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November 19, 2012 / neurograce

It’s All Relative: The neural processing of time and how it could relate to lifespan length

Our perception of time is a wobbly thing. We all know it flies when we’re having fun. But if you’ve ever found yourself waiting for a bus in the cold, sitting through an especially boring lecture, or tripping down a flight of stairs then you know it also has a habit of slowing down nearly to a halt. As it turns out, our ability to keep an internal stopwatch has been crucial for our survival. It lets us know if two events could be causally-related and allows for “cost-benefit analysis”, by giving some measure of the amount of work we’re putting into a task. But, as with most big & important mental phenomenon, we are far from a clear understanding of how it works.

Many researchers approach the question of how neurons could keep track of time by training animals to delay their activity before getting a reward. For example, as this article on the research of time perception mentions, hummingbirds were able to learn that fake flowers in the lab were refilled with nectar every 20 minutes, and returned to feed on them accordingly. Rats and other more experimentally-accessible animals can be trained to do similar behavior while having their neural activity recorded.

Results from this kind of work suggest that rather than having the equivalent of a metronome in our brains—where, say, a group of neurons is continuously firing bursts at regular intervals—time is encoded by the interactions of neurons that are firing at different times. For example, the process starts with the arrival of one event creating a wave of neural activity. If another event arrives while that wave is still present, the second event’s own activity wave will be affected by the presence of the first. So, the second event’s activity wave will be slightly different than if it had occurred after the disappearance of the first wave. The response to the second event is therefore altered in a way that is dependent on its timing relative to the first.

Naturally, these kinds of mechanisms are highly dependent on the duration of the neural response, a property that is determined by a variety of factors ranging from ion channel characteristics to network structure. How (and if) any of these factors are changed during occasions where we feel a difference in our perception of time is still a mystery. It is hard to induce the sensation of time dilation or constriction in a laboratory setting, and even harder to get a rat to tell you when they’ve felt it. The Eagleman lab , however, did manage to strap computers to human subjects and have them perform cognitive tests while in a free-fall (a far more entertaining study than most undergrad psych majors are subjected to). The subjects reported a sense of slowed-down time but their performance on the cognitive tests showed no increase in their temporal resolution. They concluded from this that the feeling of having time to notice every detail doesn’t come because you are actually perceiving more information per second, but because you remember more of that perceived information. Emotionally-charged events (such as free-falling with a computer tied to your wrist) have a way of enhancing our ability to lay down memories. So, for the same reason that people can recall where they were when Kennedy got shot or you still know exactly what you were wearing when you had your first kiss, when we are in a life-threatening event we feel retrospectively that time had slowed down.

But if we want to get at neural mechanisms of temporal processing without having to push people off a cliff with a computer on their wrist AND an electrode in their head, we are going to have to work with animals. Rather than attempt to assess if lab rats feel the same perturbations in their perception of time during fear or boredom, we can try to understand the representation of temporal information by looking at cognitive behaviors that depend on it.  Specifically, we can look at timing through the lens of learning.

Classical Pavlovian conditioning says that if a stimulus (say, a bell ringing) that causes no instinctive response is repeatedly paired with a stimulus (like the presentation of food) that does cause a response (such as salivation), the initial stimulus presented alone can cause the response. And that is why Pavlov’s dogs salivate at the sound of a bell. Importantly, the ability to learn this association depends on how far apart the two stimuli are presented in time. If you ring a bell now and give the dog a steak in two days, he is unlikely to make the connection. So, a neural representation of time is necessary for this kind of training. The acceptable length of this inter-stimulus gap has been shown to vary depending on the stimulus pairings.

Interestingly, for a specific variation of this conditioning (eyeblink conditioning), we know that the gap time also varies across species. The eyeblink conditioned response comes about when a tone is presented right before the subject gets a puff of air in their eye. The airpuff makes the subject blink, and eventually they blink just from hearing the tone. In humans, the amount of time in between the tone and the airpuff that will result in the best learning of this association is around 800ms. In rabbits, it is around 500ms. And in rats, the few studies that have been done say 280ms. What this is suggesting is something like a difference in perspective across species. Humans, rabbits, and rats have distinct opinions on how far apart in time two events can be and still have an association between them. These species appear to be working on different timescales. For humans, with an average lifespan of ~80 years, things are a bit dilated. And compared to a rabbit (~10 year lifespan), the temporal processing of a rat (~2 years) is constricted. Of course this relationship between the timescale of associative learning and average lifespan hasn’t been studied extensively and factors as simple as brain size need to be controlled for. But it would be interesting to see if the trend holds for animals with impressive lifespans, like turtles or such short-lived creatures as fruit flies (of course the task would have to be re-designed, since the eyeblink response presupposes that the animal can blink). And if we do find that neural dynamics are scaled to align with lifespan, countless more questions would burst forth from this. What is different about the neural response? Does it stem from single cell properties or differences in network structure, or both? How is this encoded genetically and can it be altered during development? And perhaps most mysteriously, why does this mechanism exist? What could be the advantages of such a normalization of time processing across species?

Overall, the study of temporal information processing, much like physicists’ study of time itself, is proving to be conceptually and practically challenging. It is also producing some confusing results that, when understood properly, could provide a profound advancement in our understanding of the brain. That day is probably pretty far off, but as long as we all have fun trying to get there, it will come soon enough.

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One Comment

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  1. Hyoung-Ryul Kang / Nov 19 2012 9:51 am

    Cross-species stories like this always entice me (you may have heard about ‘billion heartbeats in a lifetime’, or Keliber’s law). In terms of ‘why’ such normalization exists, I would guess that the influence of experience or the environment. The first is that animals should extensively learn how their own movements affect environment, so they would have been trained at learning a particular time scale of their own movements’ effect. Larger animals should have learned contingency in longer timescale more because bigger arms operate in larger range, but have larger momentum compared to muscle power, resulting in later consequences of movement. Of course this would not be the whole story — rats’, rabbits’, and humans’ optimal timing vary too little compared to their body size to be explained by this.

    Also, the optimal timing may be an evolutionary adaptation. Smaller animals may have to worry more about smaller outside events, which would happen more frequently than bigger events. An interesting prediction from this hypothesis is that herbivores would have faster timescale than carnivores of similar size.

    In either case, for any learning mechanism tuned to contingencies in a particular timing to be beneficial, the contingencies of events in other timescales should be more random or more irrelevant to the animal who’s experiencing the contingency. The optimal tuning in this case may be described by Bayes’ rule, which weighs evidence that is more reliable and more consequential.

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