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      Allocating structure to function: the strong links between neuroplasticity and natural selection

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          Abstract

          A central question in brain evolution is how species-typical behaviors, and the neural function-structure mappings supporting them, can be acquired and inherited. Advocates of brain modularity, in its different incarnations across scientific subfields, argue that natural selection must target domain-dedicated, separately modifiable neural subsystems, resulting in genetically-specified functional modules. In such modular systems, specification of neuron number and functional connectivity are necessarily linked. Mounting evidence, however, from allometric, developmental, comparative, systems-physiological, neuroimaging and neurological studies suggests that brain elements are used and reused in multiple functional systems. This variable allocation can be seen in short-term neuromodulation, in neuroplasticity over the lifespan and in response to damage. We argue that the same processes are evident in brain evolution. Natural selection must preserve behavioral functions that may co-locate in variable amounts with other functions. In genetics, the uses and problems of pleiotropy, the re-use of genes in multiple networks have been much discussed, but this issue has been sidestepped in neural systems by the invocation of modules. Here we highlight the interaction between evolutionary and developmental mechanisms to produce distributed and overlapping functional architectures in the brain. These adaptive mechanisms must be robust to perturbations that might disrupt critical information processing and action selection, but must also recognize useful new sources of information arising from internal genetic or environmental variability, when those appear. These contrasting properties of “robustness” and “evolvability” have been discussed for the basic organization of body plan and fundamental cell physiology. Here we extend them to the evolution and development, “evo-devo,” of brain structure.

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          A robust layered control system for a mobile robot

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            Neuronal circuits of the neocortex.

            We explore the extent to which neocortical circuits generalize, i.e., to what extent can neocortical neurons and the circuits they form be considered as canonical? We find that, as has long been suspected by cortical neuroanatomists, the same basic laminar and tangential organization of the excitatory neurons of the neocortex is evident wherever it has been sought. Similarly, the inhibitory neurons show characteristic morphology and patterns of connections throughout the neocortex. We offer a simple model of cortical processing that is consistent with the major features of cortical circuits: The superficial layer neurons within local patches of cortex, and within areas, cooperate to explore all possible interpretations of different cortical input and cooperatively select an interpretation consistent with their various cortical and subcortical inputs.
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              Brain-machine interfaces: past, present and future.

              Since the original demonstration that electrical activity generated by ensembles of cortical neurons can be employed directly to control a robotic manipulator, research on brain-machine interfaces (BMIs) has experienced an impressive growth. Today BMIs designed for both experimental and clinical studies can translate raw neuronal signals into motor commands that reproduce arm reaching and hand grasping movements in artificial actuators. Clearly, these developments hold promise for the restoration of limb mobility in paralyzed subjects. However, as we review here, before this goal can be reached several bottlenecks have to be passed. These include designing a fully implantable biocompatible recording device, further developing real-time computational algorithms, introducing a method for providing the brain with sensory feedback from the actuators, and designing and building artificial prostheses that can be controlled directly by brain-derived signals. By reaching these milestones, future BMIs will be able to drive and control revolutionary prostheses that feel and act like the human arm.
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                Author and article information

                Journal
                Front Hum Neurosci
                Front Hum Neurosci
                Front. Hum. Neurosci.
                Frontiers in Human Neuroscience
                Frontiers Media S.A.
                1662-5161
                07 January 2014
                2013
                : 7
                : 918
                Affiliations
                [1] 1Department of Psychology, Franklin & Marshall College Lancaster, PA, USA
                [2] 2Neuroscience and Cognitive Science Program, Institute for Advanced Computer Studies, University of Maryland College Park, MD, USA
                [3] 3Behavioral and Evolutionary Neuroscience Group, Department of Psychology, Cornell University Ithaca, NY, USA
                Author notes

                Edited by: Roberto Lent, Federal University of Rio de Janeiro, Brazil

                Reviewed by: João G. Franca, Federal University of Rio de Janeiro, Brazil; Robert A. Barton, University of Durham, UK

                *Correspondence: Barbara L. Finlay, Behavioral and Evolutionary Neuroscience Group, Department of Psychology, Cornell University, Uris Hall, Ithaca, NY 14853, USA e-mail: blf2@ 123456cornell.edu

                This article was submitted to the journal Frontiers in Human Neuroscience.

                Article
                10.3389/fnhum.2013.00918
                3882658
                24431995
                3c553ce4-b52c-48db-82af-5b27b45aa019
                Copyright © 2014 Anderson and Finlay.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 17 August 2013
                : 15 December 2013
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 187, Pages: 16, Words: 17133
                Categories
                Neuroscience
                Hypothesis and Theory Article

                Neurosciences
                cortex,visual system,neural re-use,evo-devo,modularity
                Neurosciences
                cortex, visual system, neural re-use, evo-devo, modularity

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