The Morphospace of Consciousness

We construct a complexity-based morphospace to study systems-level properties of conscious & intelligent systems. The axes of this space label 3 complexity types: autonomous, cognitive & social. Given recent proposals to synthesize consciousness, a generic complexity-based conceptualization provides a useful framework for identifying defining features of conscious & synthetic systems. Based on current clinical scales of consciousness that measure cognitive awareness and wakefulness, we take a perspective on how contemporary artificially intelligent machines & synthetically engineered life forms measure on these scales. It turns out that awareness & wakefulness can be associated to computational & autonomous complexity respectively. Subsequently, building on insights from cognitive robotics, we examine the function that consciousness serves, & argue the role of consciousness as an evolutionary game-theoretic strategy. This makes the case for a third type of complexity for describing consciousness: social complexity. Having identified these complexity types, allows for a representation of both, biological & synthetic systems in a common morphospace. A consequence of this classification is a taxonomy of possible conscious machines. We identify four types of consciousness, based on embodiment: (i) biological consciousness, (ii) synthetic consciousness, (iii) group consciousness (resulting from group interactions), & (iv) simulated consciousness (embodied by virtual agents within a simulated reality). This taxonomy helps in the investigation of comparative signatures of consciousness across domains, in order to highlight design principles necessary to engineer conscious machines. This is particularly relevant in the light of recent developments at the crossroads of cognitive neuroscience, biomedical engineering, artificial intelligence & biomimetics.Comment: 23 pages, 3 figure

Embodied Artificial Intelligence through Distributed Adaptive Control: An Integrated Framework

In this paper, we argue that the future of Artificial Intelligence research resides in two keywords: integration and embodiment. We support this claim by analyzing the recent advances of the field. Regarding integration, we note that the most impactful recent contributions have been made possible through the integration of recent Machine Learning methods (based in particular on Deep Learning and Recurrent Neural Networks) with more traditional ones (e.g. Monte-Carlo tree search, goal babbling exploration or addressable memory systems). Regarding embodiment, we note that the traditional benchmark tasks (e.g. visual classification or board games) are becoming obsolete as state-of-the-art learning algorithms approach or even surpass human performance in most of them, having recently encouraged the development of first-person 3D game platforms embedding realistic physics. Building upon this analysis, we first propose an embodied cognitive architecture integrating heterogenous sub-fields of Artificial Intelligence into a unified framework. We demonstrate the utility of our approach by showing how major contributions of the field can be expressed within the proposed framework. We then claim that benchmarking environments need to reproduce ecologically-valid conditions for bootstrapping the acquisition of increasingly complex cognitive skills through the concept of a cognitive arms race between embodied agents.Comment: Updated version of the paper accepted to the ICDL-Epirob 2017 conference (Lisbon, Portugal

Effects of Acute Insulin-Induced Hypoglycemia on Indices of Inflammation Putative mechanism for aggravating vascular disease in diabetes

OBJECTIVE: To examine the effects of acute insulin-induced hypoglycemia on inflammation, endothelial dysfunction, and platelet activation in adults with and without type 1 diabetes. RESEARCH DESIGN AND METHODS: We studied 16 nondiabetic adults and 16 subjects with type 1 diabetes during euglycemia (blood glucose 4.5 mmol/l) and hypoglycemia (blood glucose 2.5 mmol/l). Markers of inflammation, thrombosis, and endothelial dysfunction (soluble P-selectin, interleukin-6, von Willebrand factor [vWF], tissue plasminogen activator [tPA], high-sensitivity C-reactive protein [hsCRP], and soluble CD40 ligand [sCD40L]) were measured; platelet-monocyte aggregation and CD40 expression on monocytes were determined using flow cytometry. RESULTS: In nondiabetic participants, platelet activation occurred after hypoglycemia, with increments in platelet-monocyte aggregation and P-selectin (P ≤ 0.02). Inflammation was triggered with CD40 expression increasing maximally at 24 h (3.13 ± 2.3% vs. 2.06 ± 1.0%) after hypoglycemia (P = 0.009). Both sCD40L and hsCRP (P = 0.02) increased with a nonsignificant rise in vWF and tPA, indicating a possible endothelial effect. A reduction in sCD40L, tPA, and P-selectin occurred during euglycemia (P = 0.03, P ≤ 0.006, and P = 0.006, respectively). In type 1 diabetes, both CD40 expression (5.54 ± 4.4% vs. 3.65 ± 1.8%; P = 0.006) and plasma sCD40L concentrations increased during hypoglycemia (peak 3.41 ± 3.2 vs. 2.85 ± 2.8 ng/ml; P = 0.03). Platelet-monocyte aggregation also increased significantly at 24 h after hypoglycemia (P = 0.03). A decline in vWF and P-selectin occurred during euglycemia (P ≤ 0.04). CONCLUSIONS: Acute hypoglycemia may provoke upregulation and release of vasoactive substances in adults with and without type 1 diabetes. This may be a putative mechanism for hypoglycemia-induced vascular injury

Distortion of the Local Magnetic Field Appears to Neither Disrupt Nocturnal Navigation nor Cue Shelter Recognition in the Amblypygid \u3ci\u3eParaphrynus laevifrons\u3c/i\u3e

Many arthropods are known to be sensitive to the geomagnetic field and exploit the field to solve spatial problems. The polarity of the geomagnetic field is used, for instance, as an orientation cue by leafcutter ants as they travel on engineered trails in a rainforest and by Drosophila larvae as they move short distances in search of food. A ubiquitous orientation cue like the geomagnetic field may be especially useful in complex, cluttered environments like rainforests, where the reliability of celestial cues used to navigate in more open environments may be poor. The neotropical amblypygid Paraphrynus laevifrons is a nocturnal arachnid that wanders nightly in the vicinity of its shelter and occasionally travels 30 m or more in the rainforest understory before it returns to its shelter. Here, we conducted a field experiment to determine whether navigation by P. laevifrons is guided by the ambient magnetic field and a complementary laboratory experiment to assess whether a magnetic anomaly could be used to pinpoint the entrance of a shelter. In the field experiment, subjects were fitted with a radio transmitter and a small, powerful magnet or a similar-sized brass disk and displaced 10 m from their shelter. The return rate of magnet-fitted subjects was similar to that of brass-fitted subjects and to that of subjects in an earlier study fitted with only a radio transmitter. In the laboratory experiment, we trained P. laevifrons with a protocol under which the amblypygid Phrynus marginemaculatus rapidly learns—in 1–14 trials over two daily sessions—to associate an olfactory stimulus with access to a shelter. The conditioned stimulus here was a magnetic anomaly characterized by a high total field intensity and a 180° reversal of the polarity of the ambient magnetic field. The magnetic anomaly–shelter contingency was not learned in 50 trials conducted over 10 daily sessions. These results imply prima facie that P. laevifrons does not rely on a magnetic compass to locate or recognize a shelter and, perhaps, that the magnetic field cannot be detected, but alternative explanations are discussed

Diabetes and Driving

Of the nearly 19 million people in the U.S. with diagnosed diabetes (1), a large percentage will seek or currently hold a license to drive. For many, a driver's license is essential to work; taking care of family; securing access to public and private facilities, services, and institutions; interacting with friends; attending classes; and/or performing many other functions of daily life. Indeed, in many communities and areas of the U.S. the use of an automobile is the only (or the only feasible or affordable) means of transportation available. There has been considerable debate whether, and the extent to which, diabetes may be a relevant factor in determining driver ability and eligibility for a license. This position statement addresses such issues in light of current scientific and medical evidence. Sometimes people with a strong interest in road safety, including motor vehicle administrators, pedestrians, drivers, other road users, and employers, associate all diabetes with unsafe driving when in fact most people with diabetes safely operate motor vehicles without creating any meaningful risk of injury to themselves or others. When legitimate questions arise about the medical fitness of a person with diabetes to drive, an individual assessment of that person's diabetes management—with particular emphasis on demonstrated ability to detect and appropriately treat potential hypoglycemia—is necessary in order to determine any appropriate restrictions. The diagnosis of diabetes is not sufficient to make any judgments about individual driver capacity. This document provides an overview of existing licensing rules for people with diabetes, addresses the factors that impact driving for this population, and identifies general guidelines for assessing driver fitness and determining appropriate licensing restrictions

DAC-h3: A Proactive Robot Cognitive Architecture to Acquire and Express Knowledge About the World and the Self

This paper introduces a cognitive architecture for a humanoid robot to engage in a proactive, mixed-initiative exploration and manipulation of its environment, where the initiative can originate from both the human and the robot. The framework, based on a biologically-grounded theory of the brain and mind, integrates a reactive interaction engine, a number of state-of-the art perceptual and motor learning algorithms, as well as planning abilities and an autobiographical memory. The architecture as a whole drives the robot behavior to solve the symbol grounding problem, acquire language capabilities, execute goal-oriented behavior, and express a verbal narrative of its own experience in the world. We validate our approach in human-robot interaction experiments with the iCub humanoid robot, showing that the proposed cognitive architecture can be applied in real time within a realistic scenario and that it can be used with naive users

Recognizing Speech in a Novel Accent: The Motor Theory of Speech Perception Reframed

The motor theory of speech perception holds that we perceive the speech of another in terms of a motor representation of that speech. However, when we have learned to recognize a foreign accent, it seems plausible that recognition of a word rarely involves reconstruction of the speech gestures of the speaker rather than the listener. To better assess the motor theory and this observation, we proceed in three stages. Part 1 places the motor theory of speech perception in a larger framework based on our earlier models of the adaptive formation of mirror neurons for grasping, and for viewing extensions of that mirror system as part of a larger system for neuro-linguistic processing, augmented by the present consideration of recognizing speech in a novel accent. Part 2 then offers a novel computational model of how a listener comes to understand the speech of someone speaking the listener's native language with a foreign accent. The core tenet of the model is that the listener uses hypotheses about the word the speaker is currently uttering to update probabilities linking the sound produced by the speaker to phonemes in the native language repertoire of the listener. This, on average, improves the recognition of later words. This model is neutral regarding the nature of the representations it uses (motor vs. auditory). It serve as a reference point for the discussion in Part 3, which proposes a dual-stream neuro-linguistic architecture to revisits claims for and against the motor theory of speech perception and the relevance of mirror neurons, and extracts some implications for the reframing of the motor theory

Association Between Raised Inflammatory Markers and Cognitive Decline in Elderly People With Type 2 Diabetes: The Edinburgh Type 2 Diabetes Study

OBJECTIVE-To determine whether circulating levels of the inflammatory markers C-reactive protein (CRP), interleukin (IL)-6, and tumor necrosis factor (TNF)-alpha are associated with cognitive ability and estimated lifetime cognitive decline in an elderly population with type 2 diabetes. RESEARCH DESIGN AND METHODS-A cross-sectional study of 1,066 men and women aged 60-75 years with type 2 diabetes and living in Lothian, Scotland (the Edinburgh Type 2 Diabetes Study), was performed. Seven cognitive tests were used to measure abilities in memory, nonverbal reasoning, information processing speed, executive function, and mental flexibility. The results were used to derive a general intelligence factor (g). A vocabulary-based test was administered as an estimate of peak prior cognitive ability. Results on the cognitive tests were assessed for statistical association with inflammatory markers measured in a venous blood sample at the time of cognitive testing. RESULTS-Higher IL-6 and TNF-alpha levels were associated with poorer age- and sex-adjusted scores on the majority of the individual cognitive tests. They were also associated with g using standardized regression coefficients -0.074 to -0.173 (P < 0.05). After adjusting for vocabulary, education level, cardiovascular dysfunction, duration of diabetes, and glycemic control, R,6 remained associated with three of the cognitive tests and with g. CONCLUSIONS-In this representative population of people with type 2 diabetes, elevated circulating levels of inflammatory markers were associated with poorer cognitive ability. IL-6 levels were also associated with estimated lifetime cognitive decline. Diabetes 59:710-713, 201