Electrophysiological Recordings from Identified Cell Types in the Olfactory Cortex of Awake Mice.
Cell types
In vivo electrophysiology
Optogenetics
Piriform cortex
Journal
Methods in molecular biology (Clifton, N.J.)
ISSN: 1940-6029
Titre abrégé: Methods Mol Biol
Pays: United States
ID NLM: 9214969
Informations de publication
Date de publication:
2023
2023
Historique:
medline:
11
9
2023
pubmed:
9
9
2023
entrez:
9
9
2023
Statut:
ppublish
Résumé
Neural circuits consist of a myriad of distinct cell types, each with specific intrinsic properties and patterns of synaptic connectivity, which transform neural input and convey this information to downstream targets. Understanding how different features of an odor stimulus are encoded and relayed to their appropriate targets will require selective identification and manipulation of these different elements of the circuit. Here, we describe methods to obtain dense, extracellular electrophysiological recordings of odor-evoked activity in olfactory (piriform) cortex of awake, head-fixed mice, and optogenetic tools and procedures to identify genetically defined cell types within this circuit.
Identifiants
pubmed: 37688735
doi: 10.1007/978-1-0716-3425-7_16
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
209-221Subventions
Organisme : NINDS NIH HHS
ID : U19 NS112953
Pays : United States
Organisme : NIDCD NIH HHS
ID : R01 DC016782
Pays : United States
Organisme : NIDCD NIH HHS
ID : R01 DC015525
Pays : United States
Organisme : NIDCD NIH HHS
ID : K99 DC009839
Pays : United States
Informations de copyright
© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.
Références
Hubel DH, Wiesel TN (1959) Receptive fields of single neurones in the cat’s striate cortex. J Physiol 148:574–591
doi: 10.1113/jphysiol.1959.sp006308
pubmed: 14403679
pmcid: 1363130
Hubel DH, Wiesel TN (1962) Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex. J Physiol 160(106–154):2
O’Keefe J, Dostrovsky J (1971) The hippocampus as a spatial map. Preliminary evidence from unit activity in the freely-moving rat. Brain Res 34:171–175. https://doi.org/10.1016/0006-8993(71)90358-1
doi: 10.1016/0006-8993(71)90358-1
pubmed: 5124915
O’Keefe J (1976) Place units in the hippocampus of the freely moving rat. Exp Neurol 51:78–109. https://doi.org/10.1016/0014-4886(76)90055-8
doi: 10.1016/0014-4886(76)90055-8
pubmed: 1261644
Georgopoulos AP, Kalaska JF, Caminiti R, Massey JT (1982) On the relations between the direction of two-dimensional arm movements and cell discharge in primate motor cortex. J Neurosci 2:1527–1537. https://doi.org/10.1523/JNEUROSCI.02-11-01527.1982
doi: 10.1523/JNEUROSCI.02-11-01527.1982
pubmed: 7143039
pmcid: 6564361
Georgopoulos AP, Schwartz AB, Kettner RE (1986) Neuronal population coding of movement direction. Science 233:1416–1419. https://doi.org/10.1126/science.3749885
doi: 10.1126/science.3749885
pubmed: 3749885
Rigotti M, Barak O, Warden MR et al (2013) The importance of mixed selectivity in complex cognitive tasks. Nature 497:585–590. https://doi.org/10.1038/nature12160
doi: 10.1038/nature12160
pubmed: 23685452
pmcid: 4412347
Kaufman MT, Benna MK, Rigotti M et al (2022) The implications of categorical and category-free mixed selectivity on representational geometries. Curr Opin Neurobiol 77:102644. https://doi.org/10.1016/j.conb.2022.102644
doi: 10.1016/j.conb.2022.102644
pubmed: 36332415
Quian Quiroga R, Panzeri S (2009) Extracting information from neuronal populations: information theory and decoding approaches. Nat Rev Neurosci 10:173–185. https://doi.org/10.1038/nrn2578
doi: 10.1038/nrn2578
pubmed: 19229240
Buzsáki G (2010) Neural syntax: cell assemblies, synapsembles and readers. Neuron 68:362–385. https://doi.org/10.1016/j.neuron.2010.09.023
doi: 10.1016/j.neuron.2010.09.023
pubmed: 21040841
pmcid: 3005627
Buzsáki G (2004) Large-scale recording of neuronal ensembles. Nat Neurosci 7:446–451. https://doi.org/10.1038/nn1233
doi: 10.1038/nn1233
pubmed: 15114356
Steinmetz NA, Aydin C, Lebedeva A et al (2021) Neuropixels 2.0: a miniaturized high-density probe for stable, long-term brain recordings. Science 372:eabf4588. https://doi.org/10.1126/science.abf4588
doi: 10.1126/science.abf4588
pubmed: 33859006
pmcid: 8244810
Guo ZV, Li N, Huber D et al (2014) Flow of cortical activity underlying a tactile decision in mice. Neuron 81:179–194. https://doi.org/10.1016/j.neuron.2013.10.020
doi: 10.1016/j.neuron.2013.10.020
pubmed: 24361077
Semedo JD, Zandvakili A, Machens CK et al (2019) Cortical areas interact through a communication subspace. Neuron 102:249–259.e4. https://doi.org/10.1016/j.neuron.2019.01.026
doi: 10.1016/j.neuron.2019.01.026
pubmed: 30770252
pmcid: 6449210
Steinmetz NA, Zatka-Haas P, Carandini M, Harris KD (2019) Distributed coding of choice, action and engagement across the mouse brain. Nature 576:266–273. https://doi.org/10.1038/s41586-019-1787-x
doi: 10.1038/s41586-019-1787-x
pubmed: 31776518
pmcid: 6913580
Siegle JH, Jia X, Durand S et al (2021) Survey of spiking in the mouse visual system reveals functional hierarchy. Nature 592:86–92. https://doi.org/10.1038/s41586-020-03171-x
doi: 10.1038/s41586-020-03171-x
pubmed: 33473216
pmcid: 10399640
Andermann ML, Kerlin AM, Roumis DK et al (2011) Functional specialization of mouse higher visual cortical areas. Neuron 72:1025–1039. https://doi.org/10.1016/j.neuron.2011.11.013
doi: 10.1016/j.neuron.2011.11.013
pubmed: 22196337
Pinto L, Rajan K, DePasquale B et al (2019) Task-dependent changes in the large-scale dynamics and necessity of cortical regions. Neuron 104:810–824.e9. https://doi.org/10.1016/j.neuron.2019.08.025
doi: 10.1016/j.neuron.2019.08.025
pubmed: 31564591
pmcid: 7036751
Otazu GH, Chae H, Davis MB, Albeanu DF (2015) Cortical feedback Decorrelates olfactory bulb output in awake mice. Neuron 86:1461–1477. https://doi.org/10.1016/j.neuron.2015.05.023
doi: 10.1016/j.neuron.2015.05.023
pubmed: 26051422
pmcid: 7448302
Bolding KA, Franks KM (2017) Complementary codes for odor identity and intensity in olfactory cortex. eLife 6:e22630. https://doi.org/10.7554/eLife.22630
doi: 10.7554/eLife.22630
pubmed: 28379135
pmcid: 5438247
Bolding KA, Franks KM (2018) Recurrent cortical circuits implement concentration-invariant odor coding. Science 361:eaat6904. https://doi.org/10.1126/science.aat6904
doi: 10.1126/science.aat6904
pubmed: 30213885
pmcid: 6492549
Bolding KA, Nagappan S, Han B-X et al (2020) Recurrent circuitry is required to stabilize piriform cortex odor representations across brain states. eLife 9:e53125. https://doi.org/10.7554/eLife.53125
doi: 10.7554/eLife.53125
pubmed: 32662420
pmcid: 7360366
Pashkovski SL, Iurilli G, Brann D et al (2020) Structure and flexibility in cortical representations of odour space. Nature 583:253–258. https://doi.org/10.1038/s41586-020-2451-1
doi: 10.1038/s41586-020-2451-1
pubmed: 32612230
pmcid: 7450987
Zak JD, Reddy G, Vergassola M, Murthy VN (2020) Antagonistic odor interactions in olfactory sensory neurons are widespread in freely breathing mice. Nat Commun 11:3350. https://doi.org/10.1038/s41467-020-17124-5
doi: 10.1038/s41467-020-17124-5
pubmed: 32620767
pmcid: 7335155
Isaacson JS, Scanziani M (2011) How Inhibition Shapes Cortical Activity Neuron. Cur Biol 72:231–243. https://doi.org/10.1016/j.neuron.2011.09.027
doi: 10.1016/j.neuron.2011.09.027
Pi H-J, Hangya B, Kvitsiani D et al (2013) Cortical interneurons that specialize in disinhibitory control. Nature 503:521–524. https://doi.org/10.1038/nature12676
doi: 10.1038/nature12676
pubmed: 24097352
pmcid: 4017628
Kepecs A, Fishell G (2014) Interneuron cell types are fit to function. Nature 505:318–326. https://doi.org/10.1038/nature12983
doi: 10.1038/nature12983
pubmed: 24429630
pmcid: 4349583
Zeng H, Sanes JR (2017) Neuronal cell-type classification: challenges, opportunities and the path forward. Nat Rev Neurosci 18:530–546. https://doi.org/10.1038/nrn.2017.85
doi: 10.1038/nrn.2017.85
pubmed: 28775344
Economo MN, Viswanathan S, Tasic B et al (2018) Distinct descending motor cortex pathways and their roles in movement. Nature 563:79–84. https://doi.org/10.1038/s41586-018-0642-9
doi: 10.1038/s41586-018-0642-9
pubmed: 30382200
Tasic B, Yao Z, Graybuck LT et al (2018) Shared and distinct transcriptomic cell types across neocortical areas. Nature 563:72–78. https://doi.org/10.1038/s41586-018-0654-5
doi: 10.1038/s41586-018-0654-5
pubmed: 30382198
pmcid: 6456269
Fox SE, Ranck JB (1975) Localization and anatomical identification of theta and complex spike cells in dorsal hippocampal formation of rats. Exp Neurol 49:299–313. https://doi.org/10.1016/0014-4886(75)90213-7
doi: 10.1016/0014-4886(75)90213-7
pubmed: 1183529
Fox SE, Ranck JB (1981) Electrophysiological characteristics of hippocampal complex-spike cells and theta cells. Exp Brain Res 41:399–410. https://doi.org/10.1007/BF00238898
doi: 10.1007/BF00238898
pubmed: 7215500
Kubie JL, Muller RU, Bostock E (1990) Spatial firing properties of hippocampal theta cells. J Neurosci 10:1110–1123. https://doi.org/10.1523/JNEUROSCI.10-04-01110.1990
doi: 10.1523/JNEUROSCI.10-04-01110.1990
pubmed: 2329371
pmcid: 6570223
Barthó P, Hirase H, Monconduit L et al (2004) Characterization of neocortical principal cells and interneurons by network interactions and extracellular features. J Neurophysiol 92:600–608. https://doi.org/10.1152/jn.01170.2003
doi: 10.1152/jn.01170.2003
pubmed: 15056678
Fujisawa S, Amarasingham A, Harrison MT, Buzsáki G (2008) Behavior-dependent short-term assembly dynamics in the medial prefrontal cortex. Nat Neurosci 11:823–833. https://doi.org/10.1038/nn.2134
doi: 10.1038/nn.2134
pubmed: 18516033
pmcid: 2562676
English DF, McKenzie S, Evans T et al (2017) Pyramidal cell-interneuron circuit architecture and dynamics in hippocampal networks. Neuron 96:505–520.e7. https://doi.org/10.1016/j.neuron.2017.09.033
doi: 10.1016/j.neuron.2017.09.033
pubmed: 29024669
pmcid: 5659748
Lima SQ, Hromádka T, Znamenskiy P, Zador AM (2009) PINP: a new method of tagging neuronal populations for identification during in vivo electrophysiological recording. PLoS One 4:e6099. https://doi.org/10.1371/journal.pone.0006099
doi: 10.1371/journal.pone.0006099
pubmed: 19584920
pmcid: 2702752
Cardin JA, Carlén M, Meletis K et al (2010) Targeted optogenetic stimulation and recording of neurons in vivo using cell-type-specific expression of Channelrhodopsin-2. Nat Protoc 5:247–254. https://doi.org/10.1038/nprot.2009.228
doi: 10.1038/nprot.2009.228
pubmed: 20134425
pmcid: 3655719
Zhang S-J, Ye J, Miao C et al (2013) Optogenetic dissection of entorhinal-hippocampal functional connectivity. Science 340:1232627. https://doi.org/10.1126/science.1232627
doi: 10.1126/science.1232627
pubmed: 23559255
Roux L, Stark E, Sjulson L, Buzsáki G (2014) In vivo optogenetic identification and manipulation of GABAergic interneuron subtypes. Curr Opin Neurobiol 26:88–95. https://doi.org/10.1016/j.conb.2013.12.013
doi: 10.1016/j.conb.2013.12.013
pubmed: 24440414
Kim CK, Adhikari A, Deisseroth K (2017) Integration of optogenetics with complementary methodologies in systems neuroscience. Nat Rev Neurosci 18:222–235. https://doi.org/10.1038/nrn.2017.15
doi: 10.1038/nrn.2017.15
pubmed: 28303019
pmcid: 5708544
Fenno LE, Mattis J, Ramakrishnan C et al (2014) Targeting cells with single vectors using multiple-feature Boolean logic. Nat Methods 11:763–772. https://doi.org/10.1038/nmeth.2996
doi: 10.1038/nmeth.2996
pubmed: 24908100
pmcid: 4085277
Fenno LE, Ramakrishnan C, Kim YS et al (2020) Comprehensive dual- and triple-feature intersectional single-vector delivery of diverse functional payloads to cells of behaving mammals. Neuron 107:836–853.e11. https://doi.org/10.1016/j.neuron.2020.06.003
doi: 10.1016/j.neuron.2020.06.003
pubmed: 32574559
pmcid: 7687746
Madisen L, Garner AR, Shimaoka D et al (2015) Transgenic mice for intersectional targeting of neural sensors and effectors with high specificity and performance. Neuron 85:942–958. https://doi.org/10.1016/j.neuron.2015.02.022
doi: 10.1016/j.neuron.2015.02.022
pubmed: 25741722
pmcid: 4365051
Daigle TL, Madisen L, Hage TA et al (2018) A suite of transgenic driver and reporter mouse lines with enhanced brain-cell-type targeting and functionality. Cell 174:465–480.e22. https://doi.org/10.1016/j.cell.2018.06.035
doi: 10.1016/j.cell.2018.06.035
pubmed: 30007418
pmcid: 6086366
Nagappan S, Franks KM (2021) Parallel processing by distinct classes of principal neurons in the olfactory cortex. eLife 10:e73668. https://doi.org/10.7554/eLife.73668
doi: 10.7554/eLife.73668
pubmed: 34913870
pmcid: 8676325
Guo ZV, Hires SA, Li N et al (2014) Procedures for behavioral experiments in head-fixed mice. PLoS One 9:e88678. https://doi.org/10.1371/journal.pone.0088678
doi: 10.1371/journal.pone.0088678
pubmed: 24520413
pmcid: 3919818
Barkus C, Bergmann C, Branco T et al (2022) Refinements to rodent head fixation and fluid/food control for neuroscience. J Neurosci Methods 381:109705. https://doi.org/10.1016/j.jneumeth.2022.109705
doi: 10.1016/j.jneumeth.2022.109705
pubmed: 36096238
Huber D, Gutnisky DA, Peron S et al (2012) Multiple dynamic representations in the motor cortex during sensorimotor learning. Nature 484:473–478. https://doi.org/10.1038/nature11039
doi: 10.1038/nature11039
pubmed: 22538608
pmcid: 4601999
Osborne JE, Dudman JT (2014) RIVETS: a mechanical system for in vivo and in vitro electrophysiology and imaging. PLoS One 9:e89007. https://doi.org/10.1371/journal.pone.0089007
doi: 10.1371/journal.pone.0089007
pubmed: 24551206
pmcid: 3925229
The International Brain Laboratory, Aguillon-Rodriguez V, Angelaki D et al (2021) Standardized and reproducible measurement of decision-making in mice. eLife 10:e63711. https://doi.org/10.7554/eLife.63711
doi: 10.7554/eLife.63711
pmcid: 8137147
Goldey GJ, Roumis DK, Glickfeld LL et al (2014) Removable cranial windows for long-term imaging in awake mice. Nat Protoc 9:2515–2538. https://doi.org/10.1038/nprot.2014.165
doi: 10.1038/nprot.2014.165
pubmed: 25275789
pmcid: 4442707
Yger P, Spampinato GL, Esposito E et al (2018) A spike sorting toolbox for up to thousands of electrodes validated with ground truth recordings in vitro and in vivo. eLife 7:e34518. https://doi.org/10.7554/eLife.34518
doi: 10.7554/eLife.34518
pubmed: 29557782
pmcid: 5897014
Pachitariu M, Sridhar S, Stringer C (2023) Solving the spike sorting problem with Kilosort. bioRxiv, 2023-01. https://doi.org/10.1101/2023.01.07.523036
Buccino AP, Hurwitz CL, Garcia S et al (2020) SpikeInterface, a unified framework for spike sorting. eLife 9:e61834. https://doi.org/10.7554/eLife.61834
doi: 10.7554/eLife.61834
pubmed: 33170122
pmcid: 7704107
Kvitsiani D, Ranade S, Hangya B et al (2013) Distinct behavioural and network correlates of two interneuron types in prefrontal cortex. Nature 498:363–366. https://doi.org/10.1038/nature12176
doi: 10.1038/nature12176
pubmed: 23708967
pmcid: 4349584
Wolff SBE, Gründemann J, Tovote P et al (2014) Amygdala interneuron subtypes control fear learning through disinhibition. Nature 509:453–458. https://doi.org/10.1038/nature13258
doi: 10.1038/nature13258
pubmed: 24814341
Rowland DC, Obenhaus HA, Skytøen ER et al (2018) Functional properties of stellate cells in medial entorhinal cortex layer II. eLife 7:e36664. https://doi.org/10.7554/eLife.36664
doi: 10.7554/eLife.36664
pubmed: 30215597
pmcid: 6140717