Unavoidable social contagion of false memory from robots to humans.

Many of us interact with voice- or text-based conversational agents daily, but these conversational agents may unintentionally retrieve misinformation from human knowledge databases, confabulate responses on their own, or purposefully spread disinformation for political purposes. Does such misinformation or disinformation become part of our memory to further misguide our decisions? If so, can we prevent humans from suffering such social contagion of false memory? Using a social contagion of memory paradigm, here, we precisely controlled a social robot as an example of these emerging conversational agents. In a series of two experiments (ΣN = 120), the social robot occasionally misinformed participants prior to a recognition memory task. We found that the robot was as powerful as humans at influencing others. Despite the supplied misinformation being emotion- and value-neutral and hence not intrinsically contagious and memorable, 77% of the socially misinformed words became the participants' false memory. To mitigate such social contagion of false memory, the robot also forewarned the participants about its reservation toward the misinformation. However, one-time forewarnings failed to reduce false memory contagion. Even relatively frequent, item-specific forewarnings could not prevent warned items from becoming false memory, although such forewarnings helped increase the participants' overall cautiousness. Therefore, we recommend designing conversational agents to, at best, avoid providing uncertain information or, at least, provide frequent forewarnings about potentially false information. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The cross-race effect in automatic facial expression recognition violates measurement invariance.

Emotion has been a subject undergoing intensive research in psychology and cognitive neuroscience over several decades. Recently, more and more studies of emotion have adopted automatic rather than manual methods of facial emotion recognition to analyze images or videos of human faces. Compared to manual methods, these computer-vision-based, automatic methods can help objectively and rapidly analyze a large amount of data. These automatic methods have also been validated and believed to be accurate in their judgments. However, these automatic methods often rely on statistical learning models (e.g., deep neural networks), which are intrinsically inductive and thus suffer from problems of induction. Specifically, the models that were trained primarily on Western faces may not generalize well to accurately judge Eastern faces, which can then jeopardize the measurement invariance of emotions in cross-cultural studies. To demonstrate such a possibility, the present study carries out a cross-racial validation of two popular facial emotion recognition systems-FaceReader and DeepFace-using two Western and two Eastern face datasets. Although both systems could achieve overall high accuracies in the judgments of emotion category on the Western datasets, they performed relatively poorly on the Eastern datasets, especially in recognition of negative emotions. While these results caution the use of these automatic methods of emotion recognition on non-Western faces, the results also suggest that the measurements of happiness outputted by these automatic methods are accurate and invariant across races and hence can still be utilized for cross-cultural studies of positive psychology.

Sequential processing facilitates Hebb repetition learning in visuospatial domains.

Exposure to the same information improves auditory/verbal short-term memory performance, but such improvement is not always observed in visual short-term memory. In this study, we demonstrate that sequential processing makes visuospatial repetition learning efficient in a paradigm that employs a similar design previously used for an auditory/verbal domain. When we presented sets of color patches simultaneously in Experiments 1-4, recall accuracy did not increase with repetition; however, once color patches were presented sequentially in Experiment 5, accuracy did increase rapidly with repetition, even when participants engaged in articulatory suppression. Moreover, these learning dynamics matched those in Experiment 6, which used verbal materials. These findings suggest that (a) sequential focus on each item facilitates a repetition learning effect, indicating a temporal bottleneck is involved early in this process and (b) repetition learning is mechanistically similar across sensory modalities even though these modalities differently specialize in processing spatial or temporal information. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Role of visual awareness on semantic integration of sequentially presented words: An fMRI study.

Reading comprehension requires the semantic integration of words across space and time. However, it remains unclear whether comprehension requires visual awareness for such semantic integration. Compared to earlier studies that investigated semantic integration indirectly from its priming effect, we used functional magnetic resonance imaging (fMRI) to directly examine the processes of semantic integration with or without visual awareness. Specifically, we manipulated participants' visual awareness by continuous flash suppression (CFS) while they viewed a meaningful sequence of four Chinese words (i.e., an idiom) or its meaningless counterpart (i.e., a random sequence). Behaviorally, participants had better recognition memory for idioms than random sequences only when their visual awareness was interfered rather than blocked by CFS. Neurally, semantics-processing areas, such as the superior temporal gyrus and inferior frontal gyrus, were significantly activated only when participants were aware of word sequences, be they meaningful or meaningless. By contrast, orthography-processing areas, such as the fusiform gyrus and inferior occipital gyrus, were significantly activated regardless of visual awareness or word sequence. Taken together, these results suggest that visual awareness modules the functioning of the semantic neural network in the brain and facilitates reading comprehension.

Person-identifying brainprints are stably embedded in EEG mindprints.

Electroencephalography (EEG) signals measured under fixed conditions have been exploited as biometric identifiers. However, what contributes to the uniqueness of one's brain signals remains unclear. In the present research, we conducted a multi-task and multi-week EEG study with ten pairs of monozygotic (MZ) twins to examine the nature and components of person-identifiable brain signals. Through machine-learning analyses, we uncovered a person-identifying EEG component that served as "base signals" shared across tasks and weeks. Such task invariance and temporal stability suggest that these person-identifying EEG characteristics are more of structural brainprints than functional mindprints. Moreover, while these base signals were more similar within than between MZ twins, it was still possible to distinguish twin siblings, particularly using EEG signals coming primarily from late rather than early developed areas in the brain. Besides theoretical clarifications, the discovery of the EEG base signals has practical implications for privacy protection and the application of brain-computer interfaces.

Identifying Mild Cognitive Impairment by Using Human-Robot Interactions.

BACKGROUND: Mild cognitive impairment (MCI), which is common in older adults, is a risk factor for dementia. Rapidly growing health care demand associated with global population aging has spurred the development of new digital tools for the assessment of cognitive performance in older adults. OBJECTIVE: To overcome methodological drawbacks of previous studies (e.g., use of potentially imprecise screening tools that fail to include patients with MCI), this study investigated the feasibility of assessing multiple cognitive functions in older adults with and without MCI by using a social robot. METHODS: This study included 33 older adults with or without MCI and 33 healthy young adults. We examined the utility of five robotic cognitive tests focused on language, episodic memory, prospective memory, and aspects of executive function to classify age-associated cognitive changes versus MCI. Standardized neuropsychological tests were collected to validate robotic test performance. RESULTS: The assessment was well received by all participants. Robotic tests assessing delayed episodic memory, prospective memory, and aspects of executive function were optimal for differentiating between older adults with and without MCI, whereas the global cognitive test (i.e., Mini-Mental State Examination) failed to capture such subtle cognitive differences among older adults. Furthermore, robot-administered tests demonstrated sound ability to predict the results of standardized cognitive tests, even after adjustment for demographic variables and global cognitive status. CONCLUSION: Overall, our results suggest the human-robot interaction approach is feasible for MCI identification. Incorporating additional cognitive test measures might improve the stability and reliability of such robot-assisted MCI diagnoses.

What part of the brain is involved in graphic design thinking in landscape architecture?

Graphic design thinking is a key skill for landscape architects, but little is known about the links between the design process and brain activity. Based on Goel's frontal lobe lateralization hypothesis (FLLH), we used functional magnetic resonance imaging (fMRI) to scan the brain activity of 24 designers engaging in four design processes-viewing, copy drawing, preliminary ideas, and refinement-during graphic design thinking. The captured scans produced evidence of dramatic differences between brain activity when copying an existing graphic and when engaging in graphic design thinking. The results confirm that designs involving more graphic design thinking exhibit significantly more activity in the left prefrontal cortex. These findings illuminate the design process and suggest the possibility of developing specific activities or exercises to promote graphic design thinking in landscape architecture.

Social Robots for Evaluating Attention State in Older Adults.

Sustained attention is essential for older adults to maintain an active lifestyle, and the deficiency of this function is often associated with health-related risks such as falling and frailty. The present study examined whether the well-established age-effect on reducing mind-wandering, the drift to internal thoughts that are seen to be detrimental to attentional control, could be replicated by using a robotic experimenter for older adults who are not as familiar with online technologies. A total of 28 younger and 22 older adults performed a Sustained Attention to Response Task (SART) by answering thought probes regarding their attention states and providing confidence ratings for their own task performances. The indices from the modified SART suggested a well-documented conservative response strategy endorsed by older adults, which were represented by slower responses and increased omission errors. Moreover, the slower responses and increased omissions were found to be associated with less self-reported mind-wandering, thus showing consistency with their higher subjective ratings of attentional control. Overall, this study demonstrates the potential of constructing age-related cognitive profiles with attention evaluation instruction based on a social companion robot for older adults at home.

Personal Resilience Can Be Well Estimated from Heart Rate Variability and Paralinguistic Features during Human-Robot Conversations.

Mental health is as crucial as physical health, but it is underappreciated by mainstream biomedical research and the public. Compared to the use of AI or robots in physical healthcare, the use of AI or robots in mental healthcare is much more limited in number and scope. To date, psychological resilience-the ability to cope with a crisis and quickly return to the pre-crisis state-has been identified as an important predictor of psychological well-being but has not been commonly considered by AI systems (e.g., smart wearable devices) or social robots to personalize services such as emotion coaching. To address the dearth of investigations, the present study explores the possibility of estimating personal resilience using physiological and speech signals measured during human-robot conversations. Specifically, the physiological and speech signals of 32 research participants were recorded while the participants answered a humanoid social robot's questions about their positive and negative memories about three periods of their lives. The results from machine learning models showed that heart rate variability and paralinguistic features were the overall best predictors of personal resilience. Such predictability of personal resilience can be leveraged by AI and social robots to improve user understanding and has great potential for various mental healthcare applications in the future.

Lithium for schizophrenia: supporting evidence from a 12-year, nationwide health insurance database and from Akt1-deficient mouse and cellular models.

Accumulating evidence suggests AKT1 and DRD2-AKT-GSK3 signaling involvement in schizophrenia. AKT1 activity is also required for lithium, a GSK3 inhibitor, to modulate mood-related behaviors. Notably, GSK3 inhibitor significantly alleviates behavioral deficits in Akt1-/- female mice, whereas typical/atypical antipsychotics have no effect. In agreement with adjunctive therapy with lithium in treating schizophrenia, our data mining indicated that the average utilization rates of lithium in the Taiwan National Health Insurance Research Database from 2002 to 2013 are 10.9% and 6.63% in inpatients and outpatients with schizophrenia, respectively. Given that lithium is commonly used in clinical practice, it is of great interest to evaluate the effect of lithium on alleviating Akt1-related deficits. Taking advantage of Akt1+/- mice to mimic genetic deficiency in patients, behavioral impairments were replicated in female Akt1+/- mice but were alleviated by subchronic lithium treatment for 13 days. Lithium also effectively alleviated the observed reduction in phosphorylated GSK3α/ß expression in the brains of Akt1+/- mice. Furthermore, inhibition of Akt expression using an Akt1/2 inhibitor significantly reduced neurite length in P19 cells and primary hippocampal cell cultures, which was also ameliorated by lithium. Collectively, our findings implied the therapeutic potential of lithium and the importance of the AKT1-GSK3 signaling pathway.

Perceiving Self, Others, and Events Through a Religious Lens: Mahayana Buddhists vs. Christians.

Are all religions essentially the same? Are believers of different religions heading in the same mental direction? To answer these questions from a sociopsychological perspective, we compared social sensitivity and causal attribution styles between Mahayana Buddhists, who practice unbiased love and compassion toward every being, and Christians, who pursue a union with God. Despite a similar cultural background, sex ratio, age distribution, socioeconomic status, and fluid intelligence level, these two religious groups in Taiwan showed opposite tendencies when inferring the mental states of others - as religiosity increased, the theory of mind ability increased in Mahayana Buddhists but decreased in Christians. Furthermore, these two religious groups showed opposite tendencies of attributional style - as religiosity increased, self-serving bias decreased in Buddhists but increased in Christians. These marked religiosity-dependent, sociopsychological effects suggest that different religions may shape or attract their followers who are moving in quite distinct mental directions.

Christians and Buddhists Are Comparably Happy on Twitter: A Large-Scale Linguistic Analysis of Religious Differences in Social, Cognitive, and Emotional Tendencies.

Are different religions associated with different social, cognitive, and emotional tendencies? Although major world religions are known to encourage social interactions and help regulate emotions, it is less clear to what extent adherents of various religions differ in these dimensions in daily life. We thus carried out a large-scale sociolinguistic analysis of social media messages of Christians and Buddhists living in the United States. After controlling for age and gender effects on linguistic patterns, we found that Christians used more social words and fewer cognitive words than Buddhists. Moreover, adherents of both religions, similarly used more positive than negative emotion words on Twitter, although overall, Christians were slightly more positive in verbal emotional expression than Buddhists. These sociolinguistic patterns of actual rather than ideal behaviors were also paralleled by language used in the popular sacred texts of Christianity and Buddhism, with the exception that Christian texts contained more negative and fewer positive emotion words than Buddhist texts. Taken together, our results suggest that the direct or indirect influence of religious texts on the receivers of their messages may partially, but not fully, account for the verbal behavior of religious adherents.

Multistability of the Brain Network for Self-other Processing.

Early fMRI studies suggested that brain areas processing self-related and other-related information were highly overlapping. Hypothesising functional localisation of the cortex, researchers have tried to locate "self-specific" and "other-specific" regions within these overlapping areas by subtracting suspected confounding signals in task-based fMRI experiments. Inspired by recent advances in whole-brain dynamic modelling, we instead explored an alternative hypothesis that similar spatial activation patterns could be associated with different processing modes in the form of different synchronisation patterns. Combining an automated synthesis of fMRI data with a presumption-free diffusion spectrum image (DSI) fibre-tracking algorithm, we isolated a network putatively composed of brain areas and white matter tracts involved in self-other processing. We sampled synchronisation patterns from the dynamical systems of this network using various combinations of physiological parameters. Our results showed that the self-other processing network, with simulated gamma-band activity, tended to stabilise at a number of distinct synchronisation patterns. This phenomenon, termed "multistability," could serve as an alternative model in theorising the mechanism of processing self-other information.

Developing the Own-Race Advantage in 4-, 6-, and 9-Month-Old Taiwanese Infants: A Perceptual Learning Perspective.

Previous infant studies on the other-race effect have favored the perceptual narrowing view, or declined sensitivities to rarely exposed other-race faces. Here we wish to provide an alternative possibility, perceptual learning, manifested by improved sensitivity for frequently exposed own-race faces in the first year of life. Using the familiarization/visual-paired comparison paradigm, we presented 4-, 6-, and 9-month-old Taiwanese infants with oval-cropped Taiwanese, Caucasian, Filipino faces, and each with three different manipulations of increasing task difficulty (i.e., change identity, change eyes, and widen eye spacing). An adult experiment was first conducted to verify the task difficulty. Our results showed that, with oval-cropped faces, the 4 month-old infants could only discriminate Taiwanese "change identity" condition and not any others, suggesting an early own-race advantage at 4 months. The 6 month-old infants demonstrated novelty preferences in both Taiwanese and Caucasian "change identity" conditions, and proceeded to the Taiwanese "change eyes" condition. The 9-month-old infants demonstrated novelty preferences in the "change identity" condition of all three ethnic faces. They also passed the Taiwanese "change eyes" condition but could not extend this refined ability of detecting a change in the eyes for the Caucasian or Philippine faces. Taken together, we interpret the pattern of results as evidence supporting perceptual learning during the first year: the ability to discriminate own-race faces emerges at 4 months and continues to refine, while the ability to discriminate other-race faces emerges between 6 and 9 months and retains at 9 months. Additionally, the discrepancies in the face stimuli and methods between studies advocating the narrowing view and those supporting the learning view were discussed.

Strategic cognitive sequencing: a computational cognitive neuroscience approach.

We address strategic cognitive sequencing, the "outer loop" of human cognition: how the brain decides what cognitive process to apply at a given moment to solve complex, multistep cognitive tasks. We argue that this topic has been neglected relative to its importance for systematic reasons but that recent work on how individual brain systems accomplish their computations has set the stage for productively addressing how brain regions coordinate over time to accomplish our most impressive thinking. We present four preliminary neural network models. The first addresses how the prefrontal cortex (PFC) and basal ganglia (BG) cooperate to perform trial-and-error learning of short sequences; the next, how several areas of PFC learn to make predictions of likely reward, and how this contributes to the BG making decisions at the level of strategies. The third models address how PFC, BG, parietal cortex, and hippocampus can work together to memorize sequences of cognitive actions from instruction (or "self-instruction"). The last shows how a constraint satisfaction process can find useful plans. The PFC maintains current and goal states and associates from both of these to find a "bridging" state, an abstract plan. We discuss how these processes could work together to produce strategic cognitive sequencing and discuss future directions in this area.

Enhanced spontaneous oscillations in the supplementary motor area are associated with sleep-dependent offline learning of finger-tapping motor-sequence task.

Sleep is beneficial for various types of learning and memory, including a finger-tapping motor-sequence task. However, methodological issues hinder clarification of the crucial cortical regions for sleep-dependent consolidation in motor-sequence learning. Here, to investigate the core cortical region for sleep-dependent consolidation of finger-tapping motor-sequence learning, while human subjects were asleep, we measured spontaneous cortical oscillations by magnetoencephalography together with polysomnography, and source-localized the origins of oscillations using individual anatomical brain information from MRI. First, we confirmed that performance of the task at a retest session after sleep significantly increased compared with performance at the training session before sleep. Second, spontaneous δ and fast-σ oscillations significantly increased in the supplementary motor area (SMA) during post-training compared with pretraining sleep, showing significant and high correlation with the performance increase. Third, the increased spontaneous oscillations in the SMA correlated with performance improvement were specific to slow-wave sleep. We also found that correlations of δ oscillation between the SMA and the prefrontal and between the SMA and the parietal regions tended to decrease after training. These results suggest that a core brain region for sleep-dependent consolidation of the finger-tapping motor-sequence learning resides in the SMA contralateral to the trained hand and is mediated by spontaneous δ and fast-σ oscillations, especially during slow-wave sleep. The consolidation may arise along with possible reorganization of a larger-scale cortical network that involves the SMA and cortical regions outside the motor regions, including prefrontal and parietal regions.

Assembling old tricks for new tasks: a neural model of instructional learning and control.

We can learn from the wisdom of others to maximize success. However, it is unclear how humans take advice to flexibly adapt behavior. On the basis of data from neuroanatomy, neurophysiology, and neuroimaging, a biologically plausible model is developed to illustrate the neural mechanisms of learning from instructions. The model consists of two complementary learning pathways. The slow-learning parietal pathway carries out simple or habitual stimulus-response (S-R) mappings, whereas the fast-learning hippocampal pathway implements novel S-R rules. Specifically, the hippocampus can rapidly encode arbitrary S-R associations, and stimulus-cued responses are later recalled into the basal ganglia-gated pFC to bias response selection in the premotor and motor cortices. The interactions between the two model learning pathways explain how instructions can override habits and how automaticity can be achieved through motor consolidation.

Task attention facilitates learning of task-irrelevant stimuli.

Attention plays a fundamental role in visual learning and memory. One highly established principle of visual attention is that the harder a central task is, the more attentional resources are used to perform the task and the smaller amount of attention is allocated to peripheral processing because of limited attention capacity. Here we show that this principle holds true in a dual-task setting but not in a paradigm of task-irrelevant perceptual learning. In Experiment 1, eight participants were asked to identify either bright or dim number targets at the screen center and to remember concurrently presented scene backgrounds. Their recognition performances for scenes paired with dim/hard targets were worse than those for scenes paired with bright/easy targets. In Experiment 2, eight participants were asked to identify either bright or dim letter targets at the screen center while a task-irrelevant coherent motion was concurrently presented in the background. After five days of training on letter identification, participants improved their motion sensitivity to the direction paired with hard/dim targets improved but not to the direction paired with easy/bright targets. Taken together, these results suggest that task-irrelevant stimuli are not subject to the attentional control mechanisms that task-relevant stimuli abide.

Cortical dynamics of contextually cued attentive visual learning and search: spatial and object evidence accumulation.

How do humans use target-predictive contextual information to facilitate visual search? How are consistently paired scenic objects and positions learned and used to more efficiently guide search in familiar scenes? For example, humans can learn that a certain combination of objects may define a context for a kitchen and trigger a more efficient search for a typical object, such as a sink, in that context. The ARTSCENE Search model is developed to illustrate the neural mechanisms of such memory-based context learning and guidance and to explain challenging behavioral data on positive-negative, spatial-object, and local-distant cueing effects during visual search, as well as related neuroanatomical, neurophysiological, and neuroimaging data. The model proposes how global scene layout at a first glance rapidly forms a hypothesis about the target location. This hypothesis is then incrementally refined as a scene is scanned with saccadic eye movements. The model simulates the interactive dynamics of object and spatial contextual cueing and attention in the cortical What and Where streams starting from early visual areas through medial temporal lobe to prefrontal cortex. After learning, model dorsolateral prefrontal cortex (area 46) primes possible target locations in posterior parietal cortex based on goal-modulated percepts of spatial scene gist that are represented in parahippocampal cortex. Model ventral prefrontal cortex (area 47/12) primes possible target identities in inferior temporal cortex based on the history of viewed objects represented in perirhinal cortex.