Moderate associations between BDNF Val66Met gene polymorphism, musical expertise, and mismatch negativity

Auditory predictive processing relies on a complex interaction between environmental, neurophysiological, and genetic factors. In this view, the mismatch negativity (MMN) and intensive training on a musical instrument for several years have been used for studying environment-driven neural adaptations in audition. In addition, brain-derived neurotrophic factor (BDNF) has been shown crucial for both the neurogenesis and the later adaptation of the auditory system. The functional single-nucleotide polymorphism (SNP) Val66Met (rs6265) in the BDNF gene can affect BDNF protein levels, which are involved in neurobiological and neurophysiological processes such as neurogenesis and neuronal plasticity. In this study, we hypothesised that genetic variation within the BDNF gene would be associated with different levels of neuroplasticity of the auditory cortex in 74 musically trained participants. To achieve this goal, musicians and non-musicians were recruited and divided in Val/Val and Met- (Val/Met and Met/Met) carriers and their brain activity was measured with magnetoencephalography (MEG) while they listened to a regular auditory sequence eliciting different types of prediction errors. MMN responses indexing those prediction errors were overall enhanced in Val/Val carriers who underwent intensive musical training, compared to Met-carriers and non-musicians with either genotype. Although this study calls for replications with larger samples, our results provide a first glimpse of the possible role of gene-regulated neurotrophic factors in the neural adaptations of automatic predictive processing in the auditory domain after long-term training.

Brain recognition of previously learned versus novel temporal sequences: a differential simultaneous processing

Memory for sequences is a central topic in neuroscience, and decades of studies have investigated the neural mechanisms underlying the coding of a wide array of sequences extended over time. Yet, little is known on the brain mechanisms underlying the recognition of previously memorized versus novel temporal sequences. Moreover, the differential brain processing of single items in an auditory temporal sequence compared to the whole superordinate sequence is not fully understood. In this magnetoencephalography (MEG) study, the items of the temporal sequence were independently linked to local and rapid (2–8 Hz) brain processing, while the whole sequence was associated with concurrent global and slower (0.1–1 Hz) processing involving a widespread network of sequentially active brain regions. Notably, the recognition of previously memorized temporal sequences was associated to stronger activity in the slow brain processing, while the novel sequences required a greater involvement of the faster brain processing. Overall, the results expand on well-known information flow from lower- to higher order brain regions. In fact, they reveal the differential involvement of slow and faster whole brain processing to recognize previously learned versus novel temporal information.

Enhanced mismatch negativity in harmonic compared to inharmonic sounds

Many natural sounds have frequency spectra composed of integer multiples of a fundamental frequency. This property, known as harmonicity, plays an important role in auditory information processing. However, the extent to which harmonicity influences the processing of sound features beyond pitch is still unclear. This is interesting because harmonic sounds have lower information entropy than inharmonic sounds. According to predictive processing accounts of perception, this property could produce more salient neural responses due to the brain's weighting of sensory signals according to their uncertainty. In the present study, we used electroencephalography to investigate brain responses to harmonic and inharmonic sounds commonly occurring in music: Piano tones and hi‐hat cymbal sounds. In a multifeature oddball paradigm, we measured mismatch negativity (MMN) and P3a responses to timbre, intensity, and location deviants in listeners with and without congenital amusia—an impairment of pitch processing. As hypothesized, we observed larger amplitudes and earlier latencies (for both MMN and P3a) in harmonic compared with inharmonic sounds. These harmonicity effects were modulated by sound feature. Moreover, the difference in P3a latency between harmonic and inharmonic sounds was larger for controls than amusics. We propose an explanation of these results based on predictive coding and discuss the relationship between harmonicity, information entropy, and precision weighting of prediction errors.

Rapid encoding of musical tones discovered in whole-brain connectivity

Information encoding has received a wide neuroscientific attention, but the underlying rapid spatiotemporal brain dynamics remain largely unknown. Here, we investigated the rapid brain mechanisms for encoding of sounds forming a complex temporal sequence. Specifically, we used magnetoencephalography (MEG) to record the brain activity of 68 participants while they listened to a highly structured musical prelude. Functional connectivity analyses performed using phase synchronisation and graph theoretical measures showed a large network of brain areas recruited during encoding of sounds, comprising primary and secondary auditory cortices, frontal operculum, insula, hippocampus and basal ganglia. Moreover, our results highlighted the rapid transition of brain activity from primary auditory cortex to higher order association areas including insula and superior temporal pole within a whole-brain network, occurring during the first 220 ms of the encoding process. Further, we discovered that individual differences along cognitive abilities and musicianship modulated the degree centrality of the brain areas implicated in the encoding process. Indeed, participants with higher musical expertise presented a stronger centrality of superior temporal gyrus and insula, while individuals with high working memory abilities showed a stronger centrality of frontal operculum. In conclusion, our study revealed the rapid unfolding of brain network dynamics responsible for the encoding of sounds and their relationship with individual differences, showing a complex picture which extends beyond the well-known involvement of auditory areas. Indeed, our results expanded our understanding of the general mechanisms underlying auditory pattern encoding in the human brain.

Applying Spike-density component analysis for high-accuracy auditory event-related potentials in children

OBJECTIVE

Overlapping neurophysiological signals are the main obstacle preventing from using cortical auditory event-related potentials (AEPs) in clinical settings. Children AEPs are particularly affected by this problem, as their cerebral cortex is still maturing. To overcome this problem, we applied a new version of Spike-density Component Analysis (SCA), an analysis method recently developed, to isolate with high accuracy the neural components of auditory responses of 8-year-old children.

METHODS

Electroencephalography was used with 33 children to record AEPs to auditory stimuli varying in spectrotemporal features. Three different analysis approaches were adopted: the standard AEP analysis procedure, SCA with template-match (SCA-TM), and SCA with half-split average consistency (SCA-HSAC).

RESULTS

SCA-HSAC most successfully allowed the extraction of AEPs for each child, revealing that the most consistent components were P1 and N2. An immature N1 component was also detected.

CONCLUSION

Superior accuracy in isolating neural components at the individual level was demonstrated for SCA-HSAC over other SCA approaches even for children AEPs.

SIGNIFICANCE

Reliable methods of extraction of neurophysiological signals at the individual level are crucial for the application of cortical AEPs for routine diagnostic exams in clinical settings both in children and adults.

Brain predictive coding processes are associated to COMT gene Val158Met polymorphism

Predicting events in the ever-changing environment is a fundamental survival function intrinsic to the physiology of sensory systems, whose efficiency varies among the population. Even though it is established that a major source of such variations is genetic heritage, there are no studies tracking down auditory predicting processes to genetic mutations. Thus, we examined the neurophysiological responses to deviant stimuli recorded with magnetoencephalography (MEG) in 108 healthy participants carrying different variants of Val158Met single-nucleotide polymorphism (SNP) within the catechol-O-methyltransferase (COMT) gene, responsible for the majority of catecholamines degradation in the prefrontal cortex. Our results showed significant amplitude enhancement of prediction error responses originating from the inferior frontal gyrus, superior and middle temporal cortices in heterozygous genotype carriers (Val/Met) vs homozygous (Val/Val and Met/Met) carriers. Integrating neurophysiology and genetics, this study shows how the neural mechanisms underlying optimal deviant detection vary according to the gene-determined cathecolamine levels in the brain.

Decomposing neural responses to melodic surprise in musicians and non-musicians: Evidence for a hierarchy of predictions in the auditory system

Neural responses to auditory surprise are typically studied with highly unexpected, disruptive sounds. Consequently, little is known about auditory prediction in everyday contexts that are characterized by fine-grained, non-disruptive fluctuations of auditory surprise. To address this issue, we used IDyOM, a computational model of auditory expectation, to obtain continuous surprise estimates for a set of newly composed melodies. Our main goal was to assess whether the neural correlates of non-disruptive surprising sounds in a musical context are affected by musical expertise. Using magnetoencephalography (MEG), auditory responses were recorded from musicians and non-musicians while they listened to the melodies. Consistent with a previous study, the amplitude of the N1m component increased with higher levels of computationally estimated surprise. This effect, however, was not different between the two groups. Further analyses offered an explanation for this finding: Pitch interval size itself, rather than probabilistic prediction, was responsible for the modulation of the N1m, thus pointing to low-level sensory adaptation as the underlying mechanism. In turn, the formation of auditory regularities and proper probabilistic prediction were reflected in later components: The mismatch negativity (MMNm) and the P3am, respectively. Overall, our findings reveal a hierarchy of expectations in the auditory system and highlight the need to properly account for sensory adaptation in research addressing statistical learning.

Interaction between DRD2 variation and sound environment on mood and emotion-related brain activity

Sounds, like music and noise, are capable of reliably affecting individuals' mood and emotions. However, these effects are highly variable across individuals. A putative source of variability is genetic background. Here we explored the interaction between a functional polymorphism of the dopamine D2 receptor gene (DRD2 rs1076560, G>T, previously associated with the relative expression of D2S/L isoforms) and sound environment on mood and emotion-related brain activity. Thirty-eight healthy subjects were genotyped for DRD2 rs1076560 (G/G=26; G/T=12) and underwent functional magnetic resonance imaging (fMRI) during performance of an implicit emotion-processing task while listening to music or noise. Individual variation in mood induction was assessed before and after the task. Results showed mood improvement after music exposure in DRD2GG subjects and mood deterioration after noise exposure in GT subjects. Moreover, the music, as opposed to noise environment, decreased the striatal activity of GT subjects as well as the prefrontal activity of GG subjects while processing emotional faces. These findings suggest that genetic variability of dopamine receptors affects sound environment modulations of mood and emotion processing.

Within- and between-session replicability of cognitive brain processes: An MEG study with an N-back task

In the vast majority of electrophysiological studies on cognition, participants are only measured once during a single experimental session. The dearth of studies on test-retest reliability in magnetoencephalography (MEG) within and across experimental sessions is a preventing factor for longitudinal designs, imaging genetics studies, and clinical applications. From the recorded signals, it is not straightforward to draw robust and steady indices of brain activity that could directly be used in exploring behavioral effects or genetic associations. To study the variations in markers associated with cognitive functions, we extracted three event-related field (ERF) features from time-locked global field power (GFP) epochs using MEG while participants were performing a numerical N-back task in four consecutive measurements conducted during two different days separated by two weeks. We demonstrate that the latency of the M170, a neural correlate associated with cognitive functions such as working memory, was a stable parameter and did not show significant variations over time. In addition, the M170 peak amplitude and the mean amplitude of late positive component (LPP) also expressed moderate-to-strong reliability across multiple measures over time over many sensor spaces and between participants. The M170 amplitude varied more significantly between the measurements in some conditions but showed consistency over the participants over time. In addition we demonstrated significant correlation with the M170 and LPP parameters and cognitive load. The results are in line with the literature showing less within-subject fluctuation for the latency parameters and more consistency in between-subject comparisons for amplitude based features. The within-subject consistency was apparent also with longer delays between the measurements. We suggest that with a few limitations the ERF features show sufficient reliability and stability for longitudinal research designs and clinical applications for cognitive functions in single as well as cross-subject designs.

Event-related brain responses while listening to entire pieces of music

Brain responses to discrete short sounds have been studied intensively using the event-related potential (ERP) method, in which the electroencephalogram (EEG) signal is divided into epochs time-locked to stimuli of interest. Here we introduce and apply a novel technique which enables one to isolate ERPs in human elicited by continuous music. The ERPs were recorded during listening to a Tango Nuevo piece, a deep techno track and an acoustic lullaby. Acoustic features related to timbre, harmony, and dynamics of the audio signal were computationally extracted from the musical pieces. Negative deflation occurring around 100 milliseconds after the stimulus onset (N100) and positive deflation occurring around 200 milliseconds after the stimulus onset (P200) ERP responses to peak changes in the acoustic features were distinguishable and were often largest for Tango Nuevo. In addition to large changes in these musical features, long phases of low values that precede a rapid increase - and that we will call Preceding Low-Feature Phases - followed by a rapid increase enhanced the amplitudes of N100 and P200 responses. These ERP responses resembled those to simpler sounds, making it possible to utilize the tradition of ERP research with naturalistic paradigms.

The development of aesthetic responses to music and their underlying neural and psychological mechanisms

In the field of psychology, the first studies in experimental aesthetics were conducted approximately 140 years ago. Since then, research has mainly concentrated on aesthetic responses to visual art. Both the aesthetic experience of music and, especially, its development have received rather limited attention. Moreover, until now, very little attention has been paid to the investigation of the aesthetic experience of music using neuroscientific methods. Aesthetic experiences are multidimensional and include inter alia sensory, perceptual, affective, and cognitive components. Aesthetic processes are usually experienced as pleasing and rewarding and are, thus, important and valuable experiences for many people. Because of their multidimensional nature, these processes employ several brain areas. In the present review, we examine important psychological and neural mechanisms that are believed to contribute to the development of aesthetic experiences of music. We also discuss relevant research findings. With the present review, we wish to provoke further discussion and possible future investigations as we consider the investigation of aesthetic experiences to be important both scientifically and with respect to potential clinical applications.

Practice strategies of musicians modulate neural processing and the learning of sound-patterns

Previous studies suggest that pre-attentive auditory processing of musicians differs depending on the strategies used in music practicing and performance. This study aimed at systematically revealing whether there are differences in auditory processing between musicians preferring and not-preferring aural strategies such as improvising, playing by ear, and rehearsing by listening to records. Participants were assigned to aural and non-aural groups according to how much they employ aural strategies, as determined by a questionnaire. The change-related mismatch negativity (MMN) component of event-related brain potentials (ERPs) was used to probe pre-attentive neural discrimination of simple sound features and melody-like patterns. Further, the musicians' behavioral accuracy in sound perception was tested with a discrimination task and the AMMA musicality test. The data indicate that practice strategies do not affect musicians' pre-attentive neural discrimination of changes in simple sound features but do modulate the speed of neural discrimination of interval and contour changes within melody-like patterns. Moreover, while the aural and non-aural groups did not differ in their initial neural accuracy for discriminating melody-like patterns, they differed after a focused training session. A correlation between behavioral and neural measures was also obtained. Taken together, these results suggest that auditory processing of musicians who prefer aural practice strategies differs in melodic contour and interval processing and perceptual learning, rather than in simple sound processing, in comparison to musicians preferring other practice strategies.

[Effects of noise on cortical mechanisms involved in the development of linguistic sounds]

So far studies about noise effects on speech perception have been focused on the development of hearing loss and other related pathologies. However, behavioral findings indicate that speech perception and intelligibility are disrupted in presence of noise in certain clinical groups in a way that is unpredictable on the basis of the audiogram performed in silence. This observation suggests that even soft noise can modify the cerebral mechanisms underlying speech information processing. Confirming the behavioral results, electric and magnetic brain measurements showed that noise presented to healthy subjects decreases the amplitude and increases the latency of brain responses to speech sounds. Recently, further experimental data allowed us to have a deeper knowledge of the neural mechanisms interventing in difficult listening conditions. In particolar, speech sounds presented in noisy background evoke bioelectric responses in neural populations located in the right cerebral hemisphere, that otherwise would not be activated. These findings can in future contribute to unveal new aspects of the noise pathology and its assessment in an early pre-clinical stage.