Science - USA (2022-02-04)

Tethering elements foster appropriate enhancer-
promoter interactions, whereas TAD boundaries
prevent inappropriate associations.

REFERENCES AND NOTES

1. J. Dekker, L. Mirny,Cell 164 , 1110–1121 (2016).


2. H. K. Long, S. L. Prescott, J. Wysocka,Cell 167 , 1170– 1187
   (2016).


3. E. E. M. Furlong, M. Levine,Science 361 , 1341– 1345
   (2018).


4. M. I. Robson, A. R. Ringel, S. Mundlos,Mol. Cell 74 , 1110– 1122
   (2019).


5. H. Chenet al.,Nat. Genet. 50 , 1296–1303 (2018).


6. G. Andreyet al.,Science 340 , 1234167 (2013).


7. V. Narendraet al.,Science 347 , 1017–1021 (2015).


8. B. K. Kragesteenet al.,Nat. Genet. 50 , 1463–1473 (2018).


9. C. Paliouet al.,Proc. Natl. Acad. Sci. U.S.A. 116 , 12390– 12399
   (2019).


10. E. Rodríguez-Carballoet al.,Proc. Natl. Acad. Sci. U.S.A. 117 ,
    31231 – 31241 (2020).


11. Y. Ghavi-Helmet al.,Nature 512 , 96–100 (2014).


12. J. R. Dixonet al.,Nature 485 , 376–380 (2012).


13. D. G. Lupiáñezet al.,Cell 161 , 1012–1025 (2015).


14. S. S. P. Raoet al.,Cell 171 , 305–320.e24 (2017).


15. Y. Ghavi-Helmet al.,Nat. Genet. 51 , 1272–1282 (2019).


16. A. Despanget al.,Nat. Genet. 51 , 1263–1271 (2019).


17. N. Kuboet al.,Nat. Struct. Mol. Biol. 28 , 152–161 (2021).


18. T. S. Hsiehet al.,Mol. Cell 78 , 539–553.e8 (2020).


19. E. Ing-Simmonset al.,Nat. Genet. 53 , 487–499 (2021).


20. J. G. Gindhart Jr., A. N. King, T. C. Kaufman,Genetics 139 ,
    781 – 795 (1995).


21. V. C. Calhoun, A. Stathopoulos, M. Levine,Proc. Natl. Acad. Sci.
    U.S.A. 99 , 9243–9247 (2002).


22. V. C. Calhoun, M. Levine,Proc. Natl. Acad. Sci. U.S.A. 100 ,
    9878 – 9883 (2003).


23. Q. Zhouet al.,Nat. Commun. 12 , 43 (2021).


24. T. Pachanoet al.,Nat. Genet. 53 , 1036–1049 (2021).


25. M. L. Espináset al.,J. Biol. Chem. 274 , 16461– 16469
    (1999).


26. T. Mahmoudi, K. R. Katsani, C. P. Verrijzer,EMBO J. 21 ,
    1775 – 1781 (2002).


27. J. G. Gindhart Jr., T. C. Kaufman,Genetics 139 , 797– 814
    (1995).


28. V. Loubiere, G. L. Papadopoulos, Q. Szabo, A. M. Martinez,
    G. Cavalli,Sci. Adv. 6 , eaax4001 (2020).


29. P. Batut, phil-batut/transcription_imaging:
    transcription_imaging (Batut et al., 2021). Zenodo (2021);
    http://doi.org/10.5281/zenodo.5730297.

ACKNOWLEDGMENTS
We thank J. Rowley for his help in using Significant Interaction
Peak-caller (SIP) and optimizing parameters; N. Treen, X. Li,
L. Lemaire, C. Cao, A. Mariossi, P. Paul, and J. Batut for helpful
comments and suggestions; and S. Blythe and E. Gatzogiannis for
technical advice.Funding:National Institutes of Health grant R35
GM118147.Author contributions:Conceptualization: P.J.B.,
M.S.L.; Methodology: P.J.B., M.L., J.R.; Investigation: P.J.B., X.Y.B.,
Z.S.; Software: P.J.B.; Formal analysis: P.J.B., X.Y.B.; Visualization:
P.J.B., X.Y.B.; Funding acquisition: M.S.L.; Project administration:
M.S.L.; Supervision: M.S.L.; Writing–original draft: P.J.B.; Writing–
review and editing: P.J.B., M.S.L., X.Y.B.Competing interests:
The authors declare that they have no competing interests.Data and
materials availability:All Micro-C sequencing data are available
through GEO accession number GSE171396. All imaging data are
freely available upon request. All materials used in the analysis are
available upon request, and custom data analysis code is available
through GitHub (https://github.com/phil-batut/transcription_
imaging.git) and Zenodo ( 29 ).

SUPPLEMENTARY MATERIALS
science.org/doi/10.1126/science.abi7178
Materials and Methods
Figs. S1 to S14
Tables S1 to S4
References ( 30 Ð 57 )
MDAR Reproducibility Checklist

25 March 2021; resubmitted 16 October 2021
Accepted 6 December 2021
10.1126/science.abi7178

NEUROSCIENCE

Probing subthreshold dynamics of hippocampal

neurons by pulsed optogenetics

Manuel Valero^1 *, Ipshita Zutshi^1 , Euisik Yoon2,3, György Buzsáki1,4,5*

Understanding how excitatory (E) and inhibitory (I) inputs are integrated by neurons requires monitoring

their subthreshold behavior. We probed the subthreshold dynamics using optogenetic depolarizing

pulses in hippocampal neuronal assemblies in freely moving mice. Excitability decreased during sharp-

wave ripples coupled with increased I. In contrast to this“negative gain,”optogenetic probing showed

increased within-field excitability in place cells by weakening I and unmasked stable place fields in

initially non–place cells. Neuronal assemblies active during sharp-wave ripples in the home cage

predicted spatial overlap and sequences of place fields of both place cells and unmasked preexisting

place fields of non–place cells during track running. Thus, indirect probing of subthreshold dynamics in

neuronal populations permits the disclosing of preexisting assemblies and modes of neuronal operations.

U

nderstanding how neurons integrate

excitatory (E) and inhibitory (I) inputs

requires access to the neuron’s sub-

threshold dynamics ( 1 – 4 ). Because in-

tracellular monitoring of cell assemblies

in behaving animals is currently unrealistic,

different single-cell modes of operations (or

“models”) have been proposed to explain firing

characteristics in various circumstances (Fig. 1,

A and B, and fig. S1) ( 1 ). In the“tuned excita-

tion”(“blanket”inhibition) ( 1 , 5 ) and“balanced

network”models (I activity tracks E changes)

( 6 – 8 ), both membrane polarization (Vm) and

firing rate response decrease at more depolar-

izedVm(Fig. 1, A and B) ( 9 – 11 ). By contrast, in

the“reciprocal network”model, reduction of I

is coupled toVmdepolarization and increased

firing rate (Fig. 1, A and B) ( 12 – 14 ). Thus, by

varyingVmexperimentally and observing the

changes in firing rates, one can gain access

to the subthreshold behavior of neurons (fig.

S1). Adding active conductances to the model

neuron affected its quantitative features but

did not change these predictions qualitatively

(figs. S2 and S3).

We probedVmwith short optogenetic pulses.

Using micro–light-emitting diode (mLED)

probes (four shanks with threemLEDs on each

shank) ( 15 ), we recorded and probed large num-

bers of CA1 pyramidal neurons simultaneously

in freely moving calcium/calmodulin–dependent

protein kinase II alpha (CamKIIa) -Cre::Ai32

mice (Fig. 1, C and D, and fig. S4;n= 822

pyramidal neurons in four mice; 43.3 ± 8.37

pyramidal neurons per session).mLEDs were

activated (0.02 to 0.1mW, 20 ms duration) with

randomly variable (20 to 40 ms) offsets so

that stimulation of each site reccurred at

~0.3- to 0.6-s intervals Fig. 1C and fig. S5).

Random intervals (20 ms) between the light

pulses served as control epochs for compar-

ison (materials and methods). Of 822 neurons,

611 responded unequally to the three neigh-

boringmLEDs, owing to their different dis-

tances from the recorded neurons (Fig. 1, D

and E, and figs. S4 and S5), and these re-

sponses were used as a proxy for estimating

relative changes ofVmand E/I dynamics. The

evoked spike responses varied as a function

of brains state (fig. S6) but did not perturb

the firing features of the neurons (fig. S7).

No changes were observed in nonresponsive

neurons, safeguarding against local network-

induced effects (fig. S8).

During sharp-wave ripples (SPW-Rs), excit-

atory neurons increased their firing rates more

than inhibitory neurons (fig. S9) ( 6 ). In con-

trast to this population gain of excitation,

light-induced spike responses in individual

pyramidal cells decreased during SPW-Rs

(DRate;Fig.1,FtoI).IncreasingVmdepo-

larization decreased the light-induced re-

sponse during SPW-Rs (Fig. 1J), resembling

the balanced mode of operation (Fig. 1A). This

conclusion was further supported by the neg-

ative correlation between firing-rate change

during SPW-R and baseline firing rates of

neurons (r=–0.19,P<10−^7 ; fig. S10) and more

directly by intracellular experiments, in which

Vmwas systematically varied (Fig. 1, K to M),

reproducing the effect seen with optogenetic

Vmdepolarization (Fig. 1I) and favoring the

balanced E/I model.

Next, we examined the subthreshold E/I dy-

namics of place cells. During track running,

threeblocksof10baselinerunsonalinear

track were interleaved with two blocks of 40

to 50 stimulation runs (fig. S7D). We observed a

570 4 FEBRUARY 2022•VOL 375 ISSUE 6580 science.orgSCIENCE

(^1) Neuroscience Institute, Langone Medical Center, New York
University, New York, NY 10016, USA.^2 Department of
Electrical Engineering and Computer Science, University
of Michigan, Ann Arbor, MI 48109, USA.^3 Center for
Nanomedicine, Institute for Basic Science (IBS) and
Graduate Program of Nano Biomedical Engineering (Nano
BME), Yonsei University, Seoul 03722, South Korea.
(^4) Neuroscience Institute and Department of Neurology,
Langone Medical Center, New York, NY 10016, USA.^5 Center
for Neural Science, New York University, New York, NY
10003, USA.
*Corresponding author. Email: [email protected] (M.V.);
[email protected] (G.B.)
RESEARCH | REPORTS