is influenced by geometry in a similar manner. By determining the spatial pattern of action potential signalling, dendritic geometry thus helps to define the size and interdependence of functional compartments in the neuron

Dendritic Spikes Amplify the Synaptic Signal to Enhance Detection of Motion in a Simulation of the Direction-Selective Ganglion Cell

The On-Off direction-selective ganglion cell (DSGC) in mammalian retinas responds most strongly to a stimulus moving in a specific direction. The DSGC initiates spikes in its dendritic tree, which are thought to propagate to the soma with high probability. Both dendritic and somatic spikes in the DSGC display strong directional tuning, whereas somatic PSPs (postsynaptic potentials) are only weakly directional, indicating that spike generation includes marked enhancement of the directional signal. We used a realistic computational model based on anatomical and physiological measurements to determine the source of the enhancement. Our results indicate that the DSGC dendritic tree is partitioned into separate electrotonic regions, each summing its local excitatory and inhibitory synaptic inputs to initiate spikes. Within each local region the local spike threshold nonlinearly amplifies the preferred response over the null response on the basis of PSP amplitude. Using inhibitory conductances previously measured in DSGCs, the simulation results showed that inhibition is only sufficient to prevent spike initiation and cannot affect spike propagation. Therefore, inhibition will only act locally within the dendritic arbor. We identified the role of three mechanisms that generate directional selectivity (DS) in the local dendritic regions. First, a mechanism for DS intrinsic to the dendritic structure of the DSGC enhances DS on the null side of the cell's dendritic tree and weakens it on the preferred side. Second, spatially offset postsynaptic inhibition generates robust DS in the isolated dendritic tips but weak DS near the soma. Third, presynaptic DS is apparently necessary because it is more robust across the dendritic tree. The pre- and postsynaptic mechanisms together can overcome the local intrinsic DS. These local dendritic mechanisms can perform independent nonlinear computations to make a decision, and there could be analogous mechanisms within cortical circuitry

Determinants of synaptic integration and heterogeneity in rebound firing explored with data-driven models of deep cerebellar nucleus cells

Significant inroads have been made to understand cerebellar cortical processing but neural coding at the output stage of the cerebellum in the deep cerebellar nuclei (DCN) remains poorly understood. The DCN are unlikely to just present a relay nucleus because Purkinje cell inhibition has to be turned into an excitatory output signal, and DCN neurons exhibit complex intrinsic properties. In particular, DCN neurons exhibit a range of rebound spiking properties following hyperpolarizing current injection, raising the question how this could contribute to signal processing in behaving animals. Computer modeling presents an ideal tool to investigate how intrinsic voltage-gated conductances in DCN neurons could generate the heterogeneous firing behavior observed, and what input conditions could result in rebound responses. To enable such an investigation we built a compartmental DCN neuron model with a full dendritic morphology and appropriate active conductances. We generated a good match of our simulations with DCN current clamp data we recorded in acute slices, including the heterogeneity in the rebound responses. We then examined how inhibitory and excitatory synaptic input interacted with these intrinsic conductances to control DCN firing. We found that the output spiking of the model reflected the ongoing balance of excitatory and inhibitory input rates and that changing the level of inhibition performed an additive operation. Rebound firing following strong Purkinje cell input bursts was also possible, but only if the chloride reversal potential was more negative than −70 mV to allow de-inactivation of rebound currents. Fast rebound bursts due to T-type calcium current and slow rebounds due to persistent sodium current could be differentially regulated by synaptic input, and the pattern of these rebounds was further influenced by HCN current. Our findings suggest that active properties of DCN neurons could play a crucial role for signal processing in the cerebellum

Capacitance measurement of dendritic exocytosis in an electrically coupled inhibitory retinal interneuron: an experimental and computational study

Exocytotic release of neurotransmitter can be quantified by electrophysiological recording from postsynaptic neurons. Alternatively, fusion of synaptic vesicles with the cell membrane can be measured as increased capacitance by recording directly from a presynaptic neuron. The “Sine + DC” technique is based on recording from an unbranched cell, represented by an electrically equivalent RC-circuit. It is challenging to extend such measurements to branching neurons where exocytosis occurs at a distance from a somatic recording electrode. The AII amacrine is an important inhibitory interneuron of the mammalian retina and there is evidence that exocytosis at presynaptic lobular dendrites increases the capacitance. Here, we combined electrophysiological recording and computer simulations with realistic compartmental models to explore capacitance measurements of rat AII amacrine cells. First, we verified the ability of the “Sine + DC” technique to detect depolarizationevoked exocytosis in physiological recordings. Next, we used compartmental modeling to demonstrate that capacitance measurements can detect increased membrane surface area at lobular dendrites. However, the accuracy declines for lobular dendrites located further from the soma due to frequency-dependent signal attenuation. For sine wave frequencies ≥1 kHz, the magnitude of the total releasable pool of synaptic vesicles will be significantly underestimated. Reducing the sine wave frequency increases overall accuracy, but when the frequency is sufficiently low that exocytosis can be detected with high accuracy from all lobular dendrites (~100 Hz), strong electrical coupling between AII amacrines compromises the measurements. These results need to be taken into account in studies with capacitance measurements from these and other electrically coupled neurons.publishedVersio

Intracellular processing of motion information in a network of blowfly visual interneurons

In the past few decades, the lobula plate of the fly has emerged as one of the leading models for the neural processing of optic flow stimuli that give rise to visual orientation behaviors (for recent reviews see Borst and Haag, 2002; Egelhaaf et al., 2002; Egelhaaf et al., 2002; Borst and Haag, 2007). The relative simplicity and accessibility of this neural system allows researchers to characterize the neural mechanisms that are thought to link the visual stimuli and the resulting behavioral responses. In the lobula plate, a set of 60 motion sensitive lobula plate tangential cells (LPTCs) integrate visual motion information from an array of local motion detectors, which form a retinotopic map of the fly’s visual space in the lobula plate. The selective pooling of local, direction selective inputs, together with a network of unilateral and bilateral interactions between LPTCs, shape and tune the response properties of LPTCs to behaviorally relevant optic flow stimuli. Over the years, lobula plate researchers assembled a formidable array of measurement and perturbation techniques that are usually available only in in-vitro systems. Additionally, the lobula plate and its presynaptic circuitry have been the subject of extensive and detailed modeling which allows a deeper synthetic understanding of the empirical results, as well as a more efficient and detailed way to generate hypotheses. In this work I used a selection of these tools to explore the role of intracellular processing of visual motion information in lobula plate neurons and the significance of spatial segregation and aggregation of these cells’ inputs in the context of their sensory function. Previous work on a network of ten LPTCs of the vertical system (VS cells) resulted in a prediction that due to lateral, gap-junction coupling of neighboring VS cells in their axon-terminals, the receptive fields of these cells should be broader in the axonal region than in the dendritic regions. I tested and confirmed this prediction using in-vivo calcium imaging and intracellular recordings. Using single-electrode voltage clamp I was able to perturb the flow of information in these cells and isolate the source of input responsible for this broadening, confirming that the coupling indeed takes place in the axon terminal. The separation of feed-forward, synaptic input in the dendrites from lateral, gap-junction coupling in the axon-terminals allowed me to experimentally ask what is the function of the receptive field broadening. Relying on model predictions, I showed that this broadening results in a more stable and smooth representation of optic flow in the output region of the cells than in their input region, when the fly is presented with naturalistic, patchy and non-uniform stimuli. I then showed, using a simplified compartmental model that the separation of axonal gap-junctions from the dendritic synaptic input makes the gap-junction coupling more effective, and is thus necessary to ensure the functionality of the lateral interactions

The Theoretical Foundation of Dendritic Function

This collection of fifteen previously published papers, some of them not widely available, have been carefully chosen and annotated by Rall's colleagues and other leading neuroscientists.Wilfrid Rall was a pioneer in establishing the integrative functions of neuronal dendrites that have provided a foundation for neurobiology in general and computational neuroscience in particular. This collection of fifteen previously published papers, some of them not widely available, have been carefully chosen and annotated by Rall's colleagues and other leading neuroscientists. It brings together Rall's work over more than forty years, including his first papers extending cable theory to complex dendritic trees, his ground-breaking paper introducing compartmental analysis to computational neuroscience, and his studies of synaptic integration in motoneurons, dendrodendritic interactions, plasticity of dendritic spines, and active dendritic properties. Today it is well known that the brain's synaptic information is processed mostly in the dendrites where many of the plastic changes underlying learning and memory take place. It is particularly timely to look again at the work of a major creator of the field, to appreciate where things started and where they have led, and to correct any misinterpretations of Rall's work. The editors' introduction highlights the major insights that were gained from Rall's studies as well as from those of his collaborators and followers. It asks the questions that Rall proposed during his scientific career and briefly summarizes the answers.The papers include commentaries by Milton Brightman, Robert E. Burke, William R. Holmes, Donald R. Humphrey, Julian J. B. Jack, John Miller, Stephen Redman, John Rinzel, Idan Segev, Gordon M. Shepherd, and Charles Wilson

A synaptic learning rule for exploiting nonlinear dendritic computation

Information processing in the brain depends on the integration of synaptic input distributed throughout neuronal dendrites. Dendritic integration is a hierarchical process, proposed to be equivalent to integration by a multilayer network, potentially endowing single neurons with substantial computational power. However, whether neurons can learn to harness dendritic properties to realize this potential is unknown. Here, we develop a learning rule from dendritic cable theory and use it to investigate the processing capacity of a detailed pyramidal neuron model. We show that computations using spatial or temporal features of synaptic input patterns can be learned, and even synergistically combined, to solve a canonical nonlinear feature-binding problem. The voltage dependence of the learning rule drives coactive synapses to engage dendritic nonlinearities, whereas spike-timing dependence shapes the time course of subthreshold potentials. Dendritic input-output relationships can therefore be flexibly tuned through synaptic plasticity, allowing optimal implementation of nonlinear functions by single neurons

Modelling gap junction-coupled networks of olfactory bulb mitral cells

Summary of Thesis: The olfactory bulb forms the first level of input integration for olfactory receptor neurons that receive stimuli from odorant molecules in the nose. The olfactory bulb is multi channel in nature, with each channel containing its own populations of mitral cells. These channels each handle the input from neurons expressing a single type of olfactory receptor protein tuned to a unique range of odorant structures. I have constructed a mitral cell gap-junction network model with morphologically accurate mitral cells to study the behaviour of mitral cells in a channel population. The passive parameters of each of the mitral cells were determined by fitting to in vitro recordings. Sodium and potassium channels were added to the mitral cells to give the ability to generate action potentials. Gap-junctions were placed in the apical dendrite tufts of the mitral cells and their conductance adjusted to give a coupling ratio between mitral cells consistent with experimental findings. Firing was induced with twenty current injections randomly located in the apical dendrite tuft of two of the mitral cells, mimicking the multiple inputs from the olfactory receptor neurons. A protocol was used to promote an initial asynchrony in firing which was transmitted across the gap-junctions to all six mitral cells. I found that the mitral cell population would overcome this asynchrony, rapidly tending to synchronous firing. Adding calcium and calcium dependent potassium channels to the mitral cells produced burst firing patterns that were different for each of the cells. The gap-junctions did not have enough influence to overcome the asynchrony of the different burst firing patterns. The addition of calcium concentration threshold dependant glutamate release and AMPA auto receptors to the apical dendrite tuft of each mitral cell allowed the burst firing to promote self propagating synchronised firing after an initial period of asynchrony