scholarly journals Massively parallel microwire arrays integrated with CMOS chips for neural recording

2020 ◽  
Vol 6 (12) ◽  
pp. eaay2789 ◽  
Author(s):  
Abdulmalik Obaid ◽  
Mina-Elraheb Hanna ◽  
Yu-Wei Wu ◽  
Mihaly Kollo ◽  
Romeo Racz ◽  
...  
Keyword(s):  
Large Scale ◽  
Modular Design ◽  
Three Dimensional ◽  
Field Potential ◽  
Neural Interface ◽  
Neural Communication ◽  
New Strategy ◽  
Planar Silicon ◽  
Interface Devices ◽  
Silicon Based

Multi-channel electrical recordings of neural activity in the brain is an increasingly powerful method revealing new aspects of neural communication, computation, and prosthetics. However, while planar silicon-based CMOS devices in conventional electronics scale rapidly, neural interface devices have not kept pace. Here, we present a new strategy to interface silicon-based chips with three-dimensional microwire arrays, providing the link between rapidly-developing electronics and high density neural interfaces. The system consists of a bundle of microwires mated to large-scale microelectrode arrays, such as camera chips. This system has excellent recording performance, demonstrated via single unit and local-field potential recordings in isolated retina and in the motor cortex or striatum of awake moving mice. The modular design enables a variety of microwire types and sizes to be integrated with different types of pixel arrays, connecting the rapid progress of commercial multiplexing, digitisation and data acquisition hardware together with a three-dimensional neural interface.

scholarly journals Massively Parallel Microwire Arrays Integrated with CMOS chips for Neural Recording

2019 ◽  
Author(s):  
Abdulmalik Obaid ◽  
Mina-Elraheb Hanna ◽  
Yu-Wei Wu ◽  
Mihaly Kollo ◽  
Romeo Racz ◽  
...  
Keyword(s):  
Large Scale ◽  
Modular Design ◽  
Three Dimensional ◽  
Field Potential ◽  
Neural Interface ◽  
Neural Communication ◽  
New Strategy ◽  
Planar Silicon ◽  
Interface Devices ◽  
Silicon Based

AbstractMulti-channel electrical recordings of neural activity in the brain is an increasingly powerful method revealing new aspects of neural communication, computation, and prosthetics. However, while planar silicon-based CMOS devices in conventional electronics scale rapidly, neural interface devices have not kept pace. Here, we present a new strategy to interface silicon-based chips with three-dimensional microwire arrays, providing the link between rapidly-developing electronics and high density neural interfaces. The system consists of a bundle of microwires mated to large-scale microelectrode arrays, such as camera chips. This system has excellent recording performance, demonstrated via single unit and local-field potential recordings in isolated retina and in the motor cortex or striatum of awake moving mice. The modular design enables a variety of microwire types and sizes to be integrated with different types of pixel arrays, connecting the rapid progress of commercial multiplexing, digitisation and data acquisition hardware together with a three-dimensional neural interface.

scholarly journals Characterization of a-SiCx:H thin films as an encapsulation material for integrated silicon based neural interface devices

2007 ◽  
Vol 516 (1) ◽  
pp. 34-41 ◽  
Author(s):  
Jui-Mei Hsu ◽  
Prashant Tathireddy ◽  
Loren Rieth ◽  
A. Richard Normann ◽  
Florian Solzbacher
Keyword(s):  
Thin Films ◽  
Neural Interface ◽  
Interface Devices ◽  
Silicon Based

scholarly journals Elastic Three-Dimensional Graphene Sponge Fabricated by the Liquid Crystals of Controlled Large Graphene Oxide Sheets

2018 ◽  
Author(s):  
Qiuli Wei ◽  
Anaerguli Wufuer ◽  
Meisong Wang ◽  
Yuanyuan Wang ◽  
Liyi Dai
Keyword(s):  
Graphene Oxide ◽  
Liquid Crystals ◽  
Self Assembly ◽  
Large Scale ◽  
Three Dimensional ◽  
High Porosity ◽  
Graphene Sponge ◽  
New Strategy ◽  
Facile Fabrication ◽  
Graphene Oxide Sheets

Three-dimensional graphene (3DG) sponge has attracted increasing attention because it combines the unique properties of cellular materials and the excellent performance of graphene. The preparation of 3DG sponge depends mainly on the self-assembly of graphene oxide sheets. Here, we demonstrate facile fabrication of 3DG sponge with a large-scale and ordered porous structure, exploiting the liquid crystals of large graphene oxide (LGO) and ultralarge graphene oxide (ULGO) sheets. The resulting materials exhibit a low density, high porosity and elasticity. Our work explores a new strategy for organizing the ordered alignment of controlled large GO sheets and exploring the relationship between the microstructures and mechanical properties of 3DG sponge.

A silicon-based, three-dimensional neural interface: manufacturing processes for an intracortical electrode array

1991 ◽  
Vol 38 (8) ◽  
pp. 758-768 ◽  
Author(s):  
P.K. Campbell ◽  
K.E. Jones ◽  
R.J. Huber ◽  
K.W. Horch ◽  
R.A. Normann
Keyword(s):  
Three Dimensional ◽  
Electrode Array ◽  
Neural Interface ◽  
Manufacturing Processes ◽  
Silicon Based

scholarly journals Neurosharing: large-scale data sets (spike, LFP) recorded from the hippocampal-entorhinal system in behaving rats

F1000Research ◽  
2014 ◽  
Vol 3 ◽  
pp. 98 ◽  
Author(s):  
Kenji Mizuseki ◽  
Kamran Diba ◽  
Eva Pastalkova ◽  
Jeff Teeters ◽  
Anton Sirota ◽  
...  
Keyword(s):  
Hippocampal Neurons ◽  
Large Scale ◽  
Dorsal Hippocampus ◽  
Field Potential ◽  
Data Sets ◽  
Data Set ◽  
Large Scale Data ◽  
Silicon Based ◽  
Spike Waveforms ◽  
Wave Shapes

Using silicon-based recording electrodes, we recorded neuronal activity of the dorsal hippocampus and dorsomedial entorhinal cortex from behaving rats. The entorhinal neurons were classified as principal neurons and interneurons based on monosynaptic interactions and wave-shapes. The hippocampal neurons were classified as principal neurons and interneurons based on monosynaptic interactions, wave-shapes and burstiness. The data set contains recordings from 7,736 neurons (6,100 classified as principal neurons, 1,132 as interneurons, and 504 cells that did not clearly fit into either category) obtained during 442 recording sessions from 11 rats (a total of 204.5 hours) while they were engaged in one of eight different behaviours/tasks. Both original and processed data (time stamp of spikes, spike waveforms, result of spike sorting and local field potential) are included, along with metadata of behavioural markers. Community-driven data sharing may offer cross-validation of findings, refinement of interpretations and facilitate discoveries.

scholarly journals Cells in Silico – introducing a high-performance framework for large-scale tissue modeling

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Marco Berghoff ◽  
Jakob Rosenbauer ◽  
Felix Hoffmann ◽  
Alexander Schug
Keyword(s):  
In Silico ◽  
High Performance ◽  
Large Scale ◽  
Computational Models ◽  
Modular Design ◽  
Model Simulation ◽  
Three Dimensional ◽  
Cellular Potts Model ◽  
Performance Framework ◽  
Wide Range

Abstract Background Discoveries in cellular dynamics and tissue development constantly reshape our understanding of fundamental biological processes such as embryogenesis, wound-healing, and tumorigenesis. High-quality microscopy data and ever-improving understanding of single-cell effects rapidly accelerate new discoveries. Still, many computational models either describe few cells highly detailed or larger cell ensembles and tissues more coarsely. Here, we connect these two scales in a joint theoretical model. Results We developed a highly parallel version of the cellular Potts model that can be flexibly applied and provides an agent-based model driving cellular events. The model can be modular extended to a multi-model simulation on both scales. Based on the NAStJA framework, a scaling implementation running efficiently on high-performance computing systems was realized. We demonstrate independence of bias in our approach as well as excellent scaling behavior. Conclusions Our model scales approximately linear beyond 10,000 cores and thus enables the simulation of large-scale three-dimensional tissues only confined by available computational resources. The strict modular design allows arbitrary models to be configured flexibly and enables applications in a wide range of research questions. Cells in Silico (CiS) can be easily molded to different model assumptions and help push computational scientists to expand their simulations to a new area in tissue simulations. As an example we highlight a 10003 voxel-sized cancerous tissue simulation at sub-cellular resolution.

scholarly journals Short loop functional commonality identified in leukaemia proteome highlights crucial protein sub-networks

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Sun Sook Chung ◽  
Joseph C F Ng ◽  
Anna Laddach ◽  
N Shaun B Thomas ◽  
Franca Fraternali
Keyword(s):  
Protein Interactions ◽  
Large Scale ◽  
Interaction Network ◽  
Protein Protein Interactions ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
Short Loop ◽  
New Strategy ◽  
Loop Network ◽  
Protein Protein Interaction Network

Abstract Direct drug targeting of mutated proteins in cancer is not always possible and efficacy can be nullified by compensating protein–protein interactions (PPIs). Here, we establish an in silico pipeline to identify specific PPI sub-networks containing mutated proteins as potential targets, which we apply to mutation data of four different leukaemias. Our method is based on extracting cyclic interactions of a small number of proteins topologically and functionally linked in the Protein–Protein Interaction Network (PPIN), which we call short loop network motifs (SLM). We uncover a new property of PPINs named ‘short loop commonality’ to measure indirect PPIs occurring via common SLM interactions. This detects ‘modules’ of PPI networks enriched with annotated biological functions of proteins containing mutation hotspots, exemplified by FLT3 and other receptor tyrosine kinase proteins. We further identify functional dependency or mutual exclusivity of short loop commonality pairs in large-scale cellular CRISPR–Cas9 knockout screening data. Our pipeline provides a new strategy for identifying new therapeutic targets for drug discovery.

scholarly journals A Review on Additive Manufacturing Possibilities for Electrical Machines

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1940
Author(s):  
Muhammad Usman Naseer ◽  
Ants Kallaste ◽  
Bilal Asad ◽  
Toomas Vaimann ◽  
Anton Rassõlkin
Keyword(s):  
Additive Manufacturing ◽  
Large Scale ◽  
Three Dimensional ◽  
Electrical Machines ◽  
Electromagnetic Properties ◽  
Scale Production ◽  
Performance Parameters ◽  
Large Scale Production ◽  
One Step ◽  
Manufacturing Techniques

This paper presents current research trends and prospects of utilizing additive manufacturing (AM) techniques to manufacture electrical machines. Modern-day machine applications require extraordinary performance parameters such as high power-density, integrated functionalities, improved thermal, mechanical & electromagnetic properties. AM offers a higher degree of design flexibility to achieve these performance parameters, which is impossible to realize through conventional manufacturing techniques. AM has a lot to offer in every aspect of machine fabrication, such that from size/weight reduction to the realization of complex geometric designs. However, some practical limitations of existing AM techniques restrict their utilization in large scale production industry. The introduction of three-dimensional asymmetry in machine design is an aspect that can be exploited most with the prevalent level of research in AM. In order to take one step further towards the enablement of large-scale production of AM-built electrical machines, this paper also discusses some machine types which can best utilize existing developments in the field of AM.

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