First Win for the Neurorights Campaign: Chile plans to regulate all neurotech and ban the sale of brain data

IEEE Spectrum ◽  
2022 ◽  
Vol 59 (1) ◽  
pp. 26-58
Author(s):  
Eliza Strickland ◽  
Maria Gallucci
Keyword(s):  
NeuroImage ◽  
2012 ◽  
Vol 60 (2) ◽  
pp. 940-951 ◽  
Author(s):  
Adolf Pfefferbaum ◽  
Torsten Rohlfing ◽  
Margaret J. Rosenbloom ◽  
Edith V. Sullivan

2008 ◽  
Vol 27 (3) ◽  
pp. 855-862 ◽  
Author(s):  
W. M. Jainek ◽  
S. Born ◽  
D. Bartz ◽  
W. Straßer ◽  
J. Fischer
Keyword(s):  

2017 ◽  
Vol 11 ◽  
Author(s):  
Inge A. Mulder ◽  
Artem Khmelinskii ◽  
Oleh Dzyubachyk ◽  
Sebastiaan de Jong ◽  
Marieke J. H. Wermer ◽  
...  

2009 ◽  
Vol 2 ◽  
pp. JEN.S2290 ◽  
Author(s):  
Kazuyoshi Tsutsui

It is now clearly established that steroids can be synthesized de novo by the vertebrate brain. Such steroids are called neurosteroids. To understand neurosteroid action in the brain, data on the regio- and temporal-specific synthesis of neurosteroids are needed. In the middle 1990s, the Purkinje cell, an important cerebellar neuron, was identified as a major site for neurosteroid formation in vertebrates. This discovery has allowed deeper insights into neuronal neurosteroidogenesis and biological actions of neurosteroids have become clear by the studies using the Purkinje cell as an excellent cellular model, which is known to play an important role in memory and learning processes. From the past 10 years of research on mammals, we now know that the Purkinje cell actively synthesizes progesterone and estradiol de novo from cholesterol during neonatal life, when cerebellar neuronal circuit formation occurs. Both progesterone and estradiol promote dendritic growth, spinogenesis, and synaptogenesis via each cognate nuclear receptor in the developing Purkinje cell. Such neurosteroid actions that may be mediated by neurotrophic factors contribute to the formation of cerebellar neuronal circuit during neonatal life. Allopregnanolone, a progesterone metabolite, is also synthesized in the cerebellum and acts on Purkinje cell survival in the neonate. The aim of this review is to summarize the current knowledge regarding the biosynthesis and biological actions of neurosteroids in the Purkinje cell during development.


2021 ◽  
Author(s):  
Thijs L van der Plas ◽  
Jérôme Tubiana ◽  
Guillaume Le Goc ◽  
Geoffrey Migault ◽  
Michael Kunst ◽  
...  

Patterns of endogenous activity in the brain reflect a stochastic exploration of the neuronal state space that is constrained by the underlying assembly organization of neurons. Yet it remains to be shown that this interplay between neurons and their assembly dynamics indeed suffices to generate whole-brain data statistics. Here we recorded the activity from ~40,000 neurons simultaneously in zebrafish larvae, and show that a data-driven network model of neuron-assembly interactions can accurately reproduce the mean activity and pairwise correlation statistics of their spontaneous activity. This model, the compositional Restricted Boltzmann Machine, unveils ~200 neural assemblies, which compose neurophysiological circuits and whose various combinations form successive brain states. From this, we mathematically derived an interregional functional connectivity matrix, which is conserved across individual animals and correlates well with structural connectivity. This novel, assembly-based generative model of brain-wide neural dynamics enables physiology-bound perturbation experiments in silico.


2018 ◽  
Author(s):  
Andreas Wartel ◽  
Patrik Lindenfors ◽  
Johan Lind

AbstractPrimate brains differ in size and architecture. Hypotheses to explain this variation are numerous and many tests have been carried out. However, after body size has been accounted for there is little left to explain. The proposed explanatory variables for the residual variation are many and covary, both with each other and with body size. Further, the data sets used in analyses have been small, especially in light of the many proposed predictors. Here we report the complete list of models that results from exhaustively combining six commonly used predictors of brain and neocortex size. This provides an overview of how the output from standard statistical analyses changes when the inclusion of different predictors is altered. By using both the most commonly tested brain data set and a new, larger data set, we show that the choice of included variables fundamentally changes the conclusions as to what drives primate brain evolution. Our analyses thus reveal why studies have had troubles replicating earlier results and instead have come to such different conclusions. Although our results are somewhat disheartening, they highlight the importance of scientific rigor when trying to answer difficult questions. It is our position that there is currently no empirical justification to highlight any particular hypotheses, of those adaptive hypotheses we have examined here, as the main determinant of primate brain evolution.


2019 ◽  
Author(s):  
Nele Vandersickel ◽  
Enid Van Nieuwenhuyse ◽  
Nico Van Cleemput ◽  
Jan Goedgebeur ◽  
Milad El Haddad ◽  
...  

AbstractNetworks provide a powerful methodology with applications in a variety of biological, technological and social systems such as analysis of brain data, social networks, internet search engine algorithms, etc. To date, directed networks have not yet been applied to characterize the excitation of the human heart. In clinical practice, cardiac excitation is recorded by multiple discrete electrodes. During (normal) sinus rhythm or during cardiac arrhythmias, successive excitation connects neighboring electrodes, resulting in their own unique directed network. This in theory makes it a perfect fit for directed network analysis. In this study, we applied directed networks to the heart in order to describe and characterize cardiac arrhythmias. Proofof-principle was established using in-silico and clinical data. We demonstrated that tools used in network theory analysis allow to determine the mechanism and location of certain cardiac arrhythmias. We show that the robustness of this approach can potentially exceed the existing state-of-the art methodology used in clinics. Furthermore, implementation of these techniques in daily practice can improve accuracy and speed of cardiac arrhythmia analysis. It may also provide novel insights in arrhythmias that are still incompletely understood.


1997 ◽  
Vol 30 (2) ◽  
pp. 103-106
Author(s):  
Alessandra Bertoldo ◽  
Paolo Vicini ◽  
Claudio Cobelli

Sign in / Sign up

Export Citation Format

Share Document