Design for a Brain Revisited: The Neuromorphic Design and Functionality of the Interactive Space 'Ada'

Eng, Kynan; Klein, David; Bäbler, Andreas; Bernardet, Ulysses; Blanchard, Mark; Costa, Márcio O.; Delbrück, Tobi; Douglas, Rodney J.; Hepp, K.; Manzolli, Jônatas; Mintz, Matti; Roth, Fabian C.; Rutishauser, Ueli; Waßermann, Klaus; Whatley, Adrian M.; Wittmann, Aaron; Wyss, Reto; Verschure, Paul F. M. J.

doi:10.1515/revneuro.2003.14.1-2.145

Cited by 21 publications

(12 citation statements)

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“…Moreover, the PVC's overall system will itself be an intelligent entity that learns from the human participants' behavior and sometimes guides them to particular behaviors. The physical, human-accessible gateway to Presenccia's PVC extends a previous interactive space, Ada, 5 into a novel infrastructure that supports the PVC in MR (see Figure 3).…”

Section: Presence: An Example Scenariomentioning

confidence: 94%

Understanding and Realizing Presence in the Presenccia Project

Slater

Frisoli

Tecchia

et al. 2007

IEEE Comput. Grap. Appl.

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Section: Presence: An Example Scenariomentioning

confidence: 94%

Understanding and Realizing Presence in the Presenccia Project

Slater

Frisoli

Tecchia

et al. 2007

IEEE Comput. Grap. Appl.

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“…iqr is used for models of classical conditioning, including models of learning in the auditory cortex (Sánchez-Montañés et al 2000) and the cerebellum (Hofstoetter et al 2002;Herreros et al 2008) The project "Ada: the intelligent space" for the Swiss National Exposition (Expo02) was developed to behave as an artificial creature, interacting with visitors in an intuitive manner, and reflecting our present understanding of neurobiological systems (Eng et al 2003). The Ada project used iqr as its basis for the large scale integration of multiple sensors and effectors.…”

Section: Further Projectsmentioning

confidence: 99%

iqr: A Tool for the Construction of Multi-level Simulations of Brain and Behaviour

Bernardet

Verschure

2010

Neuroinform

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The brain is the most complex system we know of. Despite the wealth of data available in neuroscience, our understanding of this system is still very limited. Here we argue that an essential component in our arsenal of methods to advance our understanding of the brain is the construction of artificial brain-like systems. In this way we can encompass the multi-level organisation of the brain and its role in the context of the complete embodied real-world and real-time perceiving and behaving system. Hence, on the one hand, we must be able to develop and validate theories of brains as closing the loop between perception and action, and on the other hand as interacting with the real world. Evidence is growing that one of the sources of the computational power of neuronal systems lies in the massive and specific connectivity, rather than the complexity of single elements. To meet these challenges-multiple levels of organisation, sophisticated connectivity, and the interaction of neuronal models with the real-world-we have developed a multi-level neuronal simulation environment, iqr. This framework deals with these requirements by directly transforming them into the core elements of the simulation environment itself. iqr provides a means to design complex neuronal models graphically, and to visualise and analyse their properties on-line. In iqr connectivity is defined in a flexible, yet compact way, and simulations run at a high speed, which allows the control of real-world devices-robots in the broader sense-in real-time. The architecture of iqr is modular, providing the possibility to write new neuron, and synapse types, and custom interfaces to other hardware systems. The code of iqr is publicly accessible under the GNU General Public License (GPL). iqr has been in use since 1996 and has been the core tool for a large number of studies ranging from detailed models of neuronal systems like the cerebral cortex, and the cerebellum, to robot based models of perception, cognition and action to large-scale real-world systems. In addition, iqr has been widely used over many years to introduce students to neuronal simulation and neuromorphic control. In this paper we outline the conceptual and methodological background of iqr and its design philosophy. Thereafter we present iqr's main features and computational properties. Finally, we describe a number of projects using iqr, singling out how iqr is used for building a "synthetic insect".

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“…The realistic behavior of the silicon system suggested the possibility of implementation of similar circuits for visual prosthetics. The largest neuromorphic system built to date was an artificial organism 'Ada' that integrated a variety of sensory and behavioral modalities ( [166]). …”

Section: Neuromorphic Engineeringmentioning

confidence: 99%

Some Insights Into Computational Models of (Patho)physiological Brain Activity

et al. 2006

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-The amount of experimental data concerning physiology and anatomy of the nervous system is growing very fast, challenging our capacity to make comprehensive syntheses of the plethora of data available. Computer models of neuronal networks provide useful tools to construct such syntheses. They can be used to interpret experimental data, generate experimentally testable predictions and formulate new hypotheses regarding the function of the neural systems. Models can also act as a bridge between different levels of neuronal organization. The ultimate aim of computational neuroscience is to provide a link between behavior and underlying neural mechanisms. Depending on the specific aim of the model, there are different levels of neuronal organization at which the model can be set. Models are constructed at the microscopic (molecular and cellular), macroscopic level (local populations or systems) or dynamical systems level. Apart from purely computational models, hybrid networks are being developed in which biological neurons are connected in vitro to computer simulated neurons. Also, neuromorphic systems are recently being created using silicon chips that mimic computational operations in the brain. This article reviews various computational models of the brain and insights obtained through their simulations.Index Terms-Brain modeling, computational neuroscience, nervous system, simulation

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Design for a Brain Revisited: The Neuromorphic Design and Functionality of the Interactive Space 'Ada'

Cited by 21 publications

References 1 publication

Understanding and Realizing Presence in the Presenccia Project

Understanding and Realizing Presence in the Presenccia Project

iqr: A Tool for the Construction of Multi-level Simulations of Brain and Behaviour

Some Insights Into Computational Models of (Patho)physiological Brain Activity

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