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Language is acquired and processed in complex and dynamic naturalistic contexts, involving the simultaneous processing of connected speech, faces, bodies, objects, etc. How words and their associated concepts are encoded in the brain during real-world processing is still unknown. Here, the representational structure of concrete and abstract concepts was investigated during movie watching to address the extent to which brain responses dynamically change depending on visual context. First, across contexts, concrete and abstract concepts are shown to encode different experience-based information in separable sets of brain regions. However, these differences are reduced when multimodal context is considered. Specifically, the response profile of abstract words becomes more concrete-like when these are processed in visual scenes highly related to their meaning. Conversely, when the visual context is unrelated to a given concrete word, the activation pattern resembles more that of abstract conceptual processing. These results suggest that while concepts generally encode habitual experiences, the underlying neurobiological organisation is not fixed but depends dynamically on available contextual information., Competing Interests: VK, GV, JS No competing interests declared, (© 2024, Kewenig et al.)

Videos of magic tricks offer lots of opportunities to study the human mind. They violate the expectations of the viewer, causing prediction errors, misdirect attention, and elicit epistemic emotions. Herein we describe and share the Magic, Memory, and Curiosity (MMC) Dataset where 50 participants watched 36 magic tricks filmed and edited specifically for functional magnetic imaging (fMRI) experiments. The MMC Dataset includes a contextual incentive manipulation, curiosity ratings for the magic tricks, and incidental memory performance tested a week later. We additionally measured individual differences in working memory and constructs relevant to motivated learning. fMRI data were acquired before, during, and after learning. We show that both behavioural and fMRI data are of high quality, as indicated by basic validation analysis, i.e., variance decomposition as well as intersubject correlation and seed-based functional connectivity, respectively. The richness and complexity of the MMC Dataset will allow researchers to explore dynamic cognitive and motivational processes from various angles during task and rest., (© 2024. The Author(s).)

Visual hallucinations can be phenomenologically divided into those of a simple or complex nature. Both simple and complex hallucinations can occur in pathological and non-pathological states, and can also be induced experimentally by visual stimulation or deprivation-for example using a high-frequency, eyes-open flicker (Ganzflicker) and perceptual deprivation (Ganzfeld). Here we leverage the differences in visual stimulation that these two techniques involve to investigate the role of bottom-up and top-down processes in shifting the complexity of visual hallucinations, and to assess whether these techniques involve a shared underlying hallucinatory mechanism despite their differences. For each technique, we measured the frequency and complexity of the hallucinations produced, utilising button presses, retrospective drawing, interviews, and questionnaires. For both experimental techniques, simple hallucinations were more common than complex hallucinations. Crucially, we found that Ganzflicker was more effective than Ganzfeld at eliciting simple hallucinations, while complex hallucinations remained equivalent across the two conditions. As a result, the likelihood that an experienced hallucination was complex was higher during Ganzfeld. Despite these differences, we found a correlation between the frequency and total time spent hallucinating in Ganzflicker and Ganzfeld conditions, suggesting some shared mechanisms between the two methodologies. We attribute the tendency to experience frequent simple hallucinations in both conditions to a shared low-level core hallucinatory mechanism, such as excitability of visual cortex, potentially amplified in Ganzflicker compared to Ganzfeld due to heightened bottom-up input. The tendency to experience complex hallucinations, in contrast, may be related to top-down processes less affected by visual stimulation., (© 2024. The Author(s).)

Most research on the neurobiology of language ignores consciousness and vice versa. Here, language, with an emphasis on inner speech, is hypothesised to generate and sustain self-awareness, i.e., higher-order consciousness. Converging evidence supporting this hypothesis is reviewed. To account for these findings, a 'HOLISTIC' model of neurobiology of language, inner speech, and consciousness is proposed. It involves a 'core' set of inner speech production regions that initiate the experience of feeling and hearing words. These take on affective qualities, deriving from activation of associated sensory, motor, and emotional representations, involving a largely unconscious dynamic 'periphery', distributed throughout the whole brain. Responding to those words forms the basis for sustained network activity, involving 'default mode' activation and prefrontal and thalamic/brainstem selection of contextually relevant responses. Evidence for the model is reviewed, supporting neuroimaging meta-analyses conducted, and comparisons with other theories of consciousness made. The HOLISTIC model constitutes a more parsimonious and complete account of the 'neural correlates of consciousness' that has implications for a mechanistic account of mental health and wellbeing., (Copyright © 2022 The Author. Published by Elsevier Ltd.. All rights reserved.)

We consider the challenges in extracting stimulus-related neural dynamics from other intrinsic processes and noise in naturalistic functional magnetic resonance imaging (fMRI). Most studies rely on inter-subject correlations (ISC) of low-level regional activity and neglect varying responses in individuals. We propose a novel, data-driven approach based on low-rank plus sparse ( [Formula: see text]) decomposition to isolate stimulus-driven dynamic changes in brain functional connectivity (FC) from the background noise, by exploiting shared network structure among subjects receiving the same naturalistic stimuli. The time-resolved multi-subject FC matrices are modeled as a sum of a low-rank component of correlated FC patterns across subjects, and a sparse component of subject-specific, idiosyncratic background activities. To recover the shared low-rank subspace, we introduce a fused version of principal component pursuit (PCP) by adding a fusion-type penalty on the differences between the columns of the low-rank matrix. The method improves the detection of stimulus-induced group-level homogeneity in the FC profile while capturing inter-subject variability. We develop an efficient algorithm via a linearized alternating direction method of multipliers to solve the fused-PCP. Simulations show accurate recovery by the fused-PCP even when a large fraction of FC edges are severely corrupted. When applied to natural fMRI data, our method reveals FC changes that were time-locked to auditory processing during movie watching, with dynamic engagement of sensorimotor systems for speech-in-noise. It also provides a better mapping to auditory content in the movie than ISC.

It is assumed that there are a static set of "language regions" in the brain. Yet, language comprehension engages regions well beyond these, and patients regularly produce familiar "formulaic" expressions when language regions are severely damaged. These suggest that the neurobiology of language is not fixed but varies with experiences, like the extent of word sequence learning. We hypothesized that perceiving overlearned sentences is supported by speech production and not putative language regions. Participants underwent 2 sessions of behavioral testing and functional magnetic resonance imaging (fMRI). During the intervening 15 days, they repeated 2 sentences 30 times each, twice a day. In both fMRI sessions, they "passively" listened to those sentences, novel sentences, and produced sentences. Behaviorally, evidence for overlearning included a 2.1-s decrease in reaction times to predict the final word in overlearned sentences. This corresponded to the recruitment of sensorimotor regions involved in sentence production, inactivation of temporal and inferior frontal regions involved in novel sentence listening, and a 45% change in global network organization. Thus, there was a profound whole-brain reorganization following sentence overlearning, out of "language" and into sensorimotor regions. The latter are generally preserved in aphasia and Alzheimer's disease, perhaps explaining residual abilities with formulaic expressions in both., (© The Author(s) 2021. Published by Oxford University Press.)

Rodent and human studies have implicated an amygdala-prefrontal circuit during threat processing. One possibility is that while amygdala activity underlies core features of anxiety (e.g. detection of salient information), prefrontal cortices (i.e. dorsomedial prefrontal/anterior cingulate cortex) entrain its responsiveness. To date, this has been established in tightly controlled paradigms (predominantly using static face perception tasks) but has not been extended to more naturalistic settings. Consequently, using 'movie fMRI'-in which participants watch ecologically-rich movie stimuli rather than constrained cognitive tasks-we sought to test whether individual differences in anxiety correlate with the degree of face-dependent amygdala-prefrontal coupling in two independent samples. Analyses suggested increased face-dependent superior parietal activation and decreased speech-dependent auditory cortex activation as a function of anxiety. However, we failed to find evidence for anxiety-dependent connectivity, neither in our stimulus-dependent or -independent analyses. Our findings suggest that work using experimentally constrained tasks may not replicate in more ecologically valid settings and, moreover, highlight the importance of testing the generalizability of neuroimaging findings outside of the original context., (Copyright © 2022. Published by Elsevier Ltd.)

The ecology of human language is face-to-face interaction, comprising cues such as prosody, co-speech gestures and mouth movements. Yet, the multimodal context is usually stripped away in experiments as dominant paradigms focus on linguistic processing only. In two studies we presented video-clips of an actress producing naturalistic passages to participants while recording their electroencephalogram. We quantified multimodal cues (prosody, gestures, mouth movements) and measured their effect on a well-established electroencephalographic marker of processing load in comprehension (N400). We found that brain responses to words were affected by informativeness of co-occurring multimodal cues, indicating that comprehension relies on linguistic and non-linguistic cues. Moreover, they were affected by interactions between the multimodal cues, indicating that the impact of each cue dynamically changes based on the informativeness of other cues. Thus, results show that multimodal cues are integral to comprehension, hence, our theories must move beyond the limited focus on speech and linguistic processing.

The role of the cerebellum in speech perception remains a mystery. Given its uniform architecture, we tested the hypothesis that it implements a domain-general predictive mechanism whose role in speech is determined by connectivity. We collated all neuroimaging studies reporting cerebellar activity in the Neurosynth database (n = 8206). From this set, we found all studies involving passive speech and sound perception (n = 72, 64% speech, 12.5% sounds, 12.5% music, and 11% tones) and speech production and articulation (n = 175). Standard and coactivation neuroimaging meta-analyses were used to compare cerebellar and associated cortical activations between passive perception and production. We found distinct regions of perception- and production-related activity in the cerebellum and regions of perception-production overlap. Each of these regions had distinct patterns of cortico-cerebellar connectivity. To test for domain-generality versus specificity, we identified all psychological and task-related terms in the Neurosynth database that predicted activity in cerebellar regions associated with passive perception and production. Regions in the cerebellum activated by speech perception were associated with domain-general terms related to prediction. One hallmark of predictive processing is metabolic savings (i.e., decreases in neural activity when events are predicted). To test the hypothesis that the cerebellum plays a predictive role in speech perception, we examined cortical activation between studies reporting cerebellar activation and those without cerebellar activation during speech perception. When the cerebellum was active during speech perception, there was far less cortical activation than when it was inactive. The results suggest that the cerebellum implements a domain-general mechanism related to prediction during speech perception., (© 2021 Massachusetts Institute of Technology.)

It is well established that speech perception is improved when we are able to see the speaker talking along with hearing their voice, especially when the speech is noisy. While we have a good understanding of where speech integration occurs in the brain, it is unclear how visual and auditory cues are combined to improve speech perception. One suggestion is that integration can occur as both visual and auditory cues arise from a common generator: the vocal tract. Here, we investigate whether facial and vocal tract movements are linked during speech production by comparing videos of the face and fast magnetic resonance (MR) image sequences of the vocal tract. The joint variation in the face and vocal tract was extracted using an application of principal components analysis (PCA), and we demonstrate that MR image sequences can be reconstructed with high fidelity using only the facial video and PCA. Reconstruction fidelity was significantly higher when images from the two sequences corresponded in time, and including implicit temporal information by combining contiguous frames also led to a significant increase in fidelity. A "Bubbles" technique was used to identify which areas of the face were important for recovering information about the vocal tract, and vice versa , on a frame-by-frame basis. Our data reveal that there is sufficient information in the face to recover vocal tract shape during speech. In addition, the facial and vocal tract regions that are important for reconstruction are those that are used to generate the acoustic speech signal., Competing Interests: The authors declare no competing interest., (Copyright © 2020 the Author(s). Published by PNAS.)

Neuroimaging has advanced our understanding of human psychology using reductionist stimuli that often do not resemble information the brain naturally encounters. It has improved our understanding of the network organization of the brain mostly through analyses of 'resting-state' data for which the functions of networks cannot be verifiably labelled. We make a 'Naturalistic Neuroimaging Database' (NNDb v1.0) publically available to allow for a more complete understanding of the brain under more ecological conditions during which networks can be labelled. Eighty-six participants underwent behavioural testing and watched one of 10 full-length movies while functional magnetic resonance imaging was acquired. Resulting timeseries data are shown to be of high quality, with good signal-to-noise ratio, few outliers and low movement. Data-driven functional analyses provide further evidence of data quality. They also demonstrate accurate timeseries/movie alignment and how movie annotations might be used to label networks. The NNDb can be used to answer questions previously unaddressed with standard neuroimaging approaches, progressing our knowledge of how the brain works in the real world.

Stories play a fundamental role in human culture. They provide a mechanism for sharing cultural identity, imparting knowledge, revealing beliefs, reinforcing social bonds and providing entertainment that is central to all human societies. Here we investigated the extent to which the delivery medium of a story (audio or visual) affected self-reported and physiologically measured engagement with the narrative. Although participants self-reported greater involvement for watching video relative to listening to auditory scenes, stronger physiological responses were recorded for auditory stories. Sensors placed at their wrists showed higher and more variable heart rates, greater electrodermal activity, and even higher body temperatures. We interpret these findings as evidence that the stories were more cognitively and emotionally engaging at a physiological level when presented in an auditory format. This may be because listening to a story, rather than watching a video, is a more active process of co-creation, and that this imaginative process in the listener's mind is detectable on the skin at their wrist.

Does "the motor system" play "a role" in speech perception? If so, where, how, and when? We conducted a systematic review that addresses these questions using both qualitative and quantitative methods. The qualitative review of behavioural, computational modelling, non-human animal, brain damage/disorder, electrical stimulation/recording, and neuroimaging research suggests that distributed brain regions involved in producing speech play specific, dynamic, and contextually determined roles in speech perception. The quantitative review employed region and network based neuroimaging meta-analyses and a novel text mining method to describe relative contributions of nodes in distributed brain networks. Supporting the qualitative review, results show a specific functional correspondence between regions involved in non-linguistic movement of the articulators, covertly and overtly producing speech, and the perception of both nonword and word sounds. This distributed set of cortical and subcortical speech production regions are ubiquitously active and form multiple networks whose topologies dynamically change with listening context. Results are inconsistent with motor and acoustic only models of speech perception and classical and contemporary dual-stream models of the organization of language and the brain. Instead, results are more consistent with complex network models in which multiple speech production related networks and subnetworks dynamically self-organize to constrain interpretation of indeterminant acoustic patterns as listening context requires., (Copyright © 2016. Published by Elsevier Inc.)