Dan V. Nicolau: “What is intelligence? The case for fungal (and bacterial) intelligence”
CiNet 1F Conference Room
Endowed Professor of Engineering
Chair of the Department of Bioengineering Faculty of Engineering, McGill University
Many important problems, e.g., cryptography, network routing, require the exploration a large number of candidate solutions. Because the time required for solving these problems grows exponentially with their size, electronic computers, which operate sequentially, cannot solve them in reasonable timeframe. Unfortunately, the parallel-computation approaches proposed so far, e.g., DNA-, and quantum-computing, suffer from fundamental and practical drawbacks, which prevented their implementation. On the other hand, biological entities, from microorganisms to humans, process information in parallel, routinely, for essential tasks, such as foraging, searching for available space, competition, and cooperation. However, aside of their sheer complexity, parallel biological processes are difficult to harness for parallel computation because of a fundamental difference: biological entities process analog information, e.g., concentration gradients, whereas computing devices process numbers.
Two major classes of motile, self-propelled biological agents could be envisaged: protein linear molecular motors, where cytoskeletal filaments, such as actin filaments or microtubules are propelled by surface-immobilized molecular motors, such as myosin or kinesin, respectively; and microorganisms, such as fungi, motile bacteria and algae. While the technology involving the use of molecular motors-propelled agents advanced steadily in the last two decades, fungi and bacteria are also natural choices for the exploration of microfluidics networks encoding mathematical problems. For instance, the growth behaviour and optimality of space-searching algorithms of several fungal species has been tested in microfluidic mazes and networks. First, it was found that the growth behaviour of all species was strongly modulated by the geometry of micro-confinement. Second, the fungi used a complex growth and space-searching strategy comprising two algorithmic subsets: (i) long-range directional memory of individual hyphae and (ii) inducement of branching by physical obstruction. Third, stochastic simulations using experimentally measured parameters showed that this strategy maximizes both survival and biomass homogeneity in micro-confined networks, producing optimal results only when both algorithms are synergistically used.
The presentation conclude with an overview the several research directions regarding the computation and simulation using biological entities in microfluidics structures, weighing the opportunities and challenges offered by various technological avenues.
Dan, who is a Professor in, and the Head of the Department of Bioengineering at McGill University, has a PhD in Chemical Engineering, a MS in Cybernetics, Informatics & Statistics and a MEng in Polymer Science & Engineering. He has published ~100 papers in peer-reviewed scientific journals, a similar number of full papers in conference proceedings and 6 book chapters. He has edited one book (with U. Muller; on microarray technology and applications), and edited or co-edited the proceedings of 25 conferences. Dan is a Fellow of the International Society of Optical Engineering (SPIE). Dan’s present research aggregates around three themes: (i) micro/nano-structured surfaces for micro/nano-arrays fabricated via classical microlithography, micro-ablation and Atomic Force Microscopy; (ii) dynamic micro/nanodevices, such as microfluidics/lab-on-a-chip and devices based on protein molecular motors, with applications in diagnosis, drug discovery and biocomputation devices; (iii) intelligent-like behaviour of microorganisms in confined spaces, which manifests in the process of survival and growth.