The effects of dark chocolate on cognitive performance during cognitively demanding tasks: A randomized, single-blinded, crossover, dose-comparison study.

Dark chocolate, rich in polyphenols, increases cerebral blood flow and improves cognitive function. This study aimed to determine whether the consumption of chocolate with a high concentration of polyphenols helps to maintain cognitive performance during cognitively demanding tasks. In this randomized, single-blinded, crossover, dose-comparison study, 18 middle-aged adults consumed two types of chocolate (25 g each), one with a high concentration (635.0 mg) and the other with a low concentration (211.7 mg) of cacao polyphenols, and performed a cognitive task requiring response inhibition and selective attention over two time periods (15-30 min and 40-55 min after consumption, respectively). Autonomic nerve function and subjective feelings, such as fatigue and concentration, were measured before food intake and after the second task to assess the participant's state. The results showed that the average reaction time between the first and second sessions was not significantly different for either high- or low-concentration chocolate consumption. However, the percentage of correct responses was similar in the first (96.7 %) and second (96.8 %) sessions for high-concentration chocolate consumption and significantly lower for low-concentration chocolate consumption in the second (96.4 %) session than in the first session (97.3 %). Autonomic nerve function showed a significant increase in sympathetic nerve activity after the second task with high-concentration chocolate consumption, while subjective feelings showed an increase in mental fatigue for both chocolate types but a significant decrease in concentration only after the second task with low-concentration chocolate consumption. These findings suggest that dark chocolate consumption contributes to the maintenance of performance and concentration in continuous and demanding cognitive tasks.

Accumulation System: Distributed Neural Substrates of Perceptual Decision Making Revealed by fMRI Deconvolution.

Neural substrates of evidence accumulation have been a central issue in decision-making studies because of the prominent success of the accumulation model in explaining a wide range of perceptual decision making. Since accumulation-shaped activities have been found in multiple brain regions, which are called accumulators, questions regarding functional relations among these accumulators are emerging. This study employed the deconvolution method of functional magnetic resonance imaging (fMRI) signals from human male and female participants during object-category decision tasks, taking advantage of the whole-brain coverage of fMRI with improved availability of temporal information of the deconvolved activity. We detected the accumulation activity in many non-category-selective regions (NCSRs) over the frontal, parietal, and temporal lobes as well as category-selective regions (CSRs) of the categorization task. Importantly, the frontal regions mostly showed activity peaks matching the decision timing (classified as "type-A accumulator"), while activity peaks of the parietal and temporal regions were behind the decision (classified as "type-B accumulator"). The CSRs showed activity peaks whose timing depended on both region and stimulus preference, plausibly reflecting the competition among the alternative choices (classified as "type-C accumulator"). The results suggest that these functionally heterogeneous accumulators form a system for evidence accumulation in which the type-A accumulator regions make decisions in a general manner while the type-B and type-C accumulator regions are employed depending on the modality and content of decision tasks. The concept of the accumulation system may provide a key to understanding the universality of the accumulation model over various kinds of decision tasks.SIGNIFICANCE STATEMENT Perceptual decision making, such as deciding to walk or stop on seeing the signal colors, has been explained theoretically by the accumulation model, in which sensory information is accumulated to reach a certain threshold for making decisions. Neural substrates of this model, however, are still under elucidation among candidate regions found over the brain. We show here that, taking advantage of the whole-brain coverage of functional magnetic resonance imaging (fMRI) with improving availability of temporal information by deconvolution method, the accumulation is conducted by a system comprising many regions in different abstraction levels and only a part of these regions in the frontal cortex make decisions. The system concept may provide a key to explaining the universality of the accumulation model.

Automatic representation of a visual stimulus relative to a background in the right precuneus.

Our brains represent the position of a visual stimulus egocentrically, in either retinal or craniotopic coordinates. In addition, recent behavioral studies have shown that the stimulus position is automatically represented allocentrically relative to a large frame in the background. Here, we investigated neural correlates of the 'background coordinate' using an fMRI adaptation technique. A red dot was presented at different locations on a screen, in combination with a rectangular frame that was also presented at different locations, while the participants looked at a fixation cross. When the red dot was presented repeatedly at the same location relative to the rectangular frame, the fMRI signals significantly decreased in the right precuneus. No adaptation was observed after repeated presentations relative to a small, but salient, landmark. These results suggest that the background coordinate is implemented in the right precuneus.

Blink-related momentary activation of the default mode network while viewing videos.

It remains unknown why we generate spontaneous eyeblinks every few seconds, more often than necessary for ocular lubrication. Because eyeblinks tend to occur at implicit breakpoints while viewing videos, we hypothesized that eyeblinks are actively involved in the release of attention. We show that while viewing videos, cortical activity momentarily decreases in the dorsal attention network after blink onset but increases in the default-mode network implicated in internal processing. In contrast, physical blackouts of the video do not elicit such reciprocal changes in brain networks. The results suggest that eyeblinks are actively involved in the process of attentional disengagement during a cognitive behavior by momentarily activating the default-mode network while deactivating the dorsal attention network.

Neural correlates and effective connectivity of subjective colors during the Benham's top illusion: a functional MRI study.

Benham's top is a rotating black-and-white pattern that fuses to form concentric rings of different colors (Prevost-Fechner-Benham subjective colors [SCs]). The underlying mechanism has been explained as resulting from local retinal cell interactions, yet the cortical processing of this illusion is largely unknown. We used rapid event-related functional magnetic resonance imaging to investigate the neural mechanisms of this SC illusion. The SCs induced when Benham's top rotated at 5 Hz were compared with perceptually matched physical color (PC) stimuli to reveal differences in both the neural substrates and their dynamic interactions by means of effective connectivity. Subjects (n = 7, all with normal vision) were required to judge whether or not they perceived color in each stimulus. The activation patterns for each condition were almost identical, but the effective connectivity from V4 to V2 and V2 to V1 was stronger during SC perception than when viewing perceptually matched PCs. All subjects perceived SC when the rotation speed of Benham's top was greater than or equal to 3 Hz, which was coupled with enhanced effective connectivity between V4 and V1. These results indicate that modulation from V4 to V2 to V1 plays a significant role in SC perception during the Benham's top illusion.

"Stay tuned": inter-individual neural synchronization during mutual gaze and joint attention.

Eye contact provides a communicative link between humans, prompting joint attention. As spontaneous brain activity might have an important role in the coordination of neuronal processing within the brain, their inter-subject synchronization might occur during eye contact. To test this, we conducted simultaneous functional MRI in pairs of adults. Eye contact was maintained at baseline while the subjects engaged in real-time gaze exchange in a joint attention task. Averted gaze activated the bilateral occipital pole extending to the right posterior superior temporal sulcus, the dorso-medial prefrontal cortex, and the bilateral inferior frontal gyrus. Following a partner's gaze toward an object activated the left intraparietal sulcus. After all the task-related effects were modeled out, inter-individual correlation analysis of residual time-courses was performed. Paired subjects showed more prominent correlations than non-paired subjects in the right inferior frontal gyrus, suggesting that this region is involved in sharing intention during eye contact that provides the context for joint attention.

Visual image reconstruction from human brain activity using a combination of multiscale local image decoders.

Perceptual experience consists of an enormous number of possible states. Previous fMRI studies have predicted a perceptual state by classifying brain activity into prespecified categories. Constraint-free visual image reconstruction is more challenging, as it is impractical to specify brain activity for all possible images. In this study, we reconstructed visual images by combining local image bases of multiple scales, whose contrasts were independently decoded from fMRI activity by automatically selecting relevant voxels and exploiting their correlated patterns. Binary-contrast, 10 x 10-patch images (2(100) possible states) were accurately reconstructed without any image prior on a single trial or volume basis by measuring brain activity only for several hundred random images. Reconstruction was also used to identify the presented image among millions of candidates. The results suggest that our approach provides an effective means to read out complex perceptual states from brain activity while discovering information representation in multivoxel patterns.