Recollection of events triggered by musical stimulus
Music-evoked autobiographical memories (MEAMs) refer to the recollection of personal experiences or past events that are triggered when hearing music or some musical stimulus. While there is a degree of inter-individual variation in music listening patterns and evoked responses, MEAMs are generally triggered in response to a wide variety of music, often popular or classical genres, and are estimated to occur in the range from one to a few times per day, regardless of formal instrumental practice or music lessons. Consistent with the hallmarks of general autobiographical memories, everyday MEAMs similarly exhibit a recency effect, a reminiscence bump (later discussed in the section “The reminiscence bump”), and childhood amnesia, encoding autobiographical knowledge at several levels of specificity and across several common social and situational contexts. The phenomenon of MEAMs has been widely studied in the fields of psychology, neuroscience, and musicology. In recent years, the subject has garnered significant interest from researchers and the general public alike due to music's capacity to evoke vivid, emotional, and episodically rich autobiographical memories.
History.
The relationship between music and memory has long been recognized, with music's ability to elicit emotional responses and trigger memories dating back to ancient times. In ancient Graeco-Roman society, for instance, musical memory formed a fundamental part of social, cultural, and political life.
The scientific study of music's deep correlation with autobiographical memories gained prominence in the early 2000s, when the term “music-evoked autobiographical memory” was coined by cognitive neuroscientist Petr Janata and colleagues, who first described the phenomenon in healthy undergraduate students. At this time, Janata conducted a pioneering experiment in which his team developed a novel approach to studying autobiographical memory using a range of popular music. Analyses indicated that 30% of the presented songs evoked autobiographical memories, demonstrating the paradigm's efficacy and justifying its use in subsequent neuroimaging work.
Since Janata's work, numerous studies have contributed to the understanding of MEAMs. Researchers have investigated factors that influence the formation and retrieval of MEAMs, from the characteristics of the music stimulus to its personal relevance, with many contemporary studies citing his work.
Recording techniques.
fMRI.
Functional magnetic resonance imaging (fMRI) is a powerful neuroimaging technique that has been instrumental in advancing our understanding of MEAMs. By utilizing fMRI, researchers aim to uncover the neural mechanisms underlying this unique experience and shed light on the intricate interplay between music, memory, and emotions.
In studies exploring MEAMs, participants are typically placed inside an MRI scanner while they listen to music that holds personal significance to them. The fMRI scanner measures the blood oxygen level-dependent (BOLD) signals, which provide an indirect measure of neural activity. Researchers analyze the fMRI data to identify brain regions that exhibit increased activity during MEAM retrieval compared to control conditions. These regions are believed to play crucial roles in memory processing, emotional responses, and self-referential processing.
Beyond fMRI measurements, studies on MEAMs often incorporate additional behavioral measures such as questionnaires or interviews to capture the subjective experience and vividness of the retrieved memories. These measures help validate the connection between music and autobiographical memories and provide a richer understanding of the phenomenon.
Since fMRI measures blood oxygenation level-dependent signals, this showcases an indirect line to neural activity, which can be seen as a limitation to this recording system.
EEG.
Electroencephalography (EEG) has emerged as a valuable tool in the investigation of MEAMs. EEG allows researchers to examine the temporal dynamics of neural activity associated with MEAMs, providing insights into the underlying cognitive and emotional processes.
In studies focusing on MEAMs, participants wear a cap embedded with multiple electrodes that record electrical brain activity. EEG captures the millisecond-level fluctuations in neural oscillations, revealing the brain's real-time response to MEAMs. Researchers analyze the EEG data to identify specific patterns of brain activity, such as event-related potentials (ERPs) and oscillatory activity.
ERPs, derived from averaging the EEG signal time-locked to specific events, offer insights into the brain's response to musical stimuli. In MEAM research, researchers examine ERPs related to memory retrieval processes, such as the P300 component, which reflects attention allocation and memory updating. By comparing ERPs between music-evoked and control conditions, researchers gain insights into the neural mechanisms underlying MEAMs.
Oscillatory activity, as measured by EEG, provides further understanding of the neural dynamics during MEAMs. Researchers investigate changes in frequency bands, such as alpha, beta, and theta, associated with memory processes and emotional responses. For example, enhanced theta activity has been observed during successful memory retrieval, suggesting its involvement in encoding and recollection of music-evoked autobiographical memories.
EEGs have a hard time localizing the signals they receive from the brain which brings forth a limitation of being unable to capture information in a precise manner.
Deep learning architecture.
Deep learning has also been a tool that is used to study MEAMs. Deep learning, a subset of machine learning, involves training neural networks with multiple layers to automatically learn and extract complex patterns from data. In the context of MEAMs, deep learning architectures are used to analyze and model the relationships between music and autobiographical memories, providing valuable insights into the underlying mechanisms.
Researchers employ deep learning architectures, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs), to process and analyze musical features and associated autobiographical memory data. CNNs excel at capturing spatial patterns and are commonly used to analyze spectrograms or other representations of music. By training CNNs on large datasets of music and associated memory information, researchers can uncover patterns and correlations that may be indicative of MEAMs.
RNNs, on the other hand, are specifically designed to model sequential data and are well-suited for analyzing the temporal aspects of music and memory. Researchers use RNNs to capture the dependencies and dynamics between musical elements and autobiographical memories. By training RNNs on sequences of music and associated memory descriptions, researchers can generate predictions and gain insights into the temporal dynamics of MEAMs.
Deep learning architectures in MEAM research are not limited to CNNs and RNNs alone. Variants such as long short-term memory (LSTM) networks and generative models, such as generative adversarial networks (GANs), are also employed. LSTM networks are capable of capturing long-range dependencies and are particularly useful when modeling the temporal aspects of music-evoked memories. GANs, on the other hand, can generate new music or memory samples based on learned patterns, allowing researchers to explore the generative aspects of MEAMs.
Memory type.
In general, musical memory can be split into both explicit and implicit memory systems. “Implicit” memory refers to the unconscious, automatic storage of information, encompassing procedural memories and motor skill learning. In the context of music, implicit memory accounts for the ability to play an instrument or sing a song without consciously bringing into memory how to play it. This differs from explicit memory, a declarative memory consisting of conscious recall of a specific piece of information. Explicit memory can be further split into episodic and semantic memory. Semantic memories are stored general knowledge and facts, accounting for a general sense of familiarity of music. In contrast, episodic memories are memory for the associated context of an event, accounting for the time, place, people, emotions, and personal experiences surrounding a musical experience. By these definitions, MEAMs are typically characterized as an explicit and episodic memory type. The distinct neural activation patterns associated with semantic vs episodic memories, as evidenced by a fMRI study looking into the neural correlates of music memory, helps explain some of the observed characteristics of MEAMs. This is further discussed in the next section “Brain regions involved“.
Brain regions involved.
The act of listening to music elicits a wide range of neural responses and engages various cognitive processes, encompassing motor, auditory, emotional, memory, and reward-related functions within the brain. Processing of musical qualities in general such as timbre, tonality, and rhythm are associated with activation in temporal (superior and middle temporal gyri, insula), frontal (superior and middle frontal gyri, cingulate gyrus, precentral gyrus), parietal (inferior parietal gyrus, precuneus, postcentral gyrus), and cerebellar regions. In terms of forming and retrieving MEAMs specifically, the medial prefrontal cortex, encompassing both dorsal and ventral regions, emerges as a central hub. The dorsal MPFC responds to the autobiographical salience of music excerpts and tracks their movements through tonal space. This region exhibited a familiarity effect and showed properties of associating structural aspects of retrieval cues with episodic memories. Additionally, rostral and ventral aspects of the MPFC also exhibited responses related to familiarity, autobiographical salience, and positive valence.
The involvement of prefrontal regions in MEAMs was not limited to the MPFC. Both lateral and medial prefrontal areas showed responses, suggesting the usage of multiple memory retrieval processes to assemble semantic and episodic content into a recollective experience with an affective component. Also, the ventrolateral prefrontal cortex (VLPFC) has been implicated in processing musical structure, integrating musical events into syntactically coherent sequences.
Retrieval mechanisms.
Involuntary vs voluntary retrieval.
MEAMs can occur in a variety of settings, both through deliberate and spontaneous recall. There has been some debate in the classification of MEAMs as voluntary or involuntary autobiographical memories. Voluntary autobiographical memories are “personal memories that follow a controlled, strategic retrieval process”. Involuntary autobiographical memories are “memories of personal events that come to mind spontaneously-that is, with no conscious initiation of the retrieval process”. They are considered to be more specific, retrieved significantly faster, and accompanied by a stronger emotional response than voluntary autobiographical memories.
Current research supports the idea that MEAMs aligns more often with the latter memory retrieval mechanism, as MEAMs are similarly more specific, retrieved faster, and are accompanied by greater emotional impact than memories retrieved in silence. A recent diary study also provides support, with a higher proportion of MEAMs being reported by participants to be involuntarily rather than deliberately retrieved. However, as 20% of participants in this study used deliberate recall, involuntary retrieval is not an exclusive feature of MEAMs.
Situational context.
Involuntary memories of past events are context-sensitive, helping to explain the situational context in which MEAMs are most often evoked. Previous evidence demonstrates that involuntary memories are more likely to come back during cognitively undemanding activities, in which our mind is free to wander to thoughts about our past. These types of activities match almost perfectly with those recorded in a diary study, in which MEAMs typically occurred during routine tasks that were non-demanding on attention, such as driving, traveling, housework, and relaxing. This further introduces MEAMs as a form of music-evoked mind-wandering due to the similar type of tasks that are reported to accompany mind-wandering and daydreaming.
Memory reactivation through music.
Eight psychological mechanisms have been proposed that explain how music elicits emotions. These mechanisms include brain stem reflex (arousal or surprise caused by sudden, loud, or dissonant sounds), rhythmic entrainment (increased arousal or social connectedness through synchronization with the music's rhythm), evaluative conditioning (associations formed between music and other stimuli), emotional contagion (induction of emotions expressed in the music), visual imagery (feelings of pleasure or deep relaxation evoked by mental imagery), evocation of episodic memories (MEAMs), aesthetic judgment (such as awe or wonder), and musical expectancy and predictions. Musical expectancies and predictions are particularly relevant as they not only evoke strong emotions but also play a central role in memory processing. When listening to music, expectations based on previous experiences regarding melody, harmony, and rhythm influence our emotional reactions, actions, and musical learning. These cognitive processes associated with music facilitate the retrieval of autobiographical memories.
Music can also evoke memories through specific individual associations. For example, certain songs become connected to specific events, life periods, or relationships. This effect is reinforced by the fact that people tend to revisit their preferred music more often than other cultural products. The likelihood of familiar music evoking memories may be attributed to its ability to activate an associative network of autobiographical memories, leading to spreading activation that facilitates memory retrieval.
Moreover, music plays a significant role in the formation of both social and personal identity. Certain music becomes strongly associated with essential aspects of an individual's identity and can enhance the retrieval of autobiographical memories through increased self-reference or by triggering specific memories that are central to one's identity.
Autobiographical memory cues.
Memory cues, or memory aids, are internal patterns of thinking or external stimuli that facilitate the retrieval of stored information. Memory cues have practical applications in various domains, including education, where they aid in processing complex information, as well as in rehabilitation programs to assist individuals with memory impairments. Thus, a primary goal in these efforts is choosing