Image informatics strategies for deciphering neuronal network connectivity

Brain function relies on an intricate network of highly dynamic neuronal connections that rewires dramatically under the impulse of various external cues and pathological conditions. Among the neuronal structures that show morphologi- cal plasticity are neurites, synapses, dendritic spines and even nuclei. This structural remodelling is directly connected with functional changes such as intercellular com- munication and the associated calcium-bursting behaviour. In vitro cultured neu- ronal networks are valuable models for studying these morpho-functional changes. Owing to the automation and standardisation of both image acquisition and image analysis, it has become possible to extract statistically relevant readout from such networks. Here, we focus on the current state-of-the-art in image informatics that enables quantitative microscopic interrogation of neuronal networks. We describe the major correlates of neuronal connectivity and present workflows for analysing them. Finally, we provide an outlook on the challenges that remain to be addressed, and discuss how imaging algorithms can be extended beyond in vitro imaging studies

Dendritic Spine Shape Analysis: A Clustering Perspective

Functional properties of neurons are strongly coupled with their morphology. Changes in neuronal activity alter morphological characteristics of dendritic spines. First step towards understanding the structure-function relationship is to group spines into main spine classes reported in the literature. Shape analysis of dendritic spines can help neuroscientists understand the underlying relationships. Due to unavailability of reliable automated tools, this analysis is currently performed manually which is a time-intensive and subjective task. Several studies on spine shape classification have been reported in the literature, however, there is an on-going debate on whether distinct spine shape classes exist or whether spines should be modeled through a continuum of shape variations. Another challenge is the subjectivity and bias that is introduced due to the supervised nature of classification approaches. In this paper, we aim to address these issues by presenting a clustering perspective. In this context, clustering may serve both confirmation of known patterns and discovery of new ones. We perform cluster analysis on two-photon microscopic images of spines using morphological, shape, and appearance based features and gain insights into the spine shape analysis problem. We use histogram of oriented gradients (HOG), disjunctive normal shape models (DNSM), morphological features, and intensity profile based features for cluster analysis. We use x-means to perform cluster analysis that selects the number of clusters automatically using the Bayesian information criterion (BIC). For all features, this analysis produces 4 clusters and we observe the formation of at least one cluster consisting of spines which are difficult to be assigned to a known class. This observation supports the argument of intermediate shape types.Comment: Accepted for BioImageComputing workshop at ECCV 201

Dendritic spine shape classification from two-photon microscopy images (Dendritik diken şekillerinin iki foton mikroskopi görüntüleri kullanılarak sınıflandırılması)

Functional properties of a neuron are coupled with its morphology, particularly the morphology of dendritic spines. Spine volume has been used as the primary morphological parameter in order the characterize the structure and function coupling. However, this reductionist approach neglects the rich shape repertoire of dendritic spines. First step to incorporate spine shape information into functional coupling is classifying main spine shapes that were proposed in the literature. Due to the lack of reliable and fully automatic tools to analyze the morphology of the spines, such analysis is often performed manually, which is a laborious and time intensive task and prone to subjectivity. In this paper we present an automated approach to extract features using basic image processing techniques, and classify spines into mushroom or stubby by applying machine learning algorithms. Out of 50 manually segmented mushroom and stubby spines, Support Vector Machine was able to classify 98% of the spines correctly

Computational Approach to Dendritic Spine Taxonomy and Shape Transition Analysis

The common approach in morphological analysis of dendritic spines of mammalian neuronal cells is to categorize spines into subpopulations based on whether they are stubby, mushroom, thin, or filopodia shaped. The corresponding cellular models of synaptic plasticity, long-term potentiation, and long-term depression associate the synaptic strength with either spine enlargement or spine shrinkage. Although a variety of automatic spine segmentation and feature extraction methods were developed recently, no approaches allowing for an automatic and unbiased distinction between dendritic spine subpopulations and detailed computational models of spine behavior exist. We propose an automatic and statistically based method for the unsupervised construction of spine shape taxonomy based on arbitrary features. The taxonomy is then utilized in the newly introduced computational model of behavior, which relies on transitions between shapes. Models of different populations are compared using supplied bootstrap-based statistical tests. We compared two populations of spines at two time points. The first population was stimulated with long-term potentiation, and the other in the resting state was used as a control. The comparison of shape transition characteristics allowed us to identify the differences between population behaviors. Although some extreme changes were observed in the stimulated population, statistically significant differences were found only when whole models were compared. The source code of our software is freely available for non-commercial use1

Mapping Synaptic Pathology within Cerebral Cortical Circuits in Subjects with Schizophrenia

Converging lines of evidence indicate that schizophrenia is characterized by impairments of synaptic machinery within cerebral cortical circuits. Efforts to localize these alterations in brain tissue from subjects with schizophrenia have frequently been limited to the quantification of structures that are non-selectively identified (e.g., dendritic spines labeled in Golgi preparations, axon boutons labeled with synaptophysin), or to quantification of proteins using methods unable to resolve relevant cellular compartments. Multiple label fluorescence confocal microscopy represents a means to circumvent many of these limitations, by concurrently extracting information regarding the number, morphology, and relative protein content of synaptic structures. An important adaptation required for studies of human disease is coupling this approach to stereologic methods for systematic random sampling of relevant brain regions. In this review article we consider the application of multiple label fluorescence confocal microscopy to the mapping of synaptic alterations in subjects with schizophrenia and describe the application of a novel, readily automated, iterative intensity/morphological segmentation algorithm for the extraction of information regarding synaptic structure number, size, and relative protein level from tissue sections obtained using unbiased stereological principles of sampling. In this context, we provide examples of the examination of pre- and post-synaptic structures within excitatory and inhibitory circuits of the cerebral cortex

Serotonin 5-HT4 receptor boosts functional maturation of dendritic spines via RhoA-dependent control of F-actin

Activity-dependent remodeling of excitatory connections underpins memory formation in the brain. Serotonin receptors are known to contribute to such remodeling, yet the underlying molecular machinery remains poorly understood. Here, we employ high-resolution time-lapse FRET imaging in neuroblastoma cells and neuronal dendrites to establish that activation of serotonin receptor 5-HT4 (5-HT4R) rapidly triggers spatially-restricted RhoA activity and G13-mediated phosphorylation of cofilin, thus locally boosting the filamentous actin fraction. In neuroblastoma cells, this leads to cell rounding and neurite retraction. In hippocampal neurons in situ, 5-HT4R-mediated RhoA activation triggers maturation of dendritic spines. This is paralleled by RhoA-dependent, transient alterations in cell excitability, as reflected by increased spontaneous synaptic activity, apparent shunting of evoked synaptic responses, and enhanced long-term potentiation of excitatory transmission. The 5-HT4R/G13/RhoA signaling thus emerges as a previously unrecognized molecular pathway underpinning use-dependent functional remodeling of excitatory synaptic connections

Hippocampal Dendritic Spines Modifications Induced by Perinatal Asphyxia

Perinatal asphyxia (PA) affects the synaptic function and morphological organization. In previous works, we have shown neuronal and synaptic changes in rat neostriatum subjected to hypoxia leading to long-term ubi-protein accumulation. Since F-actin is highly concentrated in dendritic spines, modifications in its organization could be related with alterations induced by hypoxia in the central nervous system (CNS). In the present study, we investigate the effects of PA on the actin cytoskeleton of hippocampal postsynaptic densities (PSD) in 4-month-old rats. PSD showed an increment in their thickness and in the level of ubiquitination. Correlative fluorescence-electron microscopy photooxidation showed a decrease in the number of F-actin-stained spines in hippocampal excitatory synapses subjected to PA. Although Western Blot analysis also showed a slight decrease in β-actin in PSD in PA animals, the difference was not significant. Taken together, this data suggests that long-term actin cytoskeleton might have role in PSD alterations which would be a spread phenomenon induced by PA

Morphological Correlates of Long-term Potentiation and Ageing in the Hippocampus of Rats

This thesis has examined age-dependent changes in neural plasticity in rat hippocampal dentate gyrus using unbiased morphological techniques at light and electron microscope level. It considers whether there is a morphological basis to explain why some aged animals sustain, whilst others fail to sustain, potentiation in the dentate gyrus of the hippocampus after unilateral induction of LTP, 45 minutes after stimulation of the perforant pathway. Previous data in young adult rats (5 months old) have demonstrated that the morphology of dendritic spines and synapses within the hippocampus is altered at 10-30 minutes, and 24 hrs following LTP induction. The data obtained in the present study suggest that differences in spine and synaptic morphological parameters appear to be correlated with the ability to maintain LTP in the aged rats. Those maintaining LTP had a tendency to longer spine length, and a decrease in spine and synaptic densities, there was a significant increase in the number of complex axospinous perforated synapses. Here, in young rats, LTP resulted in a significant increase in the density of spine synapses and total synaptic density. The mean spine density was also higher in the stimulated hemisphere, but spine length decreased. However, there was a significant increase in the number of bifurcating spines and axospinous perforated complex synapses in the stimulated compared to the contralateral control hemisphere. An age-dependent comparison indicated that spine density and synaptic densities are significantly higher in the younger rats, but spine length was significantly greater in the aged rats. LTP does not seem to cause morphological changes per se at the time examined post potentiation. However, an important finding of the present study is that the percentage of axospinous complex perforated synapses is significantly higher in the stimulated hemisphere of aged and young rats that sustained LTP compared to those that did not. The percentage of branched spines and simple axospinous perforated synapses is significantly higher in both the stimulated & unstimulated hemisphere of aged rats that failed to sustain LTP. Therefore a proportion of the branched spines and perforated synapses would appear to be the result of high frequency stimulation, rather than LTP induction per se