Functional Magnetic Resonance Imaging of Human Brain during Rest and Viewing Movies

Neurotieteellisissä kokeissa on perinteisesti käytetty tarkasti kontrolloituja koeasetelmia ja yksinkertaisia ärsykkeitä aivojen toimintaa tutkittaessa. Viime aikoina tutkimusta on pyritty laajentamaan luonnollisempiin asetelmiin. Aivojen toimintaa on mitattu esimerkiksi koehenkilöiden katsellessa elokuvaa tai ?lepotilassa? levollisen valveillaolon aikana ilman mitään erityistä tehtävää. Tässä diplomityössä tutkitaan ihmisen aivotoimintaa luonnollisen kaltaisissa tilanteissa riippumattomien komponenttien analyysin (ICA) avulla. Lepotilassa löydettyjä verkostoja verrataan kolmessa tilanteessa; levossa ennen elokuvan (Tulitikkutehtaan tyttö, Aki Kaurismäki, 1990) katsomista, elokuvan aikana ja levossa elokuvan katsomisen jälkeen. ICA:lla löydettyjen lähde-estimaattien vakautta tutkittiin bootstrap-laskennalla. Elokuvasta annotoituja ärsykepiirteitä verrattiin niiden aivoverkostojen aikakäytökseen, joiden aikakäyttäytyminen oli samankaltaista eri koehenkilöillä. Ärsykepiirteiden avulla vertailtiin lisäksi ICA:n erottamien verkostojen laajuutta yksittäisten ärsykepiirteiden kanssa korreloituviin aivoalueisiin. ICA onnistui erottamaan merkityksellisiä toiminnallisia verkostoja aivoissa. Verkostojen laajuudessa tapahtui vain vähän muutoksia eri koetilanteiden välillä. Luonnollinen katselutilanne kuitenkin mahdollisti komponenttien jakamisen pienempiin toiminnallisiin yksiköihin kuin lepotilassa sekä data-lähtöisin, että mallipohjaisin analyysimenetelmin. Eri koehenkilöillä samankaltaisesti käyttäytyneet riippumattomat komponentit paikantuivat lähinnä aistispesifeille ja assosiaatioalueille aivojen temporaali-, oksipitaali- ja parietaalilohkoilla. Osalla komponenteista aikakäytöksen havaittiin seuraavan elokuvasta annotoituja piirteitä.Neuroscientific research of human brain function has traditionally relied on highly controlled experiments with relatively simple stimuli. Recently effort has been directed toward expanding the research into a more naturalistic context. Brain function has been measured for example during viewing movies and in a "resting state" in absence of as specific task. In this thesis, independent component analysis (ICA) is used to research human brain function in naturalistic settings. The brain networks observed at rest are compared in three conditions; resting before watching a movie (The Match Factory Girl, Aki Kaurismäki, 1990), during the movie, and resting after the movie. The stability of the source estimates obtained using ICA was evaluated using bootstrapping. The temporal structure of the independent components (ICs) was compared to stimulus features annotated from the movie. Similarity of the networks' activation time courses across subjects was used to select components that were compared with specific stimulus features. These features were also correlated directly to the preprocessed data to validate the results of ICA. ICA was successful at separating meaningful functional networks within the brain. The extent of the networks changed very little between the different conditions. However, the natural viewing condition allowed the ICs to be separated into smaller functional units than was achievable during rest using both data-driven and model based methods. The independent components exhibiting significant temporal similarity between subjects were highly concentrated in the sensory and associative areas of the temporal, occipital and parietal lobes. The activity of some ICs was found to follow distinct features of the movie

Bayesian modelling captures inter-individual differences in social belief computations in the putamen and insula

Computational models of social learning and decision-making provide mechanistic tools to investigate the neural mechanisms that are involved in understanding other people. While most studies employ explicit instructions to learn from social cues, everyday life is characterized by the spontaneous use of such signals (e.g., the gaze of others) to infer on internal states such as intentions. To investigate the neural mechanisms of the impact of gaze cues on learning and decision-making, we acquired behavioural and fMRI data from 50 participants performing a probabilistic task, in which cards with varying winning probabilities had to be chosen. In addition, the task included a computer-generated face that gazed towards one of these cards providing implicit advice. Participants\u2019 individual belief trajectories were inferred using a hierarchical Gaussian filter (HGF) and used as predictors in a linear model of neuronal activation. During learning, social prediction errors were correlated with activity in inferior frontal gyrus and insula. During decision-making, the belief about the accuracy of the social cue was correlated with activity in inferior temporal gyrus, putamen and pallidum while the putamen and insula showed activity as a function of individual differences in weighting the social cue during decision-making. Our findings demonstrate that model-based fMRI can give insight into the behavioural and neural aspects of spontaneous social cue integration in learning and decision-making. They provide evidence for a mechanistic involvement of specific components of the basal ganglia in subserving these processes

Increased functional coupling of the left amygdala and medial prefrontal cortex during the perception of communicative point-light stimuli

Interpersonal predictive coding (IPPC) describes the behavioral phenomenon whereby seeing a communicative rather than an individual action helps to discern a masked second agent. As little is known, yet, about the neural correlates of IPPC, we conducted a functional magnetic resonance imaging study in a group of 27 healthy participants using point-light displays of moving agents embedded in distractors. We discovered that seeing communicative compared to individual actions was associated with higher activation of right superior frontal gyrus, whereas the reversed contrast elicited increased neural activation in an action observation network that was activated during all trials. Our findings, therefore, potentially indicate the formation of action predictions and a reduced demand for executive control in response to communicative actions. Further, in a regression analysis, we revealed that increased perceptual sensitivity was associated with a deactivation of the left amygdala during the perceptual task. A consecutive psychophysiological interaction analysis showed increased connectivity of the amygdala with medial prefrontal cortex in the context of communicative compared to individual actions. Thus, whereas increased amygdala signaling might interfere with task-relevant processes, increased co-activation of the amygdala and the medial prefrontal cortex in a communicative context might represent the integration of mentalizing computations

Mental Action Simulation Synchronizes Action-Observation Circuits across Individuals

A frontoparietal action–observation network (AON) has been proposed to support understanding others' actions and goals. We show that the AON "ticks together" in human subjects who are sharing a third person's feelings. During functional magnetic resonance imaging, 20 volunteers watched movies depicting boxing matches passively or while simulating a prespecified boxer's feelings. Instantaneous intersubject phase synchronization (ISPS) was computed to derive multisubject voxelwise similarity of hemodynamic activity and inter-area functional connectivity. During passive viewing, subjects' brain activity was synchronized in sensory projection and posterior temporal cortices. Simulation induced widespread increase of ISPS in the AON (premotor, posterior parietal, and superior temporal cortices), primary and secondary somatosensory cortices, and the dorsal attention circuits (frontal eye fields, intraparietal sulcus). Moreover, interconnectivity of these regions strengthened during simulation. We propose that sharing a third person's feelings synchronizes the observer's own brain mechanisms supporting sensations and motor planning, thereby likely promoting mutual understanding.Peer reviewe

Lipreading a naturalistic narrative in a female population : Neural characteristics shared with listening and reading

Publisher Copyright: © 2022 The Authors. Brain and Behavior published by Wiley Periodicals LLC.Introduction: Few of us are skilled lipreaders while most struggle with the task. Neural substrates that enable comprehension of connected natural speech via lipreading are not yet well understood. Methods: We used a data-driven approach to identify brain areas underlying the lipreading of an 8-min narrative with participants whose lipreading skills varied extensively (range 6–100%, mean = 50.7%). The participants also listened to and read the same narrative. The similarity between individual participants’ brain activity during the whole narrative, within and between conditions, was estimated by a voxel-wise comparison of the Blood Oxygenation Level Dependent (BOLD) signal time courses. Results: Inter-subject correlation (ISC) of the time courses revealed that lipreading, listening to, and reading the narrative were largely supported by the same brain areas in the temporal, parietal and frontal cortices, precuneus, and cerebellum. Additionally, listening to and reading connected naturalistic speech particularly activated higher-level linguistic processing in the parietal and frontal cortices more consistently than lipreading, probably paralleling the limited understanding obtained via lip-reading. Importantly, higher lipreading test score and subjective estimate of comprehension of the lipread narrative was associated with activity in the superior and middle temporal cortex. Conclusions: Our new data illustrates that findings from prior studies using well-controlled repetitive speech stimuli and stimulus-driven data analyses are also valid for naturalistic connected speech. Our results might suggest an efficient use of brain areas dealing with phonological processing in skilled lipreaders.Peer reviewe

Aberrant computational mechanisms of social learning and decision-making in schizophrenia and borderline personality disorder

Psychiatric disorders are ubiquitously characterized by debilitating social impairments. These difficulties are thought to emerge from aberrant social inference. In order to elucidate the underlying computational mechanisms, patients diagnosed with major depressive disorder (N = 29), schizophrenia (N = 31), and borderline personality disorder (N = 31) as well as healthy controls (N = 34) performed a probabilistic reward learning task in which participants could learn from social and nonsocial information. Patients with schizophrenia and borderline personality disorder performed more poorly on the task than healthy controls and patients with major depressive disorder. Broken down by domain, borderline personality disorder patients performed better in the social compared to the non-social domain. In contrast, controls and MDD patients showed the opposite pattern and SCZ patients showed no difference between domains. In effect, borderline personality disorder patients gave up a possible overall performance advantage by concentrating their learning in the social at the expense of the non-social domain. We used computational modeling to assess learning and decision-making parameters estimated for each participant from their behavior. This enabled additional insights into the underlying learning and decision-making mechanisms. Patients with borderline personality disorder showed slower learning from social and non-social information and an exaggerated sensitivity to changes in environmental volatility, both in the non-social and the social domain, but more so in the latter. Regarding decision-making the modeling revealed that compared to controls and major depression patients, patients with borderline personality disorder and schizophrenia showed a stronger reliance on social relative to non-social information when making choices. Depressed patients did not differ significantly from controls in this respect. Overall, our results are consistent with the notion of a general interpersonal hypersensitivity in borderline personality disorder and schizophrenia based on a shared computational mechanism characterized by an over-reliance on beliefs about others in making decisions and by an exaggerated need to make sense of others during learning specifically in borderline personality disorder

Dissociable Roles of Cerebral mu-Opioid and Type 2 Dopamine Receptors in Vicarious Pain: A Combined PET-fMRI Study

Neuroimaging studies have shown that seeing others in pain activates brain regions that are involved in first-hand pain, suggesting that shared neuromolecular pathways support processing of first-hand and vicarious pain. We tested whether the dopamine and opioid neurotransmitter systems involved in nociceptive processing also contribute to vicarious pain experience. We used in vivo positron emission tomography to quantify type 2 dopamine and mu-opioid receptor (D2R and MOR, respectively) availabilities in brains of 35 subjects. During functional magnetic resonance imaging, the subjects watched short movie clips depicting persons in painful and painless situations. Painful scenes activated pain-responsive brain regions including anterior insulae, thalamus and secondary somatosensory cortices, as well as posterior superior temporal sulci. MOR availability correlated negatively with the haemodynamic responses during painful scenes in anterior and posterior insulae, thalamus, secondary and primary somatosensory cortices, primary motor cortex, and superior temporal sulci. MOR availability correlated positively with orbitofrontal haemodynamic responses during painful scenes. D2R availability was not correlated with the haemodynamic responses in any brain region. These results suggest that the opioid system contributes to neural processing of vicarious pain, and that interindividual differences in opioidergic system could explain why some individuals react more strongly than others to seeing pain

Brain-to-brain hyperclassification reveals action-specific motor mapping of observed actions in humans

Seeing an action may activate the corresponding action motor code in the observer. It remains unresolved whether seeing and performing an action activates similar action-specific motor codes in the observer and the actor. We used novel hyperclassification approach to reveal shared brain activation signatures of action execution and observation in interacting human subjects. In the first experiment, two "actors" performed four types of hand actions while their haemodynamic brain activations were measured with 3-T functional magnetic resonance imaging (fMRI). The actions were videotaped and shown to 15 "observers" during a second fMRI experiment. Eleven observers saw the videos of one actor, and the remaining four observers saw the videos of the other actor. In a control fMRI experiment, one of the actors performed actions with closed eyes, and five new observers viewed these actions. Bayesian canonical correlation analysis was applied to functionally realign observers' and actors' fMRI data. Hyperclassification of the seen actions was performed with Bayesian logistic regression trained on actors' data and tested with observers' data. Without the functional realignment, between-subjects accuracy was at chance level. With the realignment, the accuracy increased on average by 15 percentage points, exceeding both the chance level and the accuracy without functional realignment. The highest accuracies were observed in occipital, parietal and premotor cortices. Hyperclassification exceeded chance level also when the actor did not see her own actions. We conclude that the functional brain activation signatures underlying action execution and observation are partly shared, yet these activation signatures may be anatomically misaligned across individuals

Stimulus-Related Independent Component and Voxel-Wise Analysis of Human Brain Activity during Free Viewing of a Feature Film

Understanding how the brain processes stimuli in a rich natural environment is a fundamental goal of neuroscience. Here, we showed a feature film to 10 healthy volunteers during functional magnetic resonance imaging (fMRI) of hemodynamic brain activity. We then annotated auditory and visual features of the motion picture to inform analysis of the hemodynamic data. The annotations were fitted to both voxel-wise data and brain network time courses extracted by independent component analysis (ICA). Auditory annotations correlated with two independent components (IC) disclosing two functional networks, one responding to variety of auditory stimulation and another responding preferentially to speech but parts of the network also responding to non-verbal communication. Visual feature annotations correlated with four ICs delineating visual areas according to their sensitivity to different visual stimulus features. In comparison, a separate voxel-wise general linear model based analysis disclosed brain areas preferentially responding to sound energy, speech, music, visual contrast edges, body motion and hand motion which largely overlapped the results revealed by ICA. Differences between the results of IC- and voxel-based analyses demonstrate that thorough analysis of voxel time courses is important for understanding the activity of specific sub-areas of the functional networks, while ICA is a valuable tool for revealing novel information about functional connectivity which need not be explained by the predefined model. Our results encourage the use of naturalistic stimuli and tasks in cognitive neuroimaging to study how the brain processes stimuli in rich natural environments