Scientific requirements for an engineered model of consciousness

The building of a non-natural conscious system requires more than the design of physical or virtual machines with intuitively conceived abilities, philosophically elucidated architecture or hardware homologous to an animal’s brain. Human society might one day treat a type of robot or computing system as an artificial person. Yet that would not answer scientific questions about the machine’s consciousness or otherwise. Indeed, empirical tests for consciousness are impossible because no such entity is denoted within the theoretical structure of the science of mind, i.e. psychology. However, contemporary experimental psychology can identify if a specific mental process is conscious in particular circumstances, by theory-based interpretation of the overt performance of human beings. Thus, if we are to build a conscious machine, the artificial systems must be used as a test-bed for theory developed from the existing science that distinguishes conscious from non-conscious causation in natural systems. Only such a rich and realistic account of hypothetical processes accounting for observed input/output relationships can establish whether or not an engineered system is a model of consciousness. It follows that any research project on machine consciousness needs a programme of psychological experiments on the demonstration systems and that the programme should be designed to deliver a fully detailed scientific theory of the type of artificial mind being developed – a Psychology of that Machine

WHY SCHIZOPHRENIA GENETICS NEEDS EPIGENETICS: A REVIEW

Schizophrenia (SZ) is a highly heritable disorder, with about 80% of the variance attributable to genetic factors. There is accumulating evidence that both common genetic variants with small effects and rare genetic lesions with large effects determine risk of SZ. As recently shown, thousands of common single nucleotide polymorphisms (SNPs), each with small effect, cumulatively could explain about 30% of the underlying genetic risk of SZ. On the other hand, rare and large copy number variants (CNVs) with high but incomplete penetrance, variable in different individual, could explain about additional 30% of SZ cases. Although these rare CNVs frequently develop de novo, it is not clear whether they affect risk independently or via interaction with a polygenic liability in the background. Finally, the role of environmental risk factors has been well established in SZ. Environmental factors are rarely sufficient to cause SZ independently, but act in parallel or in synergy with the underlying genetic liability. Epigenetic misregulation of the genome and direct CNS injury are probably the main mechanism to mediate prenatal environmental effects (e.g., viruses, ethanol, or nutritional deficiency) whereas postnatal risk factors (e.g., stress, urbanicity, cannabis use) may also affect risk via usebased potentiation of vulnerable CNS pathways implicated in SZ. In this review, we outline a general theoretical background of epigenetic mechanisms involved in GxE interactions, and then discuss epigenetic and neurodevelopmental features of SZ based on available information from genetics, epigenetics, epidemiology, neuroscience, and clinical research. We argue that epigenetic model of SZ provides a framework to integrate a variety of diverse empirical data into a powerful etiopathogenetic synthesis. The promising future of this model is the possibility to develop truly specific prevention and treatment strategies for SZ

Multilevel distributed diagnosis and the design of a distributed network fault detection system based on the SNMP protocol.

In this thesis, we propose a new distributed diagnosis algorithm using the multilevel paradigm. This algorithm is a generalization of both the ADSD and Hi-ADSD algorithms. We present all details of the design and implementation of this multilevel adaptive distributed diagnosis algorithm called the ML-ADSD algorithm. We also present extensive simulation results comparing the performance of these three algorithms.In 1967, Preparata, Metze and Chien proposed a model and a framework for diagnosing faulty processors in a multiprocessor system. To exploit the inherent parallelism available in a multiprocessor system and thereby improving fault tolerance, Kuhl and Reddy, in 1980, pioneered a new area of research known as distributed system level diagnosis. Following this pioneering work, in 1991, Bianchini and Buskens proposed an adaptive distributed algorithm to diagnose fully connected networks. This algorithm called the ADSD algorithm has a diagnosis latency of O(N) testing rounds for a network with N nodes. With a view to improving the diagnosis latency of the ADSD algorithm, in 1998 Duarte and Nanya proposed a hierarchical distributed diagnosis algorithm for fully connected networks. This algorithm called the Hi-ADSD algorithm has a diagnosis latency of O(log2N) testing rounds. The Hi-ADSD algorithm can be viewed as a generalization of the ADSD algorithm.In all cases, the time required by the ML-ADSD algorithm is better than or the same as for the Hi-ADSD algorithm. The performance of the ML-ADSD algorithm can be improved by an appropriate choice of the number of clusters and the number of levels. Also, the ML-ADSD algorithm is scalable in the sense that only some minor modifications will be required to adapt the algorithm to networks of varying sizes. This property is not shared by the Hi-ADSD algorithm. The primary application of our research is to develop and implement a prototype network fault detection/monitoring system by integrating the ML-ADSD algorithm into a SNMP-based (Simple Network Management Protocol) fault management system. We report the details of the design and implementation of such a distributed network fault detection system

Prevalence, aetiology and maintenance of poor psychological morbidity following a minor road traffic accident: A prospective longitudinal study

The current study aimed to investigate the prevalence, aetiology and maintenance of poor psychological morbidity following a minor road traffic accident (RTA). A prospective longitudinal research design was employed and participants completed assessments within one month of their RTA and three months later. It was anticipated that, in accordance with published empirical evidence, participants would report clinically significant levels of anxiety, depression and Post-Traumatic Stress Disorder (PTSD). Informed by recent cognitive conceptualisations of PTSD (e.g. Ehlers and Clark, 2000; Brewin et al., 1996) it was hypothesised that a number of psychological factors would predict and maintain PTSD. It was found that in this sample of minor-RTA victims clinically significant levels of anxiety, depression and PTSD were present. Further examination revealed that PTSD could be significantly predicted by a number of independent variables. Anxiety sensitivity, immediate post-traumatic reaction and peri-traumatic dissociation were all found to predict PTSD. Negative interpretation of symptoms, rumination and thought suppression (taken together) were found to heavily mediate the relationships of all these predictive factors with follow-up PTSD. These maintenance factors were the only variables to independently and significantly predict follow-up PTSD. The results reinforce the importance of both negative attribution and avoidant coping in the persistence of PTSD and a number of clinical and theoretical implications are discussed

Understanding Political Radicalization: The Two-Pyramids Model

This article reviews some of the milestones of thinking about political radicalization, as scholars and security officials struggled after 9/11 to discern the precursors of terrorist violence. Recent criticism of the concept of radicalization has been recognized, leading to a 2-pyramids model that responds to the criticism by separating radicalization of opinion from radicalization of action. Security and research implications of the 2-pyramids model are briefly described, ending with a call for more attention to emotional experience in understanding both radicalization of opinion and radicalization of action

Understanding Political Radicalization: The Two-Pyramids Model

This article reviews some of the milestones of thinking about political radicalization, as scholars and security officials struggled after 9/11 to discern the precursors of terrorist violence. Recent criticism of the concept of radicalization has been recognized, leading to a 2-pyramids model that responds to the criticism by separating radicalization of opinion from radicalization of action. Security and research implications of the 2-pyramids model are briefly described, ending with a call for more attention to emotional experience in understanding both radicalization of opinion and radicalization of action

Neuronal nicotinic acetylcholine receptors: common molecular substrates of nicotine and alcohol dependence

Alcohol and nicotine are often co-abused. As many as 80-95% of alcoholics are also smokers, suggesting that ethanol and nicotine, the primary addictive component of tobacco smoke, may functionally interact in the central nervous system and/or share a common mechanism of action. While nicotine initiates dependence by binding to and activating neuronal nicotinic acetylcholine receptors (nAChRs), ligand-gated cation channels normally activated by endogenous acetylcholine (ACh), ethanol is much less specific with the ability to modulate multiple gene products including those encoding voltage-gated ion channels, and excitatory/inhibitory neurotransmitter receptors. However, emerging data indicate that ethanol interacts with nAChRs, both directly and indirectly, in the mesocorticolimbic dopaminergic (DAergic) reward circuitry to affect brain reward systems. Like nicotine, ethanol activates DAergic neurons of the ventral tegmental area (VTA) which project to the nucleus accumbens (NAc). Blockade of VTA nAChRs reduces ethanol-mediated activation of DAergic neurons, NAc DA release, consumption, and operant responding for ethanol in rodents. Thus, ethanol may increase ACh release into the VTA driving activation of DAergic neurons through nAChRs. In addition, ethanol potentiates distinct nAChR subtype responses to ACh and nicotine in vitro and in DAergic neurons. The smoking cessation therapeutic and nAChR partial agonist, varenicline, reduces alcohol consumption in heavy drinking smokers and rodent models of alcohol consumption. Finally, single nucleotide polymorphisms in nAChR subunit genes are associated with alcohol dependence phenotypes and smoking behaviors in human populations. Together, results from pre-clinical, clinical, and genetic studies indicate that nAChRs may have an inherent role in the abusive properties of ethanol, as well as in nicotine and alcohol co-dependence

A systematic review of childhood maltreatment and resting state functional connectivity

Resting-state functional connectivity (rsFC) has the potential to shed light on how childhood abuse and neglect relates to negative psychiatric outcomes. However, a comprehensive review of the impact of childhood maltreatment on the brain's resting state functional organization has not yet been undertaken. We systematically searched rsFC studies in children and youth exposed to maltreatment. Nineteen studies (total n = 3079) met our inclusion criteria. Two consistent findings were observed. Childhood maltreatment was linked to reduced connectivity between the anterior insula and dorsal anterior cingulate cortex, and with widespread heightened amygdala connectivity with key structures in the salience, default mode, and prefrontal regulatory networks. Other brain regions showing altered connectivity included the ventral anterior cingulate cortex, dorsolateral prefrontal cortex, and hippocampus. These patterns of altered functional connectivity associated with maltreatment exposure were independent of symptoms, yet comparable to those seen in individuals with overt clinical disorder. Summative findings indicate that rsFC alterations associated with maltreatment experience are related to poor cognitive and social functioning and are prognostic of future symptoms. In conclusion, maltreatment is associated with altered rsFC in emotional reactivity, regulation, learning, and salience detection brain circuits. This indicates patterns of recalibration of putative mechanisms implicated in maladaptive developmental outcomes