2D printed multicellular devices performing digital and analogue computation

Much effort has been expended on building cellular computational devices for different applications. Despite the significant advances, there are still several addressable restraints to achieve the necessary technological transference. These improvements will ease the development of end-user applications working out of the lab. In this study, we propose a methodology for the construction of printable cellular devices, digital or analogue, for different purposes. These printable devices are designed to work in a 2D surface, in which the circuit information is encoded in the concentration of a biological signal, the so-called carrying signal. This signal diffuses through the 2D surface and thereby interacts with different device components. These components are distributed in a specific spatial arrangement and perform the computation by modulating the level of the carrying signal in response to external inputs, determining the final output. For experimental validation, 2D cellular circuits are printed on a paper surface by using a set of cellular inks. As a proof-of-principle, we have printed and analysed both digital and analogue circuits using the same set of cellular inks but with different spatial topologies. The proposed methodology can open the door to a feasible and reliable industrial production of cellular circuits for multiple applications.

Magnitudes

A new realistic account of an ontology of extensive magnitudes is developed, formulated in Seven Principles. The principles are defended by the role of magnitudes in scientific explanation and in counterfactuals. Scientific laws can be formulated using this ontology of magnitudes. A metaphysics-first view of the perception of magnitudes is then defended by using this metaphysics of magnitudes. The metaphysics-first treatment permits explanation of features of the perception of extensive magnitudes. Notions of analogue computation, analogue representation, and analogue content are explained using this apparatus. Deployment of the resulting theory allows the development, against Kuhn, of a case for the objectivity of analogue perceptual content.

The Primacy of Metaphysics

Is the metaphysics of a domain prior in the order of philosophical explanation to a theory of intentional contents and meanings about that domain? Or is the opposite true? This book argues from the nature of meaning and intentional content to the conclusion that content and meaning are never prior to the metaphysics. For every domain, either a metaphysics-first view or a no-priority view is correct. Metaphysics-first views are developed for several specific domains. For extensive magnitudes, a new realistic metaphysics is developed, and this metaphysics is used to explain features of the perception of magnitudes, and to elucidate analogue computation and analogue representation. A metaphysics-first treatment of time is developed and used to develop new accounts of temporal representation, and to address some puzzles about time and present-tense content. A metaphysics-first treatment of subject and the first person develops a new account of the ownership of mental events by subjects, and argues for a greater role of agency in the first person than in earlier accounts. A noncausal metaphysics-first view is developed for the natural numbers and the real numbers. The account gives an explanatory priority to the application of numbers to properties and to ratios of magnitudes. The final chapter of the book argues the materials earlier in the book permit a new account of the limits of intelligibility. Spurious concepts, such as absolute space, are ones for which there is no account of the relation that would have to hold for a thinker to latch onto it.

Distributed neural blackboards could be more attractive

The target article demonstrates how neurocognitive modellers should not be intimidated by challenges such as Jackendoff's and should explore neurally plausible implementations of linguistic constructs. The next step is to take seriously insights offlered by neuroscience, including the robustness allowed by analogue computation with distributed representations and the power of attractor dynamics in turning analogue into nearly discrete operations.