Lifeboat Foundation

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Generally, information at lower levels is more fine-grained but can be coarse-grained at higher levels. However, only information processed at specific scales of coarse-graining appears to be available for conscious awareness. We do not have direct experience of information available at the scale of individual neurons, which is noisy and highly stochastic. Neither do we have experience of more macro-scale interactions, such as interpersonal communications. Neurophysiological evidence suggests that conscious experiences co-vary with information encoded in coarse-grained neural states such as the firing pattern of a population of neurons. In this article, we introduce a new information al theory of consciousness: Information Closure Theory of Consciousness (ICT). We hypothesize that conscious processes are processes which form non-trivial information al closure (NTIC) with respect to the environment at certain coarse-grained scales. This hypothesis implies that conscious experience is confined due to information al closure from conscious processing to other coarse-grained scales. Information Closure Theory of Consciousness (ICT) proposes new quantitative definitions of both conscious content and conscious level. With the parsimonious definitions and a hypothesize, ICT provides explanations and predictions of various phenomena associated with consciousness. The implications of ICT naturally reconcile issues in many existing theories of consciousness and provides explanations for many of our intuitions about consciousness. Most importantly, ICT demonstrates that information can be the common language between consciousness and physical reality.

Imagine you are a neuron in Alice’s brain. Your daily work is to collect neurotransmitters through dendrites from other neurons, accumulate membrane potential, and finally send signals to other neurons through action potentials along axons. However, you have no idea that you are one of the neurons in Alice’s supplementary motor area and are involved in many motor control processes for Alice’s actions, such as grabbing a cup. You are ignorant of intentions, goals, and motor plans that Alice has at any moment, even though you are part of the physiological substrate responsible for all these actions. A similar story also happens in Alice’s conscious mind. To grab a cup, for example, Alice is conscious of her intention and visuosensory experience of this action. However, her conscious experience does not reflect the dynamic of your membrane potential or the action potentials you send to other neurons every second.

To engineer proteins with useful functions, researchers usually begin with a natural protein that has a desirable function, such as emitting fluorescent light, and put it through many rounds of random mutation that eventually generate an optimized version of the protein.

This process has yielded optimized versions of many important proteins, including green fluorescent protein (GFP). However, for other proteins, it has proven difficult to generate an optimized version. MIT researchers have now developed a computational approach that makes it easier to predict mutations that will lead to better proteins, based on a relatively small amount of data.

Using this model, the researchers generated proteins with mutations that were predicted to lead to improved versions of GFP and a protein from adeno-associated virus (AAV), which is used to deliver DNA for gene therapy. They hope it could also be used to develop additional tools for neuroscience research and medical applications.

The neurosurgeon Sergio Canavero announced in 2015 that he could soon be capable of performing the world’s first human head transplant procedure. This would mean that it would be possible to remove someone’s head, and graft it onto the neck and shoulders of another person. As of yet, this has only been performed on cadavers and not on living humans.

But suppose you want to keep the face that you’ve already got? Or have grown tired of the body you inhabit? Could it ever be possible to switch brains between bodies instead?

Continue reading “Ever Wanted a Brain Transplant? Here Are The Challenges We Face” »

The brain computer interface (BCI) device can be used by inexperienced patients to play games within just a few sessions.

Neurodevelopmental disorders (NDDs) are a group of disorders in which the development of the central nervous system (CNS) is disturbed, resulting in different neurological and neuropsychiatric features, such as impaired motor function, learning, language or non-verbal communication. Frequent comorbidities include epilepsy and movement disorders. Advances in DNA sequencing technologies revealed identifiable genetic causes in an increasingly large proportion of NDDs, highlighting the need of experimental approaches to investigate the defective genes and the molecular pathways implicated in abnormal brain development. However, targeted approaches to investigate specific molecular defects and their implications in human brain dysfunction are prevented by limited access to patient-derived brain tissues. In this context, advances of both stem cell technologies and genome editing strategies during the last decade led to the generation of three-dimensional (3D) in vitro-models of cerebral organoids, holding the potential to recapitulate precise stages of human brain development with the aim of personalized diagnostic and therapeutic approaches. Recent progresses allowed to generate 3D-structures of both neuronal and non-neuronal cell types and develop either whole-brain or region-specific cerebral organoids in order to investigate in vitro key brain developmental processes, such as neuronal cell morphogenesis, migration and connectivity. In this review, we summarized emerging methodological approaches in the field of brain organoid technologies and their application to dissect disease mechanisms underlying an array of pediatric brain developmental disorders, with a particular focus on autism spectrum disorders (ASDs) and epileptic encephalopathies.

Neurodevelopmental disorders (NDDs) encompass a range of frequently co-existing conditions that include intellectual disability (ID), developmental delay (DD), and autism spectrum disorders (ASDs) (Heyne et al., 2018; Salpietro et al., 2019). ASDs represent a complex set of behaviorally defined phenotypes, characterized by impairments in social interaction, communication and restricted or stereotyped behaviors (Chen et al., 2018). Epilepsy and NDDs frequently occur together, and when refractory seizures are accompanied by cognitive slowing or regression, patients are considered to have an epileptic encephalopathy (EE) (Scheffer et al., 2017). Both ID and ASDs are clinically and etiologically heterogeneous and a unifying pathophysiology has not yet been identified for either the disorder as a whole or its core behavioral components (Myers et al., 2020). Family and twin studies suggest high (0.65–0.91) heritability (Chen et al.

Academics are proposing a new and improved way to help researchers discover when consciousness emerges in human infancy.

When over the course of development do humans become conscious? When the seventeenth-century French philosopher René Descartes was asked about infant consciousness by his critics, he eventually suggested that infants might have thoughts, albeit ones that are simpler than those of adults. Hundreds of years later, the issue of when human beings become conscious is a question which remains a challenge for psychologists and philosophers alike.

But now, in response to a recent article in Trends in Cognitive Sciences, two academics from the University of Birmingham have suggested an improved way to help scientists and researchers identify when babies become conscious.

For several years, Jimo Borjigin, a professor of neurology at the University of Michigan, had been troubled by the question of what happens to us when we die.

New research into the dying brain suggests the line between life and death may be less distinct than previously thought by Alex Blasdel.

Electroconvulsive therapy is more effective than ketamine at treating severe depression, according to a new meta-analysis.