This extended abstract outlines my invited keynote presentation of the recent work on neuromorphic networks ("CrossNets") based on hybrid CMOS/nanoelectronic ("CMOL") circuits, in the space-saving Q/A format.

The concept of 'self' has been investigated using many methodologies (e.g. the philosophical approach and the neurobiological approach) that has given rise to issues that yielded popular debates. In this paper, I endeavor to employ virtual reality as a new tool for investigating 'self'. Future directions are provided that could be further helpful in advancing our understanding about the self amidst the complexity of culture.

A self-organizing neural network is described that can associate between different modalities and also has the ability to learn perceptual sequences. This architecture is a step towards the development of a complete agent containing simplified versions of all major neural subsystems in a mammal. It aims at exploring as well as takes inspiration from the idea that cognitive function involves an internal simulation of perception and movement. We have tested the architecture in simulations as well as together with real sensors with very encouraging results.

A neural cognitive architecture would be an architecture based on simulated neurons, that provided a set of mechanisms for all cognitive behaviour. Moreover, this would be compatible with biological neural behaviour. As a result, such architectures can both form the basis of a fully-fledged AI and help to explain how cognition emerges from a collection of neurons in the human brain. The development of such a neural cognitive architecture is in its infancy, but a proto-architecture in the form of behaving agents entirely based on simulated neurons is described. These agents take natural language commands, view the environment, plan and act. The development of these agents has led to a series of questions that need to be addressed to advance the development of neural cognitive architectures. These questions include long posed ones where progress has been made, such as the binding and symbol grounding problems; issues about biological architectures including neural models and brain topology; issues of emergent behaviour such as short and long-term Cell Assembly dynamics; and issues of learning such as the stability-plasticity dilemma. These questions can act as a road map for the development of neural cognitive architectures and AIs based on them.

The phenomenon of episodic memory has been studied for over thirty years, but it is only recently that its constructive nature has been shown to be closely linked to the processes underpinning imagination. This paper builds on recent work by the authors in developing architectures for a form of imagination suitable for use in artifacts, and considers how these architectures might be extended to provide a form of episodic memory.

The brain's ability to do this in a self-stabilizing fashion employs several different types of predictive mechanisms. The lack of a single such mechanism is clarified by accumulating theoretical and empirical evidence that brain specialization is governed by computationally complementary processing streams. The present talk will discuss recent progress towards explaining fundamental brain processes such as 3D vision in natural scenes; opticflow based navigation in natural scenes towards goals around obstacles and spatial navigation in the dark; object and scene learning, recognition, and search; cognitiveemotional dynamics that direct motivated attention towards valued goals; adaptive sensory-motor control circuits, such as those that coordinate predictive smooth pursuit and saccadic eye movements; and planning circuits that temporarily represent sequences of events in working memory and learn sequential plans, including repeated events or actions. These competences clarify the global system-level organization as well as the local microcircuit level organization of many brain systems, ranging from form and motion streams in the visual cortex through inferotemporal and parietal cortex, perirhinal and parahippocampal cortex; supplementary and frontal eye fields; orbitofrontal, ventrolateral, and dorsolateral prefrontal cortex; entorhinal and hippocampal cortex; and subcortical areas including basal ganglia, amygdala, superior colliculus, and nucleus reticularis tegmenti pontis. These model systems are being transferred as they become ready to a wide variety of large-scale applications in technology.

This paper claims for a shift towards "the formal sciences" in the cognitive sciences. In order to explain the phenomenon of cognition, including aspects such as learning and intelligence, it is necessary to explore the concepts and methodologies offered by the formal sciences. In particular, category theory is proposed as the most fitting tool for the building of an unified theory of cognition. This paper proposes a radically new view based in category theory is provided. A cognitive model is informally defined as a mapping between two different structures, while a structure is the set of components of a system and their relationships. Put formally in categorical terms, a model is a functor between categories that reflects the structural invariance between them. In the paper, the theory of categories is presented as the best possible framework to deal with complex system modeling -ie: biologically inspired systems that transcend and offer a much more powerful tool kit to deal with the phenomenon of cognition that other purely verbal tools like the psychological categories that Rosch or Harnad refer.

A novel analytical methodology has proven fruitful in developing a functional identification of consciousness with operable mental control structure in human higher brain function. Two operational homologies (one associated with language, the other tool use) derived from mammalian instrumental behavioral competence are identified, each exadaptively accessible: one a specialization of attentive search to (conventional, linguistic) internalized symbolic lexicon; the second being a combination – a co-parallel activation – of symbolically specialized attention with the original external ‘spotlight’ in order to support (deliberative, choice-making) navigational tasking. The mechanism by which consciousness becomes articulated to support the specialized control requirements of three cognitive performance levels is described, in particular for the case of the social bipedal hominid. A single articulated template model is posed to intervene between the incoherent neuronal and the coherently conscious mental level of higher brain operation. This cognitive system theory logic lends itself to an explanation of the exadaptive acquisition of a cognitively objectifiable self-model from within subjective experience, and a plausible heuristic for the systematic building of self-aware mental repertoire is discovered.

The successful development of neural prostheses requires an understanding of the neurobiological bases of cognitive processes, i.e., how the collective activity of populations of neurons results in a higher-level process not predictable based on knowledge of the individual neurons and/or synapses alone. We have been studying and applying novel methods for representing nonlinear transformations of multiple spike train inputs (multiple time series of pulse train inputs) produced by synaptic and field interactions among multiple subclasses of neurons arrayed in multiple layers of incompletely connected units.

The challenge of designing a human-level learner is central to creating a computational equivalent of the human mind. It demands the level of robustness and flexibility of learning that is still only available in biological systems. Therefore, it is essential that we better understand at a computational level how biological systems naturally develop their cognitive and learning functions. In recent years, biologically inspired cognitive architectures (BICA) have emerged as a powerful new approach toward gaining this kind of understanding. The impressive success of BICA-2008 was clear evidence of this trend. As the second event in the series, BICA-2009 continues our attack on the challenge, with the overall atmosphere of excitement and promise, brainstorming, and collaboration.