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Natural language processing unfolds information overtime as spatially separated, multimodal, and interconnected neural processes. Existing noninvasive subtraction‐based neuroimaging techniques cannot simultaneously achieve the spatial and temporal resolutions required to visualize ongoing information flows across the whole brain. Here we have developed rapid phase‐encoded designs to fully exploit the temporal information latent in functional magnetic resonance imaging data, as well as overcoming scanner noise and head‐motion challenges during overt language tasks. We captured real‐time information flows as coherent hemodynamic waves traveling over the cortical surface during listening, reading aloud, reciting, and oral cross‐language interpreting tasks. We were able to observe the timing, location, direction, and surge of traveling waves in all language tasks, which were visualized as “brainstorms” on brain “weather” maps. The paths of hemodynamic traveling waves provide direct evidence for dual‐stream models of the visual and auditory systems as well as logistics models for crossmodal and cross‐language processing. Specifically, we have tracked down the step‐by‐step processing of written or spoken sentences first being received and processed by the visual or auditory streams, carried across language and domain‐general cognitive regions, and finally delivered as overt speeches monitored through the auditory cortex, which gives a complete picture of information flows across the brain during natural language functioning. Practitioner Points Phase‐encoded fMRI enables simultaneous imaging of high spatial and temporal resolution, capturing continuous spatiotemporal dynamics of the entire brain during real‐time overt natural language tasks. Spatiotemporal traveling wave patterns provide direct evidence for constructing comprehensive and explicit models of human information processing. This study unlocks the potential of applying rapid phase‐encoded fMRI to indirectly track the underlying neural information flows of sequential sensory, motor, and high‐order cognitive processes. Phase‐encoded fMRI captures the step‐by‐step spatiotemporal brain dynamics of cognitive processes. When a sentence is heard, language information is carried across the auditory cortex in multiple streams of traveling waves. This provides direct evidence for and supplement the dual‐stream model of speech processing.

Visually guided eating, biting and kissing, and avoiding objects moving toward the face and toward which the face moves require prompt, coordinated processing of spatial visual and somatosensory information in order to protect the face and the brain. Single-cell recordings in parietal cortex have identified multisensory neurons with spatially restricted, aligned visual and somatosensory receptive fields, but so far, there has been no evidence for a topographic map in this area. Here we mapped the organization of a multisensory parietal face area in humans by acquiring functional magnetic resonance images while varying the polar angle of facial air puffs and close-up visual stimuli. We found aligned maps of tactile and near-face visual stimuli at the highest level of human association cortex—namely, in the superior part of the postcentral sulcus. We show that this area may code the location of visual stimuli with respect to the face, not with respect to the retina. *NOTE: In the version of this article initially published online, there was an error in the affiliation in the html version. The first affiliation should read Department of Cognitive Science, University of California San Diego, La Jolla, California 92093, USA. The error has been corrected online.

The reach-to-eat task involves a sequence of action components including looking, reaching, grasping, and feeding. While cortical representations of individual action components have been mapped in human functional magnetic resonance imaging (fMRI) studies, little is known about the continuous spatiotemporal dynamics among these representations during the reach-to-eat task. In a periodic event-related fMRI experiment, subjects were scanned while they reached toward a food image, grasped the virtual food, and brought it to their mouth within each 16-s cycle. Fourier-based analysis of fMRI time series revealed periodic signals and noise distributed across the brain. Independent component analysis was used to remove periodic or aperiodic motion artifacts. Time-frequency analysis was used to analyze the temporal characteristics of periodic signals in each voxel. Circular statistics was then used to estimate mean phase angles of periodic signals and select voxels based on the distribution of phase angles. By sorting mean phase angles across regions, we were able to show the real-time spatiotemporal brain dynamics as continuous traveling waves over the cortical surface. The activation sequence consisted of approximately the following stages: (1) stimulus related activations in occipital and temporal cortices; (2) movement planning related activations in dorsal premotor and superior parietal cortices; (3) reaching related activations in primary sensorimotor cortex and supplementary motor area; (4) grasping related activations in postcentral gyrus and sulcus; (5) feeding related activations in orofacial areas. These results suggest that phase-encoded design and analysis can be used to unravel sequential activations among brain regions during a simulated reach-to-eat task. •Brain dynamics of the reach-to-eat task were unraveled by a phase-encoded design.•Periodic motion artifacts at stimulus frequency were identified and removed by ICA.•Relative latencies can be resolved among regions with periodic brain activations.•Surface-based traveling waves revealed spatiotemporal brain dynamics during eating.•The activation sequence was consistent with the stages of the reach-to-eat task.

The macaque monkey ventral intraparietal area (VIP) contains neurons with aligned visual-tactile receptive fields anchored to the face and upper body. Our previous fMRI studies using standard head coils found a human parietal face area (VIP+ complex; putative macaque VIP homologue) containing superimposed topological maps of the face and near-face visual space. Here, we construct high signal-to-noise surface coils and used phase-encoded air puffs and looming stimuli to map topological organization of the parietal face area at higher resolution. This area is consistently identified as a region extending between the superior postcentral sulcus and the upper bank of the anterior intraparietal sulcus (IPS), avoiding the fundus of IPS. Using smaller voxel sizes, our surface coils picked up strong fMRI signals in response to tactile and visual stimuli. By analyzing tactile and visual maps in our current and previous studies, we constructed a set of topological models illustrating commonalities and differences in map organization across subjects. The most consistent topological feature of the VIP+ complex is a central-anterior upper face (and upper visual field) representation adjoined by lower face (and lower visual field) representations ventrally (laterally) and/or dorsally (medially), potentially forming two subdivisions VIPv (ventral) and VIPd (dorsal). The lower visual field representations typically extend laterally into the anterior IPS to adjoin human area AIP, and medially to overlap with the parietal body areas at the superior parietal ridge. Significant individual variations are then illustrated to provide an accurate and comprehensive view of the topological organization of the parietal face area. •Building surface coils for high-resolution imaging of the parietal face area (VIP+).•VIP+ sits between the superior postcentral sulcus and anterior intraparietal sulcus.•VIP+ shows high intra- and inter-subject variability in topological organization.•Models of the topological organization of VIP+ with two major type categories.•VIP+ contains at least two subdivisions: VIPv (ventral) and VIPd (dorsal).

To map cortical representations of the body, we recently developed a wearable technology for automatic tactile stimulation in human functional magnetic resonance imaging (fMRI) experiments. In a two-condition block design experiment, air puffs were delivered to the face and hands periodically. Surface-based regions of interest (S-ROIs) were initially identified by thresholding a linear statistical measure of signal-to-noise ratio of periodic response. Across subjects, S-ROIs were found in the frontal, primary sensorimotor, posterior parietal, insular, temporal, cingulate, and occipital cortices. To validate and differentiate these S-ROIs, we develop a measure of temporal stability of response based on the assumption that a periodic stimulation evokes stable (low-variance) periodic fMRI signals throughout the entire scan. Toward this end, we apply time-frequency analysis to fMRI time series and use circular statistics to characterize the distribution of phase angles for data selection. We then assess the temporal variability of a periodic signal by measuring the path length of its trajectory in the complex plane. Both within and outside the primary sensorimotor cortex, S-ROIs with high temporal variability and deviant phase angles are rejected. A surface-based probabilistic group-average map is constructed for spatial screening of S-ROIs with low to moderate temporal variability in non-sensorimotor regions. Areas commonly activated across subjects are also summarized in the group-average map. In summary, this study demonstrates that analyzing temporal characteristics of the entire fMRI time series is essential for second-level selection and interpretation of S-ROIs initially defined by an overall linear statistical measure. •MR-compatible wearable technology for tactile stimulation on multiple body parts.•Second-level data selection using time-frequency analysis and circular statistics.•Measuring temporal stability of periodic fMRI time series in the complex plane.•Surface-based regions of interest and probabilistic group-average maps.

Detection and avoidance of impending obstacles is crucial to preventing head and body injuries in daily life. To safely avoid obstacles, locations of objects approaching the body surface are usually detected via the visual system and then used by the motor system to guide defensive movements. Mediating between visual input and motor output, the posterior parietal cortex plays an important role in integrating multisensory information in peripersonal space. We used functional MRI to map parietal areas that see and feel multisensory stimuli near or on the face and body. Tactile experiments using full-body air-puff stimulation suits revealed somatotopic areas of the face and multiple body parts forming a higher-level homunculus in the superior posterior parietal cortex. Visual experiments using wide-field looming stimuli revealed retinotopic maps that overlap with the parietal face and body areas in the postcentral sulcus at the most anterior border of the dorsal visual pathway. Starting at the parietal face area and moving medially and posteriorly into the lower-body areas, the median of visual polar-angle representations in these somatotopic areas gradually shifts from near the horizontal meridian into the lower visual field. These results suggest the parietal face and body areas fuse multisensory information in peripersonal space to guard an individual from head to toe.

Tonic and phasic dynamics of electroencephalographic (EEG) activities during a continuous compensatory tracking task (CTT) were analyzed using time–frequency analysis of EEG sources identified by independent component analysis (ICA). In 1-hour sessions, 70-channel EEG data were recorded while participants attempted to use frequent compensatory trackball movements to maintain a drifting disc close to a bulls-eye at screen center. Disc trajectories were converted into two moving-average performance measures, root mean square distance of the disc from screen center in 4-s (‘local’) and in 20-s (‘global’) moving time windows. Maximally independent EEG processes and their equivalent dipole source locations were obtained using the EEGLAB toolbox ( http://sccn.ucsd.edu/eeglab). Across subjects and sessions, independent EEG processes in occipital, somatomotor, and supplementary motor cortices exhibited tonic power increases during periods of high tracking error, plus additional phasic power increases in several frequency bands before and after trackball movements following disc ‘perigees’ (moments at which the disc began to drift away from the bulls-eye). These phasic activity increases, which were larger during high-error periods, reveal an intimate relation between EEG dynamics and top–down recognition of responding to threatening events. Thus during a continuous tracking task without impulsive stimulus onsets, sub-second scale EEG dynamics related to visuomotor task could be dissociated from slower spectral modulations linked to changes in performance and arousal. We tentatively interpret the observed EEG signal increases as indexing tonic and phasic modulations of the levels of task attention and engagement required to maintain visuomotor performance during sustained performance.

This study investigates the independent modulators that mediate the power spectra of electrophysiological processes, measured by electroencephalogram (EEG), in a sustained-attention experiment. EEG and behavioral data were collected during 1–2hour virtual-reality based driving experiments in which subjects were instructed to maintain their cruising position and compensate for randomly induced drift using the steering wheel. Independent component analysis (ICA) applied to 30-channel EEG data separated the recorded EEG signals into a sum of maximally temporally independent components (ICs) for each of 30 subjects. Logarithmic spectra of resultant IC activities were then decomposed by principal component analysis, followed by ICA, to find spectrally fixed and temporally independent modulators (IM). Across subjects, the spectral ICA consistently found four performance-related independent modulators: delta, delta–theta, alpha, and beta modulators that multiplicatively affected the spectra of spatially distinct IC processes when the participants experienced waves of alternating alertness and drowsiness during long-hour simulated driving. The activation of the delta–theta modulator increased monotonically as subjects' task performances decreased. Furthermore, the time courses of the theta–beta modulator were highly correlated with concurrent changes in driving errors across subjects (r=0.77±0.13). ► We apply independent component analysis to assess brain processes during driving. ► We report components' spectral dynamics and their relationship with task performance. ► We assess independent co-modulators mediating spectral activates of cortical areas. ► Task-related co-modulators are very consistent across subjects. ► Time courses of co-modulators are highly correlated with task performance.

Somatotopic mapping of human body surface using fMRI is challenging. First, it is difficult to deliver tactile stimuli in the scanner. Second, multiple stimulators are often required to cover enough area of the complex-shaped body surface, such as the face. In this study, a computer-controlled pneumatic system was constructed to automatically deliver air puffs to 12 locations on the body surface through an MR-compatible manifold (Dodecapus) mounted on a head coil inside the scanner bore. The timing of each air-puff channel is completely programmable and this allows systematic and precise stimulation on multiple locations on the body surface during functional scans. Three two-condition block-design “Localizer” paradigms were employed to localize the cortical representations of the face, lips, and fingers, respectively. Three “Phase-encoded” paradigms were employed to map the detailed somatotopic organizations of the face, lips, and fingers following each “Localizer” paradigm. Multiple somatotopic representations of the face, lips, and fingers were localized and mapped in primary motor cortex (MI), ventral premotor cortex (PMv), polysensory zone (PZ), primary (SI) and secondary (SII) somatosensory cortex, parietal ventral area (PV) and 7b, as well as anterior and ventral intraparietal areas (AIP and VIP). The Dodecapus system is portable, easy to setup, generates no radio frequency interference, and can also be used for EEG and MEG experiments. This system could be useful for non-invasive somatotopic mapping in both basic and clinical studies.

This study investigates the intricate interplay between the task-positive network and the default mode network (DMN) during transitions between overt language tasks and brief resting periods. While previous research suggests that these networks are not invariably anticorrelated, the precise timing of transitions has remained elusive. We employed rapid phase-encoded fMRI to decode brain dynamics with ultimate precision, capturing these transitions in real time. By utilizing phasor diagrams to represent the oscillatory activities, we examined the amplitudes and phases of hemodynamic fluctuations within the language network and DMN. Our findings align with existing empirical and theoretical perspectives on DMN functions and cognitive task performance, affirming the validity of our approach. We identified heterogeneous micro resting states interwoven with periods of overt speech production. Notably, various core regions of the DMN exhibited task-dependent amplitude and phase modulations, with activation strength and delay rising in line with increasing task complexity, ranging from comprehension to immediate and delayed speech production. This study sheds light on the dynamic engagement of the DMN during overt speech production, providing precise timing data of transitions between the DMN and language network. It demonstrates that rapid phase-encoded fMRI and phasor diagrams are powerful tools for measuring the switching between active tasks and micro resting states with subsecond accuracy, while also elucidating task load-dependent changes in the DMN. By accurately measuring the timing of these transitions, we gain insights into cognitive flexibility, attention, and the efficiency of information processing.