Behavioral and Neural Correlates of Visual Working Memory Reveal Metacognitive Aspects of Mental Imagery.

Mental imagery (MI) is the ability to generate visual phenomena in the absence of sensory input. MI is often likened to visual working memory (VWM): the ability to maintain and manipulate visual representations. How MI is recruited during VWM is yet to be established. In a modified orientation change-discrimination task, we examined how behavioral (proportion correct) and neural (contralateral delay activity [CDA]) correlates of precision and capacity map onto subjective ratings of vividness and number of items in MI within a VWM task. During the maintenance period, 17 participants estimated the vividness of their MI or the number of items held in MI while they were instructed to focus on either precision or capacity of their representation and to retain stimuli at varying set sizes (1, 2, and 4). Vividness and number ratings varied over set sizes; however, subjective ratings and behavioral performance correlated only for vividness rating at set size 1. Although CDA responded to set size as was expected, CDA did not reflect subjective reports on high and low vividness and on nondivergent (reported the probed number of items in mind) or divergent (reported number of items diverged from probed) rating trials. Participants were more accurate in low set sizes compared with higher set sizes and in coarse (45°) orientation changes compared with fine (15°) orientation changes. We failed to find evidence for a relationship between the subjective sensory experience of precision and capacity of MI and the precision and capacity of VWM.

Resting-state brain activity can predict target-independent aptitude in fMRI-neurofeedback training.

Neurofeedback (NF) aptitude, which refers to an individual's ability to change brain activity through NF training, has been reported to vary significantly from person to person. The prediction of individual NF aptitudes is critical in clinical applications to screen patients suitable for NF treatment. In the present study, we extracted the resting-state functional brain connectivity (FC) markers of NF aptitude, independent of NF-targeting brain regions. We combined the data from fMRI-NF studies targeting four different brain regions at two independent sites (obtained from 59 healthy adults and six patients with major depressive disorder) to collect resting-state fMRI data associated with aptitude scores in subsequent fMRI-NF training. We then trained the multiple regression models to predict the individual NF aptitude scores from the resting-state fMRI data using a discovery dataset from one site and identified six resting-state FCs that predicted NF aptitude. Subsequently, the reproducibility of the prediction model was validated using independent test data from another site. The identified FC model revealed that the posterior cingulate cortex was the functional hub among the brain regions and formed predictive resting-state FCs, suggesting that NF aptitude may be involved in the attentional mode-orientation modulation system's characteristics in task-free resting-state brain activity.

Affective auditory stimulus database: An expanded version of the International Affective Digitized Sounds (IADS-E).

Using appropriate stimuli to evoke emotions is especially important for researching emotion. Psychologists have provided several standardized affective stimulus databases-such as the International Affective Picture System (IAPS) and the Nencki Affective Picture System (NAPS) as visual stimulus databases, as well as the International Affective Digitized Sounds (IADS) and the Montreal Affective Voices as auditory stimulus databases for emotional experiments. However, considering the limitations of the existing auditory stimulus database studies, research using auditory stimuli is relatively limited compared with the studies using visual stimuli. First, the number of sample sounds is limited, making it difficult to equate across emotional conditions and semantic categories. Second, some artificially created materials (music or human voice) may fail to accurately drive the intended emotional processes. Our principal aim was to expand existing auditory affective sample database to sufficiently cover natural sounds. We asked 207 participants to rate 935 sounds (including the sounds from the IADS-2) using the Self-Assessment Manikin (SAM) and three basic-emotion rating scales. The results showed that emotions in sounds can be distinguished on the affective rating scales, and the stability of the evaluations of sounds revealed that we have successfully provided a larger corpus of natural, emotionally evocative auditory stimuli, covering a wide range of semantic categories. Our expanded, standardized sound sample database may promote a wide range of research in auditory systems and the possible interactions with other sensory modalities, encouraging direct reliable comparisons of outcomes from different researchers in the field of psychology.