Large-scale neural recordings have established that the transformation of sensory stimuli into motor outputs relies on low-dimensional dynamics at the population level, while individual neurons ...exhibit complex selectivity. Understanding how low-dimensional computations on mixed, distributed representations emerge from the structure of the recurrent connectivity and inputs to cortical networks is a major challenge. Here, we study a class of recurrent network models in which the connectivity is a sum of a random part and a minimal, low-dimensional structure. We show that, in such networks, the dynamics are low dimensional and can be directly inferred from connectivity using a geometrical approach. We exploit this understanding to determine minimal connectivity required to implement specific computations and find that the dynamical range and computational capacity quickly increase with the dimensionality of the connectivity structure. This framework produces testable experimental predictions for the relationship between connectivity, low-dimensional dynamics, and computational features of recorded neurons.
•We study network models characterized by minimal connectivity structures•For such models, low-dimensional dynamics can be directly inferred from connectivity•Computations emerge from distributed and mixed representations•Implementing specific tasks yields predictions linking connectivity and computations
Neural recordings show that cortical computations rely on low-dimensional dynamics over distributed representations. How are these generated by the underlying connectivity? Mastrogiuseppe et al. use a theoretical approach to infer low-dimensional dynamics and computations from connectivity and produce predictions linking connectivity and functional properties of neurons.
Molecular docking is a computational technique that predicts the binding affinity of ligands to receptor proteins. Although it has potential uses in nutraceutical research, it has developed into a ...formidable tool for drug development. Bioactive substances called nutraceuticals are present in food sources and can be used in the management of diseases. Finding their molecular targets can help in the creation of disease-specific new therapies. The purpose of this review was to explore molecular docking's application to the study of dietary supplements and disease management. First, an overview of the fundamentals of molecular docking and the various software tools available for docking was presented. The limitations and difficulties of using molecular docking in nutraceutical research are also covered, including the reliability of scoring functions and the requirement for experimental validation. Additionally, there was a focus on the identification of molecular targets for nutraceuticals in numerous disease models, including those for sickle cell disease, cancer, cardiovascular, gut, reproductive, and neurodegenerative disorders. We further highlighted biochemistry pathways and models from recent studies that have revealed molecular mechanisms to pinpoint new nutraceuticals' effects on disease pathogenesis. It is convincingly true that molecular docking is a useful tool for identifying the molecular targets of nutraceuticals in the management of diseases. It may offer information about how nutraceuticals work and support the creation of new therapeutics. Therefore, molecular docking has a bright future in nutraceutical research and has a lot of potentials to lead to the creation of brand-new medicines for the treatment of disease.
The Genetics of Epilepsy Perucca, Piero; Bahlo, Melanie; Berkovic, Samuel F
Annual review of genomics and human genetics,
08/2020, Letnik:
21, Številka:
1
Journal Article
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Odprti dostop
Epilepsy encompasses a group of heterogeneous brain diseases that affect more than 50 million people worldwide. Epilepsy may have discernible structural, infectious, metabolic, and immune etiologies; ...however, in most people with epilepsy, no obvious cause is identifiable. Based initially on family studies and later on advances in gene sequencing technologies and computational approaches, as well as the establishment of large collaborative initiatives, we now know that genetics plays a much greater role in epilepsy than was previously appreciated. Here, we review the progress in the field of epilepsy genetics and highlight molecular discoveries in the most important epilepsy groups, including those that have been long considered to have a nongenetic cause. We discuss where the field of epilepsy genetics is moving as it enters a new era in which the genetic architecture of common epilepsies is starting to be unraveled.
Here we report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved ...by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties and cellular resolution input-output mapping, integrated through cross-modal computational analysis. Our results advance the collective knowledge and understanding of brain cell-type organization
. First, our study reveals a unified molecular genetic landscape of cortical cell types that integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a consensus taxonomy of transcriptomic types and their hierarchical organization that is conserved from mouse to marmoset and human. Third, in situ single-cell transcriptomics provides a spatially resolved cell-type atlas of the motor cortex. Fourth, cross-modal analysis provides compelling evidence for the transcriptomic, epigenomic and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types. We further present an extensive genetic toolset for targeting glutamatergic neuron types towards linking their molecular and developmental identity to their circuit function. Together, our results establish a unifying and mechanistic framework of neuronal cell-type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties.
Epidural electrical stimulation (EES) targeting the dorsal roots of lumbosacral segments restores walking in people with spinal cord injury (SCI). However, EES is delivered with multielectrode paddle ...leads that were originally designed to target the dorsal column of the spinal cord. Here, we hypothesized that an arrangement of electrodes targeting the ensemble of dorsal roots involved in leg and trunk movements would result in superior efficacy, restoring more diverse motor activities after the most severe SCI. To test this hypothesis, we established a computational framework that informed the optimal arrangement of electrodes on a new paddle lead and guided its neurosurgical positioning. We also developed software supporting the rapid configuration of activity-specific stimulation programs that reproduced the natural activation of motor neurons underlying each activity. We tested these neurotechnologies in three individuals with complete sensorimotor paralysis as part of an ongoing clinical trial ( www.clinicaltrials.gov identifier NCT02936453). Within a single day, activity-specific stimulation programs enabled these three individuals to stand, walk, cycle, swim and control trunk movements. Neurorehabilitation mediated sufficient improvement to restore these activities in community settings, opening a realistic path to support everyday mobility with EES in people with SCI.
In this paper, we describe the design of Neurogrid, a neuromorphic system for simulating large-scale neural models in real time. Neuromorphic systems realize the function of biological neural systems ...by emulating their structure. Designers of such systems face three major design choices: 1) whether to emulate the four neural elements-axonal arbor, synapse, dendritic tree, and soma-with dedicated or shared electronic circuits; 2) whether to implement these electronic circuits in an analog or digital manner; and 3) whether to interconnect arrays of these silicon neurons with a mesh or a tree network. The choices we made were: 1) we emulated all neural elements except the soma with shared electronic circuits; this choice maximized the number of synaptic connections; 2) we realized all electronic circuits except those for axonal arbors in an analog manner; this choice maximized energy efficiency; and 3) we interconnected neural arrays in a tree network; this choice maximized throughput. These three choices made it possible to simulate a million neurons with billions of synaptic connections in real time-for the first time-using 16 Neurocores integrated on a board that consumes three watts.
Near-atomic model of microtubule-tau interactions Kellogg, Elizabeth H; Hejab, Nisreen M A; Poepsel, Simon ...
Science (American Association for the Advancement of Science),
06/2018, Letnik:
360, Številka:
6394
Journal Article
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Tau is a developmentally regulated axonal protein that stabilizes and bundles microtubules (MTs). Its hyperphosphorylation is thought to cause detachment from MTs and subsequent aggregation into ...fibrils implicated in Alzheimer's disease. It is unclear which tau residues are crucial for tau-MT interactions, where tau binds on MTs, and how it stabilizes them. We used cryo-electron microscopy to visualize different tau constructs on MTs and computational approaches to generate atomic models of tau-tubulin interactions. The conserved tubulin-binding repeats within tau adopt similar extended structures along the crest of the protofilament, stabilizing the interface between tubulin dimers. Our structures explain the effect of phosphorylation on MT affinity and lead to a model of tau repeats binding in tandem along protofilaments, tethering together tubulin dimers and stabilizing polymerization interfaces.
In order to deal with the uncertainty in the world, our brains need to be able to flexibly switch between the exploration of new sensory representations and exploitation of previously acquired ones. ...This requires forming accurate estimations of what and how much something is expected. While modeling has allowed for the development of several ways to form predictions, how the brain could implement those is still under debate. Here, we recognize acetylcholine as one of the main neuromodulators driving learning based on uncertainty, promoting the exploration of new sensory representations. We identify its interactions with cortical inhibitory interneurons and derive a biophysically grounded computational model able to capture and learn from uncertainty. This model allows us to understand inhibition beyond gain control by suggesting that different interneuron subtypes either encode predictions or estimate their uncertainty, facilitating detection of unexpected cues. Moreover, we show how acetylcholine-like neuromodulation uniquely interacts with global and local sources of inhibition, disrupting perceptual certainty and promoting the rapid acquisition of new perceptual cues. Altogether, our model proposes that cortical acetylcholine favors sensory exploration over exploitation in a cortical microcircuit dedicated to estimating sensory uncertainty.
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