Changes in spatial self-consciousness elicit grid cell-like representation in the entorhinal cortex.

Grid cells in the entorhinal cortex (EC) encode an individual's location in space, integrating both environmental and multisensory bodily cues. Notably, body-derived signals are also primary signals for the sense of self. While studies have demonstrated that continuous application of visuo-tactile bodily stimuli can induce perceptual shifts in self-location, it remains unexplored whether these illusory changes suffice to trigger grid cell-like representation (GCLR) within the EC, and how this compares to GCLR during conventional virtual navigation. To address this, we systematically induced illusory drifts in self-location toward controlled directions using visuo-tactile bodily stimulation, while maintaining the subjects' visual viewpoint fixed (absent conventional virtual navigation). Subsequently, we evaluated the corresponding GCLR in the EC through functional MRI analysis. Our results reveal that illusory changes in perceived self-location (independent of changes in environmental navigation cues) can indeed evoke entorhinal GCLR, correlating in strength with the magnitude of perceived self-location, and characterized by similar grid orientation as during conventional virtual navigation in the same virtual room. These data demonstrate that the same grid-like representation is recruited when navigating based on environmental, mainly visual cues, or when experiencing illusory forward drifts in self-location, driven by perceptual multisensory bodily cues.

Sense of self impacts spatial navigation and hexadirectional coding in human entorhinal cortex.

Grid cells in entorhinal cortex (EC) encode an individual's location in space and rely on environmental cues and self-motion cues derived from the individual's body. Body-derived signals are also primary signals for the sense of self and based on integrated sensorimotor signals (proprioceptive, tactile, visual, motor) that have been shown to enhance self-centered processing. However, it is currently unknown whether such sensorimotor signals that modulate self-centered processing impact grid cells and spatial navigation. Integrating the online manipulation of bodily signals, to modulate self-centered processing, with a spatial navigation task and an fMRI measure to detect grid cell-like representation (GCLR) in humans, we report improved performance in spatial navigation and decreased GCLR in EC. This decrease in entorhinal GCLR was associated with an increase in retrosplenial cortex activity, which was correlated with participants' navigation performance. These data link self-centered processes during spatial navigation to entorhinal and retrosplenial activity and highlight the role of different bodily factors at play when navigating in VR.

Lightweight and Amplitude-Free Ultrasonic Imaging Using Single-Bit Digitization and Instantaneous Phase Coherence.

In the field of ultrasonic nondestructive testing (NDT), the total focusing method (TFM) and its derivatives are now commercially available on portable devices and are getting more popular within the NDT community. However, its implementation requires the collection of a very large amount of data with the full matrix capture (FMC) as the worst case scenario. Analyzing all the data also requires significant processing power, and consequently, there is an interest in: 1) reducing the required storage capacity used by imaging algorithms, such as delay-and-sum (DAS) imaging and 2) allowing the transmission and postprocessing of inspection data remotely. In this study, a different implementation of the TFM algorithm is used based on the vector coherence factor (VCF) that is used as an image itself. This method, also generally known as phase coherence imaging, presents certain advantages, such as a better sensitivity to diffracting geometries, consistency of defect restitution among different views, and an amplitude-free behavior as only the instantaneous phase of the signal is considered. Some drawbacks of this method must also be mentioned, including the fact that it poorly reproduces planar reflectors and presents a lower signal-to-noise ratio (SNR) than amplitude-based methods. However, previous studies showed that it can be used as a reliable tool for crack-like defect sizing. Thus, a lightweight acquisition process is proposed through single-bit digitization of the signal, followed by a phase retrieval method based on the rising and falling edge locations, allowing to feed the phase coherence imaging algorithm. Simulated and experimental tests were first performed in this study on several side-drilled holes (SDHs) in a stainless steel block and then extended to an experimental study on angled notches in a 19.05-mm ( 3/4" )-thick steel sample plate through multiview imaging. Results obtained using the array performance indicator (API) and the contrast-to-noise ratio (CNR) as quantitative evaluation parameters showed that the proposed lightweight acquisition process, which relies on binary signals, allows a reduction of the data throughput of up to 47 times. This throughput reduction is achieved while still presenting very similar results to phase coherence imaging based on the instantaneous phase derived from the Hilbert transform of the full waveform. In an era of increasing wireless network speed and cloud computing, these results allow considering interesting perspectives for the reduction of inspection hardware costs and remote postprocessing.

Towards using convolutional neural network to locate, identify and size defects in phased array ultrasonic testing.

Machine learning algorithms are widely used in image recognition. In Phased Array Ultrasonic Testing (PAUT), images are typically formed through constructive and destructive superpositions of signals backscattered from flaws or geometric features. However, all PAUT data acquisition schemes require several emissions and the duration of the acquisition may be too slow in high-speed manufacturing. In this study, the Faster R-CNN was used to identify, locate and size flat bottom holes (FBH) and side-drilled holes (SDH) in an immersed test specimen using a single plane wave insonification. The training was performed on segmented and classified data generated using GPU-accelerated finite element simulations. SDH and FBH of different diameters, depths and lateral positions were included in the training set. The thickness of the test specimen was also variable. An ultrasonic phased array probe of 64 elements was simulated. All elements of the phased array probe were fired at the same time and the time traces from each element were recorded. The individual time traces were concatenated to form a matrix, which was then used in the training. This inspection scenario enables fast acquisition of data at the expense of poor lateral resolution in the resulting image. The trained neural network was initially tested using finite element simulations. Results were assessed in terms of the intersection of the union (IoU) between the ground truth geometry and the predicted geometry. With the simulated cases, the thickness of the test specimen was detected in all cases. When using a 40% IoU threshold, the detection rate of the FBH was 87% while only 20% for the SDH. The smallest detected FBH had a 0.56 wavelength depth and a lateral extent of 1.04 wavelength. Drawing a box using the -6dB drop method around the FBH always led to an IoU under 15%. On average, the lateral extent of the FBH using the -6dB method was three times larger than the diameter predicted by the proposed method. Then, the training was continued with a small augmented dataset of experiments (equivalent to 3% of the simulated dataset). In experiments, the results show that the test specimen was always correctly identified. When using a 40% IoU threshold the experimental detection rate of the FBH was 70%. The smallest detected defect in experiments had a depth of 2 wavelengths.

Towards an Alternative to Time of Flight Diffraction Using Instantaneous Phase Coherence Imaging for Characterization of Crack-Like Defects.

Time of flight diffraction (TOFD) is considered a reliable non-destructive testing method for the inspection of welds using a pair of single-element probes. On the other hand, ultrasonic phased array imaging has been continuously developed over the last couple of decades, and now features powerful algorithms, such as the total focusing method (TFM) and its multi-view approach to rendering detailed images of inspected parts. This article focuses on a different implementation of the TFM algorithm, relying on the coherent summation of the instantaneous signal phase. This approach presents a wide range of benefits, such as removing the need for calibration, and is highly sensitive to defect tips. This study compares the sizing and localization capabilities of the proposed method with the well-known TOFD. Both instantaneous phase algorithm and TOFD do not take advantage of the signal amplitude. Experimental tests were performed on a ¾â€³-thick steel sample with crack-like defects at different angles. Phase-based imaging techniques showed similar characterization capabilities as the standard TOFD method. However, the proposed method adds the benefit of generating an easy-to-interpret image that can help in localizing the defect. These results pave the way for a new characterization approach, especially in the field of automated ultrasonic testing (AUT).

Individual Brain Charting dataset extension, second release of high-resolution fMRI data for cognitive mapping.

We present an extension of the Individual Brain Charting dataset -a high spatial-resolution, multi-task, functional Magnetic Resonance Imaging dataset, intended to support the investigation on the functional principles governing cognition in the human brain. The concomitant data acquisition from the same 12 participants, in the same environment, allows to obtain in the long run finer cognitive topographies, free from inter-subject and inter-site variability. This second release provides more data from psychological domains present in the first release, and also yields data featuring new ones. It includes tasks on e.g. mental time travel, reward, theory-of-mind, pain, numerosity, self-reference effect and speech recognition. In total, 13 tasks with 86 contrasts were added to the dataset and 63 new components were included in the cognitive description of the ensuing contrasts. As the dataset becomes larger, the collection of the corresponding topographies becomes more comprehensive, leading to better brain-atlasing frameworks. This dataset is an open-access facility; raw data and derivatives are publicly available in neuroimaging repositories.

First-person body view modulates the neural substrates of episodic memory and autonoetic consciousness: A functional connectivity study.

Episodic memory (EM) is classically conceived as a memory for events, localized in space and time, and characterized by autonoetic consciousness (ANC) allowing to mentally travel back in time and subjectively relive an event. Building on recent evidence that the first-person visual co-perception of one's own body during encoding impacts EM, we used a scene recognition task in immersive virtual reality (VR) and measured how first-person body view would modulate peri-encoding resting-state fMRI, EM performance, and ANC. Specifically, we investigated the impact of body view on post-encoding functional connectivity in an a priori network of regions related either to EM or multisensory bodily processing and used these regions in a seed-to-whole brain analysis. Post-encoding connectivity between right hippocampus (rHC) and right parahippocampus (rPHC) was enhanced when participants encoded scenes while seeing their body. Moreover, the strength of connectivity between the rHC, rPHC and the neocortex displayed two main patterns with respect to body view. The connectivity with a sensorimotor fronto-parietal network, comprising primary somatosensory and primary motor cortices, correlated with ANC after - but not before - encoding, depending on body view. The opposite change of connectivity was found between rHC, rPHC and the medial parietal cortex (from being correlated with ANC before encoding to an absence of correlation after encoding), but irrespective of body view. Linking immersive VR and fMRI for the study of EM and ANC, these findings suggest that seeing one's own body during encoding impacts the brain activity related to EM formation by modulating the connectivity between the right hippocampal formation and the neocortical regions involved in the processing of multisensory bodily signals and self-consciousness.

Hippocampal Contribution to Ordinal Psychological Time in the Human Brain.

The chronology of events in time-space is naturally available to the senses, and the spatial and temporal dimensions of events entangle in episodic memory when navigating the real world. The mapping of time-space during navigation in both animals and humans implicates the hippocampal formation. Yet, one arguably unique human trait is the capacity to imagine mental chronologies that have not been experienced but may involve real events-the foundation of causal reasoning. Herein, we asked whether the hippocampal formation is involved in mental navigation in time (and space), which requires internal manipulations of events in time and space from an egocentric perspective. To address this question, we reanalyzed a magnetoencephalography data set collected while participants self-projected in time or in space and ordered historical events as occurring before/after or west/east of the mental self [Gauthier, B., Pestke, K., & van Wassenhove, V. Building the arrow of time… Over time: A sequence of brain activity mapping imagined events in time and space. Cerebral Cortex, 29, 4398-4414, 2019]. Because of the limitations of source reconstruction algorithms in the previous study, the implication of hippocampus proper could not be explored. Here, we used a source reconstruction method accounting explicitly for the hippocampal volume to characterize the involvement of deep structures belonging to the hippocampal formation (bilateral hippocampi [hippocampi proper], entorhinal cortices, and parahippocampal cortex). We found selective involvement of the medial temporal lobes (MTLs) with a notable lateralization of the main effects: Whereas temporal ordinality engaged mostly the left MTL, spatial ordinality engaged mostly the right MTL. We discuss the possibility of a top-down control of activity in the human hippocampal formation during mental time (and space) travels.

TbCAPs: A toolbox for co-activation pattern analysis.

Functional magnetic resonance imaging provides rich spatio-temporal data of human brain activity during task and rest. Many recent efforts have focussed on characterising dynamics of brain activity. One notable instance is co-activation pattern (CAP) analysis, a frame-wise analytical approach that disentangles the different functional brain networks interacting with a user-defined seed region. While promising applications in various clinical settings have been demonstrated, there is not yet any centralised, publicly accessible resource to facilitate the deployment of the technique. Here, we release a working version of TbCAPs, a new toolbox for CAP analysis, which includes all steps of the analytical pipeline, introduces new methodological developments that build on already existing concepts, and enables a facilitated inspection of CAPs and resulting metrics of brain dynamics. The toolbox is available on a public academic repository at https://c4science.ch/source/CAP_Toolbox.git. In addition, to illustrate the feasibility and usefulness of our pipeline, we describe an application to the study of human cognition. CAPs are constructed from resting-state fMRI using as seed the right dorsolateral prefrontal cortex, and, in a separate sample, we successfully predict a behavioural measure of continuous attentional performance from the metrics of CAP dynamics (R â€‹= â€‹0.59).

First-person view of one's body in immersive virtual reality: Influence on episodic memory.

Episodic memories (EMs) are recollections of contextually rich and personally relevant past events. EM has been linked to the sense of self, allowing one to mentally travel back in subjective time and re-experience past events. However, the sense of self has recently been linked to online multisensory processing and bodily self-consciousness (BSC). It is currently unknown whether EM depends on BSC mechanisms. Here, we used a new immersive virtual reality (VR) system that maintained the perceptual richness of life episodes and fully controlled the experimental stimuli during encoding and retrieval, including the participant's body. Our data reveal a classical EM finding, which shows that memory for complex real-life like scenes decays over time. However, here we also report a novel finding that delayed retrieval performance can be enhanced when participants view their body as part of the virtual scene during encoding. This body effect was not observed when no virtual body or a moving control object was shown, thereby linking the sense of self, and BSC in particular, to EMs. The present VR methodology and the present behavioral findings will enable to study key aspects of EM in healthy participants and may be especially beneficial for the restoration of self-relevant memories in future experiments.

Building the Arrow of Time Over Time: A Sequence of Brain Activity Mapping Imagined Events in Time and Space.

When moving, the spatiotemporal unfolding of events is bound to our physical trajectory, and time and space become entangled in episodic memory. When imagining past or future events, or being in different geographical locations, the temporal and spatial dimensions of mental events can be independently accessed and manipulated. Using time-resolved neuroimaging, we characterized brain activity while participants ordered historical events from different mental perspectives in time (e.g., when imagining being 9 years in the future) or in space (e.g., when imagining being in Cayenne). We describe 2 neural signatures of temporal ordinality: an early brain response distinguishing whether participants were mentally in the past, the present or the future (self-projection in time), and a graded activity at event retrieval, indexing the mental distance between the representation of the self in time and the event. Neural signatures of ordinality and symbolic distances in time were distinct from those observed in the homologous spatial task: activity indicating spatial order and distances overlapped in latency in distinct brain regions. We interpret our findings as evidence that the conscious representation of time and space share algorithms (egocentric mapping, distance, and ordinality computations) but different implementations with a distinctive status for the psychological "time arrow."

Common Recruitment of Angular Gyrus in Episodic Autobiographical Memory and Bodily Self-Consciousness.

Parietal cortex and adjacent parts of the temporal cortex have recently been associated with bodily self-consciousness (BSC). Similarly, growing evidence suggests that the lateral parietal cortex is crucial for the subjective aspects of episodic autobiographical memory (EAM), which is based on the conscious experience of reliving past events. However, the neuroanatomical relationship between both fundamental aspects remains currently unexplored. Moreover, despite the wealth of neuroimaging data on EAM, only few neuroimaging studies have examined BSC and even fewer examined those aspects of BSC that are most closely related to EAM. Here, we investigated whether regions in the inferior parietal lobule (IPL) that have been involved in spatial aspects of BSC (self-location and first-person perspective), as described by Ionta et al. (2011) are also active in studies investigating autobiographical memory. To examine this relation, we thus compared the regions indicated in the study by Ionta et al. (2011) based on data in healthy participants and neurological patients, with the results from a meta-analytical study we performed based on functional neuroimaging studies on EAM and semantic autobiographical memory (SAM). We report an anatomical overlap bilaterally in the angular gyrus (AG), but not in other parietal or temporal lobe structures between BSC and EAM. Moreover, there was no overlap between BSC and SAM. These preliminary data suggest that the bilateral AG may be a key structure for the conscious re-experiencing of past life episodes (EAM) and the conscious on-line experience of being located and experiencing the world in first-person (BSC).

Atlases of cognition with large-scale human brain mapping.

To map the neural substrate of mental function, cognitive neuroimaging relies on controlled psychological manipulations that engage brain systems associated with specific cognitive processes. In order to build comprehensive atlases of cognitive function in the brain, it must assemble maps for many different cognitive processes, which often evoke overlapping patterns of activation. Such data aggregation faces contrasting goals: on the one hand finding correspondences across vastly different cognitive experiments, while on the other hand precisely describing the function of any given brain region. Here we introduce a new analysis framework that tackles these difficulties and thereby enables the generation of brain atlases for cognitive function. The approach leverages ontologies of cognitive concepts and multi-label brain decoding to map the neural substrate of these concepts. We demonstrate the approach by building an atlas of functional brain organization based on 30 diverse functional neuroimaging studies, totaling 196 different experimental conditions. Unlike conventional brain mapping, this functional atlas supports robust reverse inference: predicting the mental processes from brain activity in the regions delineated by the atlas. To establish that this reverse inference is indeed governed by the corresponding concepts, and not idiosyncrasies of experimental designs, we show that it can accurately decode the cognitive concepts recruited in new tasks. These results demonstrate that aggregating independent task-fMRI studies can provide a more precise global atlas of selective associations between brain and cognition.

Time Is Not Space: Core Computations and Domain-Specific Networks for Mental Travels.

Humans can consciously project themselves in the future and imagine themselves at different places. Do mental time travel and mental space navigation abilities share common cognitive and neural mechanisms? To test this, we recorded fMRI while participants mentally projected themselves in time or in space (e.g., 9 years ago, in Paris) and ordered historical events from their mental perspective. Behavioral patterns were comparable for mental time and space and shaped by self-projection and by the distance of historical events to the mental position of the self, suggesting the existence of egocentric mapping in both dimensions. Nonetheless, self-projection in space engaged the medial and lateral parietal cortices, whereas self-projection in time engaged a widespread parietofrontal network. Moreover, while a large distributed network was found for spatial distances, temporal distances specifically engaged the right inferior parietal cortex and the anterior insula. Across these networks, a robust overlap was only found in a small region of the inferior parietal lobe, adding evidence for its role in domain-general egocentric mapping. Our findings suggest that mental travel in time or space capitalizes on egocentric remapping and on distance computation, which are implemented in distinct dimension-specific cortical networks converging in inferior parietal lobe. SIGNIFICANCE STATEMENT: As humans, we can consciously imagine ourselves at a different time (mental time travel) or at a different place (mental space navigation). Are such abilities domain-general, or are the temporal and spatial dimensions of our conscious experience separable? Here, we tested the hypothesis that mental time travel and mental space navigation required the egocentric remapping of events, including the estimation of their distances to the self. We report that, although both remapping and distance computation are foundational for the processing of the temporal and spatial dimensions of our conscious experience, their neuroanatomical implementations were clearly dissociable and engaged distinct parietal and parietofrontal networks for mental space navigation and mental time travel, respectively.

Cognitive mapping in mental time travel and mental space navigation.

The ability to imagine ourselves in the past, in the future or in different spatial locations suggests that the brain can generate cognitive maps that are independent of the experiential self in the here and now. Using three experiments, we asked to which extent Mental Time Travel (MTT; imagining the self in time) and Mental Space Navigation (MSN; imagining the self in space) shared similar cognitive operations. For this, participants judged the ordinality of real historical events in time and in space with respect to different mental perspectives: for instance, participants mentally projected themselves in Paris in nine years, and judged whether an event occurred before or after, or, east or west, of where they mentally stood. In all three experiments, symbolic distance effects in time and space dimensions were quantified using Reaction Times (RT) and Error Rates (ER). When self-projected, participants were slower and were less accurate (absolute distance effects); participants were also faster and more accurate when the spatial and temporal distances were further away from their mental viewpoint (relative distance effects). These effects show that MTT and MSN require egocentric mapping and that self-projection requires map transformations. Additionally, participants' performance was affected when self-projection was made in one dimension but judgements in another, revealing a competition between temporal and spatial mapping (Experiment 2 & 3). Altogether, our findings suggest that MTT and MSN are separately mapped although they require comparable allo- to ego-centric map conversion.

Temporal tuning properties along the human ventral visual stream.

Both our environment and our behavior contain many spatiotemporal regularities. Preferential and differential tuning of neural populations to these regularities can be demonstrated by assessing rate dependence of neural responses evoked during continuous periodic stimulation. Here, we used functional magnetic resonance imaging to measure regional variations of temporal sensitivity along the human ventral visual stream. By alternating one face and one house stimulus, we combined sufficient low-level signal modulation with changes in semantic meaning and could therefore drive all tiers of visual cortex strongly enough to assess rate dependence. We found several dissociations between early visual cortex and middle- and higher-tier regions. First, there was a progressive slowing down of stimulation rates yielding peak responses along the ventral visual stream. This finding shows the width of temporal integration windows to increase at higher hierarchical levels. Next, for fixed rates, early but not higher visual cortex responses additionally depended on the length of stimulus exposure, which may indicate increased persistence of responses to short stimuli at higher hierarchical levels. Finally, attention, which was recruited by an incidental task, interacted with stimulation rate and shifted tuning peaks toward lower frequencies. Together, these findings quantify neural response properties that are likely to be operational during natural vision and that provide putative neurofunctional substrates of mechanisms that are relevant in several psychophysical phenomena as masking and the attentional blink. Moreover, they illustrate temporal constraints for translating the deployment of attention into enhanced neural responses and thereby account for lower limits of attentional dwell time.