Human Brain/Cloud Interface

Prevalence and risk factors of brain atrophy and associated confusion state among adults from three hospitals in northern Tanzania

Introduction

brain atrophy is the reduction of brain volume often accompanied with cognitive changes. Despite the availability of computerized-tomography (CT) scanners in Tanzania, little is known about the magnitude of brain atrophy, its associated confusion state and the risk factors in adults. This study aimed to fill those knowledge gaps.

Methods

a retrospective cross-sectional hospital-based survey was conducted in northern Tanzania using a sample size of 384 CT images of adults who underwent brain CT scans in three referral hospitals. CT images were evaluated using a diagonal brain fraction (DBF) method to determine the presence of brain atrophy. Data for other covariates were also collected.

Results

we report a prevalence of 60.67% for brain atrophy and 35% for the associated confusion state. Association between confusion state and brain atrophy was statistically significant (χ² = 21.954, p<0.001). Brain atrophy was prognosticated by: age (adjusted OR: 1.11; 95% CI [1.05, 1.20], p<0.001), smoking (adjusted OR: 6.97; 95% CI [2.12, 26.19], p<0.001), alcohol-consumption (adjusted OR: 11.87; 95% CI [3.44, 40.81], p<0.001), hypertension (adjusted OR: 61.21; 95 CI [15.20, 349.43], p<0.001), type-2 diabetes mellitus (adjusted OR: 15.67; 95% CI [5.32, 52.77], p<0.001) and white matter demyelination (adjusted OR: 13.45; 95% CI [4.66, 44.25], p<0.001).

Conclusion

there is high prevalence of brain atrophy and associated confusion state among hospitalized adults in northern Tanzania. Reported prognostic factors for brain atrophy such as age, smoking, alcohol consumption, hypertension, type-2 diabetes mellitus and white matter demyelination could help focus interventions in this area.

Merging Minds: The Conceptual and Ethical Impacts of Emerging Technologies for Collective Minds

A growing number of technologies are currently being developed to improve and distribute thinking and decision-making. Rapid progress in brain-to-brain interfacing and swarming technologies promises to transform how we think about collective and collaborative cognitive tasks across domains, ranging from research to entertainment, and from therapeutics to military applications. As these tools continue to improve, we are prompted to monitor how they may affect our society on a broader level, but also how they may reshape our fundamental understanding of agency, responsibility, and other key concepts of our moral landscape.

In this paper we take a closer look at this class of technologies – Technologies for Collective Minds – to see not only how their implementation may react with commonly held moral values, but also how they challenge our underlying concepts of what constitutes collective or individual agency. We argue that prominent contemporary frameworks for understanding collective agency and responsibility are insufficient in terms of accurately describing the relationships enabled by Technologies for Collective Minds, and that they therefore risk obstructing ethical analysis of the implementation of these technologies in society. We propose a more multidimensional approach to better understand this set of technologies, and to facilitate future research on the ethics of Technologies for Collective Minds.

Kukumirwa Semombe Dzamavhu: When Voices Begin to Erupt from Bottoms, African Anthropology Becomes Colonial

On a continent where Africans suffered crises of dispossession, it is inaccurate to describe such crises as crises in representations. Drawing on Shona (people of Zimbabwe) proverb kukumirwa semombe dzamavhu (being mooed for as if one is a cow made of clay), this paper argues that colonial anthropology did not only generate crises in representations but anthropologists took it upon themselves to 'moo' for Africans. Similarly, emergent futures herald human minds being nanotechnologically scanned and transferred to clouds and into technological substrates. In this sense, crises of dispossession will worsen when humans are dispossessed of their minds, so scanned and transferred from biological brains to clouds and into technological substrates. Contributing insights to the anthropology of science and technology studies, this paper argues that with minds transferred from the biological brains, in the guise of defying mortality, Africans will be dispossessed of their voices and their minds.

Overcoming the blood–brain barrier for the therapy of malignant brain tumor: current status and prospects of drug delivery approaches

Besides the broad development of nanotechnological approaches for cancer diagnosis and therapy, currently, there is no significant progress in the treatment of different types of brain tumors. Therapeutic molecules crossing the blood–brain barrier (BBB) and reaching an appropriate targeting ability remain the key challenges. Many invasive and non-invasive methods, and various types of nanocarriers and their hybrids have been widely explored for brain tumor treatment. However, unfortunately, no crucial clinical translations were observed to date. In particular, chemotherapy and surgery remain the main methods for the therapy of brain tumors. Exploring the mechanisms of the BBB penetration in detail and investigating advanced drug delivery platforms are the key factors that could bring us closer to understanding the development of effective therapy against brain tumors. In this review, we discuss the most relevant aspects of the BBB penetration mechanisms, observing both invasive and non-invasive methods of drug delivery. We also review the recent progress in the development of functional drug delivery platforms, from viruses to cell-based vehicles, for brain tumor therapy. The destructive potential of chemotherapeutic drugs delivered to the brain tumor is also considered. This review then summarizes the existing challenges and future prospects in the use of drug delivery platforms for the treatment of brain tumors.

Poststroke Cognitive Impairment Research Progress on Application of Brain-Computer Interface

Brain-computer interfaces (BCIs), a new type of rehabilitation technology, pick up nerve cell signals, identify and classify their activities, and convert them into computer-recognized instructions. This technique has been widely used in the rehabilitation of stroke patients in recent years and appears to promote motor function recovery after stroke. At present, the application of BCI in poststroke cognitive impairment is increasing, which is a common complication that also affects the rehabilitation process. This paper reviews the promise and potential drawbacks of using BCI to treat poststroke cognitive impairment, providing a solid theoretical basis for the application of BCI in this area.

Building blocks for autonomous computing materials: Dimers, trimers, and tetramers

Autonomous computing materials for data storage and computing offer an opportunity for next generation of computing devices. Patchy nanoparticle networks, for example, have been suggested as potential candidates for emulating neuronal networks and performing brain-like computing. Here, we use molecular dynamics (MD) simulations to show that stable dimers, trimers, and tetramers can be built from citrate capped gold nanoparticles (cit-AuNPs) linked by poly(allylamine hydrochloride) (PAH) chains. We use different lengths of PAHs to build polymer-networked nanoparticle assemblies that can emulate a complex neuronal network linked by axons of varying lengths. We find that the tetramer structure can accommodate up to 11 different states when the AuNP pairs are connected by either of two polymer linkers, PAH₂₀₀ and PAH₃₀₀. We find that the heavy AuNPs contribute to the assembly's structure stability. To further illustrate the stability, the AuNP-AuNP distances in dimer, trimer, and tetramer structures are reduced by steering the cit-AuNPs closer to each other. At different distances, these steered structures are all locally stable in a 10 ns MD simulation time scale because of their connection to the AuNPs. We also find that the global potential energy minimum is at short AuNP-AuNP distances where AuNPs collapse because the -NH₃ ⁺ and -COO^- attraction reduces the potential energy. The stability and application of these fundamental structures remain to be further improved through the use of alternative polymer linkers and nanoparticles.

Advanced Bioelectrical Signal Processing Methods: Past, Present and Future Approach-Part II: Brain Signals

As it was mentioned in the previous part of this work (Part I)-the advanced signal processing methods are one of the quickest and the most dynamically developing scientific areas of biomedical engineering with their increasing usage in current clinical practice. In this paper, which is a Part II work-various innovative methods for the analysis of brain bioelectrical signals were presented and compared. It also describes both classical and advanced approaches for noise contamination removal such as among the others digital adaptive and non-adaptive filtering, signal decomposition methods based on blind source separation, and wavelet transform.

A concise review: the synergy between artificial intelligence and biomedical nanomaterials that empowers nanomedicine

Nanomedicine has recently experienced unprecedented growth and development. However, the complexity of operations at the nanoscale introduces a layer of difficulty in the clinical translation of nanodrugs and biomedical nanotechnology. This problem is further exacerbated when engineering and optimizing nanomaterials for biomedical purposes. To navigate this issue, artificial intelligence (AI) algorithms have been applied for data analysis and inference, allowing for a more applicable understanding of the complex interaction amongst the abundant variables in a system involving the synthesis or use of nanomedicine. Here, we report on the current relationship and implications of nanomedicine and AI. Particularly, we explore AI as a tool for enabling nanomedicine in the context of nanodrug screening and development, brain-machine interfaces and nanotoxicology. We also report on the current state and future direction of nanomedicine and AI in cancer, diabetes, and neurological disorder therapy.

Interface, interaction, and intelligence in generalized brain-computer interfaces

A brain-computer interface (BCI) establishes a direct communication channel between a brain and an external device. With recent advances in neurotechnology and artificial intelligence (AI), the brain signals in BCI communication have been advanced from sensation and perception to higher-level cognition activities. While the field of BCI has grown rapidly in the past decades, the core technologies and innovative ideas behind seemingly unrelated BCI systems have never been summarized from an evolutionary point of view. Here, we review various BCI paradigms and present an evolutionary model of generalized BCI technology which comprises three stages: interface, interaction, and intelligence (I3). We also highlight challenges, opportunities, and future perspectives in the development of new BCI technology.

Engineered nanoparticle network models for autonomous computing

Materials that exhibit synaptic properties are a key target for our effort to develop computing devices that mimic the brain intrinsically. If successful, they could lead to high performance, low energy consumption, and huge data storage. A 2D square array of engineered nanoparticles (ENPs) interconnected by an emergent polymer network is a possible candidate. Its behavior has been observed and characterized using coarse-grained molecular dynamics (CGMD) simulations and analytical lattice network models. Both models are consistent in predicting network links at varying temperatures, free volumes, and E-field (E⃗) strengths. Hysteretic behavior, synaptic short-term plasticity and long-term plasticity-necessary for brain-like data storage and computing-have been observed in CGMD simulations of the ENP networks in response to E-fields. Non-volatility properties of the ENP networks were also confirmed to be robust to perturbations in the dielectric constant, temperature, and affine geometry.

Neurochips: Considerations from a neurosurgeon's standpoint

A neurochip comprises a small device based on the brain-machine interfaces that emulate the functioning synapses. Its implant in the human body allows the interaction of the brain with a computer. Although the data-processing speed is still slower than that of the human brain, they are being developed. There is no ethical conflict as long as it is used for neural rehabilitation or to supply impaired or missing neurological functions. However, other applications emerge as controversial.

To the best of our knowledge, there have no been publications about the neurosurgical role in the application of this neurotechnological advance. Deliberation on neurochips is primarily limited to a small circle of scholars such as neurotechnological engineers, artists, philosophers, and bioethicists. Why do we address neurosurgeons? They will be directly involved as they could be required to perform invasive procedures.

Future neurosurgeons will have to be a different type of neurosurgeon. They will be part of interdisciplinary teams interacting with computer engineers, neurobiologist, and ethicists. Although a neurosurgeon is not expected to be an expert in all areas, they have to be familiar with them; they have to be prepared to determine indications, contraindications and risks of the procedures, participating in the decision-making processes, and even collaborating in the design of devices to preserve anatomic structures. Social, economic, and legal aspects are also inherent to the neurosurgical activity; therefore, these aspects should also be considered.

Improving scalability in systems neuroscience

Emerging technologies to acquire data at increasingly greater scales promise to transform discovery in systems neuroscience. However, current exponential growth in the scale of data acquisition is a double-edged sword. Scaling up data acquisition can speed up the cycle of discovery but can also misinterpret the results or possibly slow down the cycle because of challenges presented by the curse of high-dimensional data. Active, adaptive, closed-loop experimental paradigms use hardware and algorithms optimized to enable time-critical computation to provide feedback that interprets the observations and tests hypotheses to actively update the stimulus or stimulation parameters. In this perspective, we review important concepts of active and adaptive experiments and discuss how selectively constraining the dimensionality and optimizing strategies at different stages of discovery loop can help mitigate the curse of high-dimensional data. Active and adaptive closed-loop experimental paradigms can speed up discovery despite an exponentially increasing data scale, offering a road map to timely and iterative hypothesis revision and discovery in an era of exponential growth in neuroscience.

TechnoBrainBodies-in-Cultures: An Intersectional Case

The cyborgization of brainbodies with computer hardware and software today ranges in scope from the realization of Brain-Computer Interfaces (BCIs) to visions of mind upload to silicon, the latter being targeted toward a transhuman future. Refining posthumanist concepts to formulate a posthumanities perspective, and contrasting those approaches with transhumanist trajectories, I explore the intersectional dimension of realizations and visions of neuro-technological developments, which I name TechnoBrainBodies-in-Cultures. In an intersectional analysis, I investigate the embedding and legitimation of transhumanist visions brought about by neuroscientific research and neuro-technological development based on a concept of modern neurobiological determinism. The conjoined trajectories of BCI research and development and transhumanist visions perpetuate the inscription of intersectional norms, with the concomitant danger of producing discriminatory effects. This culminates in normative capacity being seen as a conflation of the abled, successful, white masculinized techno-brain with competition. My deeper analysis, however, also enables displacements within recent BCI research and development to be characterized: from ''thought-translation" to affective conditioning and from controllability to obstinacy within the BCI, going so far as to open the closed loop. These realizations challenge notions about the BCI's actor status and agency and foster questions about shifts in the corresponding subject-object relations. Based on these analyses, I look at the effects of neuro-technological and transhumanist governmentality on the question of whose lives are to be improved and whose lives should be excluded from these developments. Within the framework of political feminist materialisms, I combine the concept of posthumanities with my concept of TechnoBrainBodies-in-Cultures to envision and discuss a material-discursive strategy, encompassing dimensions of affect, sociality, resistance, compassion, cultural diversity, ethnic diversity, multiple sexes/sexualities, aging, dis/abilities-in short, all of this "intersectional stuff"-as well as obstinate techno-brain agencies and contumacies foreseen in these cyborgian futures.

MEG-Based Detection of Voluntary Eye Fixations Used to Control a Computer

Gaze-based input is an efficient way of hand-free human-computer interaction. However, it suffers from the inability of gaze-based interfaces to discriminate voluntary and spontaneous gaze behaviors, which are overtly similar. Here, we demonstrate that voluntary eye fixations can be discriminated from spontaneous ones using short segments of magnetoencephalography (MEG) data measured immediately after the fixation onset. Recently proposed convolutional neural networks (CNNs), linear finite impulse response filters CNN (LF-CNN) and vector autoregressive CNN (VAR-CNN), were applied for binary classification of the MEG signals related to spontaneous and voluntary eye fixations collected in healthy participants (n = 25) who performed a game-like task by fixating on targets voluntarily for 500 ms or longer. Voluntary fixations were identified as those followed by a fixation in a special confirmatory area. Spontaneous vs. voluntary fixation-related single-trial 700 ms MEG segments were non-randomly classified in the majority of participants, with the group average cross-validated ROC AUC of 0.66 ± 0.07 for LF-CNN and 0.67 ± 0.07 for VAR-CNN (M ± SD). When the time interval, from which the MEG data were taken, was extended beyond the onset of the visual feedback, the group average classification performance increased up to 0.91. Analysis of spatial patterns contributing to classification did not reveal signs of significant eye movement impact on the classification results. We conclude that the classification of MEG signals has a certain potential to support gaze-based interfaces by avoiding false responses to spontaneous eye fixations on a single-trial basis. Current results for intention detection prior to gaze-based interface's feedback, however, are not sufficient for online single-trial eye fixation classification using MEG data alone, and further work is needed to find out if it could be used in practical applications.

What's Next in Blockchain Research?

Distributed ledger technology, frequently designated as 'blockchain,' is evolving from its hype phase toward greater maturity and long-term value creation. Although many academic communities were initially slow to grasp the technology's numerous potential implications, meanwhile a substantial amount of research is dedicated to investigating the development and impact of blockchain and related technologies. As undertaken, most research projects take a specific homogenous perspective, such as a technical or business viewpoint. To date, blockchain research studies are largely missing a bridge between and across academic disciplines. Given the manifold implications of blockchain technology, a fruitful crossdisciplinary exchange is therefore needed. In this paper, we bring together researchers with varying expertise to provide a vision into what may be next in terms of concepts, applications, and research agendas. We consider business, economic, societal, legal, technical, and philosophical viewpoints and propose multiple research questions as well as hypotheses arising from these diverse viewpoints. Simultaneously, we challenge various academic communities to tackle some of the most crucial issues of current blockchain research and to develop a solid foundation for future exploration.

Summary of over Fifty Years with Brain-Computer Interfaces-A Review

Over the last few decades, the Brain-Computer Interfaces have been gradually making their way to the epicenter of scientific interest. Many scientists from all around the world have contributed to the state of the art in this scientific domain by developing numerous tools and methods for brain signal acquisition and processing. Such a spectacular progress would not be achievable without accompanying technological development to equip the researchers with the proper devices providing what is absolutely necessary for any kind of discovery as the core of every analysis: the data reflecting the brain activity. The common effort has resulted in pushing the whole domain to the point where the communication between a human being and the external world through BCI interfaces is no longer science fiction but nowadays reality. In this work we present the most relevant aspects of the BCIs and all the milestones that have been made over nearly 50-year history of this research domain. We mention people who were pioneers in this area as well as we highlight all the technological and methodological advances that have transformed something available and understandable by a very few into something that has a potential to be a breathtaking change for so many. Aiming to fully understand how the human brain works is a very ambitious goal and it will surely take time to succeed. However, even that fraction of what has already been determined is sufficient e.g., to allow impaired people to regain control on their lives and significantly improve its quality. The more is discovered in this domain, the more benefit for all of us this can potentially bring.

Assessing the Risks Posed by the Convergence of Artificial Intelligence and Biotechnology

Rapid developments are currently taking place in the fields of artificial intelligence (AI) and biotechnology, and applications arising from the convergence of these 2 fields are likely to offer immense opportunities that could greatly benefit human health and biosecurity. The combination of AI and biotechnology could potentially lead to breakthroughs in precision medicine, improved biosurveillance, and discovery of novel medical countermeasures as well as facilitate a more effective public health emergency response. However, as is the case with many preceding transformative technologies, new opportunities often present new risks in parallel. Understanding the current and emerging risks at the intersection of AI and biotechnology is crucial for health security specialists and unlikely to be achieved by examining either field in isolation. Uncertainties multiply as technologies merge, showcasing the need to identify robust assessment frameworks that could adequately analyze the risk landscape emerging at the convergence of these 2 domains.This paper explores the criteria needed to assess risks associated with Artificial intelligence and biotechnology and evaluates 3 previously published risk assessment frameworks. After highlighting their strengths and limitations and applying to relevant Artificial intelligence and biotechnology examples, the authors suggest a hybrid framework with recommendations for future approaches to risk assessment for convergent technologies.

Conceptualising technology, its development and future: The six genres of technology

One approach to developing futuristic views of technology is to draw upon experience and expertise. However, this becomes increasingly speculative as one moves to more distant timelines and visionary technological forms. This raises the question of whether it is possible to rationally predict how a technology development trajectory might unfold into the future, perhaps to some 'ultimate form', that is accessible, surfaces the necessary technological features for development as well as considers the implications for human-artefact relationships. The proposed approach is conceptually grounded in a parsimonious framework that examines different configurations of human-artefact relationships, revealing 'Six Genres of Technology'. This suggests how the shift from human-human to artefact-artefact and the increasing autonomy of the artefacts (technological beings), introduces specific features to each of the six Genres. Four features are identified in the later Genres that in combination, could be construed as, or indeed pose a threat: autonomy, intelligence, language, and autopoiesis. This paper advances the debate about future technological developments by using the proposed framework to structure an argument about the key issues that should be discussed today - so that the developments of tomorrow can be more reflectively considered, appropriately debated and knowingly pursued.

Oxygen and brain death; back from the brink

NEW FINDINGS

• What is the topic of this review? To explore the unique evolutionary origins of the human brain and critically appraise its energy budget, including limits of oxygen and glucose deprivation during anoxia and ischaemia. • What advances does it highlight? The brain appears to be more resilient to substrate depletion than traditionally thought, highlighting greater resilience and an underappreciated capacity for functional recovery.

ABSTRACT

The human brain has evolved into an unusually large, complex and metabolically expensive organ that relies entirely on a continuous supply of O₂ and glucose. It has traditionally been assumed that its exorbitant energy budget, combined with little to no energy reserves, renders it especially vulnerable to anoxia and ischaemia, with substrate depletion and progression towards cell death largely irreversible and rapid. However, new and exciting evidence suggests that neurons can survive for longer than previously thought, highlighting an unexpected resilience and underappreciated capacity for functional recovery that has changed the way we think about brain cell death. Nature has the potential to unlock some of the mysteries underlying ischaemic survival, with select vertebrates having solved the problem of anoxia-hypoxia tolerance over millions of years of evolution. Better understanding of their survival strategies, including remarkable adaptations in brain physiology and redox homeostasis, might help to identify new therapeutic targets for human diseases characterized by O₂ deprivation, ischaemia-reperfusion injury and ageing.

Bacomics: a comprehensive cross area originating in the studies of various brain-apparatus conversations

The brain is the most important organ of the human body, and the conversations between the brain and an apparatus can not only reveal a normally functioning or a dysfunctional brain but also can modulate the brain. Here, the apparatus may be a nonbiological instrument, such as a computer, and the consequent brain-computer interface is now a very popular research area with various applications. The apparatus may also be a biological organ or system, such as the gut and muscle, and their efficient conversations with the brain are vital for a healthy life. Are there any common bases that bind these different scenarios? Here, we propose a new comprehensive cross area: Bacomics, which comes from brain-apparatus conversations (BAC) + omics. We take Bacomics to cover at least three situations: (1) The brain is normal, but the conversation channel is disabled, as in amyotrophic lateral sclerosis. The task is to reconstruct or open up new channels to reactivate the brain function. (2) The brain is in disorder, such as in Parkinson's disease, and the work is to utilize existing or open up new channels to intervene, repair and modulate the brain by medications or stimulation. (3) Both the brain and channels are in order, and the goal is to enhance coordinated development between the brain and apparatus. In this paper, we elaborate the connotation of BAC into three aspects according to the information flow: the issue of output to the outside (BAC-1), the issue of input to the brain (BAC-2) and the issue of unity of brain and apparatus (BAC-3). More importantly, there are no less than five principles that may be taken as the cornerstones of Bacomics, such as feedforward and feedback control, brain plasticity, harmony, the unity of opposites and systems principles. Clearly, Bacomics integrates these seemingly disparate domains, but more importantly, opens a much wider door for the research and development of the brain, and the principles further provide the general framework in which to realize or optimize these various conversations.

Optimizing Computer-Brain Interface Parameters for Non-invasive Brain-to-Brain Interface

A non-invasive, brain-to-brain interface (BBI) requires precision neuromodulation and high temporal resolution as well as portability to increase accessibility. A BBI is a combination of the brain-computer interface (BCI) and the computer-brain interface (CBI). The optimization of BCI parameters has been extensively researched, but CBI has not. Parameters taken from the BCI and CBI literature were used to simulate a two-class medical monitoring BBI system under a wide range of conditions. BBI function was assessed using the information transfer rate (ITR), measured in bits per trial and bits per minute. The BBI ITR was a function of classifier accuracy, window update rate, system latency, stimulation failure rate (SFR), and timeout threshold. The BCI parameters, including window length, update rate, and classifier accuracy, were kept constant to investigate the effects of varying the CBI parameters, including system latency, SFR, and timeout threshold. Based on passively monitoring BCI parameters, a base ITR of 1 bit/trial was used. The optimal latency was found to be 100 ms or less, with a threshold no more than twice its value. With the optimal latency and timeout parameters, the system was able to maintain near-maximum efficiency, even with a 25% SFR. When the CBI and BCI parameters are compared, the CBI's system latency and timeout threshold should be reflected in the BCI's update rate. This would maximize the number of trials, even at a high SFR. These findings suggested that a higher number of trials per minute optimizes the ITR of a non-invasive BBI. The delays innate to each BCI protocol and CBI stimulation method must also be accounted for. The high latencies in each are the primary constraints of non-invasive BBI for the foreseeable future.

Transcending the brain: is there a cost to hacking the nervous system?

Great advancements have recently been made to understand the brain and the potential that we can extract out of it. Much of this has been centred on modifying electrical activity of the nervous system for improved physical and cognitive performance in those with clinical impairment. However, there is a risk of going beyond purely physiological performance improvements and striving for human enhancement beyond traditional human limits. Simple ethical guidelines and legal doctrine must be examined to keep ahead of technological advancement in light of the impending mergence between biology and machine. By understanding the role of modern ethics, this review aims to appreciate the fine boundary between what is considered ethically justified for current neurotechnology.