Publications

Regeneration after a peripheral nerve injury still remains a challenge, due to the limited regenerative potential of axons after injury. While the endocannabinoid system (ECS) has been widely studied for its neuroprotective and analgesic effects, its role in axonal regeneration and during the conditioning lesion remains unexplored. In this study, we observed that a peripheral nerve injury induces axonal regeneration through an increase in the endocannabinoid tone. We also enhanced the regenerative capacity of dorsal root ganglia (DRG) neurons through the inhibition of endocannabinoid degradative enzyme MAGL or a CB1R agonist. Our results suggest that the ECS, via CB1R and PI3K-pAkt pathway activation, plays an important role in promoting the intrinsic regenerative capacity of sensory neurons after injury.© 2023 The Author(s).

JTD Keywords: brain, gene-expression, lesion, nerve, receptors, targets, Clinical neuroscience, Drugs, Endogenous cannabinoid system, Molecular medicine

Drosophila is an amenable system for addressing the mechanics of morphogenesis. We describe a workflow for characterizing the mechanical properties of its ventral nerve cord (VNC), at different developmental stages, in live, flat dissected embryos employing atomic force microscopy (AFM). AFM is performed with spherical probes, and stiffness (Young's modulus) is calculated by fitting force curves with Hertz's contact model. For complete details on the use and execution of this protocol, please refer to Karkali et al. (2022).

JTD Keywords: atomic force microscopy (afm), developmental biology, model organisms, Animals, Atomic force microscopy, Atomic force microscopy (afm), Biology, Developmental biology, Drosophila, Elastic modulus, Microscopy, atomic force, Model organisms, Morphogenesis, Neurociencia, Neuroscience

The hippocampal formation displays a wide range of physiological responses to different spatial manipulations of the environment. However, very few attempts have been made to identify core computational principles underlying those hippocampal responses. Here, we capitalize on the observation that the entorhinal-hippocampal complex (EHC) forms a closed loop and projects inhibitory signals “countercurrent” to the trisynaptic pathway to build a self-supervised model that learns to reconstruct its own inputs by error backpropagation. The EHC is then abstracted as an autoencoder, with the hidden layers acting as an information bottleneck. With the inputs mimicking the firing activity of lateral and medial entorhinal cells, our model is shown to generate place cells and to respond to environmental manipulations as observed in rodent experiments. Altogether, we propose that the hippocampus builds conjunctive compressed representations of the environment by learning to reconstruct its own entorhinal inputs via gradient descent.

JTD Keywords: cognitive neuroscience, grid cells, long-term, networks, neural networks, novelty, oscillations, pattern separation, region, representation, working-memory, Cognitive neuroscience, Neural networks, Rat dentate gyrus, Systems neuroscience

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.

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

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.

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

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.

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

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.

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

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.

JTD 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

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.

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