Challenges and opportunities for large-scale electrophysiology with Neuropixels probes
By Nicholas A. Steinmetz, Christof Koch, Kenneth D. Harris, Matteo Carandini. Current Opinion in Neurobiology, 2018
318 citations recorded by the source corpus.
Electrophysiological methods are the gold standard in neuroscience because they reveal the activity of individual neurons at high temporal resolution and in arbitrary brain locations. Microelectrode arrays based on complementary metal-oxide semiconductor (CMOS) technology, such as Neuropixels probes, look set to transform these methods. Neuropixels probes provide ∼1000 recording sites on an extremely narrow shank, with on-board amplification, digitization, and multiplexing. They deliver low-noise recordings from hundreds of neurons, providing a step change in the type of data available to neuroscientists. Here we discuss the opportunities afforded by these probes for large-scale electrophysiology, the challenges associated with data processing and anatomical localization, and avenues for further improvements of the technology.
Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience
View Paper: https://www.semanticscholar.org/paper/384473914cff2a3fde7a250d97179382d9af31f0
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cellular and Molecular Neuroscience
- Friedemann Zenke
- Surya Ganguli
- Rafal Bogacz
- Claudia Clopath
- Walter Senn
- Yoshua Bengio
- Blake Aaron Richards
- Pieter R. Roelfsema
In Cognitive Neuroscience
- Friedemann Zenke
- Grace W. Lindsay
- Surya Ganguli
- Rafal Bogacz
- Xiao-Jing Wang
- Nikolaus Kriegeskorte
- Andrew M. Saxe
- Walter Senn
Citations in the corpus
- Towards the neural population doctrine. (2019, methodology): “More recently, multi-electrode arrays and imaging techniques (optical, and more recently voltage) have been used to efficiently capture the simultaneous activity of hundreds and thousands of neurons, with this number steadily growing using tools such as the Neuropixel [9].”
- A deep learning framework for neuroscience (2019, background): “the specific input/output functions of the ANNs), but 187 three components: (1) objective functions, (2) learning rules, and (3) architectures (Fig.”