Reconstruction of recurrent synaptic connectivity of thousands of neurons from simulated spiking activity

Dynamics and function of neuronal networks are determined by their synaptic connectivity. Current experimental methods to analyze synaptic network structure on the cellular level, however, cover only small fractions of functional neuronal circuits, typically without a simultaneous record of neuronal spiking activity. Here we present a method for the reconstruction of large recurrent neuronal networks from thousands of parallel spike train recordings. We employ maximum likelihood estimation of a generalized linear model of the spiking activity in continuous time. For this model the point process likelihood is concave, such that a global optimum of the parameters can be obtained by gradient ascent. Previous methods, including those of the same class, did not allow recurrent networks of that order of magnitude to be reconstructed due to prohibitive computational cost and numerical instabilities. We describe a minimal model that is optimized for large networks and an efficient scheme for its parallelized numerical optimization on generic computing clusters. For a simulated balanced random network of 1000 neurons, synaptic connectivity is recovered with a misclassification error rate of less than 1% under ideal conditions. We show that the error rate remains low in a series of example cases under progressively less ideal conditions. Finally, we successfully reconstruct the connectivity of a hidden synfire chain that is embedded in a random network, which requires clustering of the network connectivity to reveal the synfire groups. Our results demonstrate how synaptic connectivity could potentially be inferred from large-scale parallel spike train recordings.Comment: This is the final version of the manuscript from the publisher which supersedes our original pre-print version. The spike data used in this paper and the code that implements our connectivity reconstruction method are publicly available for download at http://dx.doi.org/10.5281/zenodo.17662 and http://dx.doi.org/10.5281/zenodo.17663 respectivel

Neural system prediction and identification challenge

Can we infer the function of a biological neural network (BNN) if we know the connectivity and activity of all its constituent neurons? This question is at the core of neuroscience and, accordingly, various methods have been developed to record the activity and connectivity of as many neurons as possible. Surprisingly, there is no theoretical or computational demonstration that neuronal activity and connectivity are indeed sufficient to infer the function of a BNN. Therefore, we pose the Neural Systems Identification and Prediction Challenge (nuSPIC). We provide the connectivity and activity of all neurons and invite participants (1) to infer the functions implemented (hard-wired) in spiking neural networks (SNNs) by stimulating and recording the activity of neurons and, (2) to implement predefined mathematical/biological functions using SNNs. The nuSPICs can be accessed via a web-interface to the NEST simulator and the user is not required to know any specific programming language. Furthermore, the nuSPICs can be used as a teaching tool. Finally, nuSPICs use the crowd-sourcing model to address scientific issues. With this computational approach we aim to identify which functions can be inferred by systematic recordings of neuronal activity and connectivity. In addition, nuSPICs will help the design and application of new experimental paradigms based on the structure of the SNN and the presumed function which is to be discovered

Increasing quality and managing complexity in neuroinformatics software development with continuous integration

High quality neuroscience research requires accurate, reliable and well maintained neuroinformatics applications. As software projects become larger, offering more functionality and developing a denser web of interdependence between their component parts, we need more sophisticated methods to manage their complexity. If complexity is allowed to get out of hand, either the quality of the software or the speed of development suffer, and in many cases both. To address this issue, here we develop a scalable, low-cost and open source solution for continuous integration (CI), a technique which ensures the quality of changes to the code base during the development procedure, rather than relying on a pre-release integration phase. We demonstrate that a CI based workflow, due to rapid feedback about code integration problems and tracking of code health measures, enabled substantial increases in productivity for a major neuroinformatics project and additional benefits for three further projects. Beyond the scope of the current study, we identify multiple areas in which CI can be employed to further increase the quality of neuroinformatics projects by improving development practices and incorporating appropriate development tools. Finally, we discuss what measures can be taken to lower the barrier for developers of neuroinformatics applications to adopt this useful technique

Выраженность уровневой агрессивности в эмоциональной сфере юных спортсменов-игровиков 13-15 лет

The article presents the results of studying the relationship between the levels of aggressiveness and the emotional state of young athletes playing at the age of 13-15 years. For taking corrective measures aimed at improving psycho-emotional conditions of athletes it is necessary to create the information database as regards the emotional sphere of these players. Research objective was to study the extent of aggression level in the emotional sphere of young athletes playing at the age of 13-15 years. 90 young athletes at the age of 13-15 years playing sport games have been interviewed. To identify the emotional state of the experiment participants, the presence of aggressiveness, its direction and intensity, special psychological testing has been carried out using projective methods called “Non-existent animal” and “Cactus”. Standardization of the results has been carried out on the basis of the data analysis presented in descriptive form. At preliminary investigation phase there were established the following levels of aggression: excessive, high, average and low. Further the expressiveness of level aggression in the emotional sphere of athletes was defined and analyzed. As a result of the conducted research the following conclusions are drawn: 1. Level of aggressiveness of young players 13-15 years old is not determinative for their emotional sphere. On the emotional background, young athletes, regardless of their belonging to different levels of aggressiveness, are prone to aggression. 2. The emotional sphere is significantly affected by the clash of contradictory in their essence and simultaneous emotional states that cause various forms of behavioral reactions of young players 13-15 years oldВ статье представлены результаты взаимосвязи уровней агрессивности и состояния эмоциональной сферы спортсменов-игровиков в возрасте 13-15 лет. Для применения мер по коррекции психоэмоциональных состояний спортсменов необходимо располагать информационной базой данных об эмоциональной сфере этих игроков. Целью исследования явилось обоснование выраженности уровневой агрессивности в эмоциональной сфере юных спортсменов-игровиков. В исследовании приняло участие 90 спортсменов в возрасте 13-15 лет, занимающихся игровыми видами спорта. Для выявления состояния эмоциональной сферы участников эксперимента, наличия агрессивности, ее направления и интенсивности было проведено психологическое тестирование по проективным методикам: «Несуществующее животное» и «Кактус». Стандартизация результатов осуществлялась на основе анализа данных, представленных в описательной форме. На предварительном этапе исследования установлены испытуемые с определенным уровнем агрессивности: повышенным, высоким, средним и низким. Далее определялась и анализировалась выраженность уровневой агрессивности в эмоциональной сфере спортсменов. В результате проведенного исследования сделаны следующие выводы: 1. Уровневая агрессивность игроков 13-15 лет не является определяющей в их эмоциональной сфере. На эмоциональном фоне юные спортсмены, вне зависимости от их принадлежности к различным уровням агрессивности, склонны к проявлению агрессии. 2. На эмоциональную сферу оказывает существенное влияние столкновение противоречивых по своей сути одномоментно возникающих состояний, которые вызывают различные формы поведенческих реакций игроков 13-15 ле

Terahertz biophotonics as a tool for studies of dielectric and spectral properties of biological tissues and liquids

In this review, we describe dielectric properties of biological tissues and liquids in the context of terahertz (THz) biophotonics. We discuss a model of the THz dielectric permittivity of water and water-containing media, which yields analysis of the relaxation and damped resonant molecules modes. We briefly describe modern techniques of THz spectroscopy and imaging employed in biophotonics with a strong emphasize on a THz time-domain spectroscopy. Furthermore, we consider the methods of sub-wavelength resolution THz imaging and the problem of THz wave delivery to hard to access tissues and internal organs. We consider the THz dielectric properties of biological solutions and liquids. Although strong absorption by water molecules prevents THz-waves from penetration of hydrated tissues and probing biological molecules in aqueous solutions, we discuss approaches for overcoming these drawbacks – novel techniques of freezing and temporal dehydration by application of hyperosmotic agents which have a potential for cancer detection. We review recent applications of THz technology in diagnosis of malignancies and aiding histology paying particular attention to the origin of contrast observed between healthy and pathological tissues. We consider recent applications of THz reflectometry in sensing the thinning dynamics of human pre-corneal tear film. Modern modalities of THz imaging, which relies on the concepts of multi-spectral and multi-temporal domains and employing the principles of color vision, phase analysis and tomography are discussed. Novel methods of THz spectra analysis based on machine learning, pattern recognition, chemical imaging and the revealing of the spatial distribution of various substances in a tissue, are analyzed. Advanced thermal model describing biological object irradiated by THz waves and phantoms mimicking the optical properties of tissues at THz frequencies are presented. Finally, application of the high-resolution THz spectroscopy in analytic chemistry, biology and medicine are described

Terahertz biophotonics as a tool for studies of dielectric and spectral properties of biological tissues and liquids

In this review, we describe dielectric properties of biological tissues and liquids in the context of terahertz (THz) biophotonics. We discuss a model of the THz dielectric permittivity of water and water-containing media, which yields analysis of the relaxation and damped resonant molecules modes. We briefly describe modern techniques of THz spectroscopy and imaging employed in biophotonics with a strong emphasize on a THz time-domain spectroscopy. Furthermore, we consider the methods of sub-wavelength resolution THz imaging and the problem of THz wave delivery to hard to access tissues and internal organs. We consider the THz dielectric properties of biological solutions and liquids. Although strong absorption by water molecules prevents THz-waves from penetration of hydrated tissues and probing biological molecules in aqueous solutions, we discuss approaches for overcoming these drawbacks – novel techniques of freezing and temporal dehydration by application of hyperosmotic agents which have a potential for cancer detection. We review recent applications of THz technology in diagnosis of malignancies and aiding histology paying particular attention to the origin of contrast observed between healthy and pathological tissues. We consider recent applications of THz reflectometry in sensing the thinning dynamics of human pre-corneal tear film. Modern modalities of THz imaging, which relies on the concepts of multi-spectral and multi-temporal domains and employing the principles of color vision, phase analysis and tomography are discussed. Novel methods of THz spectra analysis based on machine learning, pattern recognition, chemical imaging and the revealing of the spatial distribution of various substances in a tissue, are analyzed. Advanced thermal model describing biological object irradiated by THz waves and phantoms mimicking the optical properties of tissues at THz frequencies are presented. Finally, application of the high-resolution THz spectroscopy in analytic chemistry, biology and medicine are described