Internal registration of the seasons

Your brain doesn't just detect light. It measures the gap between dawn and dusk, and that measurement tells it whether it's July or December. Here is how that actually works.

Your master biological clock sits in the suprachiasmatic nucleus (SCN), a small structure deep in the brain. For decades, the leading model of how this clock works has been built around a deceptively elegant idea: there are not one but two coupled oscillators inside the SCN, one tracking dawn and one tracking dusk, and the distance between them encodes the length of the day.
This is how your brain knows the season.

The model was first proposed by Pittendrigh and Daan in 1976. They described a morning oscillator (M) with a period slightly longer than 24 hours, accelerated by light, and governing activity before dawn. And an evening oscillator (E) with a period slightly shorter than 24 hours, decelerated by light, and governing activity after dusk. In summer, the two oscillators are pulled far apart by long days. In winter, they compress together under short days. That internal reorganisation is the biological representation of photoperiod, and it drives seasonal changes in sleep, mood, metabolism, and physiology across virtually all mammals.

The molecular basis for this seasonal encoding has since been mapped in real SCN tissue. Under long photoperiods, SCN neurons in distinct network compartments display clearly different timing in their peak clock gene activity, spread across the day. Under short photoperiods, those same neurons compress into near-synchrony. The SCN is not a fixed clock. It is a reconfigurable network whose internal geometry changes with the seasons.

What this means in practice: the light entering your eyes does not simply signal "daytime." It is actively reshaping the internal geometry of a 20,000-neuron network that tells your body what time of year it is. That network is responding to your current light environment, including the artificial one most of us now live inside.

https://pmc.ncbi.nlm.nih.gov/articles/PMC10924288/pdf/nihms-1966322.pdf