Adolescence is a critical developmental period involving dramatic changes in behaviour and brain anatomy. The prefrontal cortex, the brain region responsible for our most complex cognitive functions, is still establishing connections during this time (Gogtay et al., 2004; Petanjek et al., 2011; Sowell et al., 2004). The trajectory of prefrontal cortex development in adolescence determines the vulnerability or resilience of individuals to adolescent-onset psychiatric diseases (Fuhrmann et al., 2015; Keshavan et al., 2014; Kessler et al., 2007; Kessler et al., 2005; Lee et al., 2014). The age at which this adolescent development occurs therefore represents a critical window during which the brain is particularly susceptible to environmental influences. Traditionally, the onset of adolescence is thought to coincide with puberty (Hollenstein and Lougheed, 2013). In humans, the age of pubertal onset has been advancing throughout the 19th, 20th, and 21st centuries, and environmental influences, such as nutrition, can pathologically alter the age of puberty (Wolf and Long, 2016). However, it remains entirely unknown whether the neural and cognitive maturational processes of adolescence can also be plastic. Here, we examine how the timing of certain adolescent developmental processes are programmed, and whether this timing can be plastic in response to a natural environmental cue, in parallel with pubertal plasticity.

Dopamine innervation to the prefrontal cortex increases substantially across adolescence, and psychopathologies of adolescent origin prominently feature dopamine dysfunction. Evidence continues to emerge that protracted dopamine innervation is a key neural process underlying the cognitive and behavioural changes that characterise adolescence (Larsen and Luna, 2018). The mesocorticolimbic dopamine system – which includes the prefrontal cortex – is unique because not only are connections being formed and lost during adolescence, but there is also long-distance displacement of dopamine axons between brain regions. At the onset of adolescence, both mesolimbic and mesocortical dopamine axons innervate the nucleus accumbens in rodents, but the mesocortical axons leave the accumbens and grow toward the prefrontal cortex during adolescence and early adulthood (Hoops et al., 2018; Reynolds et al., 2018; Reynolds et al., 2023). This is the only known case of axons growing from one brain region to another so late during development (Reynolds and Flores, 2021).

The prolonged growth trajectory renders mesocortical dopamine axons particularly vulnerable to disruption. Environmental insults during adolescence (e.g. drug abuse) alter the extent and organisation of dopamine innervation in the prefrontal cortex, leading to behavioural and cognitive changes in mice throughout adulthood (Drzewiecki and Juraska, 2020; Hoops and Flores, 2017; Reynolds and Flores, 2021). These changes often involve cognitive control, a prefrontal function that develops in parallel with dopamine innervation to the cortex in adolescence (Luna et al., 2015). Disruption of dopamine innervation frequently seems to result in ‘immature’ cognitive control persisting through adulthood (Reynolds and Flores, 2021).

Here, we examine the guidance of growing dopamine axons to the prefrontal cortex, and its timing. The guidance cue molecule Netrin-1, upon interacting with its receptor DCC, determines which dopamine axons establish connections in the nucleus accumbens and which ones leave this region to grow to the prefrontal cortex (Hoops and Flores, 2017; Reynolds and Flores, 2021; Reynolds et al., 2023). We hypothesised that the answers to how and when this extraordinary developmental feat is achieved may also lie in the Netrin-1 signalling system.

Part 1: Netrin-1 ‘paves the way’ for dopamine axons in adolescence

To identify the route by which dopamine axons grow from the nucleus accumbens to the medial prefrontal cortex, we visualised dopamine axons in the adult mouse forebrain. We observed that dopamine axons medial to the nucleus accumbens occupy a distinct area and are oriented dorsally toward the cortex (Figure 1A and B). Individual fibres can be seen crossing the boundary of the nucleus accumbens shell and joining these dorsally oriented axons (Figure 1C). We hypothesised that these are the fibres that grow to the prefrontal cortex during adolescence. If this is correct, the number of dopamine axons oriented dorsally toward the medial prefrontal cortex should continue to increase until adulthood. To test this, we used a modified unbiased stereological approach (Kim et al., 2011) where axons are counted only if they crossed the upper and lower bounds of a counting probe. We also measured the average width of the area these axons occupy. We found, in both male and female mice, that the density of dopamine axons does not change between adolescence (21 days of age) and adulthood (75 days of age; Figure 1D). However, the width of the area that dopamine axons occupy does change, increasing between adolescence and adulthood (Figure 1E). These results indicate that the total number of dopamine axons passing through this area increases over adolescence and that dopamine axons grow to the medial prefrontal cortex via this route.

Figure 1

Download asset Open asset

Next, we focussed on Netrin-1, a secreted protein that acts as a guidance cue to growing axons and is important for dopamine axon targeting in the nucleus accumbens in adolescence (Cuesta et al., 2020). Using unbiased stereology, we quantified the number of Netrin-1-expressing cell bodies along the dopamine axon route, and in an adjacent medial region as a control (Figure 1F and G). We found that in adolescence there are more Netrin-1-positive neurons within the dopamine axon route than adjacent to it. Furthermore, along the axon route the density of Netrin-1-positive cells increases toward the medial prefrontal cortex, forming a dorsoventral gradient (Figure 1H). In adulthood, there remains a higher density of Netrin-1-positive cells along the dopamine route compared to the adjacent region, however the dorsoventral gradient is no longer present (Figure 1I).

To determine if Netrin-1 along the dopamine axon route is necessary for axon navigation, we silenced Netrin-1 expression in the dorsal peduncular cortex, the transition region between the septum and the medial prefrontal cortex, at the onset of adolescence (Figure 1J and K). In adulthood, we quantified the number of dopamine axon terminals in the regions below and above the injection site. Silencing Netrin-1 did not alter dopamine terminal density below the injection, in the lateral septum (Figure 1L). In the infralimbic cortex, which is the first prefrontal cortical region the axons reach after the injection site, terminal density was reduced in the Netrin-1 knockdown group compared to controls (Figure 1L). The knockdown appears to erase the Netrin-1 path to the prefrontal cortex, resulting in dopamine axons failing to reach their correct innervation target.

It remains unknown exactly what types of cells are expressing Netrin-1 along the dopamine axon route, and how this expression is regulated to produce the Netrin-1 gradients that guide the dopamine axons. It also remains unclear where the misrouted axons end up in adulthood. Future experiments aimed at addressing these questions will provide further valuable insight into the nature of the ‘Netrin-1 pathway’. Nonetheless, our results allow us to conclude that Netrin-1 expressing cells ‘pave the way’ for dopamine axons growing to the medial prefrontal cortex.

We next examined how the Netrin-1 pathway may be important for behaviour. Dopamine input to the prefrontal cortex is a key factor in the transition from juvenile to adult behaviours that occurs in adolescence. We hypothesised that cognitive processes involving mesocortical dopamine function would be altered when these axons are misrouted in adolescence. To test our hypothesis, we used the Go/No-Go behavioural paradigm. This test quantifies inhibitory control, which matures in parallel with the innervation of dopamine axons to the prefrontal cortex in adolescence (Casey et al., 2008; Klune et al., 2021; Luna et al., 2015; Paus, 2005; Reynolds and Flores, 2021; Spear, 2000), and it is impaired in adolescent-onset disorders like depression and schizophrenia (Catts et al., 2013; Clementz et al., 2016; McTeague et al., 2016; Millan et al., 2012).

At the onset of adolescence, we injected the Netrin-1 silencing, or a scrambled control virus, bilaterally into the dorsal peduncular cortex; in adulthood we tested the mice in the Go/No-Go task. This paradigm first involves discrimination learning and reaction time training (Appendix 1 - Supplementary Analysis 1), followed by a Go/No-Go test consisting of ‘Go’ trials where mice respond to a cue as previously trained and ‘No-Go’ trials where mice must abstain from responding to the cue (Figure 1M). Correct responses to both trial types are reinforced with a food reward. We quantified the percent of ‘No-Go’ trials where the mice incorrectly responded to the cue (‘Commission Errors’) and the percent of ‘Go’ trials where the mice correctly responded (‘Rewards’ or ‘Hits’; Appendix 1 - Supplementary Analysis 2). The ability of mice to respond correctly overall to both trial types is quantified as the Correct Response Rate (Appendix 1 - Supplementary Analysis 3; Reynolds et al., 2018; Vassilev et al., 2021; Reynolds et al., 2023).

Mice injected with the Netrin-1 silencing virus differed from controls in their performance during ‘No-Go’ trials. As the mice learn to withhold their responses over the course of the test, the number of commission errors they made in No-Go trials decreased in a sigmoidal fashion (Figure 1N). The upper and lower asymptotes of the sigmoidal curve quantify the number of commission errors committed during early and late test days, respectively, while the inflection point (ED50) indicates when mice start improving their ability to inhibit their behaviour. At the start of the Go/No part of the task, the Netrin-1 silencing group make slightly fewer commission errors (Figure 1O) than control groups, although both groups begin to improve in the No-Go task at around the same time (Figure 1P). However, the Netrin-1 silencing group achieved a substantially higher level of behavioural inhibition, quantified as a lower percentage of commission errors in the last test days (Figure 1Q), indicating an improved ability to withhold their behaviour on cue. These behavioural results demonstrate that the maturation of action impulsivity is sensitive to the organisation of the ventro-dorsal Netrin-1 path that guides mesocortical dopamine axon growth. Deviations in this route associate with striking changes in the cognitive development that is characteristic of adolescence. In this case, the deviation leads to improved action impulsivity, suggesting that these dopamine axons may end up ectopically innervating a forebrain region other than the medial prefrontal cortex, enhancing cognitive control.

Part 2: UNC5C expression coincides with the onset of adolescence

When axons leave the nucleus accumbens during adolescence, they follow a Netrin-1 ‘path’ through intermediate brain regions to reach their intended innervation target. However, only a small subset of the dopamine axons that have reached the nucleus accumbens by early adolescence leave; the vast majority stay and form connections in the accumbens throughout life (Reynolds et al., 2018). The ‘decision-making’ process of whether to ‘stay’ (in the accumbens) or ‘go’ (to the cortex via the Netrin-1 path) happens during a narrow developmental window at the onset of adolescence (Reynolds et al., 2019). It remains unknown how the timing of this process is determined.

In adolescence, dopamine neurons begin to express the repulsive Netrin-1 receptor UNC5C, particularly when mesolimbic and mesocortical dopamine projections segregate in the nucleus accumbens (Manitt et al., 2010; Reynolds et al., 2018). In contrast, dopamine axons in the prefrontal cortex do not express UNC5c, except in very rare cases (Appendix 1 - Supplementary Analysis 4). In adult male mice with Unc5c haploinsufficiency, there appears to be ectopic growth of mesolimbic dopamine axons to the prefrontal cortex (Auger et al., 2013). This miswiring is associated with alterations in prefrontal cortex-dependent behaviours (Auger et al., 2013).

Using immunohistochemistry, we assessed the expression of UNC5C on nucleus accumbens dopamine axons across development. In male mice, we found little expression of UNC5C on dopamine axons at the onset of adolescence (Figure 2A), while we did find UNC5C expression on dopamine axons in adults (Figure 2B). Remarkably, when we assessed this in females, we found dopamine axons already expressing UNC5C in the nucleus accumbens at the onset of adolescence (Figure 2D), similar to adult females (Figure 2E), indicating that the onset of UNC5C expression on dopamine axons in the nucleus accumbens is sexually dimorphic, with an earlier emergence in females. We examined the nucleus accumbens in pre-adolescent female mice and indeed found little UNC5C expression on dopamine axons (Figure 2C). The onset of UNC5C expression in mesocorticolimbic dopamine axons is therefore peri-adolescent but occurs earlier in females than in males, consistent with the earlier emergence of adolescence in female rodents and the earlier onset of adolescence and puberty in humans (Wolf and Long, 2016). Differences in the precise timing of dopamine innervation to the PFC in adolescence have been suggested by findings reported in male and female rats (Willing et al., 2017).

Figure 2

Download asset Open asset

Part 3: Environmental control of the timing of adolescence

We hypothesise that at the emergence of adolescence, UNC5C expression by dopamine axons in the nucleus accumbens signals the initiation of the growth of dopamine axons to the prefrontal cortex. We therefore examined whether the developmental timings of UNC5C expression and dopamine innervation of the prefrontal cortex are similarly affected by an environmental cue known to delay pubertal development in seasonal species.

Siberian hamsters (Phodopus sungorus) regulate many aspects of their behaviour and physiology to meet the changing environmental demands of seasonality (Paul et al., 2008; Stevenson et al., 2017). In winter, they increase the thickness of their fur, exchange their brown summer coats for white winter ones, and undergo a daily torpor to conserve energy (Scherbarth and Steinlechner, 2010). In addition, adults suppress reproduction and juveniles delay puberty (Pévet, 1988; Yellon and Goldman, 1984), including developmental changes in gonadotropin releasing hormone neurons in the hypothalamus (Buchanan and Yellon, 1991; Heywood and Yellon, 1997). Reproductive organ development is delayed as part of pubertal postponement (Darrow et al., 1980; Ebling, 1994; Timonin et al., 2006). This seasonal plasticity is regulated by long or short periods of daylight (Heldmaier and Steinlechner, 1981; Hoffmann, 1978) and raises the possibility that aspects of adolescent development are sensitive to these environmental cues (Paul et al., 2018; Walker et al., 2017). To our knowledge, adaptive variation in the timing of adolescent neural development has never been recorded in any animal.

Here, we tested whether daylength regulates when dopamine axons grow to the cortex, and whether the timing of UNC5C expression in the nucleus accumbens and adolescent changes in behaviour are similarly affected.

The seasonality of adolescence

Male hamsters were examined at three ages: 15 days of age (±1), 80 days of age (±10), and 215 days of age (±20). We compared the density of the dopamine innervation to the medial prefrontal cortex in male hamsters housed under lighting conditions that replicate summer daylengths (long days, short nights) or winter daylengths (short days, long nights) (Figure 3A and B). We will refer to these two groups as ‘summer hamsters’ and ‘winter hamsters’ to emphasise the natural stimulus we are replicating in the laboratory environment. We confirmed that puberty is delayed in male winter hamsters compared to summer hamsters in the present experiment by measuring their gonadal weights across ages (Appendix 1 - Supplementary Analysis 5).

Figure 3

Download asset Open asset

In male summer hamsters, dopamine input density to the prefrontal cortex increases during adolescence, after 15 days of age and before 80 days of age (Figure 3C), consistent with dopamine axon growth in mice (Manitt et al., 2013; Manitt et al., 2011; Reynolds et al., 2018). Prefrontal cortex dopamine innervation in summer hamsters continues to increase after 80 days of age (Figure 3C).

In male winter hamsters, dopamine innervation to the prefrontal cortex is delayed until after 80 days, which coincides with their delayed pubertal onset (Figure 3D, Appendix 1 - Supplementary Analysis 5). This demonstrates that an environmental cue can determine the timing of adolescent brain development.

We then examined UNC5C expression by dopamine axons in the nucleus accumbens in male summer and winter hamsters across age classes. UNC5C expression was apparent only after the onset of adolescence in summer hamsters (Figure 3E, F, and G), as observed in male mice. However, UNC5C expression was delayed in male winter hamsters – this group did not show UNC5C expression in dopamine axons in the nucleus accumbens until after 80 days of age (Figure 3H, I, and J). This aligns with the delayed timing of mesocortical dopamine axon growth and pubertal onset in male winter hamsters and demonstrates that the emergence of UNC5C is a marker of adolescent onset in male mice.

A behavioural characteristic of adolescence is increased willingness to enter a novel environment, a behaviour that assumes an increased amount of risk (Arrant et al., 2013; Lynn and Brown, 2009). To measure this, we used the light/dark test (Bourin and Hascoët, 2003). Time spent in the light compartment is dopamine-dependent (Bahi and Dreyer, 2019; Gao and Cutler, 1993) and peaks in adolescence (Arrant et al., 2013). We will refer to this behaviour as ‘risk taking’. We assessed the developmental profile of risk taking in the light/dark box test in summer and winter hamsters across adolescence. In male summer hamsters, the risk taking increases across adolescence, peaks around 50 days, then subsequently declines (Figure 3K). However, the adolescent increase in risk taking is protracted in winter hamsters: across the age range examined we observe a gradual, consistent increase in risk taking rather than a peak and decline.

We next assessed a cohort of 215-day-old hamsters, for which both summer and winter male hamsters have undergone puberty and exhibit high levels of dopamine innervation of the prefrontal cortex (Figure 3C, D, G, and J, Appendix 1 - Supplementary Analysis 5). In these hamsters, we find no difference in risk taking between the male summer and winter groups (Figure 3L), demonstrating that, after 80 days, risk taking begins to decline in male winter hamsters and that by 215 days it has declined to the same level as in summer hamsters. Male hamsters raised under summer-mimicking long days and winter-mimicking short days both ultimately make the transition to the adult behavioural phenotype.

We also examined a second behaviour, novel object investigation. We note similar, but not identical, developmental patterns in behaviour. Both male summer and winter hamsters show peaks in novel object exploration around 50 days old, however the developmental shifts in behaviour around that peak are significantly more substantial in the summer males compared to the winter males (Appendix 1 - Supplementary Analysis 8). In 215-day-old hamsters, there is no difference in novel object exploration between summer and winter males (Appendix 1 - Supplementary Analysis 9).

An extraordinary case of decoupling puberty and adolescence

In parallel with males, we conducted equivalent experiments in female hamsters (Figure 4A and B). Under a summer-mimicking daylength, dopamine innervation to the medial prefrontal cortex increases between 15 and 80 days of age, similar to male summer hamsters (Figure 4C). There is no further increase in innervation density after 80 days of age, consistent with earlier adolescent development in females observed in other rodent species (Juraska and Willing, 2017; Kopec et al., 2018; Reynolds and Flores, 2021; Spear, 2000; Westbrook et al., 2018). We confirmed that puberty is delayed in female winter hamsters compared to summer hamsters by measuring their uterine weights (Appendix 1 - Supplementary Analysis 6) and vaginal opening (Appendix 1 - Supplementary Analysis 7) across ages.

Figure 4

Download asset Open asset

When housed under a winter-mimicking daylength, dopamine input density in the prefrontal cortex of female hamsters is not delayed as in males, but rather reaches adult levels prior to 15 days of age (Figure 4D). We replicated this unexpected finding in a separate, independent cohort of female winter hamsters (Figure 4E). This surprising result shows an intervention that accelerates adolescent cortical development.

We then measured dopamine axon density in female winter hamsters at two earlier ages: 10 and 15 days of age. Dopamine innervation increases during this period (Figure 4F), well before normal adolescence and long before pubertal development. This is an extraordinary phenomenon: a key marker of adolescent neurodevelopment is accelerated and dissociated from puberty in female hamsters raised under winter-mimicking short days (Appendix 1 - Supplementary Analyses 6,7).

The early increase in prefrontal cortex dopamine terminals in winter females is followed by a dramatic reduction between 80 and 215 days of age (Figure 4D and E). This overlaps with the delayed timing of puberty in these females (Butler et al., 2007; Appendix 1 - Supplementary Analyses 6,7). Synaptic pruning in the cortex is a well-known component of adolescent neural development across species (Huttenlocher, 1984; Koss et al., 2014; Petanjek et al., 2011). Under normal conditions, the effect of pruning on dopamine synapses is likely masked by the growth of new dopamine axons to the prefrontal cortex (Manitt et al., 2013; Manitt et al., 2011; Reynolds et al., 2018). In the case of female winter hamsters, we hypothesise that the growth of dopamine axons to the prefrontal cortex occurs early while synaptic pruning, including dopamine synapses, appears to occur later. This leads to a remarkable dissociation between two cortical developmental processes that are normally simultaneous, the behavioural implications of which are unclear.

If the developmental onset of UNC5C expression determines the timing of dopamine innervation of the prefrontal cortex, then onset of UNC5C expression should also be advanced in female winter hamsters. Hence, we examined UNC5C expression at the same ages as we examined dopamine axon growth in female hamsters. At 10 and 15 days of age, UNC5C expression is present only in the winter hamsters (Figure 4G, H, K, and L), but at 80 and 215 days of age, UNC5C expression is apparent in both summer and winter hamsters (Figure 4I, J, M, and N).

We used the light/dark box test to examine potential risk-taking implications of the extraordinary developmental trajectory we observed in the prefrontal cortex of female hamsters. In female summer and winter hamsters, the adolescent increase and peak in risk taking occurs between the ages of 15 and 80 days, as it does in summer daylength males (Figure 4O). However, contrary to what we would expect, the peak in winter females is delayed compared to summer females. A delayed peak is also observed for winter females in novel object investigation (Appendix 1 - Supplementary Analysis 10). When we assessed an independent cohort of 215-day-old female hamsters, we found no difference in risk taking (Figure 4P) or novel object investigation (Appendix 1 - Supplementary Analysis 11) between groups, indicating that, like males, female summer and winter hamsters both eventually reach the same adult level of risk taking.

In both sexes, hamsters housed under a summer-mimicking daylength showed an adolescent peak in risk taking at an age that we would predict based on results from other rodents (Arrant et al., 2013; Pietropaolo et al., 2004; Tanaka, 2015). When raised under a winter-mimicking daylength, hamsters of either sex show a protracted peak in risk taking. In males, it is delayed beyond 80 days of age, but the delay is substantially less in females. This is a counterintuitive finding considering that dopamine development in winter females appears to be accelerated. Our interpretation of this finding is that the timing of the risk-taking peak in females may reflect a balance between different adolescent developmental processes. The fact that dopamine axon growth is accelerated does not imply that all adolescent maturational processes are accelerated. Some may be delayed, e.g., those that induce axon pruning in the cortex. The timing of the risk-taking peak in winter female hamsters may therefore reflect the amalgamation of developmental processes that are advanced with those that are delayed – producing a behavioural effect that is timed somewhere in the middle. Disentangling the effects of different developmental processes on behaviour will require further experiments in hamsters, including the direct manipulation of dopamine activity in the nucleus accumbens and prefrontal cortex.

All data and code use in these analyses are available through the Open Science Framework.

1. 1. Flores et al.

   (2024) Open Science Framework

   The scheduling of adolescence with Netrin-1 and UNC5C.

   https://doi.org/10.17605/OSF.IO/DU3H4

1. 1. Arrant AE
   2. Schramm-Sapyta NL
   3. Kuhn CM

   (2013) Use of the light/dark test for anxiety in adult and adolescent male rats

   Behavioural Brain Research 256:119–127.

   https://doi.org/10.1016/j.bbr.2013.05.035

   • PubMed
   • Google Scholar
2. 1. Auger ML
   2. Schmidt ERE
   3. Manitt C
   4. Dal-Bo G
   5. Pasterkamp RJ
   6. Flores C

   (2013) unc5c haploinsufficient phenotype: striking similarities with the dcc haploinsufficiency model

   The European Journal of Neuroscience 38:2853–2863.

   https://doi.org/10.1111/ejn.12270

   • PubMed
   • Google Scholar
3. 1. Bahi A
   2. Dreyer JL

   (2019) Dopamine transporter (DAT) knockdown in the nucleus accumbens improves anxiety- and depression-related behaviors in adult mice

   Behavioural Brain Research 359:104–115.

   https://doi.org/10.1016/j.bbr.2018.10.028

   • PubMed
   • Google Scholar
4. 1. Benes FM
   2. Vincent SL
   3. Molloy R
   4. Khan Y

   (1996) Increased interaction of dopamine-immunoreactive varicosities with GABA neurons of rat medial prefrontal cortex occurs during the postweanling period

   Synapse 23:237–245.

   https://doi.org/10.1002/(SICI)1098-2396(199608)23:4<237::AID-SYN1>3.0.CO;2-8

   • PubMed
   • Google Scholar
5. 1. Berger B
   2. Tassin JP
   3. Blanc G
   4. Moyne MA
   5. Thierry AM

   (1974) Histochemical confirmation for dopaminergic innervation of the rat cerebral cortex after destruction of the noradrenergic ascending pathways

   Brain Research 81:332–337.

   https://doi.org/10.1016/0006-8993(74)90948-2

   • PubMed
   • Google Scholar
6. 1. Berger B
   2. Verney C
   3. Gay M
   4. Vigny A

   (1983) Immunocytochemical characterization of the dopaminergic and noradrenergic innervation of the rat neocortex during early ontogenyproceedings of the 9th meeting of the international neurobiology society

   Brain Research 81:263–267.

   https://doi.org/10.1016/s0079-6123(08)60028-xBerger

   • Google Scholar
7. 1. Bourin M
   2. Hascoët M

   (2003) The mouse light/dark box test

   European Journal of Pharmacology 463:55–65.

   https://doi.org/10.1016/s0014-2999(03)01274-3

   • PubMed
   • Google Scholar
8. 1. Buchanan KL
   2. Yellon SM

   (1991) Delayed puberty in the male Djungarian hamster: effect of short photoperiod or melatonin treatment on the GnRH neuronal system

   Neuroendocrinology 54:96–102.

   https://doi.org/10.1159/000125857

   • PubMed
   • Google Scholar
9. 1. Butler MP
   2. Trumbull JJ
   3. Turner KW
   4. Zucker I

   (2007) Timing of puberty and synchronization of seasonal rhythms by simulated natural photoperiods in female Siberian hamsters

   American Journal of Physiology-Regulatory, Integrative and Comparative Physiology 293:R413–R420.

   https://doi.org/10.1152/ajpregu.00216.2007

   • Google Scholar
10. 1. Caldwell M
    2. Ayo-Jibunoh V
    3. Mendoza JC
    4. Brimblecombe KR
    5. Reynolds LM
    6. Zhu Jiang XY
    7. Alarcon C
    8. Fiore E
    9. N Tomaio J
    10. Phillips GR
    11. Mingote S
    12. Flores C
    13. Casaccia P
    14. Liu J
    15. Cragg SJ
    16. McCloskey DP
    17. Yetnikoff L

    (2023) Axo-glial interactions between midbrain dopamine neurons and oligodendrocyte lineage cells in the anterior corpus callosum

    Brain Structure & Function 228:1993–2006.

    https://doi.org/10.1007/s00429-023-02695-y

    • PubMed
    • Google Scholar
11. 1. Casey BJ
    2. Jones RM
    3. Hare TA

    (2008) The adolescent brain

    Annals of the New York Academy of Sciences 1124:111–126.

    https://doi.org/10.1196/annals.1440.010

    • PubMed
    • Google Scholar
12. 1. Catts VS
    2. Fung SJ
    3. Long LE
    4. Joshi D
    5. Vercammen A
    6. Allen KM
    7. Fillman SG
    8. Rothmond DA
    9. Sinclair D
    10. Tiwari Y
    11. Tsai S-Y
    12. Weickert TW
    13. Shannon Weickert C

    (2013) Rethinking schizophrenia in the context of normal neurodevelopment

    Frontiers in Cellular Neuroscience 7:60.

    https://doi.org/10.3389/fncel.2013.00060

    • PubMed
    • Google Scholar
13. 1. Clementz BA
    2. Sweeney JA
    3. Hamm JP
    4. Ivleva EI
    5. Ethridge LE
    6. Pearlson GD
    7. Keshavan MS
    8. Tamminga CA

    (2016) Identification of distinct psychosis biotypes using brain-based biomarkers

    The American Journal of Psychiatry 173:373–384.

    https://doi.org/10.1176/appi.ajp.2015.14091200

    • PubMed
    • Google Scholar
14. 1. Cuesta S
    2. Nouel D
    3. Reynolds LM
    4. Morgunova A
    5. Torres-Berrío A
    6. White A
    7. Hernandez G
    8. Cooper HM
    9. Flores C

    (2020) Dopamine axon targeting in the nucleus accumbens in adolescence requires netrin-1

    Frontiers in Cell and Developmental Biology 8:487.

    https://doi.org/10.3389/fcell.2020.00487

    • PubMed
    • Google Scholar
15. 1. Darrow JM
    2. Davis FC
    3. Elliott JA
    4. Stetson MH
    5. Turek FW
    6. Menaker M

    (1980) Influence of photoperiod on reproductive development in the golden hamster

    Biology of Reproduction 22:443–450.

    https://doi.org/10.1095/biolreprod22.3.443

    • PubMed
    • Google Scholar
16. 1. Drzewiecki CM
    2. Juraska JM

    (2020) The structural reorganization of the prefrontal cortex during adolescence as a framework for vulnerability to the environment

    Pharmacology Biochemistry and Behavior 199:173044.

    https://doi.org/10.1016/j.pbb.2020.173044

    • Google Scholar
17. 1. Ebling FJP

    (1994) Photoperiodic differences during development in the dwarf hamsters phodopus sungorus and phodopus campbelli

    General and Comparative Endocrinology 95:475–482.

    https://doi.org/10.1006/gcen.1994.1147

    • Google Scholar
18. 1. Fuhrmann D
    2. Knoll LJ
    3. Blakemore SJ

    (2015) Adolescence as a sensitive period of brain development

    Trends in Cognitive Sciences 19:558–566.

    https://doi.org/10.1016/j.tics.2015.07.008

    • Google Scholar
19. 1. Gao B
    2. Cutler MG

    (1993) Effects of quinpirole on the behaviour shown by mice in the light-dark box and during social interactions

    Neuropharmacology 32:93–100.

    https://doi.org/10.1016/0028-3908(93)90134-o

    • PubMed
    • Google Scholar
20. 1. Gogtay N
    2. Giedd JN
    3. Lusk L
    4. Hayashi KM
    5. Greenstein D
    6. Vaituzis AC
    7. Nugent TF
    8. Herman DH
    9. Clasen LS
    10. Toga AW
    11. Rapoport JL
    12. Thompson PM

    (2004) Dynamic mapping of human cortical development during childhood through early adulthood

    PNAS 101:8174–8179.

    https://doi.org/10.1073/pnas.0402680101

    • Google Scholar
21. 1. Heldmaier G
    2. Steinlechner S

    (1981) Seasonal pattern and energetics of short daily torpor in the Djungarian hamster, Phodopus sungorus

    Oecologia 48:265–270.

    https://doi.org/10.1007/BF00347975

    • PubMed
    • Google Scholar
22. 1. Heywood SG
    2. Yellon SM

    (1997) Gonadotropin-releasing hormone neural projections to the systemic vasculature during sexual maturation and delayed puberty in the male Djungarian hamster

    Biology of Reproduction 57:873–878.

    https://doi.org/10.1095/biolreprod57.4.873

    • PubMed
    • Google Scholar
23. 1. Hoffmann K

    (1978) Effects of short photoperiods on puberty, growth and moult in the Djungarian hamster (Phodopus sungorus)

    Journal of Reproduction and Fertility 54:29–35.

    https://doi.org/10.1530/jrf.0.0540029

    • PubMed
    • Google Scholar
24. 1. Hollenstein T
    2. Lougheed JP

    (2013) Beyond storm and stress

    The American Psychologist 68:444–454.

    https://doi.org/10.1037/a0033586

    • Google Scholar
25. 1. Hoops D
    2. Flores C

    (2017) Making dopamine connections in adolescence

    Trends in Neurosciences 40:709–719.

    https://doi.org/10.1016/j.tins.2017.09.004

    • PubMed
    • Google Scholar
26. 1. Hoops D
    2. Reynolds LM
    3. Restrepo-Lozano JM
    4. Flores C

    (2018) Dopamine development in the mouse orbital prefrontal cortex is protracted and sensitive to amphetamine in adolescence

    eNeuro 5:2017.

    https://doi.org/10.1523/ENEURO.0372-17.2017

    • PubMed
    • Google Scholar
27. Book

    1. Howard V
    2. Reed M

    (2005)

    Unbiased Stereology: Three-Dimensional Measurement in Microscopy

    Garland Science/BIOS Scientific Publishers.

    • Google Scholar
28. 1. Huttenlocher PR

    (1984)

    Synapse elimination and plasticity in developing human cerebral cortex

    American Journal of Mental Deficiency 88:488–496.

    • PubMed
    • Google Scholar
29. 1. Juraska JM
    2. Willing J

    (2017) Pubertal onset as a critical transition for neural development and cognition

    Brain Research 1654:87–94.

    https://doi.org/10.1016/j.brainres.2016.04.012

    • PubMed
    • Google Scholar
30. 1. Keshavan MS
    2. Giedd J
    3. Lau JYF
    4. Lewis DA
    5. Paus T

    (2014) Changes in the adolescent brain and the pathophysiology of psychotic disorders

    The Lancet. Psychiatry 1:549–558.

    https://doi.org/10.1016/S2215-0366(14)00081-9

    • PubMed
    • Google Scholar
31. 1. Kessler RC
    2. Berglund P
    3. Demler O
    4. Jin R
    5. Merikangas KR
    6. Walters EE

    (2005) Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the national comorbidity survey replication

    Archives of General Psychiatry 62:593–602.

    https://doi.org/10.1001/archpsyc.62.6.593

    • PubMed
    • Google Scholar
32. 1. Kessler RC
    2. Amminger GP
    3. Aguilar-Gaxiola S
    4. Alonso J
    5. Lee S
    6. Ustün TB

    (2007) Age of onset of mental disorders: a review of recent literature

    Current Opinion in Psychiatry 20:359–364.

    https://doi.org/10.1097/YCO.0b013e32816ebc8c

    • PubMed
    • Google Scholar
33. 1. Kim SR
    2. Chen X
    3. Oo TF
    4. Kareva T
    5. Yarygina O
    6. Wang C
    7. During M
    8. Kholodilov N
    9. Burke RE

    (2011) Dopaminergic pathway reconstruction by Akt/Rheb‐induced axon regeneration

    Annals of Neurology 70:110–120.

    https://doi.org/10.1002/ana.22383

    • Google Scholar
34. 1. Klune CB
    2. Jin B
    3. DeNardo LA

    (2021) Linking mPFC circuit maturation to the developmental regulation of emotional memory and cognitive flexibility

    eLife 10:e64567.

    https://doi.org/10.7554/eLife.64567

    • PubMed
    • Google Scholar
35. 1. Kopec AM
    2. Smith CJ
    3. Ayre NR
    4. Sweat SC
    5. Bilbo SD

    (2018) Microglial dopamine receptor elimination defines sex-specific nucleus accumbens development and social behavior in adolescent rats

    Nature Communications 9:3769.

    https://doi.org/10.1038/s41467-018-06118-z

    • PubMed
    • Google Scholar
36. 1. Koss WA
    2. Belden CE
    3. Hristov AD
    4. Juraska JM

    (2014) Dendritic remodeling in the adolescent medial prefrontal cortex and the basolateral amygdala of male and female rats

    Synapse 68:61–72.

    https://doi.org/10.1002/syn.21716

    • PubMed
    • Google Scholar
37. 1. Kyne RF
    2. Barrett AR
    3. Brown LM
    4. Paul MJ

    (2019) Prepubertal ovarian inhibition of Light/Dark Box exploration and novel object investigation in juvenile Siberian hamsters

    Hormones and Behavior 115:104559.

    https://doi.org/10.1016/j.yhbeh.2019.07.007

    • PubMed
    • Google Scholar
38. 1. Larsen B
    2. Luna B

    (2018) Adolescence as a neurobiological critical period for the development of higher-order cognition

    Neuroscience and Biobehavioral Reviews 94:179–195.

    https://doi.org/10.1016/j.neubiorev.2018.09.005

    • PubMed
    • Google Scholar
39. 1. Lee FS
    2. Heimer H
    3. Giedd JN
    4. Lein ES
    5. Šestan N
    6. Weinberger DR
    7. Casey BJ

    (2014) Mental health: adolescent mental health--opportunity and obligation

    Science 346:547–549.

    https://doi.org/10.1126/science.1260497

    • PubMed
    • Google Scholar
40. 1. Levitt P
    2. Moore RY

    (1979) Development of the noradrenergic innervation of neocortex

    Brain Research 162:243–259.

    https://doi.org/10.1016/0006-8993(79)90287-7

    • PubMed
    • Google Scholar
41. 1. Luna B
    2. Marek S
    3. Larsen B
    4. Tervo-Clemmens B
    5. Chahal R

    (2015) An integrative model of the maturation of cognitive control

    Annual Review of Neuroscience 38:151–170.

    https://doi.org/10.1146/annurev-neuro-071714-034054

    • PubMed
    • Google Scholar
42. 1. Lynn DA
    2. Brown GR

    (2009) The ontogeny of exploratory behavior in male and female adolescent rats (Rattus norvegicus)

    Developmental Psychobiology 51:513–520.

    https://doi.org/10.1002/dev.20386

    • PubMed
    • Google Scholar
43. 1. Manitt C
    2. Labelle-Dumais C
    3. Eng C
    4. Grant A
    5. Mimee A
    6. Stroh T
    7. Flores C

    (2010) Peri-pubertal emergence of UNC-5 homologue expression by dopamine neurons in rodents

    PLOS ONE 5:e11463.

    https://doi.org/10.1371/journal.pone.0011463

    • PubMed
    • Google Scholar
44. 1. Manitt C
    2. Mimee A
    3. Eng C
    4. Pokinko M
    5. Stroh T
    6. Cooper HM
    7. Kolb B
    8. Flores C

    (2011) The netrin receptor DCC is required in the pubertal organization of mesocortical dopamine circuitry

    The Journal of Neuroscience 31:8381–8394.

    https://doi.org/10.1523/JNEUROSCI.0606-11.2011

    • PubMed
    • Google Scholar
45. 1. Manitt C
    2. Eng C
    3. Pokinko M
    4. Ryan RT
    5. Torres-Berrío A
    6. Lopez JP
    7. Yogendran SV
    8. Daubaras MJJ
    9. Grant A
    10. Schmidt ERE
    11. Tronche F
    12. Krimpenfort P
    13. Cooper HM
    14. Pasterkamp RJ
    15. Kolb B
    16. Turecki G
    17. Wong TP
    18. Nestler EJ
    19. Giros B
    20. Flores C

    (2013) dcc orchestrates the development of the prefrontal cortex during adolescence and is altered in psychiatric patients

    Translational Psychiatry 3:e338.

    https://doi.org/10.1038/tp.2013.105

    • PubMed
    • Google Scholar
46. 1. McTeague LM
    2. Goodkind MS
    3. Etkin A

    (2016) Transdiagnostic impairment of cognitive control in mental illness

    Journal of Psychiatric Research 83:37–46.

    https://doi.org/10.1016/j.jpsychires.2016.08.001

    • PubMed
    • Google Scholar
47. 1. Millan MJ
    2. Agid Y
    3. Brüne M
    4. Bullmore ET
    5. Carter CS
    6. Clayton NS
    7. Connor R
    8. Davis S
    9. Deakin B
    10. DeRubeis RJ
    11. Dubois B
    12. Geyer MA
    13. Goodwin GM
    14. Gorwood P
    15. Jay TM
    16. Joëls M
    17. Mansuy IM
    18. Meyer-Lindenberg A
    19. Murphy D
    20. Rolls E
    21. Saletu B
    22. Spedding M
    23. Sweeney J
    24. Whittington M
    25. Young LJ

    (2012) Cognitive dysfunction in psychiatric disorders: characteristics, causes and the quest for improved therapy

    Nature Reviews. Drug Discovery 11:141–168.

    https://doi.org/10.1038/nrd3628

    • PubMed
    • Google Scholar
48. 1. Miner LH
    2. Schroeter S
    3. Blakely RD
    4. Sesack SR

    (2003) Ultrastructural localization of the norepinephrine transporter in superficial and deep layers of the rat prelimbic prefrontal cortex and its spatial relationship to probable dopamine terminals

    The Journal of Comparative Neurology 466:478–494.

    https://doi.org/10.1002/cne.10898

    • PubMed
    • Google Scholar
49. Book

    1. Morin LP
    2. Wood RI

    (2001)

    A Stereotaxic Atlas of the Golden Hamster Brain

    Academic Press.

    • Google Scholar
50. 1. Paul MJ
    2. Zucker I
    3. Schwartz WJ

    (2008) Tracking the seasons: the internal calendars of vertebrates

    Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 363:341–361.

    https://doi.org/10.1098/rstb.2007.2143

    • PubMed
    • Google Scholar
51. 1. Paul MJ
    2. Probst CK
    3. Brown LM
    4. de Vries GJ

    (2018) Dissociation of Puberty and Adolescent Social Development in a Seasonally Breeding Species

    Current Biology 28:1116–1123.

    https://doi.org/10.1016/j.cub.2018.02.030

    • PubMed
    • Google Scholar
52. 1. Paus T

    (2005) Mapping brain maturation and cognitive development during adolescence

    Trends in Cognitive Sciences 9:60–68.

    https://doi.org/10.1016/j.tics.2004.12.008

    • Google Scholar
53. Book

    1. Paxinos G
    2. Franklin KBJ

    (2013)

    The mouse brain in stereotaxic coordinates

    Academic Press.

    • Google Scholar
54. 1. Petanjek Z
    2. Judaš M
    3. Šimić G
    4. Rašin MR
    5. Uylings HBM
    6. Rakic P
    7. Kostović I

    (2011) Extraordinary neoteny of synaptic spines in the human prefrontal cortex

    PNAS 108:13281–13286.

    https://doi.org/10.1073/pnas.1105108108

    • Google Scholar
55. 1. Pévet P

    (1988) The role of the pineal gland in the photoperiodic control of reproduction in different hamster species

    Reproduction, Nutrition, Developpement 28:443–458.

    https://doi.org/10.1051/rnd:19880310

    • PubMed
    • Google Scholar
56. 1. Pickel VM
    2. Joh TH
    3. Field PM
    4. Becker CG
    5. Reis DJ

    (1975) Cellular localization of tyrosine hydroxylase byimmunohistochemistry

    Journal of Histochemistry & Cytochemistry 23:1–12.

    https://doi.org/10.1177/23.1.234988

    • Google Scholar
57. 1. Pietropaolo S
    2. Branchi I
    3. Cirulli F
    4. Chiarotti F
    5. Aloe L
    6. Alleva E

    (2004) Long-term effects of the periadolescent environment on exploratory activity and aggressive behaviour in mice: social versus physical enrichment

    Physiology & Behavior 81:443–453.

    https://doi.org/10.1016/j.physbeh.2004.02.022

    • PubMed
    • Google Scholar
58. Software

    1. R Development Core Team

    (2014) R: A language and environment for statistical computing

    R Foundation for Statistical Computing, Vienna, Austria.

    https://www.r-project.org
59. 1. Reynolds LM
    2. Pokinko M
    3. Torres-Berrío A
    4. Cuesta S
    5. Lambert LC
    6. Del Cid Pellitero E
    7. Wodzinski M
    8. Manitt C
    9. Krimpenfort P
    10. Kolb B
    11. Flores C

    (2018) DCC receptors drive prefrontal cortex maturation by determining dopamine axontargeting in adolescence

    Biological Psychiatry 83:181–192.

    https://doi.org/10.1016/j.biopsych.2017.06.009

    • PubMed
    • Google Scholar
60. 1. Reynolds LM
    2. Yetnikoff L
    3. Pokinko M
    4. Wodzinski M
    5. Epelbaum JG
    6. Lambert LC
    7. Cossette MP
    8. Arvanitogiannis A
    9. Flores C

    (2019) Early adolescence is a critical period for the maturation of inhibitory behavior

    Cerebral Cortex 29:3676–3686.

    https://doi.org/10.1093/cercor/bhy247

    • Google Scholar
61. 1. Reynolds LM
    2. Flores C

    (2021) Mesocorticolimbic dopamine pathways across adolescence: diversity in development

    Frontiers in Neural Circuits 15:735625.

    https://doi.org/10.3389/fncir.2021.735625

    • Google Scholar
62. Book

    1. Reynolds LM
    2. Pantoja-Urbán AH
    3. MacGowan D
    4. Manitt C
    5. Nouel D
    6. Flores C

    (2022) Quantifying dopaminergic innervation in rodents using unbiased stereology

    Dopamine Neurotransmission.

    https://doi.org/10.1007/978-1-0716-2799-0

    • Google Scholar
63. 1. Reynolds LM
    2. Hernandez G
    3. MacGowan D
    4. Popescu C
    5. Nouel D
    6. Cuesta S
    7. Burke S
    8. Savell KE
    9. Zhao J
    10. Restrepo-Lozano JM
    11. Giroux M
    12. Israel S
    13. Orsini T
    14. He S
    15. Wodzinski M
    16. Avramescu RG
    17. Pokinko M
    18. Epelbaum JG
    19. Niu Z
    20. Pantoja-Urbán AH
    21. Trudeau LÉ
    22. Kolb B
    23. Day JJ
    24. Flores C

    (2023) Amphetamine disrupts dopamine axon growth in adolescence by a sex-specific mechanism in mice

    Nature Communications 14:4035.

    https://doi.org/10.1038/s41467-023-39665-1

    • PubMed
    • Google Scholar
64. 1. Salameh S
    2. Nouel D
    3. Flores C
    4. Hoops D

    (2018) An optimized immunohistochemistry protocol for detecting the guidance cue Netrin-1 in neural tissue

    MethodsX 5:1–7.

    https://doi.org/10.1016/j.mex.2017.12.001

    • PubMed
    • Google Scholar
65. 1. Scherbarth F
    2. Steinlechner S

    (2010) Endocrine mechanisms of seasonal adaptation in small mammals: from early results to present understanding

    Journal of Comparative Physiology B 180:935–952.

    https://doi.org/10.1007/s00360-010-0498-2

    • Google Scholar
66. 1. Séguéla P
    2. Watkins KC
    3. Descarries L

    (1988) Ultrastructural features of dopamine axon terminals in the anteromedial and the suprarhinal cortex of adult rat

    Brain Research 442:11–22.

    https://doi.org/10.1016/0006-8993(88)91427-8

    • PubMed
    • Google Scholar
67. 1. Sowell ER
    2. Thompson PM
    3. Toga AW

    (2004) Mapping changes in the human cortex throughout the span of life

    The Neuroscientist 10:372–392.

    https://doi.org/10.1177/1073858404263960

    • Google Scholar
68. 1. Spear LP

    (2000) The adolescent brain and age-related behavioral manifestations

    Neuroscience and Biobehavioral Reviews 24:417–463.

    https://doi.org/10.1016/s0149-7634(00)00014-2

    • PubMed
    • Google Scholar
69. Book

    1. Stevenson TJ
    2. Prendergast BJ
    3. Nelson RJ

    (2017)

    Mammalian seasonal rhythms: behavior and neuroendocrine substrates

    In: Pfaff DW, Joëls M, editors. Hormones, Brain and Behavior. Amsterdam: Academic Press. pp. 371–398.

    • Google Scholar
70. 1. Tanaka T

    (2015)

    Sex differences in exploratory behaviour of laboratory CD-1 mice (Mus musculus)

    Scandinavian Journal of Laboratory Animal Science 41:1–9.

    • Google Scholar
71. 1. Timonin ME
    2. Place NJ
    3. Wanderi E
    4. Wynne-Edwards KE

    (2006) Phodopus campbelli detect reduced photoperiod during development but, unlike Phodopus sungorus, retain functional reproductive physiology

    Reproduction 132:661–670.

    https://doi.org/10.1530/rep.1.00019

    • PubMed
    • Google Scholar
72. 1. Van Eden CG
    2. Hoorneman EMD
    3. Buijs RM
    4. Matthijssen MAH
    5. Geffard M
    6. Uylings HBM

    (1987) Immunocytochemical localization of dopamine in the prefrontal cortex of the rat at the light and electron microscopical level

    Neuroscience 22:849–862.

    https://doi.org/10.1016/0306-4522(87)92964-2

    • Google Scholar
73. 1. Vassilev P
    2. Pantoja-Urban AH
    3. Giroux M
    4. Nouel D
    5. Hernandez G
    6. Orsini T
    7. Flores C

    (2021) Unique effects of social defeat stress in adolescent male mice on the Netrin-1/DCC pathway, prefrontal cortex dopamine and cognition (Social stress in adolescent vs. adult male mice)

    eNeuro 8:ENEURO.0045-21.2021.

    https://doi.org/10.1523/ENEURO.0045-21.2021

    • PubMed
    • Google Scholar
74. 1. Verney C
    2. Berger B
    3. Adrien J
    4. Vigny A
    5. Gay M

    (1982) Development of the dopaminergic innervation of the rat cerebral cortex: a light microscopic immunocytochemical study using anti-tyrosine hydroxylase antibodies

    Developmental Brain Research 5:41–52.

    https://doi.org/10.1016/0165-3806(82)90111-0

    • Google Scholar
75. 1. Walker DM
    2. Bell MR
    3. Flores C
    4. Gulley JM
    5. Willing J
    6. Paul MJ

    (2017) Adolescence and reward: Making sense of neural and behavioral changes amid the Chaos

    The Journal of Neuroscience 37:10855–10866.

    https://doi.org/10.1523/JNEUROSCI.1834-17.2017

    • PubMed
    • Google Scholar
76. 1. Westbrook SR
    2. Hankosky ER
    3. Dwyer MR
    4. Gulley JM

    (2018) Age and sex differences in behavioral flexibility, sensitivity to reward value, and risky decision-making

    Behavioral Neuroscience 132:75–87.

    https://doi.org/10.1037/bne0000235

    • Google Scholar
77. 1. Willing J
    2. Cortes LR
    3. Brodsky JM
    4. Kim T
    5. Juraska JM

    (2017) Innervation of the medial prefrontal cortex by tyrosine hydroxylase immunoreactive fibers during adolescence in male and female rats

    Developmental Psychobiology 59:583–589.

    https://doi.org/10.1002/dev.21525

    • PubMed
    • Google Scholar
78. 1. Wolf RM
    2. Long D

    (2016) Pubertal development

    Pediatrics in Review 37:292–300.

    https://doi.org/10.1542/pir.2015-0065

    • PubMed
    • Google Scholar
79. 1. Yellon SM
    2. Goldman BD

    (1984) Photoperiod control of reproductive development in the male Djungarian hamster (Phodopus sungorus)

    Endocrinology 114:664–670.

    https://doi.org/10.1210/endo-114-2-664

    • PubMed
    • Google Scholar

Author details

1. Daniel Hoops

   1. Department of Psychiatry, McGill University, Montréal, Canada
   2. Douglas Mental Health University Institute, Montréal, Canada

   Contribution

   Conceptualization, Data curation, Formal analysis, Supervision, Validation, Investigation, Visualization, Methodology, Writing - original draft, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-5707-3513

2. Robert Kyne

   Neuroscience Program, University at Buffalo, SUNY, United States

   Contribution

   Investigation

   Competing interests

   No competing interests declared

3. Samer Salameh

   1. Douglas Mental Health University Institute, Montréal, Canada
   2. Integrated Program in Neuroscience, McGill University, Montreal, Canada

   Contribution

   Investigation

   Competing interests

   No competing interests declared

4. Del MacGowan

   1. Douglas Mental Health University Institute, Montréal, Canada
   2. Integrated Program in Neuroscience, McGill University, Montreal, Canada

   Contribution

   Investigation, Visualization

   Competing interests

   No competing interests declared

5. Radu Gabriel Avramescu

   1. Department of Psychiatry, McGill University, Montréal, Canada
   2. Douglas Mental Health University Institute, Montréal, Canada

   Contribution

   Investigation, Visualization

   Competing interests

   No competing interests declared

6. Elise Ewing

   1. Douglas Mental Health University Institute, Montréal, Canada
   2. Integrated Program in Neuroscience, McGill University, Montreal, Canada

   Contribution

   Investigation

   Competing interests

   No competing interests declared

7. Alina Tao He

   1. Douglas Mental Health University Institute, Montréal, Canada
   2. Integrated Program in Neuroscience, McGill University, Montreal, Canada

   Contribution

   Investigation

   Competing interests

   No competing interests declared

8. Taylor Orsini

   1. Douglas Mental Health University Institute, Montréal, Canada
   2. Integrated Program in Neuroscience, McGill University, Montreal, Canada

   Contribution

   Investigation

   Competing interests

   No competing interests declared

9. Anais Durand

   1. Douglas Mental Health University Institute, Montréal, Canada
   2. Integrated Program in Neuroscience, McGill University, Montreal, Canada

   Contribution

   Investigation

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-8125-1394

10. Christina Popescu

    1. Douglas Mental Health University Institute, Montréal, Canada
    2. Integrated Program in Neuroscience, McGill University, Montreal, Canada

    Contribution

    Investigation

    Competing interests

    No competing interests declared

11. Janet Mengyi Zhao

    1. Douglas Mental Health University Institute, Montréal, Canada
    2. Integrated Program in Neuroscience, McGill University, Montreal, Canada

    Contribution

    Investigation

    Competing interests

    No competing interests declared

12. Kelcie Shatz

    Department of Psychology, University at Buffalo, SUNY, United States

    Contribution

    Investigation

    Competing interests

    No competing interests declared

13. LiPing Li

    Department of Psychology, University at Buffalo, SUNY, United States

    Contribution

    Investigation

    Competing interests

    No competing interests declared

14. Quinn Carroll

    Department of Psychology, University at Buffalo, SUNY, United States

    Contribution

    Investigation

    Competing interests

    No competing interests declared

15. Guofa Liu

    Department of Biological Sciences, University of Toledo, Toledo, United States

    Contribution

    Resources

    Competing interests

    No competing interests declared

16. Matthew J Paul

    1. Neuroscience Program, University at Buffalo, SUNY, United States
    2. Department of Psychology, University at Buffalo, SUNY, United States

    Contribution

    Conceptualization, Resources, Supervision, Funding acquisition, Methodology, Writing – review and editing

    Competing interests

    No competing interests declared

    Additional information

    Co-senior author

    "This ORCID iD identifies the author of this article:" 0000-0002-9097-1390

17. Cecilia Flores

    1. Department of Psychiatry, McGill University, Montréal, Canada
    2. Douglas Mental Health University Institute, Montréal, Canada
    3. Department of Neurology and Neurosurgery, McGill University, Montréal, Canada
    4. Ludmer Centre for Neuroinformatics & Mental Health, McGill University, Montréal, Canada

    Contribution

    Conceptualization, Resources, Supervision, Funding acquisition, Methodology, Writing – review and editing

    For correspondence

    cecilia.flores@mcgill.ca

    Competing interests

    No competing interests declared

    Additional information

    Co-senior author

    "This ORCID iD identifies the author of this article:" 0000-0001-8606-5910

• 463

  views

• 12

  downloads

• 0

  citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.