SENSEI brings together teams with expertise in signal and image processing (Research Center “E. Piaggio”, University of Pisa, Italy), basic neuroscience, live and super-resolution imaging analysis (INSERM126-IPNP, Imaging facility of the Center for Psychiatry and Neuroscience Paris, France) and development of new imaging modalities for high-content and super-resolution microscopy (Lab for Nanobiology, Department of Chemistry, University of Leuven, belgium), working in synergy for advancing breakthroughs in 3D neuronal segmentation and morphometrics.

Project Description and Objectives

Digitizing a complete and high-fidelity map of the neurons populating the mammalian brain, comprising spines and axons, is a central endeavour for neuroscience research. In fact, our ignorance of the brain micro-circuitry underpins the difficulty of deeply exploring the function of complex neural circuits and understanding fundamental (patho)physiological brain processes. While marked improvements in imaging tools (e.g., 3D microscopy techniques) and protocols (e.g., membrane probes and clarification protocols) have enabled the visualization of large brain volumes at cellular and sub-cellular resolution, the state of the art continues to be principally limited by the difficulties in neuron segmentation, which is still far from ground-truth. This is mainly due to the lack of image processing algorithms able to deal with 3D microscopic data acquired from different imaging modalities, representing specimen processed with different procedures and belonging to different animal species.

SENSEI’s objectives are to accurately quantify neuronal morphology at tissue and molecular levels through the development of intelligent segmentation-based image processing algorithms and to improve the quality of neuronal imaging using new membrane probes for conventional and emerging super-resolution imaging technologies. Specifically, we will develop an algorithm for isolating single neurons or smaller neuronal structures from 3D datasets representing the intricacies of the brain micro-structure. 

This project will study several mammalian species (including human) both in vitro for 2D (hippocampal, cortical neurons) and in situ for 3D (tissue slices and clarified brains) in cortex, cerebellum and hippocampus. New imaging modalities and segmentation protocols will be tested on human brain tissues coming from surgical resections. Samples will be imaged both with confocal microscopy, accounting for 80 % of user needs, and advanced imaging modalities, thus bringing either high resolution details on fixed dendritic spines (e.g., STED, STORM) or on live neurons (i.e. 3D SOFI). In addition to the sub-diffraction resolution, an optical device encoding probe information in the microscope point-spread function will be constructed, allowing the fast acquisition of cellular nanostructuring in full-3D. 

SENSEI aims at facilitating 3D reconstruction of neuronal morphology and circuitry, aiding neuro-anatomical mapping, and generating models which can be used for making predictions about higher-level brain organization. The detailed analyses of neurons might shed new light on the normal development of dendritic and axonal arbours and on how these processes are altered in neuro-pathologies.

The main objective of SENSEI is to deliver a comprehensive breakthrough solution for neuronal imaging and segmentation using a robust and accurate algorithm for reconstructing 3D neuronal morphology based on datasets acquired using advanced and emerging tools. 

This goal will be achieved by addressing the following specific objectives:

  • Testing of new membrane probes and improving image acquisition of neuronal cells in 2D cultures and in 3D tissues with conventional and super-resolution microscopy;
  • Developing a framework for the statistical characterization of microscopic images;
  • Improving fast imaging of live and fixed neurons using super-resolution 3D SOFI imaging;
  • Improving a neural segmentation algorithm based on statistical models of image noise and cell signal and testing it using samples from different neuronal cells, brain sites and animal species, from rodents up to humans;
  • Extending the algorithm for the application at different scales (super-resolution and live imaging);

SENSEI aspires to the HBP Flagship directives, which emphasize the importance of the development of tools for high-fidelity 3D reconstruction of the intricacies of the mammalian brains, through a collaborative, trans-disciplinary environment. 

SENSEI outcomes will provide a set of tools for accurately reconstructing brain micro-circuitry and for extracting quantitative morphometric information of neuron shape, size and complexity. The tools delivered in SENSEI could be used for monitoring neuronal morphological abnormalities associated with neuropathies and studying neuronal development, as well as for highlighting any differences with the human counterpart.

Another possible integration between HBP and SENSEI regards the study of human brain organization. In fact, SENSEI aims at developing tools and frameworks that can facilitate the data processing for mapping brain organization, and in particular human hippocampal complex, at the micro- and nano-scale.

SENSEI aims at providing 3D reconstructions of different neuron types in their 3D arrangement while preserving the neuron volumetric information. Future developments could regard, the enrichment of segmented neurons by SENSEI with the information about neuron orientation and position within the brain, aiding at building the Rodent and Human Atlases. Moreover, the volumetric information provided by our tool for single-cell isolation from 3D microscopic datasets will provide valuable inputs to the models developed in the Brain Simulation Platform, i.e. allowing the simulation of electrophysiological cell behaviour.