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Objective: Research on visual working memory has shown that individual stimulus features are processed in both specialized sensory regions and higher cortical areas. Much less evidence exists for auditory working memory. Here, a main distinction has been proposed between the processing of spatial and non-spatial sound features. Our aim was to examine feature-specific activation patterns in auditory working memory.
Methods: We collected fMRI data while 28 healthy adults performed an auditory delayed match-to-sample task. Stimuli were abstract sounds characterized by both spatial and non-spatial information, i.e., interaural time delay and central frequency, respectively. In separate recording blocks, subjects had to memorize either the spatial or non-spatial feature, which had to be compared with a probe sound presented after a short delay. We performed both univariate and multivariate comparisons between spatial and non-spatial task blocks.
Results: Processing of spatial sound features elicited a higher activity in a small cluster in the superior parietal lobe than did sound pattern processing, whereas there was no significant activation difference for the opposite contrast. The multivariate analysis was applied using a whole-brain searchlight approach to identify feature-selective processing. The task-relevant auditory feature could be decoded from multiple brain regions including the auditory cortex, posterior temporal cortex, middle occipital gyrus, and extended parietal and frontal regions.
Conclusion: In summary, the lack of large univariate activation differences between spatial and non-spatial processing could be attributable to the identical stimulation in both tasks. In contrast, the whole-brain multivariate analysis identified feature-specific activation patterns in widespread cortical regions. This suggests that areas beyond the auditory dorsal and ventral streams contribute to working memory processing of auditory stimulus features.
Aging is accompanied by unisensory decline. To compensate for this, two complementary strategies are potentially relied upon increasingly: first, older adults integrate more information from different sensory organs. Second, according to the predictive coding (PC) model, we form “templates” (internal models or “priors”) of the environment through our experiences. It is through increased life experience that older adults may rely more on these templates compared to younger adults. Multisensory integration and predictive coding would be effective strategies for the perception of near-threshold stimuli, which may however come at the cost of integrating irrelevant information. Both strategies can be studied in multisensory illusions because these require the integration of different sensory information, as well as an internal model of the world that can take precedence over sensory input. Here, we elicited a classic multisensory illusion, the sound-induced flash illusion, in younger (mean: 27 years, N = 25) and older (mean: 67 years, N = 28) adult participants while recording the magnetoencephalogram. Older adults perceived more illusions than younger adults. Older adults had increased pre-stimulus beta-band activity compared to younger adults as predicted by microcircuit theories of predictive coding, which suggest priors and predictions are linked to beta-band activity. Transfer entropy analysis and dynamic causal modeling of pre-stimulus magnetoencephalography data revealed a stronger illusion-related modulation of cross-modal connectivity from auditory to visual cortices in older compared to younger adults. We interpret this as the neural correlate of increased reliance on a cross-modal predictive template in older adults leading to the illusory percept.
Motives motivate human behavior. Most behaviors are driven by more than one motive, yet it is unclear how different motives interact and how such motive combinations affect the neural computation of the behaviors they drive. To answer this question, we induced two prosocial motives simultaneously (multi-motive condition) and separately (single motive conditions). After the different motive inductions, participants performed the same choice task in which they allocated points in favor of the other person (prosocial choice) or in favor of themselves (egoistic choice). We used fMRI to assess prosocial choice-related brain responses and drift diffusion modeling to specify how motive combinations affect individual components of the choice process. Our results showed that the combination of the two motives in the multi-motive condition increased participants’ choice biases prior to the behavior itself. On the neural level, these changes in initial prosocial bias were associated with neural responses in the bilateral dorsal striatum. In contrast, the efficiency of the prosocial decision process was comparable between the multi-motive and the single-motive conditions. These findings provide insights into the computation of prosocial choices in complex motivational states, the motivational setting that drives most human behaviors.