From the primordial soup to self-driving cars: standards and their role in natural and technological innovation

A conceptual framework of evolutionary novelty and innovation

Since 1990 the recognition of deep homologies among metazoan developmental processes and the spread of more mechanistic approaches to developmental biology have led to a resurgence of interest in evolutionary novelty and innovation. Other evolutionary biologists have proposed central roles for behaviour and phenotypic plasticity in generating the conditions for the construction of novel morphologies, or invoked the accessibility of new regions of vast sequence spaces. These approaches contrast with more traditional emphasis on the exploitation of ecological opportunities as the primary source of novelty. This definitional cornucopia reflects differing stress placed on three attributes of novelties: their radical nature, the generation of new taxa, and ecological and evolutionary impact. Such different emphasis has led to conflating four distinct issues: the origin of novel attributes (genes, developmental processes, phenotypic characters), new functions, higher clades and the ecological impact of new structures and functions. Here I distinguish novelty (the origin of new characters, deep character transformations, or new combinations) from innovation, the ecological and evolutionary success of clades. Evidence from the fossil record of macroevolutionary lags between the origin of a novelty and its ecological success demonstrates that novelty may be decoupled from innovation, and only definitions of novelty based on radicality (rather than generativity or consequentiality) can be assessed without reference to the subsequent history of the clade to which a novelty belongs. These considerations suggest a conceptual framework for novelty and innovation, involving: (i) generation of the potential for novelty; (ii) the formation of novel attributes; (iii) refinement of novelties through adaptation; (iv) exploitation of novelties by a clade, which may coincide with a new round of ecological or environmental potentiation; followed by (v) the establishment of innovations through ecological processes. This framework recognizes that there is little empirical support for either the dominance of ecological opportunity, nor abrupt discontinuities (often caricatured as 'hopeful monsters'). This general framework may be extended to aspects of cultural and social innovation.

Innovation: an emerging focus from cells to societies

Innovations are generally unexpected, often spectacular changes in phenotypes and ecological functions. The contributions to this theme issue are the latest conceptual, theoretical and experimental developments, addressing how ecology, environment, ontogeny and evolution are central to understanding the complexity of the processes underlying innovations. Here, we set the stage by introducing and defining key terms relating to innovation and discuss their relevance to biological, cultural and technological change. Discovering how the generation and transmission of novel biological information, environmental interactions and selective evolutionary processes contribute to innovation as an ecosystem will shed light on how the dominant features across life come to be, generalize to social, cultural and technological evolution, and have applications in the health sciences and sustainability.This article is part of the theme issue 'Process and pattern in innovations from cells to societies'.

Neuromorphic neural interfaces: from neurophysiological inspiration to biohybrid coupling with nervous systems

OBJECTIVE

Computation in nervous systems operates with different computational primitives, and on different hardware, than traditional digital computation and is thus subjected to different constraints from its digital counterpart regarding the use of physical resources such as time, space and energy. In an effort to better understand neural computation on a physical medium with similar spatiotemporal and energetic constraints, the field of neuromorphic engineering aims to design and implement electronic systems that emulate in very large-scale integration (VLSI) hardware the organization and functions of neural systems at multiple levels of biological organization, from individual neurons up to large circuits and networks. Mixed analog/digital neuromorphic VLSI systems are compact, consume little power and operate in real time independently of the size and complexity of the model.

APPROACH

This article highlights the current efforts to interface neuromorphic systems with neural systems at multiple levels of biological organization, from the synaptic to the system level, and discusses the prospects for future biohybrid systems with neuromorphic circuits of greater complexity.

MAIN RESULTS

Single silicon neurons have been interfaced successfully with invertebrate and vertebrate neural networks. This approach allowed the investigation of neural properties that are inaccessible with traditional techniques while providing a realistic biological context not achievable with traditional numerical modeling methods. At the network level, populations of neurons are envisioned to communicate bidirectionally with neuromorphic processors of hundreds or thousands of silicon neurons. Recent work on brain-machine interfaces suggests that this is feasible with current neuromorphic technology.

SIGNIFICANCE

Biohybrid interfaces between biological neurons and VLSI neuromorphic systems of varying complexity have started to emerge in the literature. Primarily intended as a computational tool for investigating fundamental questions related to neural dynamics, the sophistication of current neuromorphic systems now allows direct interfaces with large neuronal networks and circuits, resulting in potentially interesting clinical applications for neuroengineering systems, neuroprosthetics and neurorehabilitation.