Increased neural activity of right temporo-parietal junction causes different effect on altruism in situations of advantageous and disadvantageous inequity.

Altruism is defined as the performance of "costly acts that confer economic benefits on other individuals", which is one of the major puzzles in the behavioural sciences today. Altruistic behaviour not only facilitates interpersonal adaptation and harmony but also enhances social welfare and social responsibility. The right temporo-parietal junction (rTPJ) has been proposed as playing a key role in guiding human altruistic behaviour, but its precise functional contribution to altruistic behaviour in situations of advantageous and disadvantageous inequity remains unclear. The purpose of this study was to modulate the activation of the rTPJ through transcranial direct current stimulation (tDCS) in order to clarify the causal role of the rTPJ in altruistic behaviour in situations of advantageous and disadvantageous inequity. A total of 106 participants were randomly assigned to one of three stimulation conditions: anodal tDCS stimulation on the rTPJ; sham tDCS stimulation on the rTPJ and anodal tDCS stimulation on the primary visual cortex (VC)as the control group, and. After 20 min of stimulation, participants undertook a modified dictator game that measured altruistic behaviour. Mixed-effect logistic regressions were applied to statistical analyses in this study. The results indicated that anodal tDCS over the rTPJ increased participants' altruistic tendency by increasing their tendency to choose altruistic options in trials with higher cost, as well as their tendency to behave altruistically in situations of advantageous but not disadvantageous inequity. These results suggested that increased neural activity of the rTPJ leads to different impacts on altruism in these two different inequity situations.

Mentalizing in an economic games context is associated with enhanced activation and connectivity in the left temporoparietal junction.

Prior studies in Social Neuroeconomics have consistently reported activation in social cognition regions during interactive economic games, suggesting mentalizing during economic choice. Such mentalizing occurs during active participation in the game, as well as during passive observation of others' interactions. We designed a novel version of the classic false-belief task (FBT) in which participants read vignettes about interactions between agents in the ultimatum and trust games and were subsequently asked to infer the agents' beliefs. We compared activation patterns during the economic games FBT to those during the classic FBT using conjunction analyses. We find significant overlap in the left temporoparietal junction (TPJ) and dorsal medial prefrontal cortex, as well as the temporal pole (TP) during two task phases: belief formation and belief inference. Moreover, generalized Psychophysiological Interaction (gPPI) analyses show that during belief formation, the right TPJ is a target of both the left TPJ and the right TP seed regions, whereas during belief inferences all seed regions show interconnectivity with each other. These results indicate that across different task types and phases, mentalizing is associated with activation and connectivity across central nodes of the social cognition network. Importantly, this is the case for both the novel economic games and the classic FBTs.

Parametric Cognitive Load Reveals Hidden Costs in the Neural Processing of Perfectly Intelligible Degraded Speech.

Speech is often degraded by environmental noise or hearing impairment. People can compensate for degradation, but this requires cognitive effort. Previous research has identified frontotemporal networks involved in effortful perception, but materials in these works were also less intelligible, and so it is not clear whether activity reflected effort or intelligibility differences. We used functional magnetic resonance imaging to assess the degree to which spoken sentences were processed under distraction and whether this depended on speech quality even when intelligibility of degraded speech was matched to that of clear speech (close to 100%). On each trial, male and female human participants either attended to a sentence or to a concurrent multiple object tracking (MOT) task that imposed parametric cognitive load. Activity in bilateral anterior insula reflected task demands; during the MOT task, activity increased as cognitive load increased, and during speech listening, activity increased as speech became more degraded. In marked contrast, activity in bilateral anterior temporal cortex was speech selective and gated by attention when speech was degraded. In this region, performance of the MOT task with a trivial load blocked processing of degraded speech, whereas processing of clear speech was unaffected. As load increased, responses to clear speech in these areas declined, consistent with reduced capacity to process it. This result dissociates cognitive control from speech processing; substantially less cognitive control is required to process clear speech than is required to understand even very mildly degraded, 100% intelligible speech. Perceptual and control systems clearly interact dynamically during real-world speech comprehension.SIGNIFICANCE STATEMENT Speech is often perfectly intelligible even when degraded, for example, by background sound, phone transmission, or hearing loss. How does degradation alter cognitive demands? Here, we use fMRI to demonstrate a novel and critical role for cognitive control in the processing of mildly degraded but perfectly intelligible speech. We compare speech that is matched for intelligibility but differs in putative control demands, dissociating cognitive control from speech processing. We also impose a parametric cognitive load during perception, dissociating processes that depend on tasks from those that depend on available capacity. Our findings distinguish between frontal and temporal contributions to speech perception and reveal a hidden cost to processing mildly degraded speech, underscoring the importance of cognitive control for everyday speech comprehension.

Effects of Thai Local Ingredient Odorants, Litsea cubeba and Garlic Essential Oils, on Brainwaves and Moods.

The functional food market is growing with a compound annual growth rate of 7.9%. Thai food recipes use several kinds of herbs. Lemongrass, garlic, and turmeric are ingredients used in Thai curry paste. Essential oils released in the preparation step create the flavor and fragrance of the famous tom yum and massaman dishes. While the biological activities of these ingredients have been investigated, including the antioxidant, anti-inflammatory, and antimicrobial activities, there is still a lack of understanding regarding the responses to the essential oils of these plants. To investigate the effects of essential oil inhalation on the brain and mood responses, electroencephalography was carried out during the non-task resting state, and self-assessment of the mood state was performed. The essential oils were prepared in several dilutions in the range of the supra-threshold level. The results show that Litsea cubeba oil inhalation showed a sedative effect, observed from alpha and beta wave power reductions. The frontal and temporal regions of the brain were involved in the wave alterations. Garlic oil increased the alpha wave power at lower concentrations; however, a sedative effect was also observed at higher concentrations. Lower dilution oil induced changes in the fast alpha activity in the frontal region. The alpha and beta wave powers were decreased with higher dilution oils, particularly in the temporal, parietal, and occipital regions. Both Litsea cubeba and turmeric oils resulted in better positive moods than garlic oil. Garlic oil caused more negative moods than the others. The psychophysiological activities and the related brain functions require further investigation. The knowledge obtained from this study may be used to design functional food products.

Modulating the activity of right temporo-parietal junction increases bidding behavior in lottery contests.

Contest often involves bids that are higher than the Nash equilibrium, and overbidding behaviour closely relates to personal reasoning and judgement. The right temporo-parietal junction (rTPJ) plays an important role in social, cognitive and inference decision-making. In the present study, we investigated the effect of transcranial direct current stimulation (tDCS) of the rTPJ on overbidding behaviour by using a modified model-lottery contests task. Our results showed that participants that received cathodal-stimulation had significantly higher expenditure compared to participants that received anodal and sham stimulation. Cathodal-stimulation may reduce the participants' ability to infer other contestants' intention or may modulate the non-monetary utility of winning. Our data indicate that excitability of the rTPJ may contribute to overbidding behaviour.

Transcriptomic evidence that von Economo neurons are regionally specialized extratelencephalic-projecting excitatory neurons.

von Economo neurons (VENs) are bipolar, spindle-shaped neurons restricted to layer 5 of human frontoinsula and anterior cingulate cortex that appear to be selectively vulnerable to neuropsychiatric and neurodegenerative diseases, although little is known about other VEN cellular phenotypes. Single nucleus RNA-sequencing of frontoinsula layer 5 identifies a transcriptomically-defined cell cluster that contained VENs, but also fork cells and a subset of pyramidal neurons. Cross-species alignment of this cell cluster with a well-annotated mouse classification shows strong homology to extratelencephalic (ET) excitatory neurons that project to subcerebral targets. This cluster also shows strong homology to a putative ET cluster in human temporal cortex, but with a strikingly specific regional signature. Together these results suggest that VENs are a regionally distinctive type of ET neuron. Additionally, we describe the first patch clamp recordings of VENs from neurosurgically-resected tissue that show distinctive intrinsic membrane properties relative to neighboring pyramidal neurons.

Computational Mechanisms for Perceptual Stability using Disparity and Motion Parallax.

Walking and other forms of self-motion create global motion patterns across our eyes. With the resulting stream of visual signals, how do we perceive ourselves as moving through a stable world? Although the neural mechanisms are largely unknown, human studies (Warren and Rushton, 2009) provide strong evidence that the visual system is capable of parsing the global motion into two components: one due to self-motion and the other due to independently moving objects. In the present study, we use computational modeling to investigate potential neural mechanisms for stabilizing visual perception during self-motion that build on neurophysiology of the middle temporal (MT) and medial superior temporal (MST) areas. One such mechanism leverages direction, speed, and disparity tuning of cells in dorsal MST (MSTd) to estimate the combined motion parallax and disparity signals attributed to the observer's self-motion. Feedback from the most active MSTd cell subpopulations suppresses motion signals in MT that locally match the preference of the MSTd cell in both parallax and disparity. This mechanism combined with local surround inhibition in MT allows the model to estimate self-motion while maintaining a sparse motion representation that is compatible with perceptual stability. A key consequence is that after signals compatible with the observer's self-motion are suppressed, the direction of independently moving objects is represented in a world-relative rather than observer-relative reference frame. Our analysis explicates how temporal dynamics and joint motion parallax-disparity tuning resolve the world-relative motion of moving objects and establish perceptual stability. Together, these mechanisms capture findings on the perception of object motion during self-motion.SIGNIFICANCE STATEMENT The image integrated by our eyes as we move through our environment undergoes constant flux as trees, buildings, and other surroundings stream by us. If our view can change so radically from one moment to the next, how do we perceive a stable world? Although progress has been made in understanding how this works, little is known about the underlying brain mechanisms. We propose a computational solution whereby multiple brain areas communicate to suppress the motion attributed to our movement relative to the stationary world, which is often responsible for a large proportion of the flux across the visual field. We simulated the proposed neural mechanisms and tested model estimates using data from human perceptual studies.

The neural circuitry of affect-induced distortions of trust.

Aversive affect is likely a key source of irrational human decision-making, but still, little is known about the neural circuitry underlying emotion-cognition interactions during social behavior. We induced incidental aversive affect via prolonged periods of threat of shock, while 41 healthy participants made investment decisions concerning another person or a lottery. Negative affect reduced trust, suppressed trust-specific activity in the left temporoparietal junction (TPJ), and reduced functional connectivity between the TPJ and emotion-related regions such as the amygdala. The posterior superior temporal sulcus (pSTS) seems to play a key role in mediating the impact of affect on behavior: Functional connectivity of this brain area with left TPJ was associated with trust in the absence of negative affect, but aversive affect disrupted this association between TPJ-pSTS connectivity and behavioral trust. Our findings may be useful for a better understanding of the neural circuitry of affective distortions in healthy and pathological populations.

MEG Assessment of Expressive Language in Children Evaluated for Epilepsy Surgery.

Establishing language dominance is an important step in the presurgical evaluation of patients with refractory epilepsy. In the absence of a universally accepted gold-standard non-invasive method to determine language dominance in the preoperative assessment, a range of tools and methodologies have recently received attention. When applied to pediatric age, many of the proposed methods, such as functional magnetic resonance imaging (fMRI), may present some challenges due to the time-varying effects of epileptogenic lesions and of on-going seizures on maturational phenomena. Magnetoencephalography (MEG) has the advantage of being insensitive to the distortive effects of anatomical lesions on brain microvasculature and to differences in the metabolism or vascularization of the developing brain and also provides a less intimidating recording environment for younger children. In this study we investigated the reliability of lateralized synchronous cortical activation during a verb generation task in a group of 28 children (10 males and 18 females, mean age 12 years) with refractory epilepsy who were evaluated for epilepsy surgery. The verb generation task was associated with significant decreases in beta oscillatory power (13-30 Hz) in frontal and temporal lobes. The MEG data were compared with other available presurgical non-invasive data including cortical stimulation, neuropsychological and fMRI data on language lateralization where available. We found that the lateralization of MEG beta power reduction was concordant with language dominance determined by one or more different assessment methods (i.e. cortical stimulation mapping, neuropsychological, fMRI or post-operative data) in 89% of patients. Our data suggest that qualitative hemispheric differences in task-related changes of spectral power could offer a promising insight into the contribution of dominant and non-dominant hemispheres in language processing and may help to characterize the specialization and lateralization of language processes in children.

Multivariate pattern analysis of the human pSTS: A comparison of three prototypical localizers.

The posterior extent of the human superior temporal sulcus (pSTS) is an important cortical region for detecting animacy, attributing agency to others, and decoding goal-directed behavior. Theoretical accounts attribute these cognitive skills to unique neural populations that have been difficult to identify empirically (Hein and Knight, 2008). The aim of this study is to evaluate the multivariate statistical structure of pSTS activation patterns when viewing different social cues. We identified a core conjunction region on pSTS from univariate responses with preference for point-light biological motion, faces and the attribution of social concepts to simple animated shapes. In a multivariate analysis, we characterized the similarity structure of the resulting activation patterns after controlling for variance in the activation profile elicited by form and motion features. We found strong antagonistic activation profiles between the social conditions and their localizer controls, a harbinger of why these canonical localizers are so effective, even in individual subjects. We also found unique patterns of similarity between the three core social conditions. Our findings are consistent with the Shultz et al. (2015) model of pSTS function in which separate neural populations exist for animacy detection from body parts versus for extracting intentional cues from movement.

Shape from Contour: Computation and Representation.

The human visual system reliably extracts shape information from complex natural scenes in spite of noise and fragmentation caused by clutter and occlusions. A fast, feedforward sweep through ventral stream involving mechanisms tuned for orientation, curvature, and local Gestalt principles produces partial shape representations sufficient for simpler discriminative tasks. More complete shape representations may involve recurrent processes that integrate local and global cues. While feedforward discriminative deep neural network models currently produce the best predictions of object selectivity in higher areas of the object pathway, a generative model may be required to account for all aspects of shape perception. Research suggests that a successful model will account for our acute sensitivity to four key perceptual dimensions of shape: topology, symmetry, composition, and deformation.

Mapping working memory retrieval in space and in time: A combined electroencephalography and electrocorticography approach.

In this study, we investigated the time course and neural correlates of the retrieval process underlying visual working memory. We made use of a rare dataset in which the same task was recorded using both scalp electroencephalography (EEG) and Electrocorticography (ECoG), respectively. This allowed us to examine with great spatial and temporal detail how the retrieval process works, and in particular how the medial temporal lobe (MTL) is involved. In each trial, participants judged whether a probe face had been among a set of recently studied faces. With a method that combines hidden semi-Markov models and multivariate pattern analysis, the neural signal was decomposed into a sequence of latent cognitive stages with information about their durations on a trial-by-trial basis. Analyzed separately, EEG and ECoG data yielded converging results on discovered stages and their interpretation, which reflected 1) a brief pre-attention stage, 2) encoding the stimulus, 3) retrieving the studied set, and 4) making a decision. Combining these stages with the high spatial resolution of ECoG suggested that activity in the temporal cortex reflected item familiarity in the retrieval stage; and that once retrieval is complete, there is active maintenance of the studied face set in the decision stage in the MTL. During this same period, the frontal cortex guides the decision by means of theta coupling with the MTL. These observations generalize previous findings on the role of MTL theta from long-term memory tasks to short-term memory tasks.

The role of the right temporo-parietal junction in social decision-making.

Identifying someone else's noncooperative intentions can prevent exploitation in social interactions. Hence, the inference of another person's mental state might be most pronounced in order to improve social decision-making. Here, we tested the hypothesis that brain regions associated with Theory of Mind (ToM), particularly the right temporo-parietal junction (rTPJ), show higher neural responses when interacting with a selfish person and that the rTPJ-activity as well as cooperative tendencies will change over time. We used functional magnetic resonance imaging (fMRI) and a modified prisoner's dilemma game in which 20 participants interacted with three fictive playing partners who behaved according to stable strategies either competitively, cooperatively or randomly during seven interaction blocks. The rTPJ and the posterior-medial prefrontal cortex showed higher activity during the interaction with a competitive compared with a cooperative playing partner. Only the rTPJ showed a high response during an early interaction phase, which preceded participants increase in defective decisions. Enhanced functional connectivity between the rTPJ and the left hippocampus suggests that social cognition and learning processes co-occur when behavioral adaptation seems beneficial.

N1 responses to images of hands in occipito-temporal event-related potentials.

Hands, much like faces, convey social information, instructions and intentions to an observer. While the neural processes of face perception have been widely studied, it was only recently that fMRI identified occipito-temporal areas sensitive to static images of hands as body parts. To complement these studies with fine-grained timing information, we measured event-related EEG potentials (ERPs) from 33 subjects who were presented with static images of hands versus faces, whole bodies, and inanimate objects as controls. Already at N1 latency, ~ 170ms, hand-related ERP patterns were manifest in two results: (1) significant differences in amplitudes for images of hands versus bodies in occipito-temporal N1 responses; (2) left lateralization of responses to images of hands, and also of the difference waveforms (hands minus bodies), quantifying hand-related responses. In line with fMRI studies of hand-sensitive areas distinct from extrastriate body area (EBA), the current findings provide electrophysiological evidence for hand-sensitive brain activation, occurring at a similarly early latency as N1 responses to faces.

Optimal measurements of hemodynamic response latency in fNIRS using the jackknife approach.

Functional near-infrared spectroscopy (fNIRS) permits measurements of changes in the concentration of oxygenated and deoxygenated hemoglobin, typically with a higher sampling rate than with other imaging methods based on the hemodynamic response. We examined the potential of the fNIRS technique to estimate variations in the latency of hemodynamic responses to experimental events and sought optimal methods to maximize the reliability and reproducibility of latency effects. We used Monte Carlo simulations using subsamples of real fNIRS measures to estimate the statistical power of different approaches (such as fixed threshold, percent of peak, fractional-area latency, for both individual-subject estimates and estimates from jackknife averages) to detect a known simulated latency shift. The simulations used measures of hemodynamic responses in the temporal lobe from two groups of young adult participants who listened to auditory stimuli, one with a blocked presentation design and one with an event-related design. We estimated the relative sensitivity of different latency measures and approaches to the measurement of latency effects of different magnitudes using realistic noise and signal-to-noise characteristics. In general, the jackknife approach provided the greatest statistical power to detect a known latency shift, without inflation of Type I error.

Neural speech recognition: continuous phoneme decoding using spatiotemporal representations of human cortical activity.

OBJECTIVE: The superior temporal gyrus (STG) and neighboring brain regions play a key role in human language processing. Previous studies have attempted to reconstruct speech information from brain activity in the STG, but few of them incorporate the probabilistic framework and engineering methodology used in modern speech recognition systems. In this work, we describe the initial efforts toward the design of a neural speech recognition (NSR) system that performs continuous phoneme recognition on English stimuli with arbitrary vocabulary sizes using the high gamma band power of local field potentials in the STG and neighboring cortical areas obtained via electrocorticography. APPROACH: The system implements a Viterbi decoder that incorporates phoneme likelihood estimates from a linear discriminant analysis model and transition probabilities from an n-gram phonemic language model. Grid searches were used in an attempt to determine optimal parameterizations of the feature vectors and Viterbi decoder. MAIN RESULTS: The performance of the system was significantly improved by using spatiotemporal representations of the neural activity (as opposed to purely spatial representations) and by including language modeling and Viterbi decoding in the NSR system. SIGNIFICANCE: These results emphasize the importance of modeling the temporal dynamics of neural responses when analyzing their variations with respect to varying stimuli and demonstrate that speech recognition techniques can be successfully leveraged when decoding speech from neural signals. Guided by the results detailed in this work, further development of the NSR system could have applications in the fields of automatic speech recognition and neural prosthetics.

Abstract linguistic structure correlates with temporal activity during naturalistic comprehension.

Neurolinguistic accounts of sentence comprehension identify a network of relevant brain regions, but do not detail the information flowing through them. We investigate syntactic information. Does brain activity implicate a computation over hierarchical grammars or does it simply reflect linear order, as in a Markov chain? To address this question, we quantify the cognitive states implied by alternative parsing models. We compare processing-complexity predictions from these states against fMRI timecourses from regions that have been implicated in sentence comprehension. We find that hierarchical grammars independently predict timecourses from left anterior and posterior temporal lobe. Markov models are predictive in these regions and across a broader network that includes the inferior frontal gyrus. These results suggest that while linear effects are wide-spread across the language network, certain areas in the left temporal lobe deal with abstract, hierarchical syntactic representations.

Decisions about the past are guided by reinstatement of specific memories in the hippocampus and perirhinal cortex.

When faced with a new challenge, we often reflect on related past experiences to guide our behavior. The ability to retrieve memories that overlap with current experience, a process known as pattern completion, is theorized as a critical function of the hippocampus. Although this view has influenced research for decades, there is little empirical support for hippocampal pattern completion to individual memory elements and its influence on behavior. We used pattern analysis of brain activity measured with functional magnetic resonance imaging to demonstrate that specific elements of past experiences are reinstated in the hippocampus, as well as perirhinal cortex (PRC), when making decisions about those experiences. Linking neural measures of specific memory reinstatement in the hippocampus and PRC to behavior with computational modeling revealed that reinstatement predicts the speed of memory-based decisions. Moreover, hippocampal activation during retrieval was selectively coupled to regions of occipito-temporal cortex that showed content-specific item reinstatement. These results provide evidence for hippocampal pattern completion and its role in the mechanisms of decision making.

Interpersonal brain synchronization in the right temporo-parietal junction during face-to-face economic exchange.

In daily life, interpersonal interactions are influenced by uncertainty about other people's intentions. Face-to-face (FF) interaction reduces such uncertainty by providing external visible cues such as facial expression or body gestures and facilitates shared intentionality to promote belief of cooperative decisions and actual cooperative behaviors in interaction. However, so far little is known about interpersonal brain synchronization between two people engaged in naturally occurring FF interactions. In this study, we combined an adapted ultimatum game with functional near-infrared spectroscopy (fNIRS) hyperscanning to investigate how FF interaction impacts interpersonal brain synchronization during economic exchange. Pairs of strangers interacted repeatedly either FF or face-blocked (FB), while their activation was simultaneously measured in the right temporo-parietal junction (rTPJ) and the control region, right dorsolateral prefrontal cortex (rDLPFC). Behaviorally, FF interactions increased shared intentionality between strangers, leading more positive belief of cooperative decisions and more actual gains in the game. FNIRS results indicated increased interpersonal brain synchronizations during FF interactions in rTPJ (but not in rDLPFC) with greater shared intentionality between partners. These results highlighted the importance of rTPJ in collaborative social interactions during FF economic exchange and warrant future research that combines FF interactions with fNIRS hyperscanning to study social brain disorders such as autism.

An architecture for encoding sentence meaning in left mid-superior temporal cortex.

Human brains flexibly combine the meanings of words to compose structured thoughts. For example, by combining the meanings of "bite," "dog," and "man," we can think about a dog biting a man, or a man biting a dog. Here, in two functional magnetic resonance imaging (fMRI) experiments using multivoxel pattern analysis (MVPA), we identify a region of left mid-superior temporal cortex (lmSTC) that flexibly encodes "who did what to whom" in visually presented sentences. We find that lmSTC represents the current values of abstract semantic variables ("Who did it?" and "To whom was it done?") in distinct subregions. Experiment 1 first identifies a broad region of lmSTC whose activity patterns (i) facilitate decoding of structure-dependent sentence meaning ("Who did what to whom?") and (ii) predict affect-related amygdala responses that depend on this information (e.g., "the baby kicked the grandfather" vs. "the grandfather kicked the baby"). Experiment 2 then identifies distinct, but neighboring, subregions of lmSTC whose activity patterns carry information about the identity of the current "agent" ("Who did it?") and the current "patient" ("To whom was it done?"). These neighboring subregions lie along the upper bank of the superior temporal sulcus and the lateral bank of the superior temporal gyrus, respectively. At a high level, these regions may function like topographically defined data registers, encoding the fluctuating values of abstract semantic variables. This functional architecture, which in key respects resembles that of a classical computer, may play a critical role in enabling humans to flexibly generate complex thoughts.