Autonomic computing architecture for SCADA cyber security

Cognitive computing relates to intelligent computing platforms that are based on the disciplines of artificial intelligence, machine learning, and other innovative technologies. These technologies can be used to design systems that mimic the human brain to learn about their environment and can autonomously predict an impending anomalous situation. IBM first used the term ‘Autonomic Computing’ in 2001 to combat the looming complexity crisis (Ganek and Corbi, 2003). The concept has been inspired by the human biological autonomic system. An autonomic system is self-healing, self-regulating, self-optimising and self-protecting (Ganek and Corbi, 2003). Therefore, the system should be able to protect itself against both malicious attacks and unintended mistakes by the operator

Biofeedback systems for stress reduction: Towards a Bright Future for a Revitalized Field

Stress has recently been baptized as the black death of the 21st century, which illustrates its threat to current health standards. This article proposes biofeedback systems as a means to reduce stress. A concise state-ofthe-art introduction on biofeedback systems is given. The field of mental health informatics is introduced. A compact state-of-the-art introduction on stress (reduction) is provided. A pragmatic solution for the pressing societal problem of illness due to chronic stress is provided in terms of closed loop biofeedback systems. A concise set of such biofeedback systems for stress reduction is presented. We end with the identification of several development phases and ethical concerns

1st INCF Workshop on Global Portal Services for Neuroscience

The goal of this meeting was to map out existing portal services for neuroscience, identify their features and future plans, and outline opportunities for synergistic developments. The workshop discussed alternative formats of future global and integrated portal services

Simultaneous Robotic Manipulation and Functional Magnetic Resonance Imaging: Feasibility in Children with Autism Spectrum Disorders

An unanswered question concerning the neural basis of autism spectrum disorders (ASD) is how sensorimotor deficits in individuals with ASD are related to abnormalities of brain function. We previously described a robotic joystick and video game system that allows us to record functional magnetic resonance images (FMRI) while adult humans make goal- directed wrist motions. We anticipated several challenges in extending this approach to studying goal-directed behaviors in children with ASD and in typically developing (TYP) children. In particular we were concerned that children with autism may express increased levels of anxiety as compared to typically developing children due to the loud sounds and small enclosed space of the MRI scanner. We also were concerned that both groups of children might become restless during testing, leading to an unacceptable amount of head movement. Here we performed a pilot study evaluating the extent to which autistic and typically developing children exhibit anxiety during our experimental protocol as well as their ability to comply with task instructions. Our experimental controls were successful in minimizing group differences in drop-out due to anxiety. Kinematic performance and head motion also were similar across groups. Both groups of children engaged cortical regions (frontal, parietal, temporal, occipital) while making goal- directed movements. In addition, the ASD group exhibited task- related correlations in subcortical regions (cerebellum, thalamus), whereas correlations in the TYP group did not reach statistical significance in subcortical regions. Four distinct regions in frontal cortex showed a significant group difference such that TYP children exhibited positive correlations between the hemodynamic response and movement, whereas children with ASD exhibited negative correlations. These findings demonstrate feasibility of simultaneous application of robotic manipulation and functional imaging to study goal-directed motor behaviors in autistic and typically developing children. The findings also suggest the presence of marked changes in neural activation during a sensorimotor task requiring goal- directed movement

A proposal for a coordinated effort for the determination of brainwide neuroanatomical connectivity in model organisms at a mesoscopic scale

In this era of complete genomes, our knowledge of neuroanatomical circuitry remains surprisingly sparse. Such knowledge is however critical both for basic and clinical research into brain function. Here we advocate for a concerted effort to fill this gap, through systematic, experimental mapping of neural circuits at a mesoscopic scale of resolution suitable for comprehensive, brain-wide coverage, using injections of tracers or viral vectors. We detail the scientific and medical rationale and briefly review existing knowledge and experimental techniques. We define a set of desiderata, including brain-wide coverage; validated and extensible experimental techniques suitable for standardization and automation; centralized, open access data repository; compatibility with existing resources, and tractability with current informatics technology. We discuss a hypothetical but tractable plan for mouse, additional efforts for the macaque, and technique development for human. We estimate that the mouse connectivity project could be completed within five years with a comparatively modest budget.Comment: 41 page

Neurocognitive Informatics Manifesto.

Informatics studies all aspects of the structure of natural and artificial information systems. Theoretical and abstract approaches to information have made great advances, but human information processing is still unmatched in many areas, including information management, representation and understanding. Neurocognitive informatics is a new, emerging field that should help to improve the matching of artificial and natural systems, and inspire better computational algorithms to solve problems that are still beyond the reach of machines. In this position paper examples of neurocognitive inspirations and promising directions in this area are given

Automated Measurement of Adherence to Traumatic Brain Injury (TBI) Guidelines using Neurological ICU Data

Using a combination of physiological and treatment information from neurological ICU data-sets, adherence to traumatic brain injury (TBI) guidelines on hypotension, intracranial pressure (ICP) and cerebral perfusion pressure (CPP) is calculated automatically. The ICU output is evaluated to capture pressure events and actions taken by clinical staff for patient management, and are then re-expressed as simplified process models. The official TBI guidelines from the Brain Trauma Foundation are similarly evaluated, so the two structures can be compared and a quantifiable distance between the two calculated (the measure of adherence). The methods used include: the compilation of physiological and treatment information into event logs and subsequently process models; the expression of the BTF guidelines in process models within the real-time context of the ICU; a calculation of distance between the two processes using two algorithms (“Direct” and “Weighted”) building on work conducted in th e business process domain. Results are presented across two categories each with clinical utility (minute-by-minute and single patient stays) using a real ICU data-set. Results of two sample patients using a weighted algorithm show a non-adherence level of 6.25% for 42 mins and 56.25% for 708 mins and non-adherence of 18.75% for 17 minutes and 56.25% for 483 minutes. Expressed as two combinatorial metrics (duration/non-adherence (A) and duration * non-adherence (B)), which together indicate the clinical importance of the non-adherence, one has a mean of A=4.63 and B=10014.16 and the other a mean of A=0.43 and B=500.0

1st INCF Workshop on Genetic Animal Models for Brain Diseases

The INCF Secretariat organized a workshop to focus on the “role of neuroinformatics in the processes of building, evaluating, and using genetic animal models for brain diseases” in Stockholm, December 13–14, 2009. Eight scientists specialized in the fields of neuroinformatics, database, ontologies, and brain disease participated together with two representatives of the National Institutes of Health and the European Union, as well as three observers of the national INCF nodes of Norway, Poland, and the United Kingdom