Blog: Neuroscientist’s create mathematical model for how the brain keeps a beat
For some, keeping a beat is as natural as breathing, whereas for others, the notion of producing and keeping a beat may seem an impossibility.
On Thursday this week, researchers announced a mathematical model that describes how the brain may keep a musical beat. The paper, published in PLOS Computational Biology, is a joint effort between Amitabha Bose of New Jersey Institute of Technology; as well as Aine Byrne and John Rinzel of New York University.
The researchers developed a neuromechanistic framework featuring computational version of a neuron that is capable of learning a beat. The beat generator neuron — or BGN, as the scientists call it — learns a beat from a stimulus frequency and then oscillates at that frequency without the presence of the stimulus frequency.
The BGN does this by learning about the period of the stimulus sound — the length of time required before the sound wave repeats itself — and thus modify its own oscillations to match that of the stimulus frequency.
This model relies on the idea of a gamma counter. Gama rhythms are those in the range of 30 to 90 Hz. The scientists in this study utilized waves at 40 Hz to count two different things important to their model: the gamma cycles between the onset of the stimulus sound and between the spikes of the BGN. Using an error-correction algorithm, the BGN is able to use the difference between how often it spikes, compared to the stimulus spikes, to learn the beat of the stimulus.
Using this approach, the BGN was able to learn isochronous beats in the frequency range of .5 Hz to 8 Hz, which the researchers say is “relevant for beat generation and perception.”
Beat perception and beat generation are related but different ideas, and the BGN is an example of the latter.
“Beat perception involves listening to an external sound source as a precursor to trying to discern and synchronize with the beat,” the paper says. “Alternatively, we might ask how do we (humans) learn and then later reproduce a beat in the absence of any external cues.”
This model is simple in that it describes only one aspect of beat generation — at the level of a single computational unit, a model of a neuron. However, the usefulness of understanding beat generation within the brain shouldn’t be discounted. Beat generation is an example of the brain’s more general ability to learn and reproduce periodic rhythms. Someday, perhaps, such a model may prove useful for a neurological disorders characterized or affected by abnormalities of this capacity.