Klaus-Peter Zauner

Robot Control with Biological Cells

At present there exists a large gap in size, performance, adaptability and robustness between natural and artificial information processors for performing coherent perception-action tasks under real-time constraints. Even the simplest organisms have an enviable capability of coping with an unknown dynamic environment. Robots, in contrast, are still clumsy if confronted with such complexity. This paper presents a bio-hybrid architecture developed for exploring an alternate approach to the control of autonomous robots. Circuits prepared from amoeboid plasmodia of the slime mold Physarum polycephalum are interfaced with an omnidirectional hexapod robot. Sensory signals from the macro-physical environment of the robot are transduced to cellular scale and processed using the unique micro-physical features of intracellular information processing. Conversely, the response form the cellular computation is amplified to yield a macroscopic output action in the environment mediated through the robots actuators.

Molecular Information Technology

Abstract Molecular materials are endowed with unique properties of unrivaled potential for high density integration of computing systems. Present applications of molecules range from organic semiconductor materials for low-cost circuits to genetically modified proteins for commercial imaging equipment. To fully realize the potential of molecules in computation, information processing concepts that relinquish narrow prescriptive control over elementary structures and functions are needed, and self-organizing architectures have to be developed. Investigations into qualitatively new concepts of information processing are underway in the areas of reaction-diffusion computing, self-assembly computing, and conformation-based computing. Molecular computing is best considered not as a competitor for conventional computing, but as an opportunity for new applications. Microrobotics and bioimmersive computing are among the domains likely to benefit from advances in molecular computing. Progress will depend on both novel computing concepts and innovations in materials. This article reviews current directions in the use of bulk and single molecules for information processing.

On-chip electrical impedance tomography for imaging biological cells.

Electrical impedance tomography is an imaging technology that spatially characterizes the electrical properties of an object. We present a miniaturized electrical impedance tomography system that can image the electrical conductivity distribution within a two-dimensional cell culture. A chip containing a circular 16-electrode array was fabricated using printed circuit board developing technology and used to inject current and to measure spatial voltage across the object. The signal stimulation and voltage data acquisition were performed using an impedance analyzer, operating in four-electrode mode. An open source software, EIDORS was used for image reconstruction. Finite element modelling was used to simulate the image reconstruction process by imaging two ellipsoidal phantoms in the circular 16-electrode array. The effect of the regularization parameter in the reconstruction algorithm and the influence from noise on the fidelity of the images has been numerically analyzed. Experimentally, we show reconstructed images of a multi-nuclear single cellular organism, Physarum Polycephalum, demonstrating the first step towards impedance imaging of single cells in culture. Our system provides a non-invasive lab-on-a-chip technology for spatially mapping the electrical properties of single cells, which would be significant and useful for diagnostic and clinical applications.

Robot control: from silicon circuitry to cells

Life-like adaptive behaviour is so far an illusive goal in robot control. A capability to act successfully in a complex, ambiguous, and harsh environment would vastly increase the application domain of robotic devices. Established methods for robot control run up against a complexity barrier, yet living organisms amply demonstrate that this barrier is not a fundamental limitation. To gain an understanding of how the nimble behaviour of organisms can be duplicated in made-for-purpose devices we are exploring the use of biological cells in robot control. This paper describes an experimental setup that interfaces an amoeboid plasmodium of Physarum polycephalum with an omnidirectional hexapod robot to realise an interaction loop between environment and plasticity in control. Through this bio-electronic hybrid architecture the continuous negotiation process between local intracellular reconfiguration on the micro-physical scale and global behaviour of the cell in a macroscale environment can be studied in a device setting.

DNA as a vehicle for the self-assembly model of computing

A DNA version of the self-assembly model of computing, feasible using currently available laboratory techniques, is proposed. Input signals are coded into unmethylated and methylated oligonucleotides which then hybridize with a backbone that contains complementary sequences. Different input signal patterns are thus represented as DNA duplexes with distinctly different conformational dynamics, in particular different equilibria of B and Z DNA. The pattern classification activity of the system is mediated by the interactions that lead to the secondary structural organization. Circular dichroism may be used for readout.

Molecular Approach to Informal Computing

Abstract Cells and organisms are natural molecular computers. The problem domains effectively addressed by these systems are complementary to, and in fundamental respects far exceed, the domains addressable by current computing devices. The vast majority of information processing problems do not have sufficiently compact formal specifications to fall within the reach of programmable machines. Our working hypothesis is that the unique properties of molecular materials are the key to extending information processing technology beyond the narrow limits of formal computing.

Scouting context-sensitive components

Natures gadgets are implemented without being planned and therefore can utilize context-sensitive components. Thus functionality that would require extensive networks of context-free components can be elicited from a minimum of material. Proteins can serve as context-sensitive components for pattern processing applications. We here describe an evolutionary search strategy currently under investigation for its potential use in conjunction with computer controlled fluidics to evaluate the computational capabilities of proteins. Our algorithm employs evolutionary search not to seek an optimum, but to seek surprises. It directs experiments and incrementally constructs an empirical model from their outcome. Reward is given for discovering conditions that exhibit a discrepancy between the prediction of the current model and the experimental result. As unexpected observations are incorporated into the model, the reward associated with them vanishes. Results obtained so far indicate that evolutionary search is a useful paradigm for characterizing the phenomenology of context-sensitive components.

On architectures of circuits implemented in simulated Belousov–Zhabotinsky droplets

When lipid vesicles filled with Belousov-Zhabotinsky (BZ) excitable chemical medium are packed in tight assembles, waves of excitation may travel between the vesicles. When several waves meet in a vesicle some fragments may deflect, others can annihilate or continue their travel undisturbed. By interpreting waves as Boolean values we can construct logical gates and assemble them in large circuits. In numerical modelling we show two architectures of one-bit half-adders implemented in BZ-vesicles.

From prescriptive programming of solid-state devices to orchestrated self-organisation of informed matter

Achieving real-time response to complex, ambiguous, high-bandwidth data is impractical with conventional programming. Only the narrow class of compressible input-output maps can be specified with feasibly sized programs. Present computing concepts enforce formalisms that are arbitrary from the perspective of the physics underlying their implementation. Efficient physical realizations are embarrassed by the need to implement the rigidly specified instructions requisite for programmable systems. The conventional paradigm of erecting strong constraints and potential barriers that narrowly prescribe structure and precisely control system state needs to be complemented with a new approach that relinquishes detailed control and reckons with autonomous building blocks. Brittle prescriptive control will need to be replaced with resilient self-organisation to approach the robustness and efficiency afforded by natural systems. Structure-function self-consistency will be key to the spontaneous generation of functional architectures that can harness novel molecular and nano materials in an effective way for increased computational power.

Towards molecular computing: co-development of microfluidic devices and chemical reaction media.

Microfluidics provides a powerful technology for both the production of molecular computing components and for the implementation of molecular computing architectures. The potential commercial applications of microfluidics drive rapid progress in this field-but at the same time focus interest on materials that are compatible with physiological aqueous conditions. For engineering applications that consider a broader range of physico-chemical conditions the narrow set of established materials for microfluidics can be a challenge. As a consequence of the large surface to volume ratio inherent in microfluidic technology the material of the device can greatly affect the chemistry in the channels of the device. In practice it is necessary to co-develop the chemical medium to be used in the device together with the microfluidic devices. We describe this process for a molecular computing architecture that makes use of excitable lipid-coated droplets of Belousov-Zhabotinsky reaction medium as its active processing components. We identify fluoropolymers with low melting temperature as a suitable substrate for microfluidics to be used in conjunction with Belousov-Zhabotinsky droplets in decane.