Using optimized voxel-based morphometry, we performed grey matter density analyses on 59 age-, sex- and intelligence-matched young adults with three distinct, progressive levels of musical training intensity or expertise Structural brain adaptations in musicians have been repeatedly demonstrated in areas involved in auditory perception and motor skills However, musical activities are not confined to auditory perception and motor performance, but are entangled with higher-order cognitive processes In consequence, neuronal systems involved in such higher-order processing may also be shaped by experience-driven plasticity We modelled expertise as a three-level regressor to study possible linear relationships of expertise with grey matter density The key finding of this study resides in a functional dissimilarity between areas exhibiting increase versus decrease of grey matter as a function of musical expertise Grey matter density increased with expertise in areas known for their involvement in higher-order cognitive processing: right fusiform gyrus (visual pattern recognition), right mid orbital gyrus (tonal sensitivity), left inferior frontal gyrus (syntactic processing, executive function, working memory), left intraparietal sulcus (visuo-motor coordination) and bilateral posterior cerebellar Crus II (executive function, working memory) and in auditory processing: left Heschl's gyrus Conversely, grey matter density decreased with expertise in bilateral perirolandic and striatal areas that are related to sensorimotor function, possibly reflecting high automation of motor skills Moreover, a multiple regression analysis evidenced that grey matter density in the right mid orbital area and the inferior frontal gyrus predicted accuracy in detecting fine-grained incongruities in tonal music

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Musical training intensity yields opposite effects on grey matter density in cognitive versus sensorimotor networks

Infrared neural stimulation (INS) has received considerable attention over the last few years. It provides an alternative method to artificially stimulate neurons without electrical current or the introduction of exogenous chromophores. One of the primary benefits of INS could be the improved spatial selectivity when compared with electrical stimulation. In the present study, we have evaluated the spatial selectivity of INS in the acutely damaged cochlea of guinea pigs and compared it to stimulation with acoustic tone pips in normal hearing animals. The radiation was delivered via a 200 μm-diameter optical fiber, which was inserted through a cochleostomy into the scala tympani of the basal cochlear turn. The stimulated section along the cochlear spiral ganglion was estimated from the neural responses recorded from the central nucleus of the inferior colliculus (ICC). ICC responses were recorded in response to cochlear INS using a multichannel penetrating electrode array. Spatial tuning curves were constructed from the responses. For INS, approximately 55% of the activation profiles showed a single maximum, ~22% had two maxima, and ~13% had multiple maxima. The remaining 10% of the profiles occurred at the limits of the electrode array and could not be classified. The majority of ICC spatial tuning curves indicated that the spread of activation evoked by optical stimuli is comparable to that produced by acoustic pips.

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Spread of cochlear excitation during stimulation with pulsed infrared radiation: inferior colliculus measurements

Using functional magnetic resonance imaging, we show for the first time that levels of musical expertise stepwise modulate higher order brain functioning. This suggests that degree of training intensity drives such cerebral plasticity. Participants (non-musicians, amateurs, and expert musicians) listened to a comprehensive set of specifically composed string quartets with hierarchically manipulated endings. In particular, we implemented 2 irregularities at musical closure that differed in salience but were both within the tonality of the piece (in-key). Behavioral sensitivity scores (d') of both transgressions perfectly separated participants according to their level of musical expertise. By contrasting brain responses to harmonic transgressions against regular endings, functional brain imaging data showed compelling evidence for stepwise modulation of brain responses by both violation strength and expertise level in a fronto-temporal network hosting universal functions of working memory and attention. Additional independent testing evidenced an advantage in visual working memory for the professionals, which could be predicted by musical training intensity. The here introduced findings of brain plasticity demonstrate the progressive impact of musical training on cognitive brain functions that may manifest well beyond the field of music processing.

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Degree of Musical Expertise Modulates Higher Order Brain Functioning

Working memory is a complex psychological construct referring to the temporary storage and active processing of information. We used functional connectivity brain network metrics quantifying local and global efficiency of information transfer for predicting individual variability in working memory performance on an n-back task in both young (n = 14) and older (n = 15) adults. Individual differences in both local and global efficiency during the working memory task were significant predictors of working memory performance in addition to age (and an interaction between age and global efficiency). Decreases in local efficiency during the working memory task were associated with better working memory performance in both age cohorts. In contrast, increases in global efficiency were associated with much better working performance for young participants; however, increases in global efficiency were associated with a slight decrease in working memory performance for older participants. Individual differences in local and global efficiency during resting-state sessions were not significant predictors of working memory performance. Significant group whole-brain functional network decreases in local efficiency also were observed during the working memory task compared to rest, whereas no significant differences were observed in network global efficiency. These results are discussed in relation to recently developed models of age-related differences in working memory.

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Changes in brain network efficiency and working memory performance in aging.

Using graph theory measures common to complex network analyses of neuroimaging data, the objective of this study was to explore the effects of increasing working memory processing load on functional brain network topology in a cohort of young adults. Measures of modularity in complex brain networks quantify how well a network is organized into densely interconnected communities. We investigated changes in both the large-scale modular organization of the functional brain network as a whole and regional changes in modular organization as demands on working memory increased from n = 1 to n = 2 on the standard n-back task. We further investigated the relationship between modular properties across working memory load conditions and behavioral performance. Our results showed that regional modular organization within the default mode and working memory circuits significantly changed from 1-back to 2-back task conditions. However, the regional modular organization was not associated with behavioral performance. Global measures of modular organization did not change with working memory load but were associated with individual variability in behavioral performance. These findings indicate that regional and global network properties are modulated by different aspects of working memory under increasing load conditions. These findings highlight the importance of assessing multiple features of functional brain network topology at both global and regional scales rather than focusing on a single network property.

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Changes in global and regional modularity associated with increasing working memory load.

The program d'plus calculates accuracy (sensitivity) and response-bias parameters using Signal Detection Theory. Choice Theory, and 'nonparametric' models. is is appropriate for data from one-interval, two- and three-interval forced-choice, same different, ABX, and oddity experimental paradigms.

Macmillan Na

Papers

d'plus: A program to calculate accuracy and bias measures from detection and discrimination data.