Sivumäärä -Number of pages 70Tiivistelmä -Abstract Working memory (WM) is at the core of any cognitive function as it is necessary for the integration of information over time. Despite WM's critical role in high-level cognitive functions, its implementation in the neural tissue is poorly understood. Preliminary studies on auditory WM show differences between linguistic and musical memory, leading to the speculation of specific neural networks encoding memory for music. Moreover, in neuroscience WM has not been studied in naturalistic listening conditions but rather in artificial settings (e.g., n-back and Sternberg tasks). Western tonal music provides naturally occurring motivic repetition and variation, recognizable units serving as WM trigger, thus allowing us to study the phenomenon of motif-tracking in the context of real music. Adopting a modern tango as stimulus, behavioural methods were used to identify the stimulus motifs and build a time-course predictor of WM neural responses. This predictor was then correlated with the participants' functional magnetic resonance imaging (fMRI) signal obtained during a continuous listening condition. Neural correlates related to the sensory processing of a set of musical features were filtered out from the brain responses to music to aid in the exclusive recruitment of executive processes of music-related WM. Correlational analysis revealed a widely distributed network of cortical and subcortical areas, predominantly right-lateralized, responding to the WM condition, including ventral and dorsal areas in the prefrontal cortex, basal ganglia, and limbic areas. Significant subcortical processing areas, active in response to the WM condition, were pruned with the removal of the acoustic content, suggesting these music-related perceptual processing areas might aid in the encoding and retrieval of WM. The pattern of dispersed neural activity indicates WM to emerge coherently from the integration of distributed neural activity spread out over different brain subsystems (motoric-, cognitive-and sensory-related areas of the brain).Asiasanat -Keywords working memory; cognitive neuroscience; music; musical motifs; functional magnetic resonance imaging ( Lashley was attempting to identify the locus of memory within the cortex, and, to do so, first trained rats to run mazes, and then removed various cortical regions. He allowed the animals to recover and tested the retention of the maze-running skills. To his surprise it was not possible to find a particular region corresponding to the ability to remember the way through a maze. Instead all the rats which had had cortex regions removed suffered some kind of impairment, and the extent of the impairment was roughly proportional to the amount of cortex taken off. Removing cortex damaged the motor and sensory capacities of the animals, and they would limp, hop, roll, or stagger, but somehow they always managed to traverse the maze. So far as memory 'as concerned, the cortex appeared to be equipotential, that is, with all regions of eq...

Musical expertise is visible both in the morphology and functionality of the brain. Recent research indicates that functional integration between multi-sensory, somato-motor, default-mode (DMN), and salience (SN) networks of the brain differentiates musicians from non-musicians during resting state. Here, we aimed at determining whether brain networks differentially exchange information in musicians as opposed to non-musicians during naturalistic music listening. Whole-brain graph-theory analyses were performed on participants' fMRI responses. Group-level differences revealed that musicians' primary hubs comprised cerebral and cerebellar sensorimotor regions whereas non-musicians' dominant hubs encompassed DMN-related regions. Community structure analyses of the key hubs revealed greater integration of motor and somatosensory homunculi representing the upper limbs and torso in musicians. Furthermore, musicians who started training at an earlier age exhibited greater centrality in the auditory cortex, and areas related to top-down processes, attention, emotion, somatosensory processing, and non-verbal processing of speech. We here reveal how brain networks organize themselves in a naturalistic music listening situation wherein musicians automatically engage neural networks that are action-based while non-musicians use those that are perception-based to process an incoming auditory stream. Hum Brain Mapp 38:2955-2970, 2017. © 2017 Wiley Periodicals, Inc.

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Music is often used to regulate emotions and mood. Typically, music conveys and induces emotions even when one does not attend to them. Studies on the neural substrates of musical emotions have, however, only examined brain activity when subjects have focused on the emotional content of the music. Here we address with functional magnetic resonance imaging (fMRI) the neural processing of happy, sad, and fearful music with a paradigm in which 56 subjects were instructed to either classify the emotions (explicit condition) or pay attention to the number of instruments playing (implicit condition) in 4-sec music clips. In the implicit vs.2 explicit condition, stimuli activated bilaterally the inferior parietal lobule, premotor cortex, caudate, and ventromedial frontal areas. The cortical dorsomedial prefrontal and occipital areas activated during explicit processing were those previously shown to be associated with the cognitive processing of music and emotion recognition and regulation. Moreover, happiness in music was associated with activity in the bilateral auditory cortex, left parahippocampal gyrus, and supplementary motor area, whereas the negative emotions of sadness and fear corresponded with activation of the left anterior cingulate and middle frontal gyrus and down-regulation of the orbitofrontal cortex. Our study demonstrates for the first time in healthy subjects the neural underpinnings of the implicit processing of brief musical emotions, particularly in frontoparietal, dorsolateral prefrontal, and striatal areas of the brain.

Musical training leads to sensory and motor neuroplastic changes in the human brain. Motivated by findings on enlarged corpus callosum in musicians and asymmetric somatomotor representation in string players, we investigated the relationship between musical training, callosal anatomy, and interhemispheric functional symmetry during music listening. Functional symmetry was increased in musicians compared to nonmusicians, and in keyboardists compared to string players. This increased functional symmetry was prominent in visual and motor brain networks. Callosal size did not significantly differ between groups except for the posterior callosum in musicians compared to nonmusicians. We conclude that the distinctive postural and kinematic symmetry in instrument playing cross-modally shapes information processing in sensory-motor cortical areas during music listening. This cross-modal plasticity suggests that motor training affects music perception.

Recent neural studies have established 3 limbic regions, namely the amygdala, the hippocampus, and the nucleus accumbens (NAc), as the fundamental nodes of the neural circuit responsible for experiencing musical emotions. Here we investigate how musical expertise modulates this circuit during continuous music listening. Eighteen nonmusicians and 21 musicians were measured with functional MRI (fMRI) while they listened to three 8-min long musical pieces representing different musical styles (tango nuevo, modern classical, and progressive rock). Functional connectivity maps of seeds belonging to the amygdala, hippocampus, and NAc were obtained for each participant. Group-level t tests revealed that, overall, musicians exhibited enhanced connectivity with the supplementary motor area (SMA), and with ventromedial and ventrolateral cerebral and cerebellar affective regions. On the contrary, nonmusicians displayed greater connectivity with subcortical regions only. We found the amygdala network previously associated with perceiving negative valence in music to be more tightly coupled in musicians than nonmusicians. Similarly, the hippocampal network previously related to tracking repeating musical motifs during continuous music listening was more coupled in musicians. The lack of group differences observed for right NAc connectivity reinforce the notion that the mesocorticolimbic reward network is not modulated by musical expertise, whereas left NAc connectivity results suggest that musical expertise intensifies the rewarding aspect of music selectively in the left hemisphere. In sum, during music listening musicians' deep perceptual and motoric knowledge of music increases the coupling between areas that process musical emotions with areas that process motor commands and pleasure.

Our sense of rhythm relies on orchestrated activity of several cerebral and cerebellar structures. Although functional connectivity studies have advanced our understanding of rhythm perception, this phenomenon has not been sufficiently studied as a function of musical training and beyond the General Linear Model (GLM) approach. Here, we studied pulse clarity processing during naturalistic music listening using a data-driven approach (independent component analysis; ICA). Participants' (18 musicians and 18 controls) functional magnetic resonance imaging (fMRI) responses were acquired while listening to music. A targeted region of interest (ROI) related to pulse clarity processing was defined, comprising auditory, somatomotor, basal ganglia, and cerebellar areas. The ICA decomposition was performed under different model orders, i.e., under a varying number of assumed independent sources, to avoid relying on prior model order assumptions. The components best predicted by a measure of the pulse clarity of the music, extracted computationally from the musical stimulus, were identified. Their corresponding spatial maps uncovered a network of auditory (perception) and motor (action) areas in an excitatory-inhibitory relationship at lower model orders, while mainly constrained to the auditory areas at higher model orders. Results revealed (a) a strengthened functional integration of action-perception networks associated with pulse clarity perception hidden from GLM analyses, and (b) group differences between musicians and non-musicians in pulse clarity processing, suggesting lifelong musical training as an important factor that may influence beat processing.

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