Homosynaptic plasticity induction causes heterosynaptic changes at the unstimulated neighbors in an induction pattern and location-specific manner.

Dendritic spines are highly dynamic structures whose structural and functional fluctuations depend on multiple factors. Changes in synaptic strength are not limited to synapses directly involved in specific activity patterns. Unstimulated clusters of neighboring spines in and around the site of stimulation can also undergo alterations in strength. Usually, when plasticity is induced at single dendritic spines with glutamate uncaging, neighboring spines do not show any significant structural fluctuations. Here, using two-photon imaging and glutamate uncaging at single dendritic spines of hippocampal pyramidal neurons, we show that structural modifications at unstimulated neighboring spines occur and are a function of the temporal pattern of the plasticity-inducing stimulus. Further, the relative location of the unstimulated neighbors within the local dendritic segment correlates with the extent of heterosynaptic plasticity that is observed. These findings indicate that naturalistic patterns of activity at single spines can shape plasticity at nearby clusters of synapses, and may play a role in priming local inputs for further modifications.

The temporal pattern of synaptic activation determines the longevity of structural plasticity at dendritic spines.

Learning is thought to involve physiological and structural changes at individual synapses. Synaptic plasticity has predominantly been studied using regular stimulation patterns, but neuronal activity in the brain normally follows a Poisson distribution. We used two-photon imaging and glutamate uncaging to investigate the structural plasticity of single dendritic spines using naturalistic activation patterns sampled from a Poisson distribution. We showed that naturalistic activation patterns elicit structural plasticity that is both NMDAR and protein synthesis-dependent. Furthermore, we uncovered that the longevity of structural plasticity is dependent on the temporal structure of the naturalistic pattern. Finally, we found that during the delivery of the naturalistic activity, spines underwent rapid structural growth that predicted the longevity of plasticity. This was not observed with regularly spaced activity. These data reveal that different temporal organizations of the same number of synaptic stimulations can produce rather distinct short and long-lasting structural plasticity.

An interactive time series image analysis software for dendritic spines.

Live fluorescence imaging has demonstrated the dynamic nature of dendritic spines, with changes in shape occurring both during development and in response to activity. The structure of a dendritic spine correlates with its functional efficacy. Learning and memory studies have shown that a great deal of the information stored by a neuron is contained in the synapses. High precision tracking of synaptic structures can give hints about the dynamic nature of memory and help us understand how memories evolve both in biological and artificial neural networks. Experiments that aim to investigate the dynamics behind the structural changes of dendritic spines require the collection and analysis of large time-series datasets. In this paper, we present an open-source software called SpineS for automatic longitudinal structural analysis of dendritic spines with additional features for manual intervention to ensure optimal analysis. We have tested the algorithm on in-vitro, in-vivo, and simulated datasets to demonstrate its performance in a wide range of possible experimental scenarios.

Pyramidal tract neurons drive amplification of excitatory inputs to striatum through cholinergic interneurons.

Corticostriatal connectivity is central for many cognitive and motor processes, such as reinforcement or action initiation and invigoration. The cortical input to the striatum arises from two main cortical populations: intratelencephalic (IT) and pyramidal tract (PT) neurons. We report a previously unknown excitatory circuit, supported by a polysynaptic motif from PT neurons to cholinergic interneurons (ChIs) to glutamate-releasing axons, which runs in parallel to the canonical monosynaptic corticostriatal connection. This motif conveys a delayed second phase of excitation to striatal spiny projection neurons, through an acetylcholine-dependent glutamate release mechanism mediated by α4-containing nicotinic receptors, resulting in biphasic corticostriatal signals. These biphasic signals are a hallmark of PT, but not IT, corticostriatal inputs, due to a stronger relative input from PT neurons to ChIs. These results describe a previously unidentified circuit mechanism by which PT activity amplifies excitatory inputs to the striatum, with potential implications for behavior, plasticity, and learning.

Homeostatic Plasticity Scales Dendritic Spine Volumes and Changes the Threshold and Specificity of Hebbian Plasticity.

Information is encoded in neural networks through changes in synaptic weights. Synaptic learning rules involve a combination of rapid Hebbian plasticity and slower homeostatic synaptic plasticity that regulates neuronal activity through global synaptic scaling. Hebbian and homeostatic plasticity have been extensively investigated, whereas much less is known about their interaction. Here we investigated structural and functional consequences of homeostatic plasticity at dendritic spines of mouse hippocampal neurons. We found that prolonged activity blockade induced spine growth, paralleling synaptic strength increases. Following activity blockade, glutamate uncaging-mediated stimulation at single spines led to size-dependent structural potentiation: smaller spines underwent robust growth, whereas larger spines remained unchanged. Moreover, spines near the stimulated spine exhibited volume changes following homeostatic plasticity, indicating that there was a breakdown of input specificity following homeostatic plasticity. Overall, these findings demonstrate that Hebbian and homeostatic plasticity interact to shape neural connectivity through non-uniform structural plasticity at inputs.

Tracking-assisted Detection of Dendritic Spines in Time-Lapse Microscopic Images.

Detecting morphological changes of dendritic spines in time-lapse microscopy images and correlating them with functional properties such as memory and learning, are fundamental and challenging problems in neurobiology research. In this paper, we propose an algorithm for dendritic spine detection in time series. The proposed approach initially performs spine detection at each time point and improves the accuracy by exploiting the information obtained from tracking of individual spines over time. To detect dendritic spines in a time point image we employ an SVM classifier trained by pre-labeled SIFT feature descriptors in combination with a dot enhancement filter. Second, to track the growth or loss of spines, we apply a SIFT-based rigid registration method for the alignment of time-series images. This step takes into account both the structure and the movement of objects, combined with a robust dynamic scheme to link information about spines that disappear and reappear over time. Next, we improve spine detection by employing a probabilistic dynamic programming approach to search for an optimum solution to accurately detect missed spines. Finally, we determine the spine location more precisely by performing a watershed-geodesic active contour model. We quantitatively assess the performance of the proposed spine detection algorithm based on annotations performed by biologists and compare its performance with the results obtained by the noncommercial software NeuronIQ. Experiments show that our approach can accurately detect and quantify spines in 2-photon microscopy time-lapse data and is able to accurately identify spine elimination and formation.

Dendritic spine classification using shape and appearance features based on two-photon microscopy.

BACKGROUND: Neuronal morphology and function are highly coupled. In particular, dendritic spine morphology is strongly governed by the incoming neuronal activity. The first step towards understanding the structure-function relationships is to classify spine shapes into the main spine types suggested in the literature. Due to the lack of reliable automated analysis tools, classification is mostly performed manually, which is a time-intensive task and prone to subjectivity. NEW METHOD: We propose an automated method to classify dendritic spines using shape and appearance features based on challenging two-photon laser scanning microscopy (2PLSM) data. Disjunctive Normal Shape Models (DNSM) is a recently proposed parametric shape representation. We perform segmentation of spine images by applying DNSM and use the resulting representation as shape features. Furthermore, we use Histogram of oriented gradients (HOG) to extract appearance features. In this context, we propose a kernel density estimation (KDE) based framework for dendritic spine classification, which uses these shape and appearance features. RESULTS: Our shape and appearance features based approach combined with Neural Network (NN) correctly classifies 87.06% of spines on a dataset of 456 spines. COMPARISON WITH EXISTING METHODS: Our proposed method outperforms standard morphological feature based approaches. Our KDE based framework also enables neuroscientists to analyze the separability of spine shape classes in the likelihood ratio space, which leads to further insights about nature of the spine shape analysis problem. CONCLUSIONS: Results validate that performance of our proposed approach is comparable to a human expert. It also enable neuroscientists to study shape statistics in the likelihood ratio space.

Synaptic competition in structural plasticity and cognitive function.

Connections between neurons can undergo long-lasting changes in synaptic strength correlating with changes in structure. These events require the synthesis of new proteins, the availability of which can lead to cooperative and competitive interactions between synapses for the expression of plasticity. These processes can occur over limited spatial distances and temporal periods, defining dendritic regions over which activity may be integrated and could lead to the physical rewiring of synapses into functional groups. Such clustering of inputs may increase the computational power of neurons by allowing information to be combined in a greater than additive manner. The availability of new proteins may be a key modulatory step towards activity-dependent, long-term growth or elimination of spines necessary for remodelling of connections. Thus, the aberrant growth or shrinkage of dendritic spines could occur if protein levels are misregulated. Indeed, such perturbations can be seen in several mental retardation disorders, wherein either too much or too little protein translation exists, matching an observed increase or decrease in spine density, respectively. Cellular events which alter protein availability could relieve a constraint on synaptic competition and disturb synaptic clustering mechanisms. These changes may be detrimental to modifications in neural circuitry following activity.

Long lasting protein synthesis- and activity-dependent spine shrinkage and elimination after synaptic depression.

Neuronal circuits modify their response to synaptic inputs in an experience-dependent fashion. Increases in synaptic weights are accompanied by structural modifications, and activity dependent, long lasting growth of dendritic spines requires new protein synthesis. When multiple spines are potentiated within a dendritic domain, they show dynamic structural plasticity changes, indicating that spines can undergo bidirectional physical modifications. However, it is unclear whether protein synthesis dependent synaptic depression leads to long lasting structural changes. Here, we investigate the structural correlates of protein synthesis dependent long-term depression (LTD) mediated by metabotropic glutamate receptors (mGluRs) through two-photon imaging of dendritic spines on hippocampal pyramidal neurons. We find that induction of mGluR-LTD leads to robust and long lasting spine shrinkage and elimination that lasts for up to 24 hours. These effects depend on signaling through group I mGluRs, require protein synthesis, and activity. These data reveal a mechanism for long lasting remodeling of synaptic inputs, and offer potential insights into mental retardation.

The dendritic branch is the preferred integrative unit for protein synthesis-dependent LTP.

The late-phase of long-term potentiation (L-LTP), the cellular correlate of long-term memory, induced at some synapses facilitates L-LTP expression at other synapses receiving stimulation too weak to induce L-LTP by itself. Using glutamate uncaging and two-photon imaging, we demonstrate that the efficacy of this facilitation decreases with increasing time between stimulations, increasing distance between stimulated spines and with the spines being on different dendritic branches. Paradoxically, stimulated spines compete for L-LTP expression if stimulated too closely together in time. Furthermore, the facilitation is temporally bidirectional but asymmetric. Additionally, L-LTP formation is itself biased toward occurring on spines within a branch. These data support the Clustered Plasticity Hypothesis, which states that such spatial and temporal limits lead to stable engram formation, preferentially at synapses clustered within dendritic branches rather than dispersed throughout the dendritic arbor. Thus, dendritic branches rather than individual synapses are the primary functional units for long-term memory storage.

Delta-catenin regulates spine and synapse morphogenesis and function in hippocampal neurons during development.

The maintenance of spine and synapse number during development is critical for neuronal circuit formation and function. Here we show that delta-catenin, a component of the cadherin-catenin cell adhesion complex, regulates spine and synapse morphogenesis during development. Genetic ablation or acute knockdown of delta-catenin leads to increases in spine and synapse density, accompanied by a decrease in tetrodotoxin induced spine plasticity. Our results indicate that delta-catenin may mediate conversion of activity-dependent signals to morphological spine plasticity. The functional role of delta-catenin in regulating spine density does not require binding to cadherins, but does require interactions with PDZ domain-containing proteins. We propose that the perturbations in spine and synaptic structure and function observed after depletion of delta-catenin during development may contribute to functional alterations in neural circuitry, the cognitive deficits observed in mutant mice, and the mental retardation pathology of Cri-du-chat syndrome.

Erbin controls dendritic morphogenesis by regulating localization of delta-catenin.

The LAP [leucine-rich and postsynaptic density-95/Discs large/zona occludens-1 (PDZ)] protein erbin and delta-catenin, a component of the cadherin-catenin cell adhesion complex, are highly expressed in neurons and associate through PDZ-mediated interaction, but have incompletely characterized neuronal functions. We show that short hairpin RNA-mediated knockdown of erbin and knockdown or genetic ablation of delta-catenin severely impaired dendritic morphogenesis in hippocampal neurons. Simultaneous loss of erbin and delta-catenin does not enhance severity of this phenotype. The dendritic phenotype observed after erbin depletion is rescued by overexpression of delta-catenin and requires a domain in delta-catenin that has been shown to regulate dendritic branching. Knockdown of delta-catenin cannot be rescued by overexpression of erbin, indicating that erbin is upstream of delta-catenin. delta-Catenin-null neurons have no alterations in global levels of active Rac1/RhoA. Knockdown of erbin results in alterations in localization of delta-catenin. These results suggest a critical role for erbin in regulating dendritic morphogenesis by maintaining appropriate localization of delta-catenin.

Delta-catenin at the synaptic-adherens junction.

Delta-catenin belongs to the p120-catenin (p120(ctn)) protein family, which is characterized by ten, characteristically spaced Armadillo repeats that bind to the juxtamembrane segment of the classical cadherins. Delta-catenin is the only member of this family that is expressed specifically in neurons, where it binds to PDZ domain proteins in the post-synaptic compartment. As a component of both adherens and synaptic junctions, delta-catenin can link the adherens junction to the synapse and, thereby, coordinate synaptic input with changes in the adherens junction. By virtue of its restriction to the post-synaptic area, delta-catenin creates an asymmetric adherens junction in the region of the synapse. The crucial nature of the specialized function of delta-catenin in neurons is demonstrated by a targeted gene mutation, which causes deficits in learning and in synaptic plasticity. Taken together, recent evidence indicates that delta-catenin is a sensor of synaptic activity and implements activity-related morphological changes at the synapse.

Deletion of the neuron-specific protein delta-catenin leads to severe cognitive and synaptic dysfunction.

Delta-catenin (delta-catenin) is a neuron-specific catenin, which has been implicated in adhesion and dendritic branching. Moreover, deletions of delta-catenin correlate with the severity of mental retardation in Cri-du-Chat syndrome (CDCS), which may account for 1% of all mentally retarded individuals. Interestingly, delta-catenin was first identified through its interaction with Presenilin-1 (PS1), the molecule most frequently mutated in familial Alzheimer's Disease (FAD). We investigated whether deletion of delta-catenin would be sufficient to cause cognitive dysfunction by generating mice with a targeted mutation of the delta-catenin gene (delta-cat(-/-)). We observed that delta-cat(-/-) animals are viable and have severe impairments in cognitive function. Furthermore, mutant mice display a range of abnormalities in hippocampal short-term and long-term synaptic plasticity. Also, N-cadherin and PSD-95, two proteins that interact with delta-catenin, are significantly reduced in mutant mice. These deficits are severe but specific because delta-cat(-/-) mice display a variety of normal behaviors, exhibit normal baseline synaptic transmission, and have normal levels of the synaptic adherens proteins E-cadherin and beta-catenin. These data reveal a critical role for delta-catenin in brain function and may have important implications for understanding mental retardation syndromes such as Cri-du-Chat and neurodegenerative disorders, such as Alzheimer's disease, that are characterized by cognitive decline.