Human-machine symbiosis overview

The interface between humans and technology is a rapidly changing field. In particular as technological methods have improved dramatically so interaction has become possible that could only be speculated about even a decade earlier. This interaction can though take on a wide range of forms. Indeed standard buttons and dials with televisual feedback are perhaps a common example. But now virtual reality systems, wearable computers and most of all, implant technology are throwing up a completely new concept, namely a symbiosis of human and machine. No longer is it sensible simply to consider how a human interacts with a machine, but rather how the human-machine symbiotic combination interacts with the outside world. In this paper we take a look at some of the recent approaches, putting implant technology in context. We also consider some specific practical examples which may well alter the way we look at this symbiosis in the future. The main area of interest as far as symbiotic studies are concerned is clearly the use of implant technology, particularly where a connection is made between technology and the human brain and/or nervous system. Often pilot tests and experimentation has been carried out apriori to investigate the eventual possibilities before human subjects are themselves involved. Some of the more pertinent animal studies are discussed briefly here. The paper however concentrates on human experimentation, in particular that carried out by the authors themselves, firstly to indicate what possibilities exist as of now with available technology, but perhaps more importantly to also show what might be possible with such technology in the future and how this may well have extensive social effects. The driving force behind the integration of technology with humans on a neural level has historically been to restore lost functionality in individuals who have suffered neurological trauma such as spinal cord damage, or who suffer from a debilitating disease such as lateral amyotrophic sclerosis. Very few would argue against the development of implants to enable such people to control their environment, or some aspect of their own body functions. Indeed this technology in the short term has applications for amelioration of symptoms for the physically impaired, such as alternative senses being bestowed on a blind or deaf individual. However the issue becomes distinctly more complex when it is proposed that such technology be used on those with no medical need, but instead who wish to enhance and augment their own bodies, particularly in terms of their mental attributes. These issues are discussed here in the light of practical experimental test results and their ethical consequences.

Towards natural human computer interaction in BCI

BCI systems require correct classification of signals interpreted from the brain for useful operation. To this end this paper investigates a method proposed in [1] to correctly classify a series of images presented to a group of subjects in [2]. We show that it is possible to use the proposed methods to correctly recognise the original stimuli presented to a subject from analysis of their EEG. Additionally we use a verification set to show that the trained classification method can be applied to a different set of data. We go on to investigate the issue of invariance in EEG signals. That is, the brain representation of similar stimuli is recognisable across different subjects. Finally we consider the usefulness of the methods investigated towards an improved BCI system and discuss how it could potentially lead to great improvements in the ease of use for the end user by offering an alternative, more intuitive control based mode of operation.

An attempt to extend human sensory capabilities by means of implant technology

In this paper an attempt is described to increase the range of human sensory capabilities by means of implant technology. The key aim is to create an additional sense by feeding signals directly to the human brain, via the nervous system rather than via a presently operable human sense. Neural implant technology was used to directly interface a human nervous system with a computer in a one off trial. The output from active ultrasonic sensors was then employed to directly stimulate the human nervous system. An experimental laboratory set up was used as a test bed to assess the usefulness of this sensory addition.

Linking human and machine brains

A look is taken here at how the use of implant technology is rapidly diminishing the effects of certain neural illnesses and distinctly increasing the range of abilities of those affected. An indication is given of a number of problem areas in which such technology has already had a profound effect, a key element being the need for a clear interface linking the human brain directly with a computer. In order to assess the possible opportunities, both human and animal studies are reported on. The main thrust of the paper is however a discussion of neural implant experimentation linking the human nervous system bi-directionally with the internet. With this in place neural signals were transmitted to various technological devices to directly control them, in some cases via the internet, and feedback to the brain was obtained from such as the fingertips of a robot hand, ultrasonic (extra) sensory input and neural signals directly from another human's nervous system. Consideration is given to the prospects for neural implant technology in the future, both in the short term as a therapeutic device and in the long term as a form of enhancement, including the realistic potential for thought communication potentially opening up commercial opportunities. Clearly though, an individual whose brain is part human - part machine can have abilities that far surpass those with a human brain alone. Will such an individual exhibit different moral and ethical values to those of a human.? If so, what effects might this have on society?

A question of identity - wiring in the human

This paper discusses the RFID implants for identification via a sensor network. Brain-computer implants linked in to a wireless network. Biometric identification via body sensors is also discussed. The use of a network as a means for remote and distance monitoring of humans opens up a range of potential uses. Where implanted identification is concerned this immediately offers high security access to specific areas by means of only an RFID device. If a neural implant is employed then clearly the information exchanged with a network can take on a much richer form, allowing for identification and response to an individual's needs based on the signals apparent on their nervous system.

On linking human and machine brains

A look is taken here at how the use of implant technology is rapidly diminishing the effects of certain neural illnesses and distinctly increasing the range of abilities of those affected. An indication is given of a number of problem areas in which such technology has already had a profound effect, a key element being the need for a clear interface linking the human brain directly with a computer. In order to assess the possible opportunities, both human and animal studies are reported on. The main thrust of the paper is, however, a discussion of neural implant experimentation linking the human nervous system bi-directionally with the internet. With this in place, neural signals were transmitted to various technological devices to directly control them, in some cases via the internet, and feedback to the brain was obtained from, for example, the fingertips of a robot hand, and ultrasonic (extra) sensory input and neural signals directly from another human's nervous system. Consideration is given to the prospects for neural implant technology in the future, both in the short term as a therapeutic device and in the long term as a form of enhancement, including the realistic potential for thought communication-potentially opening up commercial opportunities. Clearly though, an individual whose brain is part human-part machine can have abilities that far surpass those with a human brain alone. Will such an individual exhibit different moral and ethical values from those of a human? If so, what effects might this have on society? (C) 2008 Elsevier B.V. All rights reserved.

Chronic hypoxia in the human neuroblastoma SH-SY5Y causes reduced expression of the putative alpha-secretases, ADAM10 and TACE, without altering their mRNA levels

Alzheimer's disease is more frequent following an ischemic or hypoxic episode, with levels of beta-amyloid peptides elevated in brains from patients. Similar increases are found after experimental ischemia in animals. It is possible that increased beta-amyloid deposition arises from alterations in amyloid precursor protein (APP) metabolism, indeed, we have shown that exposing cells of neuronal origin to chronic hypoxia decreased the secretion of soluble APP (sAPPalpha) derived by action of alpha-secretase on APP, coinciding with a decrease in protein levels of ADAM10, a disintegrin metalloprotease which is thought to be the major alpha-secretase. In the current study, we extended those observations to determine whether the expression of ADAM10 and another putative alpha-secretase, TACE, as well as the beta-secretase, BACE1 were regulated by chronic hypoxia at the level of protein and mRNA. Using Western blotting and RT-PCR, we demonstrate that after 48 h chronic hypoxia, such that sAPPalpha secretion is decreased by over 50%, protein levels of ADAM10 and TACE and by approximately 60% and 40% respectively with no significant decrease in BACE1 levels. In contrast, no change in the expression of the mRNA for these proteins could be detected. Thus, we conclude that under CH the level of the putative alpha-secretases, ADAM10 and TACE are regulated by post-translational mechanisms, most probably proteolysis, rather than at the level of transcription.

A novel scheme for human-friendly and time-delays robust neuropredictive teleoperation

A novel Neuropredictive Teleoperation (NPT) Scheme is presented. The design results from two key ideas: the exploitation of the measured or estimated neural input to the human arm or its electromyograph (EMG) as the system input and the employment of a predictor of the arm movement, based on this neural signal and an arm model, to compensate for time delays in the system. Although a multitude of such models, as well as measuring devices for the neural signals and the EMG, have been proposed, current telemanipulator research has only been considering highly simplified arm models. In the present design, the bilateral constraint that the master and slave are simultaneously compliant to each other's state (equal positions and forces) is abandoned, thus obtaining a simple to analyzesuccession of only locally controlled modules, and a robustness to time delays of up to 500 ms. The proposed designs were inspired by well established physiological evidence that the brain, rather than controlling the movement on-line, programs the arm with an action plan of a complete movement, which is then executed largely in open loop, regulated only by local reflex loops. As a model of the human arm the well-established Stark model is employed, whose mathematical representation is modified to make it suitable for an engineering application. The proposed scheme is however valid for any arm model. BIBO-stability and passivity results for a variety of local control laws are reported. Simulation results and comparisons with traditional designs also highlight the advantages of the proposed design.

The future of human-machine interaction: implant technology

In this paper a look is taken at how the use of implant and electrode technology can be employed to create biological brains for robots, to enable human enhancement and to diminish the effects of certain neural illnesses. In all cases the end result is to increase the range of abilities of the recipients. An indication is given of a number of areas in which such technology has already had a profound effect, a key element being the need for a clear interface linking a biological brain directly with computer technology. The emphasis is placed on practical scientific studies that have been and are being undertaken and reported on. The area of focus is the use of electrode technology, where either a connection is made directly with the cerebral cortex and/or nervous system or where implants into the human body are involved. The paper also considers robots that have biological brains in which human neurons can be employed as the sole thinking machine for a real world robot body.

Adaptive evolution of four microcephaly genes and the evolution of brain size in anthropoid primates

The anatomical basis and adaptive function of the expansion in primate brain size have long been studied; however, we are only beginning to understand the genetic basis of these evolutionary changes. Genes linked to human primary microcephaly have received much attention as they have accelerated evolutionary rates along lineages leading to humans. However, these studies focus narrowly on apes, and the link between microcephaly gene evolution and brain evolution is disputed. We analyzed the molecular evolution of four genes associated with microcephaly (ASPM, CDK5RAP2, CENPJ, MCPH1) across 21 species representing all major clades of anthropoid primates. Contrary to prevailing assumptions, positive selection was not limited to or intensified along the lineage leading to humans. In fact we show that all four loci were subject to positive selection across the anthropoid primate phylogeny. We developed clearly defined hypotheses to explicitly test if selection on these loci was associated with the evolution of brain size. We found positive relationships between both CDK5RAP2 and ASPM and neonatal brain mass and somewhat weaker relationships between these genes and adult brain size. In contrast, there is no evidence linking CENPJ and MCPH1 to brain size evolution. The stronger association of ASPM and CDK5RAP2 evolution with neonatal brain size than with adult brain size is consistent with these loci having a direct effect on prenatal neuronal proliferation. These results suggest that primate brain size may have at least a partially conserved genetic basis. Our results contradict a previous study that linked adaptive evolution of ASPM to changes in relative cortex size; however, our analysis indicates that this conclusion is not robust. Our finding that the coding regions of two widely expressed loci has experienced pervasive positive selection in relation to a complex, quantitative developmental phenotype provides a notable counterexample to the commonly asserted hypothesis that cisregulatory regions play a dominant role in phenotypic evolution. Key words: ASPM, MCPH1, CDK5RAP2, CENPJ, brain, neurogenesis, primates.

Intermittently-visual tracking experiments reveal the roles of error-correction and predictive mechanisms in the human visual-motor control system

Prediction mechanism is necessary for human visual motion to compensate a delay of sensory-motor system. In a previous study, “proactive control” was discussed as one example of predictive function of human beings, in which motion of hands preceded the virtual moving target in visual tracking experiments. To study the roles of the positional-error correction mechanism and the prediction mechanism, we carried out an intermittently-visual tracking experiment where a circular orbit is segmented into the target-visible regions and the target-invisible regions. Main results found in this research were following. A rhythmic component appeared in the tracer velocity when the target velocity was relatively high. The period of the rhythm in the brain obtained from environmental stimuli is shortened more than 10%. The shortening of the period of rhythm in the brain accelerates the hand motion as soon as the visual information is cut-off, and causes the precedence of hand motion to the target motion. Although the precedence of the hand in the blind region is reset by the environmental information when the target enters the visible region, the hand motion precedes the target in average when the predictive mechanism dominates the error-corrective mechanism.

Bifurcations and state changes in the human alpha rhythm: Theory and experiment

Despite many decades investigating scalp recordable 8–13-Hz (alpha) electroencephalographic activity, no consensus has yet emerged regarding its physiological origins nor its functional role in cognition. Here we outline a detailed, physiologically meaningful, theory for the genesis of this rhythm that may provide important clues to its functional role. In particular we find that electroencephalographically plausible model dynamics, obtained with physiological admissible parameterisations, reveals a cortex perched on the brink of stability, which when perturbed gives rise to a range of unanticipated complex dynamics that include 40-Hz (gamma) activity. Preliminary experimental evidence, involving the detection of weak nonlinearity in resting EEG using an extension of the well-known surrogate data method, suggests that nonlinear (deterministic) dynamics are more likely to be associated with weakly damped alpha activity. Thus rather than the “alpha rhythm” being an idling rhythm it may be more profitable to conceive it as a readiness rhythm.

Dynamical complexity in a mean-field model of human EEG

A recently proposed mean-field theory of mammalian cortex rhythmogenesis describes the salient features of electrical activity in the cerebral macrocolumn, with the use of inhibitory and excitatory neuronal populations (Liley et al 2002). This model is capable of producing a range of important human EEG (electroencephalogram) features such as the alpha rhythm, the 40 Hz activity thought to be associated with conscious awareness (Bojak & Liley 2007) and the changes in EEG spectral power associated with general anesthetic effect (Bojak & Liley 2005). From the point of view of nonlinear dynamics, the model entails a vast parameter space within which multistability, pseudoperiodic regimes, various routes to chaos, fat fractals and rich bifurcation scenarios occur for physiologically relevant parameter values (van Veen & Liley 2006). The origin and the character of this complex behaviour, and its relevance for EEG activity will be illustrated. The existence of short-lived unstable brain states will also be discussed in terms of the available theoretical and experimental results. A perspective on future analysis will conclude the presentation.

Human frontal lobes are not relatively large

One of the most pervasive assumptions about human brain evolution is that it involved relative enlargement of the frontal lobes. We show that this assumption is without foundation. Analysis of five independent data sets using correctly scaled measures and phylogenetic methods reveals that the size of human frontal lobes, and of specific frontal regions, is as expected relative to the size of other brain structures. Recent claims for relative enlargement of human frontal white matter volume, and for relative enlargement shared by all great apes, seem to be mistaken. Furthermore, using a recently developed method for detecting shifts in evolutionary rates, we find that the rate of change in relative frontal cortex volume along the phylogenetic branch leading to humans was unremarkable and that other branches showed significantly faster rates of change. Although absolute and proportional frontal region size increased rapidly in humans, this change was tightly correlated with corresponding size increases in other areas andwhole brain size, and with decreases in frontal neuron densities. The search for the neural basis of human cognitive uniqueness should therefore focus less on the frontal lobes in isolation and more on distributed neural networks.