Large-scale recording of neuronal ensembles

@article{Buzski2004LargescaleRO,
  title={Large-scale recording of neuronal ensembles},
  author={Gy{\"o}rgy Buzs{\'a}ki},
  journal={Nature Neuroscience},
  year={2004},
  volume={7},
  pages={446-451}
}
  • G. Buzsáki
  • Published 1 May 2004
  • Biology
  • Nature Neuroscience
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… 
View on Nature
buzsakilab.org
1,581 Citations
Highly Influential Citations
90
Background Citations
770
Methods Citations
176
Results Citations
10

1,581 Citations

Statistical modeling of spiking activity in large scale neuronal networks
TLDR
This approach shows how to incorporate the extra-stimulus data in identifying single cell firing properties, as well as taking a step toward reconciling the understanding of single cells with the computations being performed by the larger network.
Detecting cell assemblies in large neuronal populations
Predicting synchronous firing of large neural populations from sequential recordings
TLDR
This work shows that it can infer the activity of a full population of retina ganglion cells from sequential recordings, using a novel method based on copula distributions and maximum entropy modeling, and could generalize to predict the population responses to different stimuli and even to different experiments.
Characterizing single neuron activity patterns and dynamics using multi-scale spontaneous neuronal activity recordings of cat and mouse cortex
TLDR
This thesis shows that ongoing spontaneous brain activity contains substantial structure that can be used to further the understanding of brain function.
Framework for automated sorting of neural spikes from Neuralynx-acquired tetrode recordings in freely-moving mice
TLDR
It is predicted that within the broad field of bioelectronic medicine, those teams that incorporate high-density neural recording devices to their armamentarium might find the simple-to-execute framework quite valuable as they expand their analytical footprint.
NeuroGrid: recording action potentials from the surface of the brain
TLDR
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.
Assembly Detection in Continuous Neural Spike Train Data
TLDR
This work presents a method based on modeling spikes by influence regions of a user-specified width around the exact spike times and a clustering-like grouping of similar spike trains that is able to cope with two core challenges of this complex task: temporal imprecision and selective participation.
Online detection and sorting of extracellularly recorded action potentials in human medial temporal lobe recordings, in vivo
Combined Single Neuron Unit Activity and Local Field Potential Oscillations in a Human Visual Recognition Memory Task
TLDR
Recordings using hybrid electrodes, containing both micro- and clinical macroelectrodes, to simultaneously sample both large-scale network oscillations and single neuron spiking activity in the medial temporal lobe structures of human subjects during a visual recognition memory task are described.
Revealing cell assemblies at multiple levels of granularity
...
...

References

SHOWING 1-10 OF 72 REFERENCES
Automatic sorting for multi-neuronal activity recorded with tetrodes in the presence of overlapping spikes.
TLDR
The present procedure applies the ICA and the efficiency of the ordinary spike-sorting technique (k-means clustering) to solve the spike-overlapping and the nonstationarity problems with no limitation on the number of single neurons to be separated and provides insights into the local circuit bases of excitatory and inhibitory interactions among neighboring neurons.
Interaction between spike waveform classification and temporal sequence detection
What ensemble recordings reveal about functional hippocampal cell encoding.
Organization of cell assemblies in the hippocampus
TLDR
Here it is found that the spike times of hippocampal pyramidal cells can be predicted more accurately by using the Spike times of simultaneously recorded neurons in addition to the animals location in space, suggesting that cell assemblies are synchronized at this timescale.
Using multi-neuron population recordings for neural prosthetics
  • J. Chapin
  • Biology, Psychology
    Nature Neuroscience
  • 2004
TLDR
M Mathematical analysis of neural population codes allows extraction of 'motor signals' from neuronal population recordings in the motor cortices, which can then be used in real-time to directly control movement of a robot arm.
Neuronal ensembles : strategies for recording and decoding
Brain-state- and cell-type-specific firing of hippocampal interneurons in vivo
TLDR
It is reported that three distinct interneuron types—basket, axo-axonic and oriens–lacunosum-moleculare cells—visualized and defined by synaptic connectivity as well as by neurochemical markers, contribute differentially to theta and ripple oscillations in anaesthetized rats.
Replay and Time Compression of Recurring Spike Sequences in the Hippocampus
TLDR
It is hypothesized that the endogenously expressed spike sequences during sleep reflect reactivation of the circuitry modified by previous experience and serve to consolidate information in neuronal networks.
Accuracy of tetrode spike separation as determined by simultaneous intracellular and extracellular measurements.
TLDR
It is hypothesized that automatic spike-sorting algorithms have the potential to significantly lower error rates, and implementation of a semi-automatic classification system confirms this suggestion, reducing errors close to the estimated optimum, in the range 0-8%.
Reliability and State Dependence of Pyramidal Cell–Interneuron Synapses in the Hippocampus an Ensemble Approach in the Behaving Rat
...
...