A team of researchers from UCLA has created a model of how the brain could potentially tell time and has also tested a part of the model on human subjects.
“If you toss a pebble into a lake,” he explained, “the ripples of water produced by the pebble’s impact act like a signature of the pebble’s entry time. The farther the ripples travel the more time has passed.
“We propose that a similar process takes place in the brain that allows it to track time,” he added. “Every time the brain processes a sensory event, such as a sound or flash of light, it triggers a cascade of reactions between brain cells and their connections. Each reaction leaves a signature that enables the brain-cell network to encode time.”
The UCLA team used a computer model to test this theory. By simulating a network of interconnected brain cells in which each connection changed over time in response to stimuli, they were able to show that the network could tell time.
Their simulations indicated that a specific event is encoded within the context of events that precede it. In other words, if one could measure the response of many neurons in the brain to a tone or a flash of light, the response would not only reveal the nature of the event, but the other events that preceded it and when they occurred.
The UCLA team tested the model by asking research volunteers in the study to judge the interval between two auditory tones under a variety of different conditions. The researchers found that volunteers’ sense of timing was impaired when the interval was randomly preceded by a “distracter” tone.
“Our results suggest that the timing mechanisms that underlie our ability to recognize speech and enjoy music are distributed throughout the brain, and do not resemble the conventional clocks we wear on our wrists,” said Buonomano.
Here’s the actual abstract of the Feb 1st Neuron article:
Decisions based on the timing of sensory events are fundamental to sensory processing. However, the mechanisms by which the brain measures time over ranges of milliseconds to seconds remain unclear. The dominant model of temporal processing proposes that an oscillator emits events that are integrated to provide a linear metric of time. We examine an alternate model in which cortical networks are inherently able to tell time as a result of time-dependent changes in network state. Using computer simulations we show that within this framework, there is no linear metric of time, and that a given interval is encoded in the context of preceding events. Human psychophysical studies were used to examine the predictions of the model. Our results provide theoretical and experimental evidence that, for short intervals, there is no linear metric of time, and that time may be encoded in the high-dimensional state of local neural networks.
This journal article very much focuses on the dynamics of a generic cortical networks. If you’re interested in the hypothesized brain areas that seem to contribute time telling this review, entitled What Makes Us Tick? Functional and Neural Mechanisms of Interval Timing by Catalin V. Buhusi & Warren H. Meck might, be for you:
Time is a fundamental dimension of life. It is crucial for decisions about quantity, speed of movement and rate of return, as well as for motor control in walking, speech, playing or appreciating music, and participating in sports. Traditionally, the way in which time is perceived, represented and estimated has been explained using a pacemaker-accumulator model that is not only straightforward, but also surprisingly powerful in explaining behavioural and biological data. However, recent advances have challenged this traditional view. It is now proposed that the brain represents time in a distributed manner and tells the time by detecting the coincidental activation of different neural populations.