---
_id: '12562'
abstract:
- lang: eng
text: Presynaptic inputs determine the pattern of activation of postsynaptic neurons
in a neural circuit. Molecular and genetic pathways that regulate the selective
formation of subsets of presynaptic inputs are largely unknown, despite significant
understanding of the general process of synaptogenesis. In this study, we have
begun to identify such factors using the spinal monosynaptic stretch reflex circuit
as a model system. In this neuronal circuit, Ia proprioceptive afferents establish
monosynaptic connections with spinal motor neurons that project to the same muscle
(termed homonymous connections) or muscles with related or synergistic function.
However, monosynaptic connections are not formed with motor neurons innervating
muscles with antagonistic functions. The ETS transcription factor ER81 (also known
as ETV1) is expressed by all proprioceptive afferents, but only a small set of
motor neuron pools in the lumbar spinal cord of the mouse. Here we use conditional
mouse genetic techniques to eliminate Er81 expression selectively from motor neurons.
We find that ablation of Er81 in motor neurons reduces synaptic inputs from proprioceptive
afferents conveying information from homonymous and synergistic muscles, with
no change observed in the connectivity pattern from antagonistic proprioceptive
afferents. In summary, these findings suggest a role for ER81 in defined motor
neuron pools to control the assembly of specific presynaptic inputs and thereby
influence the profile of activation of these motor neurons.
acknowledgement: The authors gratefully thank Dr. Silvia Arber, University of Basel
and Friedrich Miescher Institute for Biomedical Research, for support and in whose
lab the data were collected. For advice on statistical analysis, we thank Michael
Bottomley from the Statistical Consulting Center, College of Science and Mathematics,
Wright State University.
article_processing_charge: No
article_type: original
author:
- first_name: David R.
full_name: Ladle, David R.
last_name: Ladle
- first_name: Simon
full_name: Hippenmeyer, Simon
id: 37B36620-F248-11E8-B48F-1D18A9856A87
last_name: Hippenmeyer
orcid: 0000-0003-2279-1061
citation:
ama: Ladle DR, Hippenmeyer S. Loss of ETV1/ER81 in motor neurons leads to reduced
monosynaptic inputs from proprioceptive sensory neurons. Journal of Neurophysiology.
2023;129(3):501-512. doi:10.1152/jn.00172.2022
apa: Ladle, D. R., & Hippenmeyer, S. (2023). Loss of ETV1/ER81 in motor neurons
leads to reduced monosynaptic inputs from proprioceptive sensory neurons. Journal
of Neurophysiology. American Physiological Society. https://doi.org/10.1152/jn.00172.2022
chicago: Ladle, David R., and Simon Hippenmeyer. “Loss of ETV1/ER81 in Motor Neurons
Leads to Reduced Monosynaptic Inputs from Proprioceptive Sensory Neurons.” Journal
of Neurophysiology. American Physiological Society, 2023. https://doi.org/10.1152/jn.00172.2022.
ieee: D. R. Ladle and S. Hippenmeyer, “Loss of ETV1/ER81 in motor neurons leads
to reduced monosynaptic inputs from proprioceptive sensory neurons,” Journal
of Neurophysiology, vol. 129, no. 3. American Physiological Society, pp. 501–512,
2023.
ista: Ladle DR, Hippenmeyer S. 2023. Loss of ETV1/ER81 in motor neurons leads to
reduced monosynaptic inputs from proprioceptive sensory neurons. Journal of Neurophysiology.
129(3), 501–512.
mla: Ladle, David R., and Simon Hippenmeyer. “Loss of ETV1/ER81 in Motor Neurons
Leads to Reduced Monosynaptic Inputs from Proprioceptive Sensory Neurons.” Journal
of Neurophysiology, vol. 129, no. 3, American Physiological Society, 2023,
pp. 501–12, doi:10.1152/jn.00172.2022.
short: D.R. Ladle, S. Hippenmeyer, Journal of Neurophysiology 129 (2023) 501–512.
date_created: 2023-02-15T14:46:14Z
date_published: 2023-03-01T00:00:00Z
date_updated: 2023-09-05T12:13:34Z
day: '01'
department:
- _id: SiHi
doi: 10.1152/jn.00172.2022
external_id:
isi:
- '000957721600001'
pmid:
- '36695533'
intvolume: ' 129'
isi: 1
issue: '3'
keyword:
- Physiology
- General Neuroscience
language:
- iso: eng
month: '03'
oa_version: None
page: 501-512
pmid: 1
publication: Journal of Neurophysiology
publication_identifier:
eissn:
- 1522-1598
issn:
- 0022-3077
publication_status: published
publisher: American Physiological Society
quality_controlled: '1'
status: public
title: Loss of ETV1/ER81 in motor neurons leads to reduced monosynaptic inputs from
proprioceptive sensory neurons
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 129
year: '2023'
...
---
_id: '8023'
abstract:
- lang: eng
text: Uniform random sparse network architectures are ubiquitous in computational
neuroscience, but the implicit hypothesis that they are a good representation
of real neuronal networks has been met with skepticism. Here we used two experimental
data sets, a study of triplet connectivity statistics and a data set measuring
neuronal responses to channelrhodopsin stimuli, to evaluate the fidelity of thousands
of model networks. Network architectures comprised three neuron types (excitatory,
fast spiking, and nonfast spiking inhibitory) and were created from a set of rules
that govern the statistics of the resulting connection types. In a high-dimensional
parameter scan, we varied the degree distributions (i.e., how many cells each
neuron connects with) and the synaptic weight correlations of synapses from or
onto the same neuron. These variations converted initially uniform random and
homogeneously connected networks, in which every neuron sent and received equal
numbers of synapses with equal synaptic strength distributions, to highly heterogeneous
networks in which the number of synapses per neuron, as well as average synaptic
strength of synapses from or to a neuron were variable. By evaluating the impact
of each variable on the network structure and dynamics, and their similarity to
the experimental data, we could falsify the uniform random sparse connectivity
hypothesis for 7 of 36 connectivity parameters, but we also confirmed the hypothesis
in 8 cases. Twenty-one parameters had no substantial impact on the results of
the test protocols we used.
article_processing_charge: No
article_type: original
author:
- first_name: Christian
full_name: Tomm, Christian
last_name: Tomm
- first_name: Michael
full_name: Avermann, Michael
last_name: Avermann
- first_name: Carl
full_name: Petersen, Carl
last_name: Petersen
- first_name: Wulfram
full_name: Gerstner, Wulfram
last_name: Gerstner
- first_name: Tim P
full_name: Vogels, Tim P
id: CB6FF8D2-008F-11EA-8E08-2637E6697425
last_name: Vogels
orcid: 0000-0003-3295-6181
citation:
ama: Tomm C, Avermann M, Petersen C, Gerstner W, Vogels TP. Connection-type-specific
biases make uniform random network models consistent with cortical recordings.
Journal of Neurophysiology. 2014;112(8):1801-1814. doi:10.1152/jn.00629.2013
apa: Tomm, C., Avermann, M., Petersen, C., Gerstner, W., & Vogels, T. P. (2014).
Connection-type-specific biases make uniform random network models consistent
with cortical recordings. Journal of Neurophysiology. American Physiological
Society. https://doi.org/10.1152/jn.00629.2013
chicago: Tomm, Christian, Michael Avermann, Carl Petersen, Wulfram Gerstner, and
Tim P Vogels. “Connection-Type-Specific Biases Make Uniform Random Network Models
Consistent with Cortical Recordings.” Journal of Neurophysiology. American
Physiological Society, 2014. https://doi.org/10.1152/jn.00629.2013.
ieee: C. Tomm, M. Avermann, C. Petersen, W. Gerstner, and T. P. Vogels, “Connection-type-specific
biases make uniform random network models consistent with cortical recordings,”
Journal of Neurophysiology, vol. 112, no. 8. American Physiological Society,
pp. 1801–1814, 2014.
ista: Tomm C, Avermann M, Petersen C, Gerstner W, Vogels TP. 2014. Connection-type-specific
biases make uniform random network models consistent with cortical recordings.
Journal of Neurophysiology. 112(8), 1801–1814.
mla: Tomm, Christian, et al. “Connection-Type-Specific Biases Make Uniform Random
Network Models Consistent with Cortical Recordings.” Journal of Neurophysiology,
vol. 112, no. 8, American Physiological Society, 2014, pp. 1801–14, doi:10.1152/jn.00629.2013.
short: C. Tomm, M. Avermann, C. Petersen, W. Gerstner, T.P. Vogels, Journal of Neurophysiology
112 (2014) 1801–1814.
date_created: 2020-06-25T13:08:30Z
date_published: 2014-10-15T00:00:00Z
date_updated: 2021-01-12T08:16:35Z
day: '15'
ddc:
- '570'
doi: 10.1152/jn.00629.2013
extern: '1'
external_id:
pmid:
- '24944218'
file:
- access_level: open_access
checksum: 7c06a086da6f924342650de6dc555c3f
content_type: application/pdf
creator: cziletti
date_created: 2020-07-16T10:12:13Z
date_updated: 2020-07-16T10:12:13Z
file_id: '8122'
file_name: 2014_JNeurophysiol_Tomm.pdf
file_size: 1632295
relation: main_file
success: 1
file_date_updated: 2020-07-16T10:12:13Z
has_accepted_license: '1'
intvolume: ' 112'
issue: '8'
language:
- iso: eng
license: https://creativecommons.org/licenses/by/3.0/
month: '10'
oa: 1
oa_version: Published Version
page: 1801-1814
pmid: 1
publication: Journal of Neurophysiology
publication_identifier:
eissn:
- 1522-1598
issn:
- 0022-3077
publication_status: published
publisher: American Physiological Society
quality_controlled: '1'
status: public
title: Connection-type-specific biases make uniform random network models consistent
with cortical recordings
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/3.0/legalcode
name: Creative Commons Attribution 3.0 Unported (CC BY 3.0)
short: CC BY (3.0)
type: journal_article
user_id: D865714E-FA4E-11E9-B85B-F5C5E5697425
volume: 112
year: '2014'
...
---
_id: '3532'
abstract:
- lang: eng
text: Multichannel tetrode array recording in awake behaving animals provides a
powerful method to record the activity of large numbers of neurons. The power
of this method could be extended if further information concerning the intracellular
state of the neurons could be extracted from the extracellularly recorded signals.
Toward this end, we have simultaneously recorded intracellular and extracellular
signals from hippocampal CA1 pyramidal cells and interneurons in the anesthetized
rat. We found that several intracellular parameters can be deduced from extracellular
spike waveforms. The width of the intracellular action potential is defined precisely
by distinct points on the extracellular spike. Amplitude changes of the intracellular
action potential are reflected by changes in the amplitude of the initial negative
phase of the extracellular spike, and these amplitude changes are dependent on
the state of the network. In addition, intracellular recordings from dendrites
with simultaneous extracellular recordings from the soma indicate that, on average,
action potentials are initiated in the perisomatic region and propagate to the
dendrites at 1.68 m/s. Finally we determined that a tetrode in hippocampal area
CA1 theoretically should be able to record electrical signals from similar to
1,000 neurons. Of these, 60-100 neurons should generate spikes of sufficient amplitude
to be detectable from the noise and to allow for their separation using current
spatial clustering methods. This theoretical maximum is in contrast to the approximately
six units that are usually detected per tetrode. From this, we conclude that a
large percentage of hippocampal CA1 pyramidal cells are silent in any given behavioral
condition.
acknowledgement: We thank M. Recce for comments on the manuscript and J. Hetke and
K.Wise for supplying us with the silicon probes (1P41RR09754).This work was supported
by National Institutes of Health Grants NS-34994,MH-54671, and MH-12403 (to D.
A. Henze), the Epilepsy Foundation of American (D. A.Henze), and an Eotvos fellowship
(Z. Borhegyi).
article_processing_charge: No
article_type: original
author:
- first_name: Darrell
full_name: Henze, Darrell
last_name: Henze
- first_name: Zsolt
full_name: Borhegyi, Zsolt
last_name: Borhegyi
- first_name: Jozsef L
full_name: Csicsvari, Jozsef L
id: 3FA14672-F248-11E8-B48F-1D18A9856A87
last_name: Csicsvari
orcid: 0000-0002-5193-4036
- first_name: Akira
full_name: Mamiya, Akira
last_name: Mamiya
- first_name: Kenneth
full_name: Harris, Kenneth
last_name: Harris
- first_name: György
full_name: Buzsáki, György
last_name: Buzsáki
citation:
ama: Henze D, Borhegyi Z, Csicsvari JL, Mamiya A, Harris K, Buzsáki G. Intracellular
features predicted by extracellular recordings in the hippocampus in vivo. Journal
of Neurophysiology. 2000;84(1):390-400. doi:10.1152/jn.2000.84.1.390
apa: Henze, D., Borhegyi, Z., Csicsvari, J. L., Mamiya, A., Harris, K., & Buzsáki,
G. (2000). Intracellular features predicted by extracellular recordings in the
hippocampus in vivo. Journal of Neurophysiology. American Physiological
Society. https://doi.org/10.1152/jn.2000.84.1.390
chicago: Henze, Darrell, Zsolt Borhegyi, Jozsef L Csicsvari, Akira Mamiya, Kenneth
Harris, and György Buzsáki. “Intracellular Features Predicted by Extracellular
Recordings in the Hippocampus in Vivo.” Journal of Neurophysiology. American
Physiological Society, 2000. https://doi.org/10.1152/jn.2000.84.1.390.
ieee: D. Henze, Z. Borhegyi, J. L. Csicsvari, A. Mamiya, K. Harris, and G. Buzsáki,
“Intracellular features predicted by extracellular recordings in the hippocampus
in vivo,” Journal of Neurophysiology, vol. 84, no. 1. American Physiological
Society, pp. 390–400, 2000.
ista: Henze D, Borhegyi Z, Csicsvari JL, Mamiya A, Harris K, Buzsáki G. 2000. Intracellular
features predicted by extracellular recordings in the hippocampus in vivo. Journal
of Neurophysiology. 84(1), 390–400.
mla: Henze, Darrell, et al. “Intracellular Features Predicted by Extracellular Recordings
in the Hippocampus in Vivo.” Journal of Neurophysiology, vol. 84, no. 1,
American Physiological Society, 2000, pp. 390–400, doi:10.1152/jn.2000.84.1.390.
short: D. Henze, Z. Borhegyi, J.L. Csicsvari, A. Mamiya, K. Harris, G. Buzsáki,
Journal of Neurophysiology 84 (2000) 390–400.
date_created: 2018-12-11T12:03:49Z
date_published: 2000-07-01T00:00:00Z
date_updated: 2023-05-02T14:31:13Z
day: '01'
doi: 10.1152/jn.2000.84.1.390
extern: '1'
external_id:
pmid:
- '10899213'
intvolume: ' 84'
issue: '1'
language:
- iso: eng
month: '07'
oa_version: None
page: 390 - 400
pmid: 1
publication: Journal of Neurophysiology
publication_identifier:
issn:
- 0022-3077
publication_status: published
publisher: American Physiological Society
publist_id: '2854'
quality_controlled: '1'
status: public
title: Intracellular features predicted by extracellular recordings in the hippocampus
in vivo
type: journal_article
user_id: ea97e931-d5af-11eb-85d4-e6957dddbf17
volume: 84
year: '2000'
...
---
_id: '3548'
abstract:
- lang: eng
text: Simultaneous recording from large numbers of neurons is a prerequisite for
understanding their cooperative behavior. Various recording techniques and spike
separation methods are being used toward this goal. However, the error rates involved
in spike separation have not yet been quantified. We studied the separation reliability
of “tetrode” (4-wire electrode) recorded spikes by monitoring simultaneously from
the same cell intracellularly with a glass pipette and extracellularly with a
tetrode. With manual spike sorting, we found a trade-off between Type I and Type
II errors, with errors typically ranging from 0 to 30% depending on the amplitude
and firing pattern of the cell, the similarity of the waveshapes of neighboring
neurons, and the experience of the operator. Performance using only a single wire
was markedly lower, indicating the advantages of multiple-site monitoring techniques
over single-wire recordings. For tetrode recordings, error rates were increased
by burst activity and during periods of cellular synchrony. The lowest possible
separation error rates were estimated by a search for the best ellipsoidal cluster
shape. Human operator performance was significantly below the estimated optimum.
Investigation of error distributions indicated that suboptimal performance was
caused by inability of the operators to mark cluster boundaries accurately in
a high-dimensional feature space. We therefore hypothesized that automatic spike-sorting
algorithms have the potential to significantly lower error rates. Implementation
of a semi-automatic classification system confirms this suggestion, reducing errors
close to the estimated optimum, in the range 0-8%.
acknowledgement: The costs of publication of this article were defrayed in part by
the payment of page charges. The article must therefore be hereby marked ‘‘advertisement’
’in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. We thank
R. Bruno for performing cluster analysis and drawing our attention to the AutoClass
program, M. Recce and P. Mitra for suggestions withdata analysis and comments on
the manuscript, C. King, G. Dragoi, and X.Leinekugel for performing cluster analysis,
and J. Hetke and K. Wise for supplying silicon probes. The data used in this paper
are available on request by e-mail to G. Buzsaki. This work was supported by National
Institutes of Health Grants NS-34994,413 MH-54671, and MH-12403 (to D. A. Henze)
and by the Epilepsy Foundationof America (to D. A. Henze).
article_processing_charge: No
article_type: original
author:
- first_name: Kenneth
full_name: Harris, Kenneth
last_name: Harris
- first_name: Darrell
full_name: Henze, Darrell
last_name: Henze
- first_name: Jozsef L
full_name: Csicsvari, Jozsef L
id: 3FA14672-F248-11E8-B48F-1D18A9856A87
last_name: Csicsvari
orcid: 0000-0002-5193-4036
- first_name: Hajima
full_name: Hirase, Hajima
last_name: Hirase
- first_name: György
full_name: Buzsáki, György
last_name: Buzsáki
citation:
ama: Harris K, Henze D, Csicsvari JL, Hirase H, Buzsáki G. Accuracy of tetrode spike
separation as determined by simultaneous intracellular and extracellular measurements.
Journal of Neurophysiology. 2000;84(1):401-414. doi:10.1152/jn.2000.84.1.401
apa: Harris, K., Henze, D., Csicsvari, J. L., Hirase, H., & Buzsáki, G. (2000).
Accuracy of tetrode spike separation as determined by simultaneous intracellular
and extracellular measurements. Journal of Neurophysiology. American Physiological
Society. https://doi.org/10.1152/jn.2000.84.1.401
chicago: Harris, Kenneth, Darrell Henze, Jozsef L Csicsvari, Hajima Hirase, and
György Buzsáki. “Accuracy of Tetrode Spike Separation as Determined by Simultaneous
Intracellular and Extracellular Measurements.” Journal of Neurophysiology.
American Physiological Society, 2000. https://doi.org/10.1152/jn.2000.84.1.401.
ieee: K. Harris, D. Henze, J. L. Csicsvari, H. Hirase, and G. Buzsáki, “Accuracy
of tetrode spike separation as determined by simultaneous intracellular and extracellular
measurements,” Journal of Neurophysiology, vol. 84, no. 1. American Physiological
Society, pp. 401–414, 2000.
ista: Harris K, Henze D, Csicsvari JL, Hirase H, Buzsáki G. 2000. Accuracy of tetrode
spike separation as determined by simultaneous intracellular and extracellular
measurements. Journal of Neurophysiology. 84(1), 401–414.
mla: Harris, Kenneth, et al. “Accuracy of Tetrode Spike Separation as Determined
by Simultaneous Intracellular and Extracellular Measurements.” Journal of Neurophysiology,
vol. 84, no. 1, American Physiological Society, 2000, pp. 401–14, doi:10.1152/jn.2000.84.1.401.
short: K. Harris, D. Henze, J.L. Csicsvari, H. Hirase, G. Buzsáki, Journal of Neurophysiology
84 (2000) 401–414.
date_created: 2018-12-11T12:03:54Z
date_published: 2000-07-01T00:00:00Z
date_updated: 2023-05-02T14:16:45Z
day: '01'
doi: 10.1152/jn.2000.84.1.401
extern: '1'
external_id:
pmid:
- '10899214 '
intvolume: ' 84'
issue: '1'
language:
- iso: eng
month: '07'
oa_version: None
page: 401 - 414
pmid: 1
publication: Journal of Neurophysiology
publication_identifier:
issn:
- 0022-3077
publication_status: published
publisher: American Physiological Society
publist_id: '2837'
quality_controlled: '1'
status: public
title: Accuracy of tetrode spike separation as determined by simultaneous intracellular
and extracellular measurements
type: journal_article
user_id: ea97e931-d5af-11eb-85d4-e6957dddbf17
volume: 84
year: '2000'
...