Emotions and the perception of pain

As published in the last issue of JAMA (The Journal of the American Medical Association) by Irene Tracey (Oxford University) emotions and motivations play an important role in the mechanisms of the perception of pain in the human brain. Using brain imaging techniques with patients suffering chronic pain neuroscientists have discovered that pain perception areas are activated at the same time as expectation areas. In one hand, anxiety and anticipation can worsen a pain experience. On the other hand, positive experiences can relieve the pain perception.

Cognition and consciousness mechanisms obviously greatly affect the amount of perceived pain. As Tracey argues, pain requires much attention. She has demonstrated that inattentive or amused subjects feel less discomfort when applying heat in the hand. In fact, distraction techniques are being evaluated as painkillers.

Other conscious pain inhibitors are motivations. When a harmful stimulus appears, the perception of the pain can be reduced if there is a reason to ignore the pain. For instance, during the search for food, endogenous opioids are released to eliminate the pain feeling, Tracey explains in her paper.

Interview with Rodolfo Llinás

This is a link to an interview with Rodolfo Llinás conducted by Sérgio Strejilevich in Brain & Mind electronic magazine on Neuroscience:

The body of the interview (excerpt from Brain & Mind electronic magazine number 6. June 1998) is also available below.

Continue reading “Interview with Rodolfo Llinás”

IDA and LIDA

The following systems are based on Baars’ GWT (Global Workspace Theory) and have been developed by University of Memphis Cognitive Computing Research Group:

IDA (Intelligent Distribution Agent) addresses the Navy’s problem of job distribution using the Conscious Agent Framework. IDA is a verycomplex agent that perceives e-mails from sailors, deliberates on the right jobs for the sailor and negotiates with the sailor in the context of sailor’s preferences and Navy’s policies. This project is funded by ONR (Office of Naval Research) and NPRST (Naval Personnel Research, Studies, and Technology).

LIDA (Learning IDA) adds various mode of human-like learning to the IDA architecture, including perceptual, episodic, procedural and attentional learning.

LIDA-AV is applied to the realm of cognitive robotics, LIDA-AV aims to control an autonomous vehicle with the LIDA technology.

CERA

CERA (Conscious and Emotional Reasoning Architecture) is a software architecture that allows the integration of different cognitive components into a single autonomous system. It is designed to be a flexible research framework in which different consciousness and emotion models can be integrated and tested. The CERA native components have been already implemented following the object oriented design methodology. Original design requirements are to fulfil nine modules of reasoning consciousness and their associated functionality [1]. These foundation classes can be extended and modified in a way that the desired models are represented and interrelated. This software engineering process is called CERA instantiation, as it produces a domain specific instance of CERA.

An instantiation called K-CERA (Khepera CERA) is described in [1], where we have adapted the foundation classes for the specific domain of unknown environment exploration using the Khepera robot. CERA foundation classes are designed to integrate reasoning consciousness with the rest of possible cognitive components of a model of the mind. CERA is structured in a three-layer architecture.

CERA layered design. The core layer is where the reasoning consciousness model foundation classes are located. Then, the instantiation layer adds the domain-specific cognitive systems. Finally, the top layer encloses the agent-specific perception and motor systems.

The inner layer, called CERA Core, encloses the reasoning consciousness model. Next layer is the instantiation layer, which contains the domain-specific cognitive components as discussed above. On top of the instantiation layer, an additional so called physical layer is required to adapt the cognitive components to the actual sensorimotor machinery of the autonomous robot.

The CERA core, which comprises the reasoning consciousness modules, defines a framework for implementing versatile cognitive processes. However, the knowledge representation is not concretely defined in this layer. An abstract knowledge class is used in CERA core in order to make the high level RCM processes definition representation-independent. This means that CERA core per se cannot be instantiated. A domain-specific instantiation layer is always required in order to build a complete cognitive model. Analogously, the physical layer is required in order to implement the actual autonomous agent control system.

[1] Arrabales Moreno, R. and Sanchis de Miguel, A. “A Machine Consciousness Approach to Autonomous Mobile Robotics”. In: 5th International Cognitive Robotics Workshop. AAAI-06. Boston, MA. July 2006.

Self-Awareness in Robots

What do robots dream of?

This is the title of a perspective paper published this week in Science written by Christoph Adami. The author argues that robots that create and update internal models of their own structure may be able to better adapt to the world. Indeed, the robot developed by J. C. Bongard, H. Lipson, and V. Zykov is able to self-detect his own damages and generate a new gaits adapted to its new (damaged) situation. This capability can improve the use of robots in dangerous enrironments. Usually, animals adapt their gaits to any injure they may have. However, this is not common in machines. Bongard et al. have developed a four legged robot able to sense its own movements and structure and calculate new adapted gait models after it has suffered a damaged.

Centre for Consciousness

The Australian National University Centre for Consciousness was set up in August 2004 as part of David Chalmers’ ARC Federation Fellowship project. The project statement is as follows:

This project aims to develop a research centre that will be a world leader in the study of consciousness. The focus will be the question: how does human consciousness represent the world? The science of consciousness has seen explosive growth internationally in the last decade, but the relationship between consciousness and representation is not well-understood. Through local and international collaboration, researchers will develop a framework for understanding the representational content of consciousness and will analyze experimental work at the leading edge of neuroscience and cognitive science. This will help us to understand the nature of consciousness itself.

The Centre focuses especially on the nature of consciousness, the nature of representation and intentionality, and on the relationship between these domains. A broad approach is taken to these issues, bringing in relevant work from numerous neighboring areas of philosophy and of cognitive science.

Consciousness and Cognition

Consciousness and Cognition: An International Journal provides a forum for a natural-science approach to the issues of consciousness, voluntary control, and self. The journal features empirical research (in the form of regular articles and short reports) and theoretical articles. Book reviews, integrative theoretical and critical literature reviews, and tutorial reviews are also published. The journal aims to be both scientifically rigorous and open to novel contributions.

Topics of interest include but are not limited to:

• Implicit memory
• Selective and directed attention
• Priming, subliminal or otherwise
• Neuroelectric correlates of awareness and decision-making
• Assessment of awareness; protocol analysis
• The properties of automaticity in perception and action
• Relations between awareness and attention
• Models of the thalamocortical complex
• Blindsight
• The neuropathology of consciousness and voluntary control
• Pathology of self and self-awareness
• The development of the self-concept in children

 Visit Elsevier Consciousness and Cognition description page.