Lifeboat Foundation

A Brain-Computer Interface (BCI) is a promising technology that has received increased attention in recent years. BCIs create a direct link from your brain to a computer. This technology has applications to many industries and sectors of our life. BCIs redefine how we approach medical treatment and communication for individuals with various conditions or injuries. BCIs also have applications in entertainment, specifically video games and VR. From being able to control a prosthetic limb with your mind, to being able to play a video game with your mind—the potential of BCIs are endless.

What are your thoughts on Brain-Computer Interfaces? Let us know!
Any disruptive technologies you would like us to cover? Dm us on our Instagram (@toyvirtualstructures).
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Summary: CGRP neurons found in subregions of the thalamus and brainstem relay multisensory threat information to the amygdala. These neural circuits are essential for the formation of aversive memories, a new study reports.

Source: Salk Institute.

Salk scientists have uncovered a molecular pathway that distills threatening sights, sounds and smells into a single message: Be afraid.

Source:

#neuroscience #neurotwitter #neurology #science #sciencetwitter #medtwitter #Bioinformatics #biochemistry #biotechnology #anatomy #neuroanatomy

Summary: In humans, microglia develop in different ways, undergoing growth patterns that go up and down, creating waves throughout our brain development.

Source: University of Southampton.

New research published today by the University of Southampton shows new insight in how our brain develops, that can pave the way for treating neurological disorders.

6G radiation is affecting brain cells. As 6G as the successor of 5G is poised to take over the world, should we worry? I feel so.

Discovery could help assess new communication technology and also develop therapies to treat brain diseases, Beijing researchers say.

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In recent decades, the scientific study of consciousness has significantly increased our understanding of this elusive phenomenon. Yet, despite critical development in our understanding of the functional side of consciousness, we still lack a fundamental theory regarding its phenomenal aspect. There is an “explanatory gap” between our scientific knowledge of functional consciousness and its “subjective,” phenomenal aspects, referred to as the “hard problem” of consciousness. The phenomenal aspect of consciousness is the first-person answer to “what it’s like” question, and it has thus far proved recalcitrant to direct scientific investigation. Naturalistic dualists argue that it is composed of a primitive, private, non-reductive element of reality that is independent from the functional and physical aspects of consciousness. Illusionists, on the other hand, argue that it is merely a cognitive illusion, and that all that exists are ultimately physical, non-phenomenal properties. We contend that both the dualist and illusionist positions are flawed because they tacitly assume consciousness to be an absolute property that doesn’t depend on the observer. We develop a conceptual and a mathematical argument for a relativistic theory of consciousness in which a system either has or doesn’t have phenomenal consciousness with respect to some observer. Phenomenal consciousness is neither private nor delusional, just relativistic. In the frame of reference of the cognitive system, it will be observable (first-person perspective) and in other frame of reference it will not (third-person perspective). These two cognitive frames of reference are both correct, just as in the case of an observer that claims to be at rest while another will claim that the observer has constant velocity. Given that consciousness is a relativistic phenomenon, neither observer position can be privileged, as they both describe the same underlying reality. Based on relativistic phenomena in physics we developed a mathematical formalization for consciousness which bridges the explanatory gap and dissolves the hard problem. Given that the first-person cognitive frame of reference also offers legitimate observations on consciousness, we conclude by arguing that philosophers can usefully contribute to the science of consciousness by collaborating with neuroscientists to explore the neural basis of phenomenal structures.

As one of the most complex structures we know of nature, the brain poses a great challenge to us in understanding how higher functions like perception, cognition, and the self arise from it. One of its most baffling abilities is its capacity for conscious experience (van Gulick, 2014). Thomas Nagel (1974) suggests a now widely accepted definition of consciousness: a being is conscious just if there is “something that it is like” to be that creature, i.e., some subjective way the world seems or appears from the creature’s point of view. For example, if bats are conscious, that means there is something it is like for a bat to experience its world through its echolocational senses. On the other hand, under deep sleep (with no dreams) humans are unconscious because there is nothing it is like for humans to experience their world in that state.

In the last several decades, consciousness has transformed from an elusive metaphysical problem into an empirical research topic. Nevertheless, it remains a puzzling and thorny issue for science. At the heart of the problem lies the question of the brute phenomena that we experience from a first-person perspective—e.g., what it is like to feel redness, happiness, or a thought. These qualitative states, or qualia, compose much of the phenomenal side of consciousness. These qualia are arranged into spatial and temporal patterns and formal structures in phenomenal experience, called eidetic or transcendental structures¹. For example, while qualia pick out how a specific note sounds, eidetic structures refer to the temporal form of the whole melody. Hence, our inventory of the elusive properties of phenomenal consciousness includes both qualia and eidetic structures.

In this review, we undertake a critical appraisal of eight published studies providing first evidence that a history of attention-deficit/hyperactivity disorder (ADHD) may increase risk for the later-life development of a neurodegenerative disease, in particular Lewy body diseases (LBD), by up to five-fold. Most of these studies have used data linked to health records in large population registers and include impressive sample sizes and adequate follow-up periods. We identify a number of methodological limitations as well, including potential diagnostic inaccuracies arising from the use of electronic health records, biases in the measurement of ADHD status and symptoms, and concerns surrounding the representativeness of ADHD and LBD cohorts. Consequently, previously reported risk associations may have been underestimated due to the high likelihood of potentially missed ADHD cases in groups used as “controls”, or alternatively previous estimates may be inflated due to the inclusion of confounding comorbidities or non-ADHD cases within “exposed” groups that may have better accounted for dementia risk. Prospective longitudinal studies involving well-characterized cases and controls are recommended to provide some reassurance about the validity of neurodegenerative risk estimates in ADHD.

Attention-deficit hyperactivity disorder (ADHD) is a psychiatric disorder beginning in childhood that is characterized by core symptoms of inattention, impulsivity, and hyperactivity (Biederman and Faraone, 2005; American Psychiatric Association, 2013; Faraone et al., 2015). Diagnostic criteria require symptoms to present in early childhood, before age 12, and cause impairment in daily activities in more than one setting (e.g., home, school, social environment, and/or interpersonal relationships; American Psychiatric Association, 2013). Although it is largely considered a childhood disorder, 40–60% of cases of ADHD persist into adulthood (Culpepper and Mattingly, 2010; Michielsen et al., 2012; Volkow and Swanson, 2013; Asherson et al., 2016), and the overall prevalence of adult ADHD ranges from 2 to 4% (Kieling and Rohde, 2012; Fayyad et al., 2017).

ADHD may persist into later life as well. Roughly 3% of adults over age 50 suffer from significant symptoms of attention-deficit/hyperactivity disorder (ADHD; Michielsen et al., 2012; Kooij et al., 2016), often presenting as executive dysfunction (e.g., absent-mindedness) and memory impairments (e.g., forgetfulness or difficulty learning new things; Rosler et al., 2010; Thorell et al., 2017; Callahan et al., 2021). These symptoms overlap with those of early neurodegenerative disease (Ivanchak et al., 2012; Pollack, 2012; Goodman et al., 2016; Callahan et al., 2017), and it is currently unclear whether ADHD is associated with an increased neurodegenerative risk, or if it is being misdiagnosed due to symptom overlap (Callahan et al., 2017). Clarifying this issue is crucial to reduce dementia misdiagnoses, and to guide treatment, which will differ depending on whether the disease course is assumed to be neurodegenerative or not.

Certain tasks—such as recognizing patterns and language—are performed highly efficiently by a human brain, requiring only about one ten-thousandth of the energy of a conventional, so-called “von Neumann” computer. One of the reasons lies in the structural differences: In a von Neumann architecture, there is a clear separation between memory and processor, which requires constant moving of large amounts of data. This is time-and energy-consuming—the so-called von Neumann bottleneck. In the brain, the computational operation takes place directly in the data memory and the biological synapses perform the tasks of memory and processor at the same time.

In Forschungszentrum Jülich, scientists have been working for more than 15 years on special data storage devices and components that can have similar properties to the synapses in the human brain. So-called memristive memory devices, also known as memristors, are considered to be extremely fast and energy-saving, and can be miniaturized very well down to the nanometer range. The functioning of memristive cells is based on a very special effect: Their electrical resistance is not constant, but can be changed and reset again by applying an external voltage, theoretically continuously. The change in resistance is controlled by the movement of oxygen ions. If these move out of the semiconducting metal oxide layer, the material becomes more conductive and the electrical resistance drops. This change in resistance can be used to store information.

The processes that can occur in cells are complex and vary depending on the material system. Three researchers from the Jülich Peter Grünberg Institute—Prof. Regina Dittmann, Dr. Stephan Menzel, and Prof. Rainer Waser—have therefore compiled their research results in a detailed review article, “Nanoionic memristive phenomena in metal oxides: the valence change mechanism.” They explain in detail the various physical and chemical effects in memristors and shed light on the influence of these effects on the switching properties of memristive cells and their reliability.

A team of researchers in the Faculty of Engineering of The University of Hong Kong (HKU) has developed a coin-sized system that can read weak electrochemical signals and can be used for personalized health monitoring and the measurement of such conditions as diabetes, cardiovascular diseases and mental health. The discovery was featured on the cover of Analytical Chemistry.

The PERfECT System—an acronym for Personalized Electronic Reader for Electrochemical Transistors—is the world’s smallest system of its kind, measuring 1.5 cm x 1.5 cm x 0.2 cm and weighing only 0.4 gram. It is easily wearable, for instance integrated with a smartwatch or as a patch, to allow for continuous monitoring of biosignals such as glucose levels and antibody concentrations in blood and even sweat.

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