Can rhythm-mediated reward boost learning, memory, and social connection? Perspectives for future research.

Studies of rhythm processing and of reward have progressed separately, with little connection between the two. However, consistent links between rhythm and reward are beginning to surface, with research suggesting that synchronization to rhythm is rewarding, and that this rewarding element may in turn also boost this synchronization. The current mini review shows that the combined study of rhythm and reward can be beneficial to better understand their independent and combined roles across two central aspects of cognition: 1) learning and memory, and 2) social connection and interpersonal synchronization; which have so far been studied largely independently. From this basis, it is discussed how connections between rhythm and reward can be applied to learning and memory and social connection across different populations, taking into account individual differences, clinical populations, human development, and animal research. Future research will need to consider the rewarding nature of rhythm, and that rhythm can in turn boost reward, potentially enhancing other cognitive and social processes.

Musical genre-dependent behavioural and EEG signatures of action planning. A comparison between classical and jazz pianists.

It is well established that musical training induces sensorimotor plasticity. However, there are remarkable differences in how musicians train for proficient stage performance. The present EEG study outlines for the first time clear-cut neurobiological differences between classical and jazz musicians at high and low levels of action planning, revealing genre-specific cognitive strategies adopted in production. Pianists imitated chord progressions without sound that were manipulated in terms of harmony and context length to assess high-level planning of sequence-structure, and in terms of the manner of playing to assess low-level parameter specification of single acts. Jazz pianists revised incongruent harmonies faster as revealed by an earlier reprogramming negativity and beta power decrease, hence neutralising response costs, albeit at the expense of a higher number of manner errors. Classical pianists in turn experienced more conflict during incongruent harmony, as shown by theta power increase, but were more ready to implement the required manner of playing, as indicated by higher accuracy and beta power decrease. These findings demonstrate that specific demands and action focus of training lead to differential weighting of hierarchical action planning. This suggests different enduring markers impressed in the brain when a musician practices one or the other style.

Neural networks for harmonic structure in music perception and action.

The ability to predict upcoming structured events based on long-term knowledge and contextual priors is a fundamental principle of human cognition. Tonal music triggers predictive processes based on structural properties of harmony, i.e., regularities defining the arrangement of chords into well-formed musical sequences. While the neural architecture of structure-based predictions during music perception is well described, little is known about the neural networks for analogous predictions in musical actions and how they relate to auditory perception. To fill this gap, expert pianists were presented with harmonically congruent or incongruent chord progressions, either as musical actions (photos of a hand playing chords) that they were required to watch and imitate without sound, or in an auditory format that they listened to without playing. By combining task-based functional magnetic resonance imaging (fMRI) with functional connectivity at rest, we identified distinct sub-regions in right inferior frontal gyrus (rIFG) interconnected with parietal and temporal areas for processing action and audio sequences, respectively. We argue that the differential contribution of parietal and temporal areas is tied to motoric and auditory long-term representations of harmonic regularities that dynamically interact with computations in rIFG. Parsing of the structural dependencies in rIFG is co-determined by both stimulus- or task-demands. In line with contemporary models of prefrontal cortex organization and dual stream models of visual-spatial and auditory processing, we show that the processing of musical harmony is a network capacity with dissociated dorsal and ventral motor and auditory circuits, which both provide the infrastructure for predictive mechanisms optimising action and perception performance.

Computer-generated holograms for optical neural networks: on-axis versus off-axis geometry.

For optical neural networks implemented with computer-generated planar holograms the spacebandwidth product of the hologram is a major consideration. Off-axis holograms can be fabricated with a single binary transmission mask. However, the carrier frequency greatly increases the space-bandwidth product. On axis-holograms use a lower space-bandwidth product to encode interconnections but require a multilevel phase transmission profile. Significant errors can result during the fabrication of multilevel phase structures. With modification of the on-axis geometry the effects of the fabrication errors can be reduced while a lower space-bandwidth product per interconnection is retained. The interconnection accuracy, the diffraction efficiency, the and sensitivity to fabrication errors are compared for the off-axis, the on-axis, and the modified on-axis diffraction geometries.

Design and analysis of fixed planar holographic interconnects for optical neural networks.

A neural-network architecture of multifaceted planar interconnection holograms and optoelectronic neurons is analyzed. Various computer-generated hologram techniques are analyzed and tested for their ability to produce an interconnection hologram with high-accuracy interconnects and high diffraction efficiency. A new technique is developed by using the Gerchberg-Saxton algorithm, followed by a random-search error minimization that produces the highest interconnect accuracy and the highest diffraction efficiency of the techniques tested. Analysis of the system shows that the hologram has the capacity to connect 5000 neuron outputs to 5000 neuron inputs with bipolar synapses and that the encoded synaptic weights have an accuracy of ~5 bits. A simple feedback system is constructed and demonstrated.

Statistical performance of outer-product associative memory models.

A figure of merit, the probability a bit is correct after update, is used to evaluate the performance of randomly coded outer-product associative memory models. Networks with bipolar binary states and nonzero diagonal connections are shown to yield the best performance with respect to this figure of merit. A surprising result is that an all-positive network, one with binary states and positive connections, is superior to a standard Hopfield style network with binary states and bipolar connections. A prescription for the optimal threshold point for the all-positive network is given.