FMRI

Trait empathy is an essential personality feature in the intricacy of typical social inclinations of individuals. Empathy is likely supported by multilevel neuronal network functioning, whereas local topological properties determine network integrity. In the present functional MRI study (N = 116), we aimed to trace empathic traits to the intrinsic brain network architecture. Empathy was conceived as composed of two dimensions within the concept of pre-reflective, intersubjective understanding. Vicarious experience consists of the tendency to resonate with the feelings of other individuals, whereas intuitive understanding refers to a natural awareness of others’ emotional states. Analyses of graph theoretical measures of centrality showed a relationship between the fronto-parietal network and psychometric measures of vicarious experience, whereas intuitive understanding was associated with sensorimotor and subcortical networks. Salience network regions could constitute hubs for information processing underlying both dimensions. The network properties related to empathy dimensions mainly concern inter-network information flow. Moreover, interaction effects implied several sex differences in the relationship between functional network organization and trait empathy. These results reveal that distinct intrinsic topological network features explain individual differences in separate dimensions of intersubjective understanding. The findings could help understand the impact of brain damage or stimulation through alterations of empathy-related network integrity.

The division of human learning systems into reward and punishment opponent modules is still a debated issue. While the implication of ventral prefrontostriatal circuits in reward-based learning is well established, the neural underpinnings of punishmentbased learning remain unclear. To elucidate the causal implication of brain regions that were related to punishment learning in a previous functional neuroimaging study, we tested the effects of brain damage on behavioral performance, using the same task contrasting monetary gains and losses. Cortical and subcortical candidate regions, the anterior insula and dorsal striatum, were assessed in patients presenting brain tumor and Huntington disease, respectively. Both groups exhibited selective impairment of punishment-based learning. Computational modeling suggested complementary roles for these structures: the anterior insula might be involved in learning the negative value of loss-predicting cues, whereas the dorsal striatum might be involved in choosing between those cues so as to avoid the worst.

The most common form of synaesthesia is grapheme-colour synaesthesia. However, rarer forms of synaesthesia also exist, such as word-gustatory and olfactory-gustatory synaesthesia, whereby a word or smell will induce a specific. In this study we describe a single individual (LJ) who experiences a concurrent olfactory stimulus when presented with congruent visual images. For some visual stimuli, he perceives a strong and automatic olfactory percept, which has existed throughout his life. In this study, we explore whether his experiences are a new form of synaesthesia or simply vivid imagery. Unlike other forms of synaesthesia, the concurrent odour is congruent to the visual inducer. For example, a photograph of dress shoes will elicit the smell of leather. We presented LJ and several control participants with 75 images of everyday objects. Their task was to indicate the strength of any perceived odours induced by the visual images. LJ rated several of the images as inducing a concurrent odour, while controls did not have any such percept. Images that LJ reported as inducing the strongest odours were used, along with colour-matched control images, in the context of an fMRI experiment. Participants were given a one-back task to maintain attention. A block-design odour localizer was presented to localize the piriform cortex (primary olfactory cortex). We found an increased BOLD response in the piriform cortex for the odour-inducing images compared to the control images in LJ. There was no difference in BOLD response between these two stimulus types in the control participants. A subsequent olfactory imagery task did not elicit enhanced activity in the piriform cortex in LJ, suggesting his perceptual experiences may not be based on olfactory imagery.

Background: Analysis of the human connectome using functional magnetic resonance imaging (fMRI) started in the mid-1990s and attracted increasing attention in attempts to discover the neural underpinnings of human cognition and neurological disorders. In general, brain connectivity patterns from fMRI data are classified as statistical dependencies (functional connectivity) or causal interactions (effective connectivity) among various neural units. Computational methods, especially graph theory-based methods, have recently played a significant role in understanding brain connectivity architecture.

Objectives: Thanks to the emergence of graph theoretical analysis, the main purpose of the current paper is to systematically review how brain properties can emerge through the interactions of distinct neuronal units in various cognitive and neurological applications using fMRI. Moreover, this article provides an overview of the existing functional and effective connectivity methods used to construct the brain network, along with their advantages and pitfalls.

Methods: In this systematic review, the databases Science Direct, Scopus, arXiv, Google Scholar, IEEE Xplore, PsycINFO, PubMed, and SpringerLink are employed for exploring the evolution of computational methods in human brain connectivity from 1990 to the present, focusing on graph theory. The Cochrane Collaboration's tool was used to assess the risk of bias in individual studies.

Results: Our results show that graph theory and its implications in cognitive neuroscience have attracted the attention of researchers since 2009 (as the Human Connectome Project launched), because of their prominent capability in characterizing the behavior of complex brain systems. Although graph theoretical approach can be generally applied to either functional or effective connectivity patterns during rest or task performance, to date, most articles have focused on the resting-state functional connectivity.

Conclusions: This review provides an insight into how to utilize graph theoretical measures to make neurobiological inferences regarding the mechanisms underlying human cognition and behavior as well as different brain disorders.

We examined the neural basis of self-regulation in individuals from a cohort of preschoolers who performed the delay-ofgratification task 4 decades ago. Nearly 60 individuals, now in their mid-forties, were tested on "hot" and "cool" versions of a go/ nogo task to assess whether delay of gratification in childhood predicts impulse control abilities and sensitivity to alluring cues (happy faces). Individuals who were less able to delay gratification in preschool and consistently showed low self-control abilities in their twenties and thirties performed more poorly than did high delayers when having to suppress a response to a happy face but not to a neutral or fearful face. This finding suggests that sensitivity to environmental hot cues plays a significant role in individuals' ability to suppress actions toward such stimuli. A subset of these participants (n = 26) underwent functional imaging for the first time to test for biased recruitment of frontostriatal circuitry when required to suppress responses to alluring cues. Whereas the prefrontal cortex differentiated between nogo and go trials to a greater extent in high delayers, the ventral striatum showed exaggerated recruitment in low delayers. Thus, resistance to temptation as measured originally by the delay-of-gratification task is a relatively stable individual difference that predicts reliable biases in frontostriatal circuitries that integrate motivational and control processes.

Is it possible for neural responses to others' rewards to be as strong as those for the self? Although prior fMRI studies have demonstrated that watching others get rewards can activate one's own reward centers, such vicarious reward activation has always been less strong than responses to rewards for oneself. In the present study we manipulated participants' self-construal (independent vs. interdependent) and found that, when an independent selfconstrual was primed, subjects showed greater activation in the bilateral ventral striatum in response to winning money for the self (vs. for a friend) during a gambling game. However, priming an interdependent self-construal resulted in comparable activation in these regions in response to winning money for the self and for a friend. Our findings suggest that interdependence may cause people to experience rewards for a close other as strongly as they experience rewards for the self.

The impulsive behavior that is often characteristic of adolescence may reflect underlying neurodevelopmental processes. Moreover, impulsivity is a multi-dimensional construct, and it is plausible that distinct brain networks contribute to its different cognitive, clinical and behavioral aspects. As these networks have not yet been described, we identified distinct cortical and subcortical networks underlying successful inhibitions and inhibition failures in a large sample (n = 1,896) of 14-year-old adolescents. Different networks were associated with drug use (n = 1,593) and attention-deficit hyperactivity disorder symptoms (n = 342). Hypofunctioning of a specific orbitofrontal cortical network was associated with likelihood of initiating drug use in early adolescence. Right inferior frontal activity was related to the speed of the inhibition process (n = 826) and use of illegal substances and associated with genetic variation in a norepinephrine transporter gene (n = 819). Our results indicate that both neural endophenotypes and genetic variation give rise to the various manifestations of impulsive behavior.

Aim: In recent years, connectivity studies using neuroimaging data have increased the understanding of the organization of large-scale structural and functional brain networks. However, data analysis is time consuming as rigorous procedures must be assured, from structuring data and pre-processing to modality specific data procedures. Until now, no single toolbox was able to perform such investigations on truly multimodal image data from beginning to end, including the combination of different connectivity analyses. Thus, we have developed the Multimodal Imaging Brain Connectivity Analysis (MIBCA) toolbox with the goal of diminishing time waste in data processing and to allow an innovative and comprehensive approach to brain connectivity. Materials and Methods: The MIBCA toolbox is a fully automated all-in-one connectivity toolbox that offers pre-processing, connectivity and graph theoretical analyses of multimodal image data such as diffusion-weighted imaging, functional magnetic resonance imaging (fMRI) and positron emission tomography (PET). It was developed in MATLAB environment and pipelines well-known neuroimaging softwares such as Freesurfer, SPM, FSL, and Diffusion Toolkit. It further implements routines for the construction of structural, functional and effective or combined connectivity matrices, as well as, routines for the extraction and calculation of imaging and graph-theory metrics, the latter using also functions from the the Brain Connectivity Toolbox. Finally, the toolbox performs group statistical analysis and enables data visualization in the form of matrices, 3D brain graphs and connectograms. In this paper the MIBCA toolbox is presented by illustrating its capabilities using multimodal image data from a group of 35 healthy subjects (19-73 years old) with volumetric T1-weighted, diffusion tensor imaging, and resting state fMRI data, and 10 subjets with 18F-Altanserin PET data also. Results: It was observed both a high inter-hemispheric symmetry and an intra-hemispheric modularity associated with structural data, whilst functional data presented lower inter-hemispheric symmetry and a high inter-hemispheric modularity. Furthermore, when testing for differences between two subgroups (<40 and >40 years old adults) we observed a significant reduction in the volume and thickness, and an increase in the mean diffusivity of most of the subcortical/cortical regions. Conclusion: While bridging the gap between the high numbers of packages and tools widely available for the neuroimaging community in one toolbox, MIBCA also offers different possibilities for combining, analysing and visualising data in novel ways, enabling a better understanding of the human brain. 11 PrePrints For a long time there has been an interest in unravelling the mechanisms and circuitry 14 that allow the human being to perform very complex tasks. At the microscale, one of the 15 first attempts was to undergo post-mortem dissections of neural tissue and try to infer 16 the architecture of different neuro-anatomical systems (Buren and Baldwin, 1958). To 17 distinguish between different types of neurons (the functional and structural unit of the 18 central nervous system) histological staining was used (Eickhoff et al., 2006). However, 19 these studies were not able to show how structure is linked to individual functions. The 20 first results were obtained by the use of different techniques such as animal axonal 21 tracing, which allows to undercover the neural connections from its origin to where 22 they project (Schmahmann et al., 2007). Although such studies lead to an increased 23 knowledge of the neural connectivity patterns at the microscale, a further step is still 24 necessary to understand brain connectivity at a macroscale level (Dell'Acqua et al., 25 2013). 26 The motivation of the study of macroscale brain connectivity is then to map different 27 patterns of activation and different routes of information that link highly specialized 28 centres of information and explain their integration in the major network (Rubinov and 29 Sporns, 2010).

Two lines of evidence indicate that there exists a reciprocal inhibitory relationship between opposed brain net- works. First, most attention-demanding cognitive tasks activate a stereotypical set of brain areas, known as the task-positive network and simultaneously deactivate a different set of brain regions, commonly referred to as the task negative or default mode network. Second, functional connectivity analyses show that these same opposed networks are anti-correlated in the resting state. We hypothesize that these reciprocally inhibitory effects reflect two incompatible cognitive modes, each of which may be directed towards understanding the external world. Thus, engaging one mode activates one set of regions and suppresses activity in the other. We test this hypothesis by identifying two types of problem-solving task which, on the basis of prior work, have been consistently asso- ciated with the task positive and task negative regions: tasks requiring social cognition, i.e., reasoning about the mental states of other persons, and tasks requiring physical cognition, i.e., reasoning about the causal/mechanical properties of inanimate objects. Social and mechanical reasoning tasks were presented to neurologically normal participants during fMRI. Each task type was presented using both text and video clips. Regardless of presenta- tion modality, we observed clear evidence of reciprocal suppression: social tasks deactivated regions associated with mechanical reasoning and mechanical tasks deactivated regions associated with social reasoning. These findings are not explained by self-referential processes, task engagement, mental simulation, mental time travel or external vs. internal attention, all factors previously hypothesized to explain default mode network activity. Analyses of resting state data revealed a close match between the regions our tasks identified as reciprocally inhibitory and regions of maximal anti-correlation in the resting state. These results indicate the reciprocal inhi- bition is not attributable to constraints inherent in the tasks, but is neural in origin. Hence, there is a physiological constraint on our ability to simultaneously engage two distinct cognitive modes. Further work is needed to more precisely characterize these opposing cognitive domains.

Aiming to provide a tentative framework for the study of the neural correlates of aesthetic preference, we review three recent neuroimaging studies carried out with the purpose of locating brain activity associated with decisions about the beauty of visual stimuli (Cela-Conde et al., 2004; Kawabata and Zeki, 2004; Vartanian and Goel, 2004). We find that the results of the three studies are not in line with previous neuropsychological data. Moreover, there are no coincidences among their results. However, when they are mapped on to Chatterjee’s (2003) neuropsychological model of aesthetic preference it becomes clear that neuroimaging data are not contradictory, but complementary, and their interpretation is enriched. The results of these studies suggest that affective processes have an important role in aesthetic preference, and that they are integrated with cognitive processes to reach a decision regarding the beauty of visual stimuli. Future studies must aim to clarify whether certain methodological procedures are better suited to study any of the particular cognitive operations involved in aesthetic preference, and ascertain the extent to which the proposed framework is compatible with the aesthetic appreciation of musical stimuli.

Keywords: Brain; fMRI; MEG; aesthetic preference; beauty.

We investigated a unique way in which adolescent peer influence occurs on social media. We developed a novel
functional MRI (fMRI) paradigm to simulate Instagram, a popular social photo-sharing tool, and measured adolescents’
behavioral and neural responses to likes, a quantifiable form of social endorsement and potential source of peer
influence. Adolescents underwent fMRI while viewing photos ostensibly submitted to Instagram. They were more
likely to like photos depicted with many likes than photos with few likes; this finding showed the influence of virtual
peer endorsement and held for both neutral photos and photos of risky behaviors (e.g., drinking, smoking). Viewing
photos with many (compared with few) likes was associated with greater activity in neural regions implicated in
reward processing, social cognition, imitation, and attention. Furthermore, when adolescents viewed risky photos (as
opposed to neutral photos), activation in the cognitive-control network decreased. These findings highlight possible
mechanisms underlying peer influence during adolescence.

To cope with the increasing economic complexity of modern life we need a better financial education what implies a better knowledge of how our brain process financial decision making. This is the subject of Neurofinances an emerging multidisciplinary area of research at the frontiers of Neurosciences, Economy, Finances and Accounting. Taking advantage of the new non-invasive Neurosciences techniques to study the human brain, Neurofinances is investigating the brain activity associated with financial decision. Here we discuss how Functional Magnetic Ressonance Imaging (fMRI) and Electroencephalogram (EEG) are being used in these studies. A short survey of fMRI studies is presented. Because we believe that EEG is the tool of choice for studying decision making, we present some results from our group on stock market investment decision. Finally, we conclude that how this kind of knowledge may be of guidance on financial education.

The multi-dimensional nature of pain renders difficult a holistic understanding of it. The conceptual framework of pain is said to be cognitive-evaluative, in addition to being sensory-discriminative and affective-motivational. To compare participants' brain-behavior response before and after a 6-week mindfulness-based stress reduction training course on mindfulness in relation to pain modulation, three questionnaires (the Dallas Pain Questionnaire, Short Form McGill Pain Questionnaire-SFMPQ, and Kentucky Inventory of Mindfulness) as well as resting-state functional magnetic resonance imaging were administered to participants, divided into a pain-afflicted group (N = 18) and a control group (N = 16). Our results showed that the pain-afflicted group experienced significantly less pain after the mindfulness treatment than before, as measured by the SFMPQ. In conjunction, an increased connection from the anterior insular cortex (AIC) to the dorsal anterior midcingulate cortex (daMCC) was observed in the post-training pain-afflicted group and a significant correlation was found between AIC-daMCC connectivity and SFMPQ scores. The results suggest that mindfulness training can modulate the brain network dynamics underlying the subjective experience of pain.

В докладе представлены результаты первичного корпусного анализа, направленного на поиск стимульных материалов для двух серий экспериментов (психолингвистического и с использованием функционально-резонансной томографии). Эксперименты призваны пролить свет на восприятие речевых сбоев и прагматических мануальных жестов — как по отдельности, так и связи между собой. Показано, что характеристики естественного дискурса существенно затрудняют поиск требуемых для экспериментов фрагментов.