Background: “One for all, and all for one,” the famous rallying cry of the Three Musketeers, in Alexandre Dumas’s popular novel, certainly applies to the 20,000 cells composing the suprachiasmatic nuclei (SCN). These cells work together to form the central clock that coordinates body rhythms in tune with the day-night cycle. Like virtually every body cell, individual SCN cells exhibit autonomous circadian oscillations, but this rhythmicity only reaches a high level of precision and robustness when the cells are coupled with their neighbors. Therefore, understanding the functional network organization of SCN cells beyond their core rhythmicity is an important issue in circadian biology. Summary: The present review summarizes the main results from our recent study demonstrating the feasibility of recording SCN cells in freely moving mice and the significance of variations in intracellular calcium over several timescales. Key Message: We discuss how in vivo imaging at the cell level will be pivotal to interrogate the mammalian master clock, in an integrated context that preserves the SCN network organization, with intact inputs and outputs.

One remarkable feature of neuroendocrine systems resides in their temporal dynamics, characterized by pulsatile patterns of hormonal secretion into the bloodstream. These rhythmic pulses not only underscore the temporal dimension of endocrine signaling but also convey its functional significance. Typical examples include the preovulatory surge in luteinizing hormone crucial for female reproduction [1, 2], intermittent pulses of circulating growth hormone that encode sex dimorphism in rodent liver metabolism [3, 4], and the ultradian rhythm in cortisol release pivotal for regulating various bodily functions, from inflammatory processes to cognitive psychophysiology [5, 6].

Neuroendocrine pulses are intricately governed by established systemic regulations, which entail complex hormonal feedforward and feedback loops among various organs along each neuroendocrine axis. Moreover, pulses arise from oscillatory mechanisms operating at the cellular level or from emergent properties within cell networks, spanning across neuroendocrine organs and upstream structures like the suprachiasmatic nuclei (SCN), where the master circadian clock resides [7]. Despite the long-standing use of traditional reductionist methods such as cell culture or tissue explants to interrogate the mechanisms underlying neuroendocrine dynamics [8‒11], addressing cell network and single cell dynamics within their systemic regulatory context remains a formidable challenge in contemporary neuroendocrinology.

In the past decade, significant technical advancements have revolutionized neuroscience. Innovations such as fiber photometry and miniaturized fluorescence microscopes now enable the visualization of vital indicators in live animal models, facilitating real-time monitoring of fluctuations at both cell population and single cell levels [12‒15]. Optogenetic and chemogenetic tools have further allowed for the assessment of functional and behavioral outcomes by activating or inhibiting individual cells or targeted cell populations. These methodologies have already demonstrated success in investigating neuroendocrine systems, including the intricate regulation of the pituitary gland and hypothalamic neurons governing reproduction and food intake [16‒20].

In a recent endeavor, we employed a microendoscope to study cell calcium dynamics in the SCN of freely moving mice [21]. Here, we highlight the key findings from this proof-of-principle study and discuss how this innovative approach will significantly contribute to our understanding of the circadian pacemaker in its fully preserved input-oscillator-output configuration.

Circadian clocks have emerged through several independent evolutionary events and are ubiquitous across all kingdoms of life [22]. This widespread distribution underscores their crucial adaptive significance in coping with the predictable fluctuations of day and night on Earth’s surface. Rather than passively reacting to variations in light intensity and temperature, living organisms are assumed to leverage their circadian clocks to anticipate and synchronize with daily environmental changes [23‒25]. This proactive behavior enables them to fine-tune their behavior and physiology, thereby enhancing their overall fitness and bolstering their prospects for survival.

In mammals, the SCN contain the central clock that coordinates body rhythms in tune with the day-night cycle [7, 26]. They form a paired tiny region of only 20,000 cells each nestled deep in the brain, in the ventral hypothalamus. Within these cells, much like in virtually every other cell of the body, a molecular mechanism governed by so-called clock genes engaged in transcription-translation feedback loops generates near-24-h oscillations. Yet, although this cell-autonomous oscillator is inherently irregular and inconsistent, specific intercellular communications in the SCN bestow upon it two imperative properties of a circadian pacemaker: precision and robustness [26‒30]. Precision ensures dependable circadian oscillations with consistent periods, while robustness enables the pacemaker to withstand external disturbances, preventing, for instance, mistaking a full moon night for day or a cloudy day for night.

Paradoxically, while the robustness of the circadian pacemaker proves invaluable in natural day-night conditions, it becomes a double-edged sword in the era of artificial lighting, particularly prevalent in modern society. The circadian clock struggles to adapt to the work schedules of rotating or night shift workers, heightening the risk of long-term health issues such as metabolic syndrome, cardiovascular accidents, cancer, or depression [31, 32]. Jetlag, a direct consequence of circadian inertia stemming from clock robustness, plagues those traversing time zones. More generally, the lack of flexibility of our circadian clock is the source of discrepancies between biological time and social schedules for many of us [33, 34]. This social jetlag also correlates with depression scores and other mental health disorders [35‒37].

Given that cell-cell communications within the SCN bolster the robustness of the circadian pacemaker, disrupting the SCN cell network presents a potential strategy to mitigate circadian misalignment and its ramifications in a modern 24/7 society, active 24 h a day, 7 days a week [38]. Pioneering studies have demonstrated remarkably swift responses to experimental jetlag in mouse models with altered interneuronal coupling in the SCN. Specifically, mice exhibiting impaired vasopressin receptor transduction [39] or disrupted sonic hedgehog signaling in neuromedin S-containing neurons [40] re-entrain almost instantly when exposed to a new light phase. Consequently, these cellular pathways represent promising targets beyond the core clock mechanism for modulating circadian rhythmicity.

The circuit-level organization of the SCN has undergone extensive study, revealing that it comprises several neuronal subtypes distinguished by their location and the expression of specific gene markers, many of which encode neuropeptides [41, 42]. While multiple subpopulations of SCN neurons contribute to circadian rhythmicity [43, 44], none has been identified as a unique, clearly defined pacemaker population [26]. Recent research has expanded our understanding by demonstrating that not only neurons but also astrocytes exhibit rhythmic oscillations and play a role in circadian timekeeping [45‒48]. These cellular populations are coordinated through synaptic neurotransmission and volume diffusion of paracrine factors [49‒52], yet they do not oscillate perfectly in phase. Instead, circadian waves in clock gene expression or cytosolic calcium concentration [Ca2+]i – but not in voltage and electrical firing – propagate throughout SCN slices, illustrating a complex phase relationship between different SCN regions [53‒56]. Importantly, alterations in the stereotyped spatiotemporal pattern observed in slices from mice housed under different day lengths underscore the plasticity of the SCN network architecture [57]. The development of in in vivo imaging technologies now offers the ability to observe the SCN cell network in freely moving mice at a cellular resolution. This advancement promises to provide further insights into its operational mechanisms and modulation, complementing the wealth of data garnered from in vitro preparations.

The various techniques used to monitor and manipulate SCN cell activity in vivo, from microdialysis studies to optogenetics, have already been reviewed elsewhere [58]. In vivo multiunit electrophysiology has long been an approach of choice to monitor longitudinally the circadian variations in action potential firing from the SCN of living animals. This was instrumental to reveal the intrinsic nature of SCN rhythmicity, with higher firing rates during daytime, which persisted in animals housed under constant darkness even after physical disconnection of the SCN from their surrounding tissues [59‒61]. This approach also contributed in highlighting the dampening in SCN rhythmicity in the course of aging [62], or the changes in circadian waveforms in animals exposed to different photoperiods [63]. Later on, the advent of fiber photometry provided further insight into SCN rhythmicity in vivo by enabling the monitoring of bioluminescent or fluorescent reporters of clock gene activity or [Ca2+]i oscillations in the SCN of living animals [64, 65].

However, these techniques are constrained by their dramatic lack of spatial resolution. Even though single-unit signals can be extracted from multiunit recordings [66], the unambiguous access to electrical activity pattern of one given cell over long periods of time remains hardly possible. Even when reporter expression is targeted to specific cell types, fiber photometry only collects signals averaged at a cell population level. Recently, rapid [Ca2+]i events lasting a few seconds and modulated in response to light exposure were reported from the VIP-containing cell population through an optic fiber aimed at the SCN of freely behaving mice [64]. This observation suggests the occurrence of wide-scale synchronized [Ca2+]i activity among light-responsive neurons within the SCN cell network, but this hypothesis has yet to be tested through microscopy at a cellular resolution level.

Microendoscopic devices now provide access to high-resolution imaging of brain cells in freely moving animals [13, 14]. Gradient index (GRIN) lenses are widely used as an optical relay between deep brain regions of interest and the miniscope objective, at the skull surface. However, despite this attractive promise, it is important to consider the potential negative consequences of inserting such glass devices into the brain of a mouse. To test whether this approach could be suitable for studying the SCN, we first checked the levels in circulating corticosterone in mice with a GRIN lens (diameter 0.6 mm, length 7.44 mm) positioned 50–100 µm dorsally to the SCN [21]. Our measurements revealed that overall stress hormone remained low, and followed typical variations along the day, with lower corticosterone concentration in the middle of the resting phase of the mice compared to just before their active phase. These indicators of well-being and the preserved circadian regulation of an important neuroendocrine axis provide reasonable confidence in the experimental setup for investigating SCN cell signaling in vivo.

We thus used the miniscope-GRIN lens setup to monitor the fluorescence emitted by the genetically encoded calcium indicator GCaMP6f in the mouse SCN. GCaMP6f expression was achieved in SCN cells through viral transduction, involving a single surgical procedure for GRIN lens implantation, injection of adeno-associated virus, and fixation of the miniscope baseplate. This approach enabled us to visualize GCaMP6f fluorescence in individual SCN cells longitudinally over several days, providing unprecedented access to changes in [Ca2+]i across various timescales.

The global GCaMP6 signal exhibited important variations along the day-night cycle, peaking during daytime and reaching its lowest point at night. These variations were independent of the light cycle as they persisted under constant darkness, in line with earlier photometric observations of GCaMP fluorescence in the SCN [64, 65]. This global rhythmicity depicted a remarkable consistency in daily [Ca2+]i rhythmicity at the individual cell level. We found that more than 90% of the recorded SCN cells actually presented daily fluctuations in their [Ca2+]i levels, and all of them were in phase with the global aggregate signal, reaching their higher [Ca2+]i in the middle of the light phase. Minor differences in the timing of cell [Ca2+]i peaks among the various mice investigated in our study suggest potential differences between subregions of the SCN. While this hypothesis remains to be tested, it is important to acknowledge that the positioning of the GRIN lens dorsally to the SCN, aimed at preserving their integrity, may inherently limit the diversity of sites studied.

Interestingly, daily cell [Ca2+]i rhythms underwent significant alterations in the SCN of Cry1−/− Cry2−/− double mutant mice, devoid of a functional circadian molecular clock (hereafter referred to as Cry−/− mice). Not only did the proportion of rhythmic cells dramatically diminish (to 59%), but rhythmic cells also no longer appeared in phase, even when Cry−/− mice were housed under a regular 12-h light:12-h dark cycle. Intriguingly, some cells even reached their peak in basal [Ca2+]i during the middle of the dark phase, 180° opposite to the typical rhythm observed in the SCN of control mice. This unexpected finding is particularly striking given that Cry−/− mice typically exhibit rhythmic locomotor behavior under light-dark conditions, along with light-induced increases in electrical activity in their SCN [11, 67, 68]. Hence, the daily rhythm in basal cell [Ca2+]i level underscores the circadian clockwork-dependent cell synchronization within the SCN network of living mice.

In addition to monitoring the slow variations in basal [Ca2+]i, the microendoscopic imaging technique could also resolve fast-peaking [Ca2+]i transients, occurring within the subsecond to second time range. In contrast to the high degree of coordination between SCN cells regarding their basal [Ca2+]i rhythms, this [Ca2+]i spiking activity followed a much broader range of daily patterns in the very same cells. [Ca2+]i spikes showed significant day-night rhythmicity in both frequency and amplitude, in about half of the recorded cells. However, certain cells were more active during either daytime, nighttime, or around light phase transitions, when their basal [Ca2+]i level was high, low, or intermediate, respectively. This unexpected diversity in the daily activity patterns of SCN cells highlights the complex dynamics within the SCN network.

This new finding of two distinct [Ca2+]i dynamics, slow variation in basal [Ca2+]i levels and fast [Ca2+]i transients, coexisting in the same cells but independently modulated throughout the day-night cycle, prompts inquiry into their origins. Empirical evidence suggests that circadian rhythmicity in [Ca2+]i levels primarily arises from Ca2+ entries resulting from changes in membrane excitability, which is also the cause of action potential-driven [Ca2+]i spikes [53, 56, 69]. How then can certain SCN cells exhibit more [Ca2+]i spikes at their lowest basal [Ca2+]i? One potential explanation lies in depolarization-induced electrical silencing observed in a subset of SCN neurons [70], offering insight into this apparent paradox. In addition, the contribution of intracellular Ca2+ stores to either the slow or fast [Ca2+]i dynamics remains plausible in subsets of SCN neurons, which may support their independent regulation [51, 71‒73]. Thus, in vivo cell imaging presents a genuinely novel paradigm for investigating the mechanisms underlying cell [Ca2+]i signaling in the SCN.

The better understanding of these mechanisms will also make it possible to manipulate basal [Ca2+]i levels and [Ca2+]i spikes, to disentangle the respective roles of each [Ca2+]i dynamics. The highly coordinated rhythm in basal [Ca2+]i levels is undoubtedly a distinctive hallmark of the SCN cell network that turns individual circadian cell oscillators into a robust and precise circadian pacemaker. Furthermore, the diversity in daily circadian [Ca2+]i activity patterns may define subsets of cells involved in regulating specific SCN outputs. These multiple patterns, encompassing [Ca2+]i spikes modulated in frequency and amplitude upon a changing baseline, also provide a near infinite number of combinations of [Ca2+]i signals to encode multiple functions in SCN cells [74, 75]. Hence, the dual slow and fast [Ca2+]i dynamics support unity and diversity of SCN cell signaling, and likely represent the two hands of the same clock.

Unexpectedly, a considerable proportion of SCN cells displayed their peak in [Ca2+]i activity preferentially during the night [21]. This is in contrast with extensive observations of a daytime peak in SCN activity, in both nocturnal and diurnal species [26]. However, several studies have documented SCN neurons ticking in an antiparallel manner to their neighbors, including neurons responsible for “siesta” during the regular phase of locomotor activity, i.e., during nighttime in nocturnal mice [76, 77]. Our data suggest that the proportion of such “inverted” neurons may be higher in the dorsal half of the SCN, the area of focus for our recordings. In line with this assumption, an independent in vivo [Ca2+]i imaging study also reported nocturnal [Ca2+]i events in vasopressin-containing neurons, which are primarily located in the dorsal SCN [78]. Alternatively, the high activity levels observed at night with the miniscope may reflect an even more general feature of the SCN in vivo, potentially elucidating the reduced amplitude of daily multiunit electrical firing recorded in vivo as compared to in vitro preparations [60].

Finally, microendoscopic imaging with a high spatial and temporal resolution also grants privileged access to the dynamic features of intercellular coupling in the SCN in vivo. We have observed [Ca2+]i spikes occurring concurrently within a substantial number of cells [21], which resulted in fast fluctuations of the global fluorescence signal, akin to [Ca2+]i events previously observed at the SCN neuron population level with fiber photometry [64]. This consistent coactivity throughout all phases of the light cycle, which remains observable in the SCN of Cry−/− mice [21], likely represents the signature of cells interconnected either directly or via shared inputs. Further characterization of simultaneous [Ca2+]i spiking activity in SCN cells in vivo will improve our understanding of the Ca2+-dependent circuit-level organization of the mammalian circadian pacemaker.

Our study established the first evidence of feasibility in utilizing a miniscope paired with a GRIN lens to monitor [Ca2+]i dynamics at a cellular level in the SCN of freely behaving mice. Remarkably, the GRIN lens implanted dorsally to the SCN has proven effective in preserving the intrinsic circadian rhythmicity in a key endocrine output, while allowing for the visualization of [Ca2+]i signals within single SCN cells, and their organization at the circuit level across the light-dark cycle. Overall, this innovative approach holds significant promise for investigating the circadian pacemaker within a fully integrated context.

In addition to validating in vivo the high coordination of daily unitary rhythms in basal neuronal [Ca2+]i, as previously observed in in vitro preparations, our findings unveiled a surprising diversity in fast [Ca2+]i activity patterns. Do specific activity patterns delineate SCN neuron subpopulations, based on their neuropeptide contents, their location in the SCN, the inputs they receive and/or their outputs? Future experiments are poised to delve deeper into characterizing the distinct neuronal populations contributing to the diversity in activity patterns.

Monitoring GCaMP probes or other fluorescent indicators such as circadian clock reporters or the recently engineered G-protein-coupled receptor activation sensors [79‒82], will offer privileged insights into the physiology of SCN cell and the dynamics of their network organization, across the lifespan. Undoubtedly, harnessing the capability to selectively target specific cell types (e.g., neurons vs. astrocytes), coupled with the advent of dual-color imaging systems, will substantially expand the scope of future investigations. For instance, the technique will facilitate the exploration of how the SCN cell network undergoes remodeling during abrupt light phase shifts simulating jetlag, and under various photoperiods. It will grant unprecedented access to SCN plasticity during health and disease, such as throughout the course of gestation and lactation in female reproduction [83], or during aging [62]. Importantly, the ability to track the same individual longitudinally as its own control will reduce the need for animal involvement in experimental procedures.

Last but certainly not least, in vivo cell imaging paves a new path towards comprehending the SCN in their intricate systemic environment, a realm hitherto inaccessible. Following the recent discovery by Rae Silver and her research team of a venous portal system linking the SCN to the organum vasculosum of the lamina terminalis, the SCN must be recognized as a genuine neuroendocrine structure [84]. As local blood vessels can collect and convey undiluted SCN products towards their targets, this newfound route of communication may soon prove essential for mammalian circadian timekeeping [85, 86]. Consequently, unraveling the regulation of the SCN portal system, in relation with SCN cell rhythmicity, will represent a significant stride forward in our understanding of circadian rhythms. In this perspective, the microendoscopic approach, which enables the measurement of portal blood flow or the intra- and extravasation of fluorescent markers throughout day and night, unequivocally rises to meet the new challenge of SCN physiology.

The author thanks Patrice Mollard for discussion and support, and the IPAM-IGF core facility, member of Biocampus-Montpellier and France BioImaging (ANR-10-INBS-04).

The author has no conflicts of interest to declare.

X.B. is supported by the Centre National pour la Recherche Scientifique (CNRS) and the Fédération pour la Recherche sur le Cerveau (FRC, Neurodon 2021). The original study was supported by grants from Agence Nationale pour la Recherche (ANR-15-CE14-0012 and ANR-18-CE14-0017-01) and the France BioImaging ANR-10-INSB-04 “Investments for the Future.”

X.B. wrote the paper.

1.
Piet
R
.
Circadian and kisspeptin regulation of the preovulatory surge
.
Peptides
.
2023
;
163
:
170981
.
2.
Porteous
R
,
Haden
P
,
Hackwell
ECR
,
Singline
A
,
Herde
MK
,
Desai
R
, et al
.
Reformulation of PULSAR for analysis of pulsatile LH secretion and a revised model of estrogen-negative feedback in mice
.
Endocrinology
.
2021
;
162
(
11
):
bqab165
.
3.
Bur
IM
,
Cohen-Solal
AM
,
Carmignac
D
,
Abecassis
PY
,
Chauvet
N
,
Martin
AO
, et al
.
The circadian clock components CRY1 and CRY2 are necessary to sustain sex dimorphism in mouse liver metabolism
.
J Biol Chem
.
2009
;
284
(
14
):
9066
73
.
4.
Rampersaud
A
,
Connerney
J
,
Waxman
DJ
.
Plasma growth hormone pulses induce male-biased pulsatile chromatin opening and epigenetic regulation in adult mouse liver
.
Elife
.
2023
;
12
.
5.
Kalafatakis
K
,
Russell
GM
,
Ferguson
SG
,
Grabski
M
,
Harmer
CJ
,
Munafò
MR
, et al
.
Glucocorticoid ultradian rhythmicity differentially regulates mood and resting state networks in the human brain: a randomised controlled clinical trial
.
Psychoneuroendocrinology
.
2021
;
124
:
105096
.
6.
Russell
G
,
Kalafatakis
K
,
Durant
C
,
Marchant
N
,
Thakrar
J
,
Thirard
R
, et al
.
Ultradian hydrocortisone replacement alters neuronal processing, emotional ambiguity, affect and fatigue in adrenal insufficiency: the PULSES trial
.
J Intern Med
.
2024
;
295
(
1
):
51
67
.
7.
Ono
D
, et al
.
The suprachiasmatic nucleus at 50: looking back, then looking forward
.
J Biol Rhythms
.
2024
;
39
(
2
):
135
165
.
8.
Bonnefont
X
.
Circadian timekeeping and multiple timescale neuroendocrine rhythms
.
J Neuroendocrinol
.
2010
;
22
(
3
):
209
16
.
9.
Fazli
M
,
Bertram
R
.
Conversion of spikers to bursters in pituitary cell networks: is it better to disperse for maximum exposure or circle the wagons
.
PLoS Comput Biol
.
2024
;
20
(
1
):
e1011811
.
10.
Romano
N
,
Yip
SH
,
Hodson
DJ
,
Guillou
A
,
Parnaudeau
S
,
Kirk
S
, et al
.
Plasticity of hypothalamic dopamine neurons during lactation results in dissociation of electrical activity and release
.
J Neurosci
.
2013
;
33
(
10
):
4424
33
.
11.
Albus
H
,
Bonnefont
X
,
Chaves
I
,
Yasui
A
,
Doczy
J
,
van der Horst
GTJ
, et al
.
Cryptochrome-deficient mice lack circadian electrical activity in the suprachiasmatic nuclei
.
Curr Biol
.
2002
;
12
(
13
):
1130
3
.
12.
Simpson
EH
,
Akam
T
,
Patriarchi
T
,
Blanco-Pozo
M
,
Burgeno
LM
,
Mohebi
A
, et al
.
Lights, fiber, action! A primer on in vivo fiber photometry
.
Neuron
.
2024
;
112
(
5
):
718
39
.
13.
Ghosh
KK
,
Burns
LD
,
Cocker
ED
,
Nimmerjahn
A
,
Ziv
Y
,
Gamal
AE
, et al
.
Miniaturized integration of a fluorescence microscope
.
Nat Methods
.
2011
;
8
(
10
):
871
8
.
14.
Malvaut
S
,
Constantinescu
VS
,
Dehez
H
,
Doric
S
,
Saghatelyan
A
.
Deciphering brain function by miniaturized fluorescence microscopy in freely behaving animals
.
Front Neurosci
.
2020
;
14
:
819
.
15.
Zhou
ZC
,
Gordon-Fennell
A
,
Piantadosi
SC
,
Ji
N
,
Smith
SL
,
Bruchas
MR
, et al
.
Deep-brain optical recording of neural dynamics during behavior
.
Neuron
.
2023
;
111
(
23
):
3716
38
.
16.
Atasoy
D
,
Betley
JN
,
Su
HH
,
Sternson
SM
.
Deconstruction of a neural circuit for hunger
.
Nature
.
2012
;
488
(
7410
):
172
7
.
17.
Coutinho
EA
,
Prescott
M
,
Hessler
S
,
Marshall
CJ
,
Herbison
AE
,
Campbell
RE
.
Activation of a classic hunger circuit slows luteinizing hormone pulsatility
.
Neuroendocrinology
.
2020
;
110
(
7–8
):
671
87
.
18.
Han
SY
,
Morris
PG
,
Kim
JC
,
Guru
S
,
Pardo-Navarro
M
,
Yeo
SH
, et al
.
Mechanism of kisspeptin neuron synchronization for pulsatile hormone secretion in male mice
.
Cell Rep
.
2023
;
42
(
1
):
111914
.
19.
Hoa
O
,
Lafont
C
,
Fontanaud
P
,
Guillou
A
,
Kemkem
Y
,
Kineman
RD
, et al
.
Imaging and manipulating pituitary function in the awake mouse
.
Endocrinology
.
2019
;
160
(
10
):
2271
81
.
20.
Vas
S
,
Wall
E
,
Zhou
Z
,
Kalmar
L
,
Han
SY
,
Herbison
AE
.
Long-term recordings of arcuate nucleus kisspeptin neurons across the mouse estrous cycle
.
Endocrinology
.
2024
;
165
(
3
):
bqae009
.
21.
El Cheikh Hussein
L
,
Fontanaud
P
,
Mollard
P
,
Bonnefont
X
.
Nested calcium dynamics support daily cell unity and diversity in the suprachiasmatic nuclei of free-behaving mice
.
PNAS Nexus
.
2022
;
1
(
3
):
pgac112
.
22.
Edgar
RS
,
Green
EW
,
Zhao
Y
,
van Ooijen
G
,
Olmedo
M
,
Qin
X
, et al
.
Peroxiredoxins are conserved markers of circadian rhythms
.
Nature
.
2012
;
485
(
7399
):
459
64
.
23.
Bloch
G
,
Barnes
BM
,
Gerkema
MP
,
Helm
B
.
Animal activity around the clock with no overt circadian rhythms: patterns, mechanisms and adaptive value
.
Proc Biol Sci
.
2013
;
280
(
1765
):
20130019
.
24.
Woelfle
MA
,
Ouyang
Y
,
Phanvijhitsiri
K
,
Johnson
CH
.
The adaptive value of circadian clocks: an experimental assessment in cyanobacteria
.
Curr Biol
.
2004
;
14
(
16
):
1481
6
.
25.
Yerushalmi
S
,
Green
RM
.
Evidence for the adaptive significance of circadian rhythms
.
Ecol Lett
.
2009
;
12
(
9
):
970
81
.
26.
Hastings
MH
,
Maywood
ES
,
Brancaccio
M
.
Generation of circadian rhythms in the suprachiasmatic nucleus
.
Nat Rev Neurosci
.
2018
;
19
(
8
):
453
69
.
27.
El Cheikh Hussein
L
,
Mollard
P
,
Bonnefont
X
.
Molecular and cellular networks in the suprachiasmatic nuclei
.
Int J Mol Sci
.
2019
;
20
(
8
):
2052
.
28.
Honma
S
,
Nakamura
W
,
Shirakawa
T
,
Honma
K
.
Diversity in the circadian periods of single neurons of the rat suprachiasmatic nucleus depends on nuclear structure and intrinsic period
.
Neurosci Lett
.
2004
;
358
(
3
):
173
6
.
29.
Liu
AC
,
Welsh
DK
,
Ko
CH
,
Tran
HG
,
Zhang
EE
,
Priest
AA
, et al
.
Intercellular coupling confers robustness against mutations in the SCN circadian clock network
.
Cell
.
2007
;
129
(
3
):
605
16
.
30.
Welsh
DK
,
Logothetis
DE
,
Meister
M
,
Reppert
SM
.
Individual neurons dissociated from rat suprachiasmatic nucleus express independently phased circadian firing rhythms
.
Neuron
.
1995
;
14
(
4
):
697
706
.
31.
Cordina-Duverger
E
,
Menegaux
F
,
Popa
A
,
Rabstein
S
,
Harth
V
,
Pesch
B
, et al
.
Night shift work and breast cancer: a pooled analysis of population-based case-control studies with complete work history
.
Eur J Epidemiol
.
2018
;
33
(
4
):
369
79
.
32.
McHill
AW
,
Melanson
EL
,
Higgins
J
,
Connick
E
,
Moehlman
TM
,
Stothard
ER
, et al
.
Impact of circadian misalignment on energy metabolism during simulated nightshift work
.
Proc Natl Acad Sci U S A
.
2014
;
111
(
48
):
17302
7
.
33.
Roenneberg
T
,
Pilz
LK
,
Zerbini
G
,
Winnebeck
EC
.
Chronotype and social jetlag: a (self-) critical review
.
Biology
.
2019
;
8
(
3
):
54
.
34.
Wittmann
M
,
Dinich
J
,
Merrow
M
,
Roenneberg
T
.
Social jetlag: misalignment of biological and social time
.
Chronobiol Int
.
2006
;
23
(
1–2
):
497
509
.
35.
Caliandro
R
,
Streng
AA
,
van Kerkhof
LWM
,
van der Horst
GTJ
,
Chaves
I
.
Social jetlag and related risks for human health: a timely review
.
Nutrients
.
2021
;
13
(
12
):
4543
.
36.
Foster
RG
,
Peirson
SN
,
Wulff
K
,
Winnebeck
E
,
Vetter
C
,
Roenneberg
T
.
Sleep and circadian rhythm disruption in social jetlag and mental illness
.
Prog Mol Biol Transl Sci
.
2013
;
119
:
325
46
.
37.
Levandovski
R
,
Dantas
G
,
Fernandes
LC
,
Caumo
W
,
Torres
I
,
Roenneberg
T
, et al
.
Depression scores associate with chronotype and social jetlag in a rural population
.
Chronobiol Int
.
2011
;
28
(
9
):
771
8
.
38.
Hastings
MH
.
Physiology. A looser clock to cure jet lag
.
Science
.
2013
;
342
(
6154
):
52
3
.
39.
Yamaguchi
Y
,
Suzuki
T
,
Mizoro
Y
,
Kori
H
,
Okada
K
,
Chen
Y
, et al
.
Mice genetically deficient in vasopressin V1a and V1b receptors are resistant to jet lag
.
Science
.
2013
;
342
(
6154
):
85
90
.
40.
Tu
HQ
,
Li
S
,
Xu
YL
,
Zhang
YC
,
Li
PY
,
Liang
LY
, et al
.
Rhythmic cilia changes support SCN neuron coherence in circadian clock
.
Science
.
2023
;
380
(
6648
):
972
9
.
41.
Abrahamson
EE
,
Moore
RY
.
Suprachiasmatic nucleus in the mouse: retinal innervation, intrinsic organization and efferent projections
.
Brain Res
.
2001
;
916
(
1–2
):
172
91
.
42.
Wen
S
,
Ma
D
,
Zhao
M
,
Xie
L
,
Wu
Q
,
Gou
L
, et al
.
Spatiotemporal single-cell analysis of gene expression in the mouse suprachiasmatic nucleus
.
Nat Neurosci
.
2020
;
23
(
3
):
456
67
.
43.
Lee
IT
,
Chang
AS
,
Manandhar
M
,
Shan
Y
,
Fan
J
,
Izumo
M
, et al
.
Neuromedin s-producing neurons act as essential pacemakers in the suprachiasmatic nucleus to couple clock neurons and dictate circadian rhythms
.
Neuron
.
2015
;
85
(
5
):
1086
102
.
44.
Mieda
M
,
Okamoto
H
,
Sakurai
T
.
Manipulating the cellular circadian period of arginine vasopressin neurons alters the behavioral circadian period
.
Curr Biol
.
2016
;
26
(
18
):
2535
42
.
45.
Barca-Mayo
O
,
Pons-Espinal
M
,
Follert
P
,
Armirotti
A
,
Berdondini
L
,
De Pietri Tonelli
D
.
Astrocyte deletion of Bmal1 alters daily locomotor activity and cognitive functions via GABA signalling
.
Nat Commun
.
2017
;
8
:
14336
.
46.
Brancaccio
M
,
Edwards
MD
,
Patton
AP
,
Smyllie
NJ
,
Chesham
JE
,
Maywood
ES
, et al
.
Cell-autonomous clock of astrocytes drives circadian behavior in mammals
.
Science
.
2019
;
363
(
6423
):
187
92
.
47.
Brancaccio
M
,
Patton
AP
,
Chesham
JE
,
Maywood
ES
,
Hastings
MH
.
Astrocytes control circadian timekeeping in the suprachiasmatic nucleus via glutamatergic signaling
.
Neuron
.
2017
;
93
(
6
):
1420
35 e5
.
48.
Tso
CF
,
Simon
T
,
Greenlaw
AC
,
Puri
T
,
Mieda
M
,
Herzog
ED
.
Astrocytes regulate daily rhythms in the suprachiasmatic nucleus and behavior
.
Curr Biol
.
2017
;
27
(
7
):
1055
61
.
49.
Maywood
ES
,
Chesham
JE
,
O'Brien
JA
,
Hastings
MH
.
A diversity of paracrine signals sustains molecular circadian cycling in suprachiasmatic nucleus circuits
.
Proc Natl Acad Sci U S A
.
2011
;
108
(
34
):
14306
11
.
50.
Park
J
,
Zhu
H
,
O'Sullivan
S
,
Ogunnaike
BA
,
Weaver
DR
,
Schwaber
JS
, et al
.
Single-cell transcriptional analysis reveals novel neuronal phenotypes and interaction networks involved in the central circadian clock
.
Front Neurosci
.
2016
;
10
:
481
.
51.
Hong
JH
,
Jeong
B
,
Min
CH
,
Lee
KJ
.
Circadian waves of cytosolic calcium concentration and long-range network connections in rat suprachiasmatic nucleus
.
Eur J Neurosci
.
2012
;
35
(
9
):
1417
25
.
52.
Yamaguchi
S
,
Isejima
H
,
Matsuo
T
,
Okura
R
,
Yagita
K
,
Kobayashi
M
, et al
.
Synchronization of cellular clocks in the suprachiasmatic nucleus
.
Science
.
2003
;
302
(
5649
):
1408
12
.
53.
Enoki
R
,
Kuroda
S
,
Ono
D
,
Hasan
MT
,
Ueda
T
,
Honma
S
, et al
.
Topological specificity and hierarchical network of the circadian calcium rhythm in the suprachiasmatic nucleus
.
Proc Natl Acad Sci U S A
.
2012
;
109
(
52
):
21498
503
.
54.
Enoki
R
,
Oda
Y
,
Mieda
M
,
Ono
D
,
Honma
S
,
Honma
KI
.
Synchronous circadian voltage rhythms with asynchronous calcium rhythms in the suprachiasmatic nucleus
.
Proc Natl Acad Sci U S A
.
2017
;
114
(
12
):
E2476
85
.
55.
Pauls
S
,
Foley
NC
,
Foley
DK
,
LeSauter
J
,
Hastings
MH
,
Maywood
ES
, et al
.
Differential contributions of intra-cellular and inter-cellular mechanisms to the spatial and temporal architecture of the suprachiasmatic nucleus circadian circuitry in wild-type, cryptochrome-null and vasoactive intestinal peptide receptor 2-null mutant mice
.
Eur J Neurosci
.
2014
;
40
(
3
):
2528
40
.
56.
Brancaccio
M
,
Maywood
ES
,
Chesham
JE
,
Loudon
ASI
,
Hastings
MH
.
A Gq-Ca2+ axis controls circuit-level encoding of circadian time in the suprachiasmatic nucleus
.
Neuron
.
2013
;
78
(
4
):
714
28
.
57.
Azzi
A
,
Evans
JA
,
Leise
T
,
Myung
J
,
Takumi
T
,
Davidson
AJ
, et al
.
Network dynamics mediate circadian clock plasticity
.
Neuron
.
2017
;
93
(
2
):
441
50
.
58.
Davidson
AJ
,
Beckner
D
,
Bonnefont
X
.
A journey in the brain's clock: in vivo veritas
.
Biology
.
2023
;
12
(
8
):
1136
.
59.
Inouye
ST
,
Kawamura
H
.
Persistence of circadian rhythmicity in a mammalian hypothalamic “island” containing the suprachiasmatic nucleus
.
Proc Natl Acad Sci U S A
.
1979
;
76
(
11
):
5962
6
.
60.
Meijer
JH
,
Schaap
J
,
Watanabe
K
,
Albus
H
.
Multiunit activity recordings in the suprachiasmatic nuclei: in vivo versus in vitro models
.
Brain Res
.
1997
;
753
(
2
):
322
7
.
61.
Vansteensel
MJ
,
Yamazaki
S
,
Albus
H
,
Deboer
T
,
Block
GD
,
Meijer
JH
.
Dissociation between circadian Per1 and neuronal and behavioral rhythms following a shifted environmental cycle
.
Curr Biol
.
2003
;
13
(
17
):
1538
42
.
62.
Nakamura
TJ
,
Nakamura
W
,
Yamazaki
S
,
Kudo
T
,
Cutler
T
,
Colwell
CS
, et al
.
Age-related decline in circadian output
.
J Neurosci
.
2011
;
31
(
28
):
10201
5
.
63.
Meijer
JH
,
Michel
S
.
Neurophysiological analysis of the suprachiasmatic nucleus: a challenge at multiple levels
.
Methods Enzymol
.
2015
;
552
:
75
102
.
64.
Jones
JR
,
Simon
T
,
Lones
L
,
Herzog
ED
.
SCN VIP neurons are essential for normal light-mediated resetting of the circadian system
.
J Neurosci
.
2018
;
38
(
37
):
7986
95
.
65.
Mei
L
,
Fan
Y
,
Lv
X
,
Welsh
DK
,
Zhan
C
,
Zhang
EE
.
Long-term in vivo recording of circadian rhythms in brains of freely moving mice
.
Proc Natl Acad Sci U S A
.
2018
;
115
(
16
):
4276
81
.
66.
Schaap
J
,
Albus
H
,
VanderLeest
HT
,
Eilers
PHC
,
Détári
L
,
Meijer
JH
.
Heterogeneity of rhythmic suprachiasmatic nucleus neurons: implications for circadian waveform and photoperiodic encoding
.
Proc Natl Acad Sci U S A
.
2003
;
100
(
26
):
15994
9
.
67.
Mrosovsky
N
.
Further characterization of the phenotype of mCry1/mCry2-deficient mice
.
Chronobiol Int
.
2001
;
18
(
4
):
613
25
.
68.
van der Horst
GT
,
Muijtjens
M
,
Kobayashi
K
,
Takano
R
,
Kanno
S
,
Takao
M
, et al
.
Mammalian Cry1 and Cry2 are essential for maintenance of circadian rhythms
.
Nature
.
1999
;
398
(
6728
):
627
30
.
69.
Colwell
CS
.
Circadian modulation of calcium levels in cells in the suprachiasmatic nucleus
.
Eur J Neurosci
.
2000
;
12
(
2
):
571
6
.
70.
Belle
MD
,
Diekman
CO
,
Forger
DB
,
Piggins
HD
.
Daily electrical silencing in the mammalian circadian clock
.
Science
.
2009
;
326
(
5950
):
281
4
.
71.
Enoki
R
,
Ono
D
,
Kuroda
S
,
Honma
S
,
Honma
KI
.
Dual origins of the intracellular circadian calcium rhythm in the suprachiasmatic nucleus
.
Sci Rep
.
2017
;
7
:
41733
.
72.
Ikeda
M
,
Ikeda
M
.
Bmal1 is an essential regulator for circadian cytosolic Ca²+ rhythms in suprachiasmatic nucleus neurons
.
J Neurosci
.
2014
;
34
(
36
):
12029
38
.
73.
Ikeda
M
,
Sugiyama
T
,
Wallace
CS
,
Gompf
HS
,
Yoshioka
T
,
Miyawaki
A
, et al
.
Circadian dynamics of cytosolic and nuclear Ca2+ in single suprachiasmatic nucleus neurons
.
Neuron
.
2003
;
38
(
2
):
253
63
.
74.
Berridge
MJ
.
The AM and FM of calcium signalling
.
Nature
.
1997
;
386
(
6627
):
759
60
.
75.
Carrillo-Reid
L
,
Yuste
R
.
Playing the piano with the cortex: role of neuronal ensembles and pattern completion in perception and behavior
.
Curr Opin Neurobiol
.
2020
;
64
:
89
95
.
76.
Collins
B
,
Pierre-Ferrer
S
,
Muheim
C
,
Lukacsovich
D
,
Cai
Y
,
Spinnler
A
, et al
.
Circadian VIPergic neurons of the suprachiasmatic nuclei sculpt the sleep-wake cycle
.
Neuron
.
2020
;
108
(
3
):
486
99 e5
.
77.
Yoshikawa
T
,
Pauls
S
,
Foley
N
,
Taub
A
,
LeSauter
J
,
Foley
D
, et al
.
Phase gradients and anisotropy of the suprachiasmatic network: discovery of phaseoids
.
eNeuro
.
2021
;
8
(
5
):
ENEURO.0078–21.2021
.
78.
Stowie
A
,
Qiao
Z
,
Buonfiglio
DDC
,
Beckner
DM
,
Ehlen
JC
,
Benveniste
M
, et al
.
Arginine-vasopressin-expressing neurons in the murine suprachiasmatic nucleus exhibit a circadian rhythm in network coherence in vivo
.
Proc Natl Acad Sci U S A
.
2023
;
120
(
4
):
e2209329120
.
79.
Deng
F
,
Wan
J
,
Li
G
,
Dong
H
,
Xia
X
,
Wang
Y
, et al
.
Improved green and red GRAB sensors for monitoring spatiotemporal serotonin release in vivo
.
Nat Methods
.
2024
;
21
(
4
):
692
702
.
80.
Dong
H
,
Li
M
,
Yan
Y
,
Qian
T
,
Lin
Y
,
Ma
X
, et al
.
Genetically encoded sensors for measuring histamine release both in vitro and in vivo
.
Neuron
.
2023
;
111
(
10
):
1564
76 e6
.
81.
Qian
T
,
Wang
H
,
Wang
P
,
Geng
L
,
Mei
L
,
Osakada
T
, et al
.
A genetically encoded sensor measures temporal oxytocin release from different neuronal compartments
.
Nat Biotechnol
.
2023
;
41
(
7
):
944
57
.
82.
Zhuo
Y
,
Luo
B
,
Yi
X
,
Dong
H
,
Miao
X
,
Wan
J
, et al
.
Improved green and red GRAB sensors for monitoring dopaminergic activity in vivo
.
Nat Methods
.
2024
;
21
(
4
):
680
91
.
83.
Abitbol
K
,
Debiesse
S
,
Molino
F
,
Mesirca
P
,
Bidaud
I
,
Minami
Y
, et al
.
Clock-dependent and system-driven oscillators interact in the suprachiasmatic nuclei to pace mammalian circadian rhythms
.
PLoS One
.
2017
;
12
(
10
):
e0187001
.
84.
Yao
Y
,
Taub
AB
,
LeSauter
J
,
Silver
R
.
Identification of the suprachiasmatic nucleus venous portal system in the mammalian brain
.
Nat Commun
.
2021
;
12
(
1
):
5643
.
85.
Silver
R
,
Yao
Y
,
Roy
RK
,
Stern
JE
.
Parallel trajectories in the discovery of the SCN-OVLT and pituitary portal pathways: legacies of Geoffrey Harris
.
J Neuroendocrinol
.
2023
;
35
(
9
):
e13245
.
86.
Yao
Y
,
Green
IK
,
Taub
AB
,
Tazebay
R
,
LeSauter
J
,
Silver
R
.
Vasculature of the suprachiasmatic nucleus: pathways for diffusible output signals
.
J Biol Rhythms
.
2023
;
38
(
6
):
571
85
.