By: Viviana Caro, Annina Huhtala, Henry Lee, Andrew McNeill, Kate Schwarz
“Your memory is a monster; you forget – it doesn’t. It simply files things away”, wrote John Irving in his enticing novel A Prayer for Owen Meany. But how do memories form in the first place? And could the storyteller be right, does our brain store more than we can actively evoke?
According to current understanding in neuroscience, we are tracking our environment at a rate of milliseconds, whether it be what we see, touch, taste, smell, or hear. This process is fully automatic, mostly unconscious, and we can’t switch it off, as it has evolved to keep us safe. When we take a walk in a park, our brains keep calculating probabilities about what will happen next and compare the present moment to past experiences. When we hear footsteps from behind, we assume they belong to a runner, not to a hungry beast, and we keep calm. It seems that sensory data is not something we actively remember, but it’s stored in our long-term memory.
Neuroscientist Roberta Bianco is shedding light to these mechanisms with the help of music. In her recent study, she tested participants with soundtracks that included rapid, only milliseconds-long, sound sequences, to see whether people form long-term memories by just being exposed to auditory stimuli. The results? People detected these very brief patterns in novel music excerpts even after seven weeks of first hearing them. Bianco’s research confirms the idea that humans have the ability to build models from sensory input.
For researchers to better understand music perception, they have investigated how we encode and store music in our memory. Most forms of music have sequences and patterns that contain groups of notes and rhythms. Whenever we hear music, our auditory system does a great job at recognising these patterns and spotting any unexpected notes or chords. This effortless processing is called statistical learning, and it affects how we listen to and memorise music. We implicitly learn ‘normal’ sequences and patterns in music and build predictive models to estimate what will happen next and to notice irregularities.
In a study by Koelsch and colleagues, a group of participants, who were right handed non-musicians, passively listened to two chord progressions while the electrical activity in their brains was recorded using electroencephalography, EEG. The chord progressions ended in either an expected chord or unexpected chord. In the example below, the last chord of the second progression is a D flat major chord within a C major chord progression, which is unexpected. The graph shows that when a chord violates Western music theory rules, the brain notices.
In the experiment, participants’ brains showed a strong, negative response to the incongruent endings. The incongruent chord being a violation to the progression they expected.
In a recent study, Bianco and colleagues had pianists play a chord sequence without hearing a sound. The results showed that the incongruent endings activated temporal-frontal networks, which are brain areas associated with memory, even in silence – demonstrating that the brain stores a meticulous representation of patterns in memory. To build strong predictive models, our brain needs long term exposure to melodic patterns. Our brain encodes and groups the information into tiny ‘storage units’ or n-grams. The more we get exposed to a specific melodic pattern, the stronger and more salient the n-grams become, incurring in fast retrieval of information. Most memories decay when time passes, but Bianco’s work indicates that when models are reinforced, they last longer despite memory decay.
How precise are these predictive models then? To understand how reliable our memory really is, Bianco and colleagues exposed participants briefly to melodic patterns and then tested how well they could recall them. Participants could recognise some patterns, but in most cases the results were relatively poor. Bianco then tested reaction times to recurring melodies. Results showed that repeating patterns were recognised much faster. For Bianco, this lack of correlation between familiarity and reaction time indicates a dissociation between what we remember implicitly and the degree of which we can explicitly recall. It seems that our cautious brain preserves as much information as possible, even if that information is not relevant to the task at hand, and stocks it away in long-term memory. It does this to protect the capacity of our short term memory. If short term memory gets saturated, we are not able to adapt and control our behaviour in the present moment; therefore, storing information in the long-term memory is a way to economise cognitive resources.
For how long does our long-term memory store information? Bianco and her group set up an experiment where listeners heard both novel music excerpts which had planted in them musical sequences that they had heard seven weeks before. Incredibly, the participants recognised the previously heard patterns, which lasted a matter of milliseconds, even after seven weeks!
Bianco’s research in music helps us to gain more understanding of how memory works. It’s fascinating how hearing patterns, and pattern violations, can lead to the brain effortlessly constructing a model that is sensitive in detecting and identifying repeating structures. Of course, the implications of Bianco and her group’s research is far reaching. Understanding the way our brain preserves sequential information, and the way it deteriorates could be essential in the application of therapeutic medicine for those who have cognitive impairment.
Our brain is very much like a computer; it can create and update complicated models. In addition, it can pick up data actively and store it in our passive memory bank just in case we need it again. Our brain is also a bit like a jukebox player, that collects and archives all the songs and sounds from its environment. There is no disputing the facts however that this computer and jukebox give us the tools to make sense of our environment and make decisions about the world around us. After all, there is also some truth to how our memory is a monster, but there’s still a lot we don’t understand about this particular monster. Perhaps we should, ultimately, it’s our beautiful monster that we’re taking care of.
References:
Bianco, R., Harrison, P. M. C., Hu, M., Bolger, C., Picken, S., & Marcus, T. (2020). Long-term implicit memory for sequential auditory patterns in humans. BioRxiv, https://doi.org/10.1101/2020.02.14.949404.
Cowan, N. (2008). What are the differences between long-term, short-term, and working memory?. Progress in Brain Research, 169, 323-338.
Conway, C. M., & Pisoni, D. B. (2008). Neurocognitive basis of implicit learning of sequential structure and its relation to language processing. Annals of the New York Academy of Sciences, 1145, 113–131. https://doi.org/10.1196/annals.1416.009.
Daikoku, T. (2019). Statistical learning and the uncertainty of melody and bass line in music. PloS One, 14(12), E0226734.
Koelsch, S., Gunter, T. C., Wittfoth, M., & Sammler, D. (2005). Interaction between syntax processing in language and in music: An ERP study. Journal of Cognitive Neuroscience, 17(10), 1565–1577. https://doi.org/10.1162/089892905774597290.
Tillmann, B., Bigand, E., & Bharucha, J. J. (2000). Implicit Learning of Tonality: A Self-Organizing Approach. Psychological Review, 107(4), 885–913. https://doi.org/10.1037//0033-295X.107.4.885.