Um LogoUniversity of Michigan mathematicians and their British colleagues claim that they have detected the signal that the brain sends to the rest of the body to manage biological rhythms, a discovery that apparently invalidates a long-held assumption about our internal clock.

Understanding how the human biological clock operates is said to be an important step towards rectifying sleep problems such as insomnia and jet lag. Fresh insights about the body’s central pacemaker might also, sometime; progress efforts to treat diseases affected by the internal clock, counting cancer, Alzheimer’s disease and mood disorders. This was mentioned by the University of Michigan mathematician, Daniel Forger.

Forger, an associate professor of mathematics and a member of the U-M’s Center for Computational Medicine and Bioinformatics, commented, “Knowing what the signal is will help us learn how to adjust it, in order to help people. We have cracked the code, and the information could have a tremendous impact on all sorts of diseases that are affected by the clock.”

The body’s chief time-keeper exists in an area of the central brain known as the suprachiasmatic nuclei, or SCN. For several years, researchers have believed that it is the pace at which SCN cells shoot electrical pulses during the day and slow at night, apparently manages time-keeping throughout the body.

A metronome in the brain ticks rapidly throughout the day and apparently slows its speed at night. The rest of the body hears the ticking and regulates its daily rhythms, also called as circadian rhythms, accordingly. This is the thought that has been believed to be true for several years. But new evidence suggests that the old theory may be incorrect.

The correct signaling mechanism is supposed to be quite different. The timing signal sent from the SCN is programmed in an intricate firing pattern that had formerly been unnoticed. This was mentioned by Forger and U-M graduate student Casey Diekman, along with Dr. Mino Belle and Hugh Piggins of the University of Manchester in England.

To examine the guess made by Forger and Diekman’s mathematical model, the British scientists gathered data on firing patterns from more than around 400 mouse SCN cells. The U-M scientists then plugged the experimental outcomes into their model and discovered that the experimental data were almost exactly what the model had predicted.

Though the experiments were conducted on mice, Forger mentioned that it may be probable that a similar mechanism is at work in humans, since timekeeping systems are said to be alike in all mammals.

The SCN has both clock cells and non-clock cells. For several years, circadian-biology researchers have been recording electrical signals from a combination of both kinds of cells. That apparently led to a deceptive picture of the clock’s inner workings.

But Forger’s British colleagues were apparently able to detach clock cells from non-clock cells by zeroing in on the ones that expressed the per1 gene. Then they recorded electrical signals which were generated fully by those clock cells. The design that appeared supposedly boosted the daring novel theory.

The researchers discovered that during the day, SCN cells expressing per1 maintain an electrically energized state but do not fire. They fire for a short period around dusk, and then apparently stay quiet throughout the night before discharging another surge of activity around dawn. This firing pattern is believed to be an indicator, or code, the brain sends to the rest of the body so that it could keep time.

Diekman explained, “The old theory was that the cells in the SCN which contain the clock are firing fast during the day but slow at night. But now we’ve shown that the cells that actually contain the clock mechanism are silent during the day, when everybody thought they were firing fast.”

Piggins mentioned, “The findings force us to completely reassess what we thought we knew about electrical activity in the brain’s circadian clock.” In addition, the results demonstrate the importance of interdisciplinary collaborative research.”

Belle mentioned that it increases significant questions about whether the brain performs in an analog or a digital way.

The finding was published in the journal Science.