Establishment of Circadian Rhythm Experiments using Bengalese Finches

Abstract

Marked increases in sleep deprivation and circadian rhythm disruption adversely affect human health and the quality of life. In particular, the expansion of nighttime lighting associated with a 24-h society and digital technology has promoted late-night activity in mothers and children. Studies have examined the effects of circadian disruption on brain development in chickens, which are diurnal animals with genomic similarities to humans; however, adult chickens lack post-hatching parental care, which limits their utility in analyses of parent–offspring interactions. In this study, we investigated the potential use of Bengalese finches (Lonchura striata domestica) as model animals for circadian rhythm and physiological research. Given that the small size of Bengalese finches makes it difficult to implant nanotags directly, we developed and fitted specialized garments containing nanotags. After one week under experimental light cycle conditions, rectal temperature and weight were measured, and the activity recorded by the nanotags was analyzed. The nanotag garments did not impede Bengalese finch flight nor did they influence body temperature, weight, or whole-blood glucose levels. Finches housed under a 12-h:12-h light–dark cycle exhibited minimal activity during the dark phase and increased activity after the lights were turned on, reaching peak levels above 40 counts. In contrast, finches housed under constant 24-h light exhibited relatively continuous activity levels of 5–20 counts, with no distinct resting phase. The results demonstrate that locomotor activity rhythms in Bengalese finches are strongly regulated by environmental lighting conditions, and that nanotag placement using specialized garments enables non-invasive physiological and behavioral monitoring. Overall, our findings support the use of Bengalese finches as a practical and effective model for circadian rhythm research to facilitate studies on physiological regulation, development, and future investigations into parent–offspring interactions.

Introduction

Exposure to artificial light at night has increased dramatically, leading to the widespread disruption of circadian rhythms. Individuals engaged in occupations involving shift work or transmeridian travel (e.g., international flight attendants and pilots) are particularly affected by chronic circadian misalignment and sleep deprivation; however, circadian disruption is no longer confined to such specialized professions and has become prevalent across the general population. Epidemiological and experimental studies have demonstrated that artificial light-induced circadian disruption is associated with sleep disorders, cognitive impairment, and an increased risk of neurodegenerative diseases, including dementia[1,2].

Circadian disruption may be especially detrimental during early development, a period characterized by heightened sensitivity to environmental stimuli. Children in early developmental stages are highly vulnerable to environmental perturbations, and the disruption of circadian rhythms during this period leads to insufficient sleep in children and increases sleep deprivation in caregivers, constituting a major social concern. Adequate intake of fish or n-3 polyunsaturated fatty acids (n-3 PUFAs) during pregnancy can reduce the risk of sleep insufficiency in 1-year-old children[3]. In addition, positive associations between the dietary intake of n-3 PUFAs and sleep–wake activity have been reported in juvenile and adult mice, suggesting a potential link between lipid nutrition and the regulation of sleep and circadian behavior[4]. Such findings suggest that maternal factors and parent–offspring interactions play important roles in the establishment of circadian rhythms and sleep regulation during early development.

Rodents, particularly mice, have been widely used to investigate the molecular and neural mechanisms underlying circadian rhythms and sleep–wake regulation[5,6]. However, as nocturnal animals, mice present inherent limitations when modeling circadian regulation in diurnal species such as humans. Therefore, diurnal animal models represent an important complementary approach. Studies in chickens, a diurnal avian species, have shown that circadian disruption can adversely affect brain development during early life[7]. However, chickens pose limitations for studies of parent–offspring interactions, as they generally do not engage in prolonged direct care of chicks. Moreover, their large body size, housing requirements, and maintenance costs limit their suitability for long-term, high-resolution behavioral analyses.

The Bengalese finch (Lonchura striata domestica) is a small domesticated songbird that has been extensively studied in the context of vocal communication and learning[8,9]. It is diurnal and exhibits robust parental care behavior[10]. Both parents construct nests and actively rear their offspring, with the mother providing direct oral feeding in the nest for approximately 4 weeks until fledging[10]. This prolonged, intimate parent–offspring interaction makes the Bengalese finch an attractive potential model for investigating the interplay between circadian rhythms, sleep–wake regulation, and the social environment during development. Furthermore, their small size, ease of husbandry, and tolerance to experimental manipulation have facilitated reproducible and cost-effective longitudinal studies.

In this study, we aimed to establish a non-invasive locomotor activity monitoring system using lightweight nanotags for the Bengalese finch, enabling the continuous assessment of activity rhythms under naturalistic housing conditions. This system serves as a foundation for evaluating diurnal avian models in circadian biology research. This integrative approach provides a methodological framework for animal experiments using Bengalese finches and is expected to advance circadian rhythm research by linking behavioral rhythms with metabolic states under defined environmental conditions.

Materials and Methods

Animals

Bengalese finches (1 year old) were purchased from Bird Load Naniwa, Osaka, Japan. All experiments were conducted exclusively with male birds to minimize the variability attributable to sex differences. They were housed in group stainless-steel cages (MB-90, W475×H565×D475 mm, Marukan Co., Ltd., Osaka, Japan) with ad libitum access to tap water and food pellets (Natural Pet Foods Co., Ltd., Ibaraki, Japan). The environment was maintained at 22 ± 4 °C and approximately 60% relative humidity under a 12-h:12-h light–dark (LD) cycle, with lights on at 07:00 and off at 19:00.

Lighting condition

An overview of the experimental design is presented in Fig. 1A. To evaluate the effects of environmental light conditions on locomotor activity and physiological parameters, Bengalese finches were randomly assigned, 1 month after purchase, to one of two lighting conditions (n = 5 birds per group): a standard LD cycle group or a constant light (LL) group. In the LD group, birds were maintained under a 12 h:12 h LD cycle, with lights on at 07:00 and lights off at 19:00. Illuminance at the cage level was measured at multiple positions around the cages using a lux meter. The mean illuminance during the light phase in the LD group was 920 lx (range: 813–1012 lux), whereas that during the dark phase was maintained at <1 lx. Birds in the LL group were continuously exposed to illumination throughout the experimental period with a mean illuminance of 977 lx (range: 902–1057 lux). The Zeitgeber time (ZT) was defined as ZT0 corresponding to lights on (07:00) and ZT12 to lights off (19:00). The LL group was initially raised under LD conditions; therefore, ZT0–ZT12 and ZT12–ZT24 were defined as the relative light and dark phases, respectively. The birds were maintained under these conditions for 7 days. The day on which the lighting conditions were changed was designated as Day 0.

Fig. 1.

Wearable nanotag system for locomotor activity monitoring in Bengalese finches. (A) Experimental design for the lighting test using the nanotag system. Rectal temperature measurement, RT; body weight measurement, BW; wearing nanotag, NT; 12 h-12 h light–dark cycle, LD; constant light conditions, LL. (B) Representative photograph of a Bengalese finch wearing a custom-designed lightweight garment with an integrated nanotag. The garment measured approximately 3.4 cm in width, 4.5 cm in length, and 1.1 cm in neck circumference, and was tailored to fit adult Bengalese finches. The garment was securely fitted without restricting wing movement or flight and allowed stable attachment of the nanotag for non-invasive, long-term locomotor activity monitoring. (C) Frontal and lateral photograph of an adult Bengalese finch wearing the garment.

Locomotor activity measurement using the Nano-Tag system

Nanotags (W140×H170×D70 mm, Kissei Comtec Co., Ltd., Nagano, Japan) were used to measure bird activity. The nanotags were placed on clothing designed to be worn by Bengalese finches (Fig. 1B, C); the nanotag-equipped garment weighed 3.3 g (Nano-Tag weight is 2.8 g + the cloth weight is 0.5 g). Birds were fitted with garments at 09:15 h on Day 0. The garments were custom-made by the Transgenic Group, Inc. (Fukuoka, Japan).

The recorded locomotor activity data were transferred to the nanotag/Viewer program (Kissei Comtec Co., Ltd.) using a FeliCa reader (RC-S360; Sony Corp., Tokyo, Japan) held within 1 cm of the tag. The locomotor activity was quantified as cross-count values obtained using a nanotag. Locomotor activity was quantified for each recording interval by counting the instances in which the composite signal derived from a predefined threshold[11] set to 100. Activity data were processed using the nanotag/Viewer software (Kissei Comtec Co., Ltd.), and the resulting activity counts were aggregated into 1-h bins. Activity levels were measured over six days, from Day 1 to Day 6. After rectal temperature (RT) and body weight (BW) were measured on Day 7, the nanotag-equipped garment was removed.

Rectal temperature and body weight measurements

RT was measured using a temperature sensor (AD-1687, A&D Co., Ltd., Tokyo, Japan), and BW was measured using a mass scale (CJ-620, Shinko Denshi Co., Ltd., Tokyo, Japan) at 9:00 on Day 0 and Day 7. Measurements were taken on Day 0 before the birds were fitted with the nanotag-equipped garment, and on Day 7 while the birds were wearing the garment. This timing minimized the impact of attaching and removing the device. The BW values on Day 7 were calculated by subtracting the combined weight of the garment and nanotag.

Data analysis

The data are presented as the mean ± the standard error of the mean (SEM). Statistical analyses were conducted using the Stat View software (version 5, SAS Institute, Cary, NC, USA). Locomotor activity data were analyzed using a repeated-measures two-way ANOVA, with lighting conditions and ZTs as fixed factors and individual birds treated as repeated measures. Post hoc comparisons were performed using Tukey’s multiple comparison test. Results were considered significant if the probability of error was less than 5% (P < 0.05).

To visualize locomotor activity rhythms at the individual level, double-plotted actograms were generated for each bird using 1-h binned activity data. The first 24 h of activity was plotted on the left side of each row and the subsequent 24 h was plotted on the right side, allowing visual assessment of day-to-day changes in activity patterns. Actograms were generated using Python (version 3.13) with the pandas and matplotlib libraries.

To quantitatively evaluate circadian periodicity, Lomb–Scargle periodogram analysis was performed using 1-h binned locomotor activity data collected over six consecutive days. The dominant period (τ) and spectral power were calculated for each individual bird to assess the strength and stability of circadian rhythmicity under LD and LL conditions. Lomb–Scargle analyses were conducted using Python (version 3.13) with the scipy and astropy libraries.

Additionally, to quantitatively evaluate circadian rhythmicity, cosinor analyses were performed using 1-h binned locomotor activity data collected over six consecutive days. A 24-h cosine function was fitted to the activity data of each bird to estimate the rhythm amplitude and acrophase. Cosinor analyses were conducted using Python (version 3.13) with the SciPy, pandas, and matplotlib libraries.

To assess the potential acclimation effects following nanotag attachment, the total locomotor activity during the early recording phase (days 1 and 2) and late recording phase (days 5 and 6) was compared for each bird using the Wilcoxon signed-rank test.

Results

Differences in activity between LL and LD cycles

The locomotor activity, as recorded by the nanotags, for each bird in the LD group was plotted for each of the six recording days (Fig. 2A–F). Fig. 3 shows the total activity levels for each 12-h period, defined as ZT0–ZT12 (07:00–19:00) and ZT12–ZT24 (19:00–07:00). Statistical analyses revealed a significant ZT × group interaction (Day1: F[1,8] = 26.93, P < 0.01, Fig. 3A; Day2: F[1,8] = 31.29, P < 0.01, Fig. 3B; Day3: F[1,8] = 24.50, P < 0.01, Fig. 3C; Day4: F[1,8] = 48.79, P < 0.01, Fig. 3D; Day5: F[1,8] = 37.44, P < 0.01, Fig. 3E; and Day6: F[1,8] = 35.75, P < 0.01, Fig. 3F). Post-hoc analysis showed that the activity levels during ZT0–ZT12 were significantly higher in the LD group than in the LL group on all 6 days (Fig. 3A–F). Furthermore, the activity levels during ZT12–ZT24 in the LD group were near zero and were significantly lower than those in the LL group each day (Fig. 2A–F). During the recording period, locomotor activity in the LD group showed a progressive increase during the light phase, reaching peak values exceeding 40 counts (Fig. 2A–F). In contrast, birds under LL conditions exhibited relatively constant activity levels during both ZT0–ZT12 and ZT12–ZT24, averaging approximately 10 counts with no evident phase-dependent modulation (Fig. 2A–F, Fig. 3A–F).

Fig. 2.

Raw locomotor activity data of Bengalese finches. Representative raw locomotor activity traces obtained using wearable nanotags are shown. These data correspond to the summarized locomotor activity rhythms presented in Fig. 3, and represent the original activity recordings used for the rhythm analysis. Samples 1–5 correspond to Bengalese finches maintained under a 12 h:12 h LD cycle, and samples 6–10 correspond to birds maintained under LL conditions. Zeitgeber time (ZT) was defined as ZT0 = 07:00 (lights on) and ZT12 = 19:00 (lights off). In the LL group, ZT0–ZT12 (white) and ZT12–ZT24 (shaded) were defined as the relative light and dark phases, respectively. (A–F) Locomotor activity profiles on Days 1–6. Data are presented as mean ± SEMs. A sample of 10 Bengalese finches was used; n = 5 per group.

Fig. 3.

Locomotor activity rhythms of Bengalese finches. Representative time-series plots of locomotor activity measured using the wearable nanotag system. Activity counts are shown across 6 consecutive days under a 12 h:12 h (LD cycle or LL). ZT was defined as ZT0 or ZT24= 07:00 (light on time) and ZT12 = 19:00 (light off time). The LL group had initially been raised under LD periods; therefore, ZT0–ZT12 and ZT12–ZT24 were defined as the relative light and dark phases, respectively. Samples 1–5 denote Bengalese finches in the LD group, and samples 6–10 denote finches in the LL group. (A–F) Locomotor activity profiles on Days 1–6. Data are presented as mean ± SEMs. **P < 0.01. A sample of 10 Bengalese finches was used; n = 5 per group.

To evaluate potential acclimation to the wearable nanotag garment following attachment, the total locomotor activity during the early recording phase (days 1–2) was compared with that during the late recording phase (days 5–6) for each bird (Supplementary Fig. S1). Total locomotor activity was significantly higher during days 5 and 6 than during days 1 and 2 (Wilcoxon signed-rank test, P < 0.01), suggesting gradual acclimation to the wearable device after attachment.

To further assess circadian rhythmicity, we generated double-plotted actograms for each bird using 1-h binned locomotor activity data (Fig. 4). In the LD group, all five birds showed a clear day–night organization of locomotor activity, with activity concentrated during the light phase and minimal activity during the dark phase. In contrast, birds in the LL group showed a flatter distribution of activity across the 24-h cycle, with less distinct separation between the subjective light and subjective dark phases.

Fig. 4.

Individual actograms of the locomotor activity of Bengalese finches under the LD and LL conditions. Activity was monitored continuously using the wearable nanotag system from July 12 (Day 1) to July 17 (Day 6). Hourly activity was calculated as the mean number of vibration counts recorded in 30-s intervals and visualized as actograms. Each row represents one experimental Bengalese finch (Nos. 1–10). Bengalese finches 1–5 were maintained under a 12-h light:12-h dark cycle (LD), whereas Bengalese finches 6–10 were maintained under the LL condition. Dark shading indicates the dark phase in the LD condition. Color intensity represents locomotor activity levels, with warmer colors indicating higher activity. Under the LD condition, Bengalese finches exhibited robust diurnal rhythmicity, with higher daytime activity and reduced nighttime activity. In contrast, Bengalese finches maintained under the LL condition showed dispersed activity patterns and weakened rhythmic organization.

The Lomb–Scargle periodogram analysis further supported the presence of robust daily rhythmicity in the LD group (Fig. 5). The dominant periods in the LD group were tightly clustered around 24 h, ranging from 23.4 to 23.7 h, with relatively high spectral power. In contrast, the LL group showed weaker and more variable periodicity, with dominant periods of 19.0–24.8 h and lower spectral power. These results suggest that LL attenuates and destabilizes daily locomotor rhythmicity, rather than simply shifting the rhythm uniformly. These analyses provide a quantitative evaluation of circadian rhythmicity under both LD and LL conditions.

Fig. 5.

Lomb–Scargle periodogram analysis of locomotor activity rhythms in Bengalese finches under the LD and LL conditions. Periodograms were generated using 1-h binned locomotor activity data collected over 6 consecutive days. Peaks indicate dominant periodic components (τ). Bengalese finches maintained under the LD condition exhibited strong rhythmic peaks near 24 h, whereas those maintained under the LL condition showed weaker and more variable rhythmicity.

Effects of the nanotag garment on physiological parameters

During the week, the birds wore a nanotag garment, which did not appear to affect movement or flight (Supplementary Video 1). There were no significant changes in BW (day × group interaction, F[1,8] = 0.89, P > 0.05, Table 1) or RT (day × group interaction, F[1,8] = 0.12, P > 0.05, Table 2) throughout the 1-week experimental period following nanotag placement.

Table 2.  Changes in rectal temperature of Bengalese finches under different lighting conditions

Lighting condition	Bird No.	Day 0 (°C)	Day 7 (°C)
LD (standard light–dark)	1	40.3	40.2
	2	40.1	40.3
	3	40.0	39.7
	4	40.4	41.0
	5	39.9	40.1
	Average	40.1 ± 0.1	40.3 ± 0.2
LL (constant light)	6	40.2	39.4
	7	40.2	38.8
	8	40.4	40.3
	9	40.1	39.2
	10	40.0	40.5
	Average	40.2 ± 0.1	39.6 ± 0.3

Rectal temperature was measured on Day 0 and Day 7 at 09:00 using a digital temperature sensor. Data are shown for individual birds, with group means ± SEM.

Discussion

Changes in lifestyle associated with industrial development have been increasingly recognized as major contributors to circadian disruption and related adverse effects on human health. These effects are particularly pronounced during early life because infant sleep is highly sensitive to disturbances in circadian regulation. Unlike adults, who can exert some control over their daily routines, fetuses and infants are largely passive recipients of environmental influences and are especially vulnerable to circadian disruption[12]. Neural development is thought to be closely linked to sleep–wake rhythms during early postnatal life, particularly in the first year after birth[13]. However, the molecular and neural mechanisms underlying this association remain unknown.

To advance our understanding of circadian and sleep regulation during development, we established the Bengalese finch as an experimental model. As an initial step, we developed a species-specific wearable garment incorporating a nanotag to enable the measurement of locomotor activity in this small avian species. To assess whether long-term wear interfered with daily behavior or imposed physiological stress, the finches wore the nanotag garment for 1 week and were monitored using continuous video recording. Video analyses confirmed that the birds exhibited normal behaviors, including free flight, feeding, and drinking, throughout the observation period (Supplementary Video 1).

Building on this validation, we successfully quantified the locomotor activity in finches using a wearable nanotag-based monitoring system. Because commercially available nanotags are too large for implantation in Bengalese finches, this non-invasive, garment-based solution provides a practical alternative that can be easily applied without surgical intervention, making the approach broadly accessible. The garment did not interfere with free flight, feeding, or water intake, nor did it affect the BW or resting time, indicating that the birds were able to maintain normal locomotor behavior while wearing the device. However, the total locomotor activity during the final recording phase (days 5–6) was significantly higher than that during the initial phase (days 1–2) (Wilcoxon signed-rank test, P < 0.01; Supplementary Fig. S1), suggesting that the birds gradually acclimated to the wearable device after attachment. Notably, although the nanotagged garment (3.3 g) represented approximately 20% of the body mass of the Bengalese finches (15–16 g), substantially exceeding the commonly cited 5% guideline for attached devices[14], no overt adverse effects were observed within the scope of this study. Nevertheless, subtle physiological or behavioral stress responses that were not detectable by locomotor observation alone may still have occurred. Therefore, further investigations incorporating physiological stress indicators such as fecal corticosterone levels are needed to evaluate the impact of the load more comprehensively. Using this wearable system, we examined locomotor activity under LD and LL conditions. Double-plotted actograms and Lomb–Scargle periodogram analyses further demonstrated that the wearable nanotag system enabled both qualitative and quantitative evaluation of circadian locomotor rhythmicity in Bengalese finches. Under LD conditions, Bengalese finches exhibited robust daily rhythmicity, with activity concentrated during the light phase and a dominant periodicity near 24 h. In contrast, LL conditions resulted in weaker and less stable rhythmicity, suggesting that LL attenuated and destabilized the circadian organization rather than simply shifting activity timing uniformly. Additional cosinor analyses supported the utility of the wearable nanotag system for quantitative evaluation of circadian locomotor rhythmicity in Bengalese finches (Supplementary Fig. S2). Bengalese finches maintained under LD conditions exhibited relatively high-amplitude circadian oscillations with stable acrophases near the light phase, whereas LL conditions markedly reduced oscillatory amplitude and rhythm stability. These findings were consistent with both the actogram and Lomb–Scargle analyses and further suggested that LL disrupts circadian locomotor organization rather than simply inducing a uniform phase shift. By integrating a small diurnal avian species with a lightweight, wearable activity monitor, this study overcame several key limitations associated with models that use nocturnal rodents or larger avian species. This system enables the detailed, long-term monitoring of circadian behavior in freely moving animals under natural conditions, providing a practical and biologically relevant platform for circadian research.

Given the robust and sustained parental care behaviors of Bengalese finches[10], the wearable nanotag system may provide a useful platform for future studies investigating how parental circadian disruption influences offspring development through behavioral and physiological pathways. However, the present study was conducted exclusively on adult male Bengalese finches; therefore, the applicability of wearable devices to female birds and active breeding pairs remains unclear. Further studies are necessary to determine whether wearable garments can be used without affecting complex parental behaviors, such as incubation, chick feeding, or other reproductive behaviors. Future studies incorporating female individuals and breeding pairs are important to evaluate the potential sex-dependent effects and validate the broader applicability of this system.

This methodological framework is expected to advance circadian rhythm research in avian systems and provide a complementary experimental model for understanding how environmental and social factors interact to shape biological timing across developmental stages and species.

Ethical Approval

Animal experiments were conducted at Medicinal Chemistry Pharmaceutical Co., Ltd. (Kobe, Japan) after obtaining approval (approval number: 2024A01) from the Institutional Animal Care and Use Committee of Medicinal Chemistry Pharmaceutical Co., Ltd. We analyzed the data from Kyushu University.

Funding

This study was supported by the TransGenic Group Inc., Fukuoka, Japan (Grant No. 24006).

Acknowledgements

We thank Wataru Toriumi at the Fukuoka Center for Disease Control and Prevention for technical support with actogram generation and Lomb–Scargle periodogram analysis. This paper was proofread by Textcheck.

Author Contributions

Haruka Nishimura: Writing – original draft; writing – review and editing; Conceptualization, Investigation, Software, Data curation, Methodology, Supervision, Formal Analysis, Project administration, Validation, Resources and Visualization. Shunichi Kitajima: Writing – review and editing, Investigation, Software, Data curation, Methodology, Supervision, Formal analysis, Project administration, Validation, Resources and Visualization. Eiki Takahashi: Writing–review and editing, Conceptualization, Investigation, Software, Data curation, Methodology, Supervision, Formal Analysis, Project administration, Validation, Resources and Visualization.

Conflict of Interest

The authors declare that this study was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest.

Supplementary Materials

The online version contains supplementary material available at

https://doi.org/10.2141/jpsa.2026017

References

• [1]  Voigt RM, Ouyang B andKeshavarzian A. Outdoor nighttime light exposure (light pollution) is associated with Alzheimer’s disease. medRxiv, 15: 24302831. 2024. https://doi.org/10.1101/2024.02.14.24302831
• [2]  Duncan MJ, Hawkins MR, Bytyqi L, Whitlock HR, Shepard S, Cox MF, Drinkard EG, Macheda T, Roberts KN, Kohler K, Schmidt M, Johnson CE, Sunderam S, O’Hara BF, Murphy MP andBachstetter AD. Dim light at night impacts circadian rhythms and Alzheimer’s disease-like neuroinflammation and neuropathology in humanized APP SAA knock-in mice. bioRxiv, 3: 680043. 2025. https://doi.org/10.1101/2025.10.02.680043
• [3]  Sugimori N, Hamazaki K, Matsumura K, Kasamatsu H, Tsuchida A, Inadera H, Kamijima M, Yamazaki S, Ohya Y, Kishi R, Yaegashi N, Hashimoto K, Mori C, Ito S, Yamagata Z, Inadera H, Nakayama T, Iso H, Shima M, Kurozawa Y, Suganuma N, Kusuhara K andKatoh T; Japan Environment Children’s Study Group. Association between mothers’ fish intake during pregnancy and infants’ sleep duration: a nationwide longitudinal study—The Japan Environment and Children’s Study (JECS). Eur J Nutr, 61: 679–686. 2022. PMID:34505173, https://doi.org/10.1007/s00394-021-02671-4
• [4]  Decoeur F, Benmamar-Badel A, Leyrolle Q, Persillet M, Layé S andNadjar A. Dietary N-3 PUFA deficiency affects sleep-wake activity in basal condition and in response to an inflammatory challenge in mice. Brain Behav Immun, 85: 162–169. 2020. PMID:31100369, https://doi.org/10.1016/j.bbi.2019.05.016
• [5]  Korf HW andvon Gall C. Mouse models in circadian rhythm and melatonin research. J Pineal Res, 76: e12986. 2024. PMID:38965880, https://doi.org/10.1111/jpi.12986
• [6]  Hor CN, Yeung J, Jan M, Emmenegger Y, Hubbard J, Xenarios I, Naef F andFranken P. Sleep–wake-driven and circadian contributions to daily rhythms in gene expression and chromatin accessibility in the murine cortex. Proc Natl Acad Sci USA, 116: 25773–25783. 2019. PMID:31776259, https://doi.org/10.1073/pnas.1910590116
• [7]  Haraguchi S, Kamata M, Tokita T, Tashiro K, Sato M, Nozaki M, Okamoto-Katsuyama M, Shimizu I, Han G, Chowdhury VS, Lei XF, Miyazaki T, Kim-Kaneyama J, Nakamachi T, Matsuda K, Ohtaki H, Tokumoto T, Tachibana T, Miyazaki A andTsutsui K. Light-at-night exposure affects brain development through pineal allopregnanolone-dependent mechanisms. eLife, 8: e45306. 2019. PMID:31566568, https://doi.org/10.7554/eLife.45306
• [8]  Nicholson DA, Roberts TF andSober SJ. Thalamostriatal and cerebellothalamic pathways in a songbird, the Bengalese finch. J Comp Neurol, 526: 1550–1570. 2018. PMID:29520771, https://doi.org/10.1002/cne.24428
• [9]  Hampton CM, Sakata JT andBrainard MS. An avian basal ganglia-forebrain circuit contributes differentially to syllable versus sequence variability of adult Bengalese finch song. J Neurophysiol, 101: 3235–3245. 2009. PMID:19357331, https://doi.org/10.1152/jn.91089.2008
• [10]  Walther Seiler H, Gahr M, Goldsmith AR andGüttinger HR. Prolactin and gonadal steroids during the reproductive cycle of the Bengalese finch (Lonchura striata var. domestica, Estrildidae), a nonseasonal breeder with biparental care. Gen Comp Endocrinol, 88: 83–90. 1992. PMID:1426966, https://doi.org/10.1016/0016-6480(92)90196-Q
• [11]  Yoshizawa T, Shimada S, Takizawa Y, Makino T, Kanada Y, Ito Y, Ochiai T andMatsumoto K. Continuous measurement of locomotor activity during convalescence and acclimation in group-housed rats. Exp Anim, 68: 277–283. 2019. PMID:30760650, https://doi.org/10.1538/expanim.18-0097
• [12]  Wong SD, Wright KP, Jr, Spencer RL, Vetter C, Hicks LM, Jenni OG andLeBourgeois MK. Development of the circadian system in early life: maternal and environmental factors. J Physiol Anthropol, 41: 22. 2022. PMID:35578354, https://doi.org/10.1186/s40101-022-00294-0
• [13]  Hoshino K. Problems in the development of the sleep–wake rhythm influence neurodevelopmental disorders in children. Diagnostics (Basel), 13: 1859. 2023. PMID:37296711, https://doi.org/10.3390/diagnostics13111859
• [14]  Barron DG, Brawn JD andWeatherhead PJ. Meta‐analysis of transmitter effects on avian behaviour and ecology. Methods Ecol Evol, 1: 180–187. 2010. https://doi.org/10.1111/j.2041-210X.2010.00013.x