by Keyword: Neuroscience

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Palmisano, I., Danzi, M. C., Hutson, T. H., Zhou, L., McLachlan, E., Serger, E., Shkura, K., Srivastava, P. K., Hervera, A., Neill, N. O., Liu, T., Dhrif, H., Wang, Z., Kubat, M., Wuchty, S., Merkenschlager, M., Levi, L., Elliott, E., Bixby, J. L., Lemmon, V. P., Di Giovanni, S., (2019). Epigenomic signatures underpin the axonal regenerative ability of dorsal root ganglia sensory neurons Nature Neuroscience 22, (11), 1913-1924

Axonal injury results in regenerative success or failure, depending on whether the axon lies in the peripheral or the CNS, respectively. The present study addresses whether epigenetic signatures in dorsal root ganglia discriminate between regenerative and non-regenerative axonal injury. Chromatin immunoprecipitation for the histone 3 (H3) post-translational modifications H3K9ac, H3K27ac and H3K27me3; an assay for transposase-accessible chromatin; and RNA sequencing were performed in dorsal root ganglia after sciatic nerve or dorsal column axotomy. Distinct histone acetylation and chromatin accessibility signatures correlated with gene expression after peripheral, but not central, axonal injury. DNA-footprinting analyses revealed new transcriptional regulators associated with regenerative ability. Machine-learning algorithms inferred the direction of most of the gene expression changes. Neuronal conditional deletion of the chromatin remodeler CCCTC-binding factor impaired nerve regeneration, implicating chromatin organization in the regenerative competence. Altogether, the present study offers the first epigenomic map providing insight into the transcriptional response to injury and the differential regenerative ability of sensory neurons.

Keywords: Cell biology, Computational biology and bioinformatics, Molecular biology, Neuroscience

Gil, V., Del Río, J. A., (2019). Generation of 3-d collagen-based hydrogels to analyze axonal growth and behavior during nervous system development Journal of Visualized Experiments , (148), e59481

This protocol uses natural type I collagen to generate three-dimensional (3-D) hydrogel for monitoring and analyzing the axonal growth. The protocol is centered on culturing small pieces of embryonic or early postnatal rodent brains inside a 3-D hydrogel formed by the rat tail tendon-derived type I collagen with specific porosity. Tissue pieces are cultured inside the hydrogel and confronted to specific brain fragments or genetically-modified cell aggregates to produce and secrete molecules suitable for creating a gradient inside the porous matrix. The steps of this protocol are simple and reproducible but include critical steps to be considered carefully during its development. Moreover, the behavior of growing axons can be monitored and analyzed directly using a phase-contrast microscope or mono/multiphoton fluorescence microscope after fixation by immunocytochemical methods.

Keywords: 3-D hydrogel cultures, Axonal growth, Cell transfection, Chemoattraction, Chemorepulsion, Embryonic nervous system, Issue 148, Neuroscience, Tissue explants

Arsiwalla, Xerxes D., Verschure, Paul, (2018). Measuring the complexity of consciousness Frontiers in Neuroscience 12, (424), Article 424

The grand quest for a scientific understanding of consciousness has given rise to many new theoretical and empirical paradigms for investigating the phenomenology of consciousness as well as clinical disorders associated to it. A major challenge in this field is to formalize computational measures that can reliably quantify global brain states from data. In particular, information-theoretic complexity measures such as integrated information have been proposed as measures of conscious awareness. This suggests a new framework to quantitatively classify states of consciousness. However, it has proven increasingly difficult to apply these complexity measures to realistic brain networks. In part, this is due to high computational costs incurred when implementing these measures on realistically large network dimensions. Nonetheless, complexity measures for quantifying states of consciousness are important for assisting clinical diagnosis and therapy. This article is meant to serve as a lookup table of measures of consciousness, with particular emphasis on clinical applicability. We consider both, principle-based complexity measures as well as empirical measures tested on patients. We address challenges facing these measures with regard to realistic brain networks, and where necessary, suggest possible resolutions. We address challenges facing these measures with regard to realistic brain networks, and where necessary, suggest possible resolutions.

Keywords: Consciousness in the Clinic, Computational neuroscience, Complexity measures, Clinical Neuroscience, Measures of consciousness

Arsiwalla, X. D., Pacheco, D., Principe, A., Rocamora, R., Verschure, P., (2018). A temporal estimate of integrated information for intracranial functional connectivity Artificial Neural Networks and Machine Learning (Lecture Notes in Computer Science) 27th International Conference on Artificial Neural Networks (ICANN 2018) , Springer, Cham (Rhodes, Greece) 11140, 403-412

A major challenge in computational and systems neuroscience concerns the quantification of information processing at various scales of the brain’s anatomy. In particular, using human intracranial recordings, the question we ask in this paper is: How can we estimate the informational complexity of the brain given the complex temporal nature of its dynamics? To address this we work with a recent formulation of network integrated information that is based on the Kullback-Leibler divergence between the multivariate distribution on the set of network states versus the corresponding factorized distribution over its parts. In this work, we extend this formulation for temporal networks and then apply it to human brain data obtained from intracranial recordings in epilepsy patients. Our findings show that compared to random re-wirings of the data, functional connectivity networks, constructed from human brain data, score consistently higher in the above measure of integrated information. This work suggests that temporal integrated information may indeed be a good starting point as a future measure of cognitive complexity.

Keywords: Brain networks, Complexity measures, Computational neuroscience, Functional connectivity

Marco, S., Gutiérrez-Gálvez, A., Lansner, A., Martinez, D., Rospars, J. P., Beccherelli, R., Perera, A., Pearce, T., Vershure, P., Persaud, K., (2013). Biologically inspired large scale chemical sensor arrays and embedded data processing Proceedings of SPIE - The International Society for Optical Engineering Smart Sensors, Actuators, and MEMS VI , SPIE Digital Library (Grenoble, France) 8763, 1-15

Biological olfaction outperforms chemical instrumentation in specificity, response time, detection limit, coding capacity, time stability, robustness, size, power consumption, and portability. This biological function provides outstanding performance due, to a large extent, to the unique architecture of the olfactory pathway, which combines a high degree of redundancy, an efficient combinatorial coding along with unmatched chemical information processing mechanisms. The last decade has witnessed important advances in the understanding of the computational primitives underlying the functioning of the olfactory system. EU Funded Project NEUROCHEM (Bio-ICT-FET- 216916) has developed novel computing paradigms and biologically motivated artefacts for chemical sensing taking inspiration from the biological olfactory pathway. To demonstrate this approach, a biomimetic demonstrator has been built featuring a large scale sensor array (65K elements) in conducting polymer technology mimicking the olfactory receptor neuron layer, and abstracted biomimetic algorithms have been implemented in an embedded system that interfaces the chemical sensors. The embedded system integrates computational models of the main anatomic building blocks in the olfactory pathway: The olfactory bulb, and olfactory cortex in vertebrates (alternatively, antennal lobe and mushroom bodies in the insect). For implementation in the embedded processor an abstraction phase has been carried out in which their processing capabilities are captured by algorithmic solutions. Finally, the algorithmic models are tested with an odour robot with navigation capabilities in mixed chemical plumes.

Keywords: Antennal lobes, Artificial olfaction, Computational neuroscience, Olfactory bulbs, Plume tracking, Abstracting, Actuators, Algorithms, Biomimetic processes, Chemical sensors, Conducting polymers, Data processing, Flavors, Odors, Robots, Smart sensors, Embedded systems

Gil, V., Del Río, J. A., (2012). Analysis of axonal growth and cell migration in 3D hydrogel cultures of embryonic mouse CNS tissue Nature Protocols 7, (2), 268-280

This protocol uses rat tail-derived type I collagen hydrogels to analyze key processes in developmental neurobiology, such as chemorepulsion and chemoattraction. The method is based on culturing small pieces of brain tissue from embryonic or early perinatal mice inside a 3D hydrogel formed by rat tail-derived type I collagen or, alternatively, by commercial Matrigel. The neural tissue is placed in the hydrogel with other brain tissue pieces or cell aggregates genetically modified to secrete a particular molecule that can generate a gradient inside the hydrogel. The present method is uncomplicated and generally reproducible, and only a few specific details need to be considered during its preparation. Moreover, the degree and behavior of axonal growth or neural migration can be observed directly using phase-contrast, fluorescence microscopy or immunocytochemical methods. This protocol can be carried out in 4 weeks.

Keywords: Cell biology, Cell culture, Developmental biology, Imaging, Model organisms, Neuroscience, Tissue culture