High-density extracellular probes reveal dendritic backpropagation and facilitate neuron classification

AbstractDifferent neuron types serve distinct roles in neural processing. Extracellular electrical recordings are extensively used to study brain function but are typically blind to cell identity. Morpho-electric properties of neurons measured on spatially dense electrode arrays might be useful for distinguishing neuron types. Here we used Neuropixels probes to record from cortical and subcortical regions of the mouse brain. Extracellular waveforms of each neuron were detected across many channels and showed distinct spatiotemporal profiles among brain regions. Classification of neurons by brain region was improved with multi-channel compared to single-channel waveforms. In visual cortex, waveform clustering identified the canonical regular spiking (RS) and fast spiking (FS) classes, but also uncovered a subclass of RS units with unidirectional backpropagating action potentials (BAPs). Moreover, BAPs were observed in many hippocampal RS cells. Overall, waveform analysis of spikes from high-density probes aids neuron identification and can reveal dendritic backpropagation.

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High-density extracellular probes reveal dendritic backpropagation and facilitate neuron classification

Journal of Neurophysiology ◽

10.1152/jn.00680.2018 ◽

2019 ◽

Vol 121 (5) ◽

pp. 1831-1847 ◽

Cited By ~ 11

Author(s):

Xiaoxuan Jia ◽

Joshua H. Siegle ◽

Corbett Bennett ◽

Samuel D. Gale ◽

Daniel J. Denman ◽

...

Keyword(s):

Action Potentials ◽

Hippocampal Neurons ◽

Single Channel ◽

Brain Network ◽

High Density ◽

Waveform Analysis ◽

Cell Type ◽

Electrode Arrays

Different neuron types serve distinct roles in neural processing. Extracellular electrical recordings are extensively used to study brain function but are typically blind to cell identity. Morphoelectrical properties of neurons measured on spatially dense electrode arrays have the potential to distinguish neuron types. We used high-density silicon probes to record from cortical and subcortical regions of the mouse brain. Extracellular waveforms of each neuron were detected across many channels and showed distinct spatiotemporal profiles among brain regions. Classification of neurons by brain region was improved with multichannel compared with single-channel waveforms. In visual cortex, unsupervised clustering identified the canonical regular-spiking (RS) and fast-spiking (FS) classes but also indicated a subclass of RS units with unidirectional backpropagating action potentials (BAPs). Moreover, BAPs were observed in many hippocampal RS cells. Overall, waveform analysis of spikes from high-density probes aids neuron identification and can reveal dendritic backpropagation. NEW & NOTEWORTHY It is challenging to identify neuron types with extracellular electrophysiology in vivo. We show that spatiotemporal action potentials measured on high-density electrode arrays can capture cell type-specific morphoelectrical properties, allowing classification of neurons across brain structures and within the cortex. Moreover, backpropagating action potentials are reliably detected in vivo from subpopulations of cortical and hippocampal neurons. Together, these results enhance the utility of dense extracellular electrophysiology for cell-type interrogation of brain network function.

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An automated method for precise axon reconstruction from recordings of high-density micro-electrode arrays

10.1101/2021.06.12.448051 ◽

2021 ◽

Author(s):

Alessio Paolo Buccino ◽

Xinyue Yuan ◽

Vishalini Emmenegger ◽

Xiaohan Xue ◽

Tobias Gaenswein ◽

...

Keyword(s):

Action Potential ◽

Action Potentials ◽

Electrical Potential ◽

Simulated Data ◽

Signal Propagation ◽

High Density ◽

Electrode Arrays ◽

Action Potential Propagation ◽

Automated Method ◽

Propagation Velocities

Neurons communicate with each other by sending action potentials through their axons. The velocity of axonal signal propagation describes how fast electrical action potentials can travel, and can be affected in a human brain by several pathologies, including multiple sclerosis, traumatic brain injury and channelopathies. High-density microelectrode arrays (HD-MEAs) provide unprecedented spatio-temporal resolution to extracellularly record neural electrical activity. The high density of the recording electrodes enables to image the activity of individual neurons down to subcellular resolution, which includes the propagation of axonal signals. However, axon reconstruction, to date, mainly relies on a manual approach to select the electrodes and channels that seemingly record the signals along a specific axon, while an automated approach to track multiple axonal branches in extracellular action-potential recordings is still missing. In this article, we propose a fully automated approach to reconstruct axons from extracellular electrical-potential landscapes, so-called "electrical footprints" of neurons. After an initial electrode and channel selection, the proposed method first constructs a graph, based on the voltage signal amplitudes and latencies. Then, the graph is interrogated to extract possible axonal branches. Finally, the axonal branches are pruned and axonal action-potential propagation velocities are computed. We first validate our method using simulated data from detailed reconstructions of neurons, showing that our approach is capable of accurately reconstructing axonal branches. We then apply the reconstruction algorithm to experimental recordings of HD-MEAs and show that it can be used to determine axonal morphologies and signal-propagation velocities at high throughput. We introduce a fully automated method to reconstruct axonal branches and estimate axonal action-potential propagation velocities using HD-MEA recordings. Our method yields highly reliable and reproducible velocity estimations, which constitute an important electrophysiological feature of neuronal preparations.

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Motor Unit Tracking Using High Density Surface Electromyography (HDsEMG)

Methods of Information in Medicine ◽

10.3414/me13-02-0049 ◽

2015 ◽

Vol 54 (03) ◽

pp. 221-226 ◽

Cited By ~ 3

Author(s):

B. T. H. M. Sleutjes ◽

M. De Vos ◽

J. H. Blok ◽

I. Montfoort ◽

B. Mijović ◽

...

Keyword(s):

Motor Unit ◽

Action Potentials ◽

Motor Units ◽

Surface Emg ◽

High Density ◽

Electrode Arrays ◽

Motor Unit Action Potentials ◽

Motor Unit Action ◽

Angular Displacements ◽

Unit Action

SummaryIntroduction: This article is part of the Focus Theme of Methods of Information in Medicine on “Biosignal Interpretation: Advanced Methods for Neural Signals and Images”.Objectives: The study discusses a technique to automatically correct for effects of electrode grid displacement across serial surface EMG measurements with high-density electrode arrays (HDsEMG). The goal is to match motor unit signatures from subsequent measurements and by this, achieve automated motor unit tracking.Methods: Test recordings of voluntary muscle contractions using HDsEMG were performed on three healthy individuals. Electrode grid displacements were mimicked in repeated recordings while measuring the exact position of the grid. A concept of accounting for translational and rotational displacements by making the projection of the recorded motor unit action potentials is first introduced. Then, this concept was tested for the performed measurements attempting the automated matching of the similar motor unit action potentials across different trials.Results: The ability to perform automated correction (projection) of the isolated motor unit action potentials was first shown using large angular displacements. Then, for accidental (small) displacements of the recording grid, the ability to automatically track motor units across different measurement trials was shown. It was possible to track 10 –15% of identified motor units.Conclusions: This proof of concept study demonstrates an automated correction allowing the identification of an increased number of same motor unit action potentials across different measurements. By this, great potential is demonstrated for assisting motor unit tracking studies, indicating that otherwise electrode displacements cannot always be precisely described.

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Two modes of inhibitory neuronal shutdown distinctly amplify seizures in humans

10.1101/2020.10.09.20204206 ◽

2020 ◽

Author(s):

Omar J. Ahmed ◽

Tibin T. John ◽

Shyam K. Sudhakar ◽

Ellen K.W. Brennan ◽

Alcides Lorenzo Gonzalez ◽

...

Keyword(s):

Brain Function ◽

Action Potentials ◽

Computational Models ◽

Neuronal Firing ◽

Inhibitory Neurons ◽

Normal Brain ◽

Neuronal Control ◽

Normal Brain Function ◽

Fast Spiking

ABSTRACTInhibitory neurons are critical for normal brain function but dysregulated in disorders such as epilepsy. At least two theories exist for how inhibition may acutely decrease during a seizure: hyperpolarization of fast-spiking (FS) inhibitory neurons by other inhibitory neurons, or depolarization block (DB) of FS neurons resulting in an inability to fire action potentials. Firing rate alone is unable to disambiguate these alternatives. Here, we show that human FS neurons can stop firing due to both hyperpolarization and DB within the same seizure. However, only DB of FS cells is associated with dramatic increases in local seizure amplitude, unobstructed traveling waves, and transient increases in excitatory neuronal firing. This result is independent of seizure etiology or focus. Computational models of DB reproduce the in vivo human biophysics. These methods enable intracellular decoding using only extracellular recordings in humans and explain the otherwise ambiguous inhibitory neuronal control of human seizures.

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Non-parametric physiological classification of retinal ganglion cells in the mouse retina

10.1101/407635 ◽

2018 ◽

Author(s):

Jonathan Jouty ◽

Gerrit Hilgen ◽

Evelyne Sernagor ◽

Matthias H. Hennig

Keyword(s):

Retinal Ganglion Cells ◽

Visual Information ◽

Large Scale ◽

Distance Measure ◽

Ganglion Cells ◽

High Density ◽

Mouse Retina ◽

Retinal Ganglion ◽

Electrode Arrays

Retinal ganglion cells, the sole output neurons of the retina, exhibit surprising diversity. A recent study reported over 30 distinct types in the mouse retina, indicating that the processing of visual information is highly parallelised in the brain. The advent of high density multi-electrode arrays now enables recording from many hundreds to thousands of neurons from a single retina. Here we describe a method for the automatic classification of large-scale retinal recordings using a simple stimulus paradigm and a spike train distance measure as a clustering metric. We evaluate our approach using synthetic spike trains, and demonstrate that major known cell types are identified in high-density recording sessions from the mouse retina with around 1000 retinal ganglion cells. A comparison across different retinas reveals substantial variability between preparations, suggesting pooling data across retinas should be approached with caution. As a parameter-free method, our approach is broadly applicable for cellular physiological classification in all sensory modalities.

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Induction of human somatostatin and parvalbumin neurons by expressing a single transcription factor LIM homeobox 6

eLife ◽

10.7554/elife.37382 ◽

2018 ◽

Vol 7 ◽

Cited By ~ 9

Author(s):

Fang Yuan ◽

Xin Chen ◽

Kai-Heng Fang ◽

Yuanyuan Wang ◽

Mingyan Lin ◽

...

Keyword(s):

Transcription Factor ◽

Pluripotent Stem Cells ◽

Brain Function ◽

Action Potentials ◽

Normal Brain ◽

Gabaergic Interneurons ◽

Electrophysiological Properties ◽

Normal Brain Function ◽

Fast Spiking ◽

Parvalbumin Neurons

Human GABAergic interneurons (GIN) are implicated in normal brain function and in numerous mental disorders. However, the generation of functional human GIN subtypes from human pluripotent stem cells (hPSCs) has not been established. By expressing LHX6, a transcriptional factor that is critical for GIN development, we induced hPSCs to form GINs, including somatostatin (SST, 29%) and parvalbumin (PV, 21%) neurons. Our RNAseq results also confirmed the alteration of GIN identity with the overexpression of LHX6. Five months after transplantation into the mouse brain, the human GABA precursors generated increased population of SST and PV neurons by overexpressing LHX6. Importantly, the grafted human GINs exhibited functional electrophysiological properties and even fast-spiking-like action potentials. Thus, expression of the single transcription factor LHX6 under our GIN differentiation condition is sufficient to robustly induce human PV and SST subtypes.

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Learning and control

10.1093/oso/9780199674923.003.0026 ◽

2018 ◽

Author(s):

Ivan Herreros

Keyword(s):

Machine Learning ◽

Reinforcement Learning ◽

Brain Function ◽

Control Strategies ◽

Learning Problems ◽

Animal Learning ◽

Feed Forward Control ◽

Machine Learning Applications ◽

And Control

This chapter discusses basic concepts from control theory and machine learning to facilitate a formal understanding of animal learning and motor control. It first distinguishes between feedback and feed-forward control strategies, and later introduces the classification of machine learning applications into supervised, unsupervised, and reinforcement learning problems. Next, it links these concepts with their counterparts in the domain of the psychology of animal learning, highlighting the analogies between supervised learning and classical conditioning, reinforcement learning and operant conditioning, and between unsupervised and perceptual learning. Additionally, it interprets innate and acquired actions from the standpoint of feedback vs anticipatory and adaptive control. Finally, it argues how this framework of translating knowledge between formal and biological disciplines can serve us to not only structure and advance our understanding of brain function but also enrich engineering solutions at the level of robot learning and control with insights coming from biology.

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HIV Infection Is Associated with Attenuated Frontostriatal Intrinsic Connectivity: A Preliminary Study

Journal of the International Neuropsychological Society ◽

10.1017/s1355617715000156 ◽

2015 ◽

Vol 21 (3) ◽

pp. 203-213 ◽

Cited By ~ 39

Author(s):

Jonathan C. Ipser ◽

Gregory G. Brown ◽

Amanda Bischoff-Grethe ◽

Colm G. Connolly ◽

Ronald J. Ellis ◽

...

Keyword(s):

Hiv Infection ◽

Brain Regions ◽

Group Differences ◽

Hiv Rna ◽

Functional Connections ◽

Intrinsic Connectivity ◽

Dorsolateral Prefrontal ◽

Independent Replication ◽

Subcortical Regions ◽

The Brain

AbstractHIV-associated cognitive impairments are prevalent, and are consistent with injury to both frontal cortical and subcortical regions of the brain. The current study aimed to assess the association of HIV infection with functional connections within the frontostriatal network, circuitry hypothesized to be highly vulnerable to HIV infection. Fifteen HIV-positive and 15 demographically matched control participants underwent 6 min of resting-state functional magnetic resonance imaging (RS-fMRI). Multivariate group comparisons of age-adjusted estimates of connectivity within the frontostriatal network were derived from BOLD data for dorsolateral prefrontal cortex (DLPFC), dorsal caudate and mediodorsal thalamic regions of interest. Whole-brain comparisons of group differences in frontostriatal connectivity were conducted, as were pairwise tests of connectivity associations with measures of global cognitive functioning and clinical and immunological characteristics (nadir and current CD4 count, duration of HIV infection, plasma HIV RNA). HIV – associated reductions in connectivity were observed between the DLPFC and the dorsal caudate, particularly in younger participants (<50 years, N=9). Seropositive participants also demonstrated reductions in dorsal caudate connectivity to frontal and parietal brain regions previously demonstrated to be functionally connected to the DLPFC. Cognitive impairment, but none of the assessed clinical/immunological variables, was also associated with reduced frontostriatal connectivity. In conclusion, our data indicate that HIV is associated with attenuated intrinsic frontostriatal connectivity. Intrinsic connectivity of this network may therefore serve as a marker of the deleterious effects of HIV infection on the brain, possibly via HIV-associated dopaminergic abnormalities. These findings warrant independent replication in larger studies. (JINS, 2015, 21, 1–11)

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A rigorous approach for testing the constructionist hypotheses of brain function

Behavioral and Brain Sciences ◽

10.1017/s0140525x1100149x ◽

2012 ◽

Vol 35 (3) ◽

pp. 148-149 ◽

Cited By ~ 11

Author(s):

Gopikrishna Deshpande ◽

K. Sathian ◽

Xiaoping Hu ◽

Joseph A. Buckhalt

Keyword(s):

Granger Causality ◽

Strong Evidence ◽

Bayesian Modeling ◽

Brain Function ◽

Brain Regions ◽

Causal Modeling ◽

Dynamic Causal Modeling ◽

Rigorous Approach ◽

Target Article ◽

Co Activation

AbstractAlthough the target article provides strong evidence against the locationist view, evidence for the constructionist view is inconclusive, because co-activation of brain regions does not necessarily imply connectivity between them. We propose a rigorous approach wherein connectivity between co-activated regions is first modeled using exploratory Granger causality, and then confirmed using dynamic causal modeling or Bayesian modeling.

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