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      NeuroGrid: recording action potentials from the surface of the brain

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          Abstract

          Recording from neural networks at the resolution of action potentials is critical for understanding how information is processed in the brain. Here, we address this challenge by developing an organic material-based, ultra-conformable, biocompatible and scalable neural interface array (the ‘NeuroGrid’) that can record both LFP and action potentials from superficial cortical neurons without penetrating the brain surface. Spikes with features of interneurons and pyramidal cells were simultaneously acquired by multiple neighboring electrodes of the NeuroGrid, allowing for isolation of putative single neurons in rats. Spiking activity demonstrated consistent phase modulation by ongoing brain oscillations and was stable in recordings exceeding one week. We also recorded LFP-modulated spiking activity intra-operatively in patients undergoing epilepsy surgery. The NeuroGrid constitutes an effective method for large-scale, stable recording of neuronal spikes in concert with local population synaptic activity, enhancing comprehension of neural processes across spatiotemporal scales and potentially facilitating diagnosis and therapy for brain disorders.

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          Most cited references 38

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          Dynamic predictions: oscillations and synchrony in top-down processing.

          Classical theories of sensory processing view the brain as a passive, stimulus-driven device. By contrast, more recent approaches emphasize the constructive nature of perception, viewing it as an active and highly selective process. Indeed, there is ample evidence that the processing of stimuli is controlled by top-down influences that strongly shape the intrinsic dynamics of thalamocortical networks and constantly create predictions about forthcoming sensory events. We discuss recent experiments indicating that such predictions might be embodied in the temporal structure of both stimulus-evoked and ongoing activity, and that synchronous oscillations are particularly important in this process. Coherence among subthreshold membrane potential fluctuations could be exploited to express selective functional relationships during states of expectancy or attention, and these dynamic patterns could allow the grouping and selection of distributed neuronal responses for further processing.
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            Dissolvable films of silk fibroin for ultrathin conformal bio-integrated electronics.

            Electronics that are capable of intimate, non-invasive integration with the soft, curvilinear surfaces of biological tissues offer important opportunities for diagnosing and treating disease and for improving brain/machine interfaces. This article describes a material strategy for a type of bio-interfaced system that relies on ultrathin electronics supported by bioresorbable substrates of silk fibroin. Mounting such devices on tissue and then allowing the silk to dissolve and resorb initiates a spontaneous, conformal wrapping process driven by capillary forces at the biotic/abiotic interface. Specialized mesh designs and ultrathin forms for the electronics ensure minimal stresses on the tissue and highly conformal coverage, even for complex curvilinear surfaces, as confirmed by experimental and theoretical studies. In vivo, neural mapping experiments on feline animal models illustrate one mode of use for this class of technology. These concepts provide new capabilities for implantable and surgical devices.
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              Large-scale recording of neuronal ensembles.

              How does the brain orchestrate perceptions, thoughts and actions from the spiking activity of its neurons? Early single-neuron recording research treated spike pattern variability as noise that needed to be averaged out to reveal the brain's representation of invariant input. Another view is that variability of spikes is centrally coordinated and that this brain-generated ensemble pattern in cortical structures is itself a potential source of cognition. Large-scale recordings from neuronal ensembles now offer the opportunity to test these competing theoretical frameworks. Currently, wire and micro-machined silicon electrode arrays can record from large numbers of neurons and monitor local neural circuits at work. Achieving the full potential of massively parallel neuronal recordings, however, will require further development of the neuron-electrode interface, automated and efficient spike-sorting algorithms for effective isolation and identification of single neurons, and new mathematical insights for the analysis of network properties.
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                Author and article information

                Journal
                9809671
                21092
                Nat Neurosci
                Nat. Neurosci.
                Nature neuroscience
                1097-6256
                1546-1726
                29 November 2014
                22 December 2014
                February 2015
                01 August 2015
                : 18
                : 2
                : 310-315
                Affiliations
                [1 ])NYU Neuroscience Institute, School of Medicine, New York University, New York, NY 10016, USA
                [2 ])Department of Neurology, Comprehensive Epilepsy Center, New York University, New York, NY 10016, USA
                [3 ])Department of Bioelectronics, Ecole Nationale Supérieure des Mines, CMP-EMSE, MOC, 13541 Gardanne, France
                Author notes

                Author contributions

                D.K., G.G.M., and G.B. conceived the project. D.K. designed, fabricated, and characterized the devices. D.K. and J.G. did the rodent in vivo experiments. D.K. and J.G. analyzed neural data. D.K., J.G., and T.T. did the intra-operative patient recordings. W.D. was the attending neurosurgeon and supervised the intra-operative recordings. T.T. and O.D. supervised the epilepsy patient recordings and IRB. D.K., J.G., and G.B. wrote the paper with input from the other authors.

                Article
                NIHMS645113
                10.1038/nn.3905
                4308485
                25531570
                Categories
                Article

                Neurosciences

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