Reduced processing of afforded actions while observing mental content as ongoing mental phenomena.

While consciousness is typically considered equivalent to mental contents, certain meditation practices-including open monitoring (OM)-are said to enable a unique conscious state where meditators can experience mental content from a de-reified perspective as "ongoing phenomena." Phenomenologically, such a state is considered as reduction of intentionality, the mental act upon mental content. We hypothesised that this de-reified state would be characterised by reduced mental actional processing of affording objects. We recruited two groups of participants, meditators with long-term experience in cultivating a de-reified state, and demographically-matched novice meditators. Participants performed a task with images in two configurations-where objects did (high-affordance) and did not imply actions (low-affordance)-following both a baseline and OM-induced de-reified state, along with EEG recordings. While long-term meditators exhibited preferential processing of high-affordance images compared to low-affordance images during baseline, such an effect was abolished during the OM state, as hypothesised. For novices, however, the high-affordance configuration was preferred over the low-affordance one both during baseline and OM. Perceptual durations of objects across conditions positively correlated with the degree of µ-rhythm desynchronization, indicating that neural processing of affordance impacted perceptual awareness. Our results indicate that OM styles of meditation may help in mentally decoupling otherwise automatic cognitive processing of mental actions by affording objects.

Recruitment of the premotor cortex during arithmetic operations by the monkey.

Arithmetic operations are complex mental processes rooted in the abstract concept of numerosity. Despite the significance, the neural architecture responsible for these operations has remained largely uncharted. In this study, we explored the presence of specific neuronal activity in the dorsal premotor cortex of the monkey dedicated to numerical addition and subtraction. Our findings reveal that many of these neural activities undergo a transformation, shifting their coding from arithmetic to motor representations. These motor representations include information about which hand to use and the number of steps involved in the action. We consistently observed that cells related to the right-hand encoded addition, while those linked to the left-hand encoded subtraction, suggesting that arithmetic operations and motor commands are intertwining with each other. Furthermore, we used a multivariate decoding technique to predict the monkey's behaviour based on the activity of these arithmetic-related cells. The classifier trained to discern arithmetic operations, including addition and subtraction, not only predicted the arithmetic decisions but also the subsequent motor actions of the right and left-hand. These findings imply a cognitive extension of the motor cortex's function, where inherent neural systems are repurposed to facilitate arithmetic operations.

Predicting Driver's mental workload using physiological signals: A functional data analysis approach.

This study investigates the impact of advanced driver-assistance systems on drivers' mental workload. Using a combination of physiological signals including ECG, EMG, EDA, EEG (af4 and fc6 channels from the theta band), and eye diameter data, this study aims to predict and categorize drivers' mental workload into low, adequate, and high levels. Data were collected from five different driving situations with varying cognitive demands. A functional linear regression model was employed for prediction, and the accuracy rate was calculated. Among the 31 tested combinations of physiological variables, 9 combinations achieved the highest accuracy result of 90%. These results highlight the potential benefits of utilizing raw physiological signal data and employing functional data analysis methods to understand and assess driver mental workload. The findings of this study have implications for the design and improvement of driver-assistance systems to optimize safety and performance.

The HPA and SAM axis mediate the impairment of creativity under stress.

With the ever-changing social environment, individual creativity is facing a severe challenge induced by stress. However, little is known regarding the underlying mechanisms by which acute stress affects creative cognitive processing. The current research explored the impacts of the neuroendocrine response on creativity under stress and its underlying cognitive flexibility mechanisms. The enzyme-linked immuno sorbent assay was employed to assess salivary cortisol, which acted as a marker of stress-induced activation of the hypothalamic-pituitary-adrenal (HPA) axis. Eye blink rate (EBR) and pupil diameter were measured as respective indicators of dopamine and noradrenaline released by the activation of the sympathetic-adrenal-medullary (SAM) axis. The Wisconsin card task (WCST) measured cognitive flexibility, while the alternative uses task (AUT) and the remote association task (RAT) measured separately divergent and convergent thinking in creativity. Results showed higher cortisol increments following acute stress induction in the stress group than control group. Ocular results showed that the stress manipulation significantly increased EBR and pupil diameter compared to controls, reflecting increased SAM activity. Further analysis revealed that stress-released cortisol impaired the originality component of the AUT, reducing cognitive flexibility as measured by perseverative errors on the WCST task. Serial mediation analyses showed that both EBR and pupil diameter were also associated with increased perseverative errors leading to poor originality on the AUT. These findings confirm that physiological arousal under stress can impair divergent thinking through the regulation of different neuroendocrine pathways, in which the deterioration of flexible switching plays an important mediating role.

How Exergaming with Virtual Reality Enhances Specific Cognitive and Visuo-Motor Abilities: An Explorative Study.

Virtual reality (VR) is the computer simulation of a three-dimensional environment that a person can interact with using special electronic equipment, such as a headset with an integrated display. Often coupled with VR, exergames are video games that involve physical exercise. Little is known regarding the chronic effects of exergaming through VR chon cognitive functions. Eleven young participants were enrolled in this crossover exploratory study. They had to follow two trainings of 5 consecutive days, 15 min per day, interspaced by a 1-month washout period. Trainings were performed in a random order: (1) a video training using shadow boxing fitness videos (SBV) and (2) a VR training using a three-dimensional game where the aim is to cut moving cubes with a sword in each hand. Before and after each training period, a battery of cognitive tests was performed to assess executive functions, such as attention (change blindness), reaction time, response inhibition (go/no-go, Stroop task), or flexibility (trail making test). Fine motor skills were also evaluated through a Fitt's task. No effect of the SBV training was observed on any of the cognitive functions tested. On the contrary, a significant increased performance in selective attention and observation tests was found after VR training, as well as in inhibitory processes (Stroop and go/no-go). Other performances were unaffected by either VR or SBV training. The present study argues that VR exergaming is a promising tool to promote cognitive enhancement but targets specific functions according to the type of interface/game that is used.

A dual-task approach to inform the taxonomy of inhibition-related processes.

Response inhibition is key to controlled behavior and is commonly investigated with the stop-signal paradigm. The authors investigated how response inhibition is situated within a taxonomy of control processes by combining multiple forms of control within dual tasks. Response inhibition, as measured by stop-signal reaction time (SSRT), was impaired when combined with shape matching, but not the flanker task, and when combined with cued task switching, but not predictable task switching, suggesting that response inhibition may be weakly or variably impaired when combined with selective attention and set shifting demands, respectively. Response inhibition was also consistently impaired when combined with the N-back or directed forgetting tasks, putative measures of working memory. Impairments of response inhibition by other control demands appeared to be primarily driven by task context, as SSRT slowing was similar for trials where control demands were either high (e.g., task switch) or low (e.g., task stay). These results demonstrate that response inhibition processes are often impaired in the context of other control demands, even on trials where direct engagement of those other control processes is not required. This suggests a taxonomy of control in which response inhibition overlaps with related control processes, especially working memory. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Functional connectivity during orthographic, phonological, and semantic processing of Chinese characters identifies distinct visuospatial and phonosemantic networks.

While neuroimaging studies have identified brain regions associated with single word reading, its three constituents, namely, orthography, phonology, and meaning, and the functional connectivity of their networks remain underexplored. This study examined the neurocognitive underpinnings of these neural activations and functional connectivity of the identified brain regions using a within-subject design. Thirty-one native Mandarin speakers performed orthographic, phonological, and semantic judgment tasks during functional magnetic resonance imaging. The results indicated that the three processes shared a core network consisting of a large region in the left prefrontal cortex, fusiform gyrus, and medial superior frontal gyrus but not the superior temporal gyrus. Orthographic processing more strongly recruited the left dorsolateral prefrontal cortex, left superior parietal lobule and bilateral fusiform gyri; semantic processing more strongly recruited the left inferior frontal gyrus and left middle temporal gyrus, whereas phonological processing more strongly activated the dorsal part of the precentral gyrus. Functional connectivity analysis identified a posterior visuospatial network and a frontal phonosemantic network interfaced by the left middle frontal gyrus. We conclude that reading Chinese recruits cognitive resources that correspond to basic task demands with unique features best explained in connection with the individual reading subprocesses.

Moderate-to-vigorous physical activity is associated with processing speed, but not learning and memory, in cognitively impaired persons with multiple sclerosis.

BACKGROUND: Physical activity (PA), measured as steps/day, correlates with cognition in persons with MS. OBJECTIVES: The current study extended previous research by examining the association between device-measured PA and cognitive outcomes based on neuropsychological testing among persons with MS who were pre-screened for cognitive impairment. METHODS: The sample included 60 persons with MS who underwent cognitive performance tests (SDMT, CVLT-II, and BVMT-R) and wore an accelerometer on an elastic waist band during the waking hours of a 7-day period for measuring PA across the activity spectrum (sedentary behavior, light PA [LPA], and moderate-to-vigorous PA [MVPA]. The data were analyzed with bivariate and partial Spearman rank-order correlations in using SPSS. RESULTS: MVPA had statistically significant correlations with SDMT, CVLT-II, and BVMT-R. LPA had a statistically significant correlation with SDMT, but not CVLT-II or BVMT-R. Sedentary behavior did not demonstrate statistically significant correlations with any cognitive outcomes. MVPA had statistically significant correlations with SDMT, after controlling for age, sex, education, and disability status. All other correlations were not statistically significant after controlling for covariates. CONCLUSION: This initial cross-sectional data supports the design of PA interventions that target ambulatory PA as a form of MVPA for managing MS-related CPS impairment in MS.

Rethinking fast and slow processing in autism.

Following the popularity of dual process models in social and cognitive psychology, there is major interest in the possibility that autism is associated with impaired "fast" intuitive thinking but enhanced "slow" or "rational" deliberative thinking. If correct, this has great potential to help understand various strengths and difficulties characteristic of autism. Previous empirical investigations of this phenomenon, however, are marred by concerns about the measurement of intuitive and deliberative processing, as well as broader problems in clinical psychological science (e.g., small underpowered studies, lack of replication). Making a step change, we conducted four large-scale studies to examine dual processing in autism, including a preregistered comparison of 200 autistic and nonautistic adults. Participants completed contemporary cognitive and self-report measures of intuitive and deliberative processing, as well as a psychometrically robust measure of general cognitive ability. Except for lower self-reported intuitive thinking, we found no unique contributions of autism to intuitive or deliberative thinking across all four studies, as evidenced by frequentist and Bayesian analyses. Overall, these studies indicate that intuitive and deliberative thinking is neither enhanced nor particularly impaired in relation to autism. We deliberate on the implications of these findings for theories of autism and future investigation of strengths and difficulties in autistic people. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Rewarding cognitive effort increases the intrinsic value of mental labor.

Current models of mental effort in psychology, behavioral economics, and cognitive neuroscience typically suggest that exerting cognitive effort is aversive, and people avoid it whenever possible. The aim of this research was to challenge this view and show that people can learn to value and seek effort intrinsically. Our experiments tested the hypothesis that effort-contingent reward in a working-memory task will induce a preference for more demanding math tasks in a transfer phase, even though participants were aware that they would no longer receive any reward for task performance. In laboratory Experiment 1 (n = 121), we made reward directly contingent on mobilized cognitive effort as assessed via cardiovascular measures (ß-adrenergic sympathetic activity) during the training task. Experiments 2a to 2e (n = 1,457) were conducted online to examine whether the effects of effort-contingent reward on subsequent demand seeking replicate and generalize to community samples. Taken together, the studies yielded reliable evidence that effort-contingent reward increased participants' demand seeking and preference for the exertion of cognitive effort on the transfer task. Our findings provide evidence that people can learn to assign positive value to mental effort. The results challenge currently dominant theories of mental effort and provide evidence and an explanation for the positive effects of environments appreciating effort and individual growth on people's evaluation of effort and their willingness to mobilize effort and approach challenging tasks.

A hierarchical Bayesian model to find brain-behaviour associations in incomplete data sets.

Canonical Correlation Analysis (CCA) and its regularised versions have been widely used in the neuroimaging community to uncover multivariate associations between two data modalities (e.g., brain imaging and behaviour). However, these methods have inherent limitations: (1) statistical inferences about the associations are often not robust; (2) the associations within each data modality are not modelled; (3) missing values need to be imputed or removed. Group Factor Analysis (GFA) is a hierarchical model that addresses the first two limitations by providing Bayesian inference and modelling modality-specific associations. Here, we propose an extension of GFA that handles missing data, and highlight that GFA can be used as a predictive model. We applied GFA to synthetic and real data consisting of brain connectivity and non-imaging measures from the Human Connectome Project (HCP). In synthetic data, GFA uncovered the underlying shared and specific factors and predicted correctly the non-observed data modalities in complete and incomplete data sets. In the HCP data, we identified four relevant shared factors, capturing associations between mood, alcohol and drug use, cognition, demographics and psychopathological measures and the default mode, frontoparietal control, dorsal and ventral networks and insula, as well as two factors describing associations within brain connectivity. In addition, GFA predicted a set of non-imaging measures from brain connectivity. These findings were consistent in complete and incomplete data sets, and replicated previous findings in the literature. GFA is a promising tool that can be used to uncover associations between and within multiple data modalities in benchmark datasets (such as, HCP), and easily extended to more complex models to solve more challenging tasks.

Multi-timepoint pattern analysis: Influence of personality and behavior on decoding context-dependent brain connectivity dynamics.

Behavioral traits are rarely considered in task-evoked functional magnetic resonance imaging (MRI) studies, yet these traits can affect how an individual engages with the task, and thus lead to heterogeneity in task-evoked brain responses. We aimed to investigate whether interindividual variation in behavior associates with the accuracy of predicting task-evoked changes in the dynamics of functional brain connectivity measured with functional MRI. We developed a novel method called multi-timepoint pattern analysis (MTPA), in which binary logistic regression classifiers were trained to distinguish rest from each of 7 tasks (i.e., social cognition, working memory, language, relational, motor, gambling, emotion) based on functional connectivity dynamics measured in 1,000 healthy adults. We found that connectivity dynamics for multiple pairs of large-scale networks enabled individual classification between task and rest with accuracies exceeding 70%, with the most discriminatory connections relatively unique to each task. Crucially, interindividual variation in classification accuracy significantly associated with several behavioral, cognition and task performance measures. Classification between task and rest was generally more accurate for individuals with higher intelligence and task performance. Additionally, for some of the tasks, classification accuracy improved with lower perceived stress, lower aggression, higher alertness, and greater endurance. We conclude that heterogeneous dynamic adaptations of functional brain networks to changing cognitive demands can be reliably captured as linearly separable patterns by MTPA. Future studies should account for interindividual variation in behavior when investigating context-dependent dynamic functional connectivity.

Postural responses to specific types of long-term memory during visually induced roll self-motion.

A large body of research has shown that visually induced self-motion (vection) and cognitive processing may interfere with each other. The aim of this study was to assess the interactive effects of a visual motion inducing vection (uniform motion in roll) versus a visual motion without vection (non-uniform motion) and long-term memory processing using the characteristics of standing posture (quiet stance). As the level of interference may be related to the nature of the cognitive tasks used, we examined the effect of visual motion on a memory task which requires a spatial process (episodic recollection) versus a memory task which does not require this process (semantic comparisons). Results confirm data of the literature showing that compensatory postural response in the same direction as background motion. Repeatedly watching visual uniform motion or increasing the cognitive load with a memory task did not decrease postural deviations. Finally, participants were differentially controlling their balance according to the memory task but this difference was significant only in the vection condition and in the plane of background motion. Increased sway regularity (decreased entropy) combined with decreased postural stability (increase variance) during vection for the episodic task would indicate an ineffective postural control. The different interference of episodic and semantic memory on posture during visual motion is consistent with the involvement of spatial processes during episodic memory recollection. It can be suggested that spatial disorientation due to visual roll motion preferentially interferes with spatial cognitive tasks, as spatial tasks can draw on resources expended to control posture.

Can prediction and retrodiction explain whether frequent multi-word phrases are accessed 'precompiled' from memory or compositionally constructed on the fly?

An important debate on the architecture of the language faculty has been the extent to which it relies on a compositional system that constructs larger units from morphemes to words to phrases to utterances on the fly and in real time using grammatical rules; or a system that chunks large preassembled, stored units of language from memory; or some combination of both approaches. Good empirical evidence exists for both 'computed' and 'large stored' forms in language, but little is known about what shapes multi-word storage/ access or compositional processing. Here we explored whether predictive and retrodictive processes are a likely determinant of multi-word storage/ processing. Our results suggest that forward and backward predictability are independently informative in determining the lexical cohesiveness of multi-word phrases. In addition, our results call for a reevaluation of the role of retrodiction in contemporary language processing accounts (cf. Ferreira and Chantavarin, 2018).

Can we get human nature right?

Few questions in science are as controversial as human nature. At stake is whether our basic concepts and emotions are all learned from experience, or whether some are innate. Here, I demonstrate that reasoning about innateness is biased by the basic workings of the human mind. Psychological science suggests that newborns possess core concepts of "object" and "number." Laypeople, however, believe that newborns are devoid of such notions but that they can recognize emotions. Moreover, people presume that concepts are learned, whereas emotions (along with sensations and actions) are innate. I trace these beliefs to two tacit psychological principles: intuitive dualism and essentialism. Essentialism guides tacit reasoning about biological inheritance and suggests that innate traits reside in the body; per intuitive dualism, however, the mind seems ethereal, distinct from the body. It thus follows that, in our intuitive psychology, concepts (which people falsely consider as disembodied) must be learned, whereas emotions, sensations, and emotions (which are considered embodied) are likely innate; these predictions are in line with the experimental results. These conclusions do not speak to the question of whether concepts and emotions are innate, but they suggest caution in its scientific evaluation.

Emotion dynamics in movie dialogues.

Emotion dynamics is a framework for measuring how an individual's emotions change over time. It is a powerful tool for understanding how we behave and interact with the world. In this paper, we introduce a framework to track emotion dynamics through one's utterances. Specifically we introduce a number of utterance emotion dynamics (UED) metrics inspired by work in Psychology. We use this approach to trace emotional arcs of movie characters. We analyze thousands of such character arcs to test hypotheses that inform our broader understanding of stories. Notably, we show that there is a tendency for characters to use increasingly more negative words and become increasingly emotionally discordant with each other until about 90% of the narrative length. UED also has applications in behavior studies, social sciences, and public health.

The effect of encoding task on the forgetting of object gist and details.

One important feature of episodic memory is that it contains fine-grained and vividly recollected details. How to improve and maintain detailed information over time has been one of the central issues in memory research. Previous studies have inconsistent findings on whether detailed memory is forgotten more rapidly than gist memory. In this study, we investigated to what extent different encoding tasks modulated forgetting of gist and detailed information. In three experiments, participants were presented pictures of common objects and were asked to name them (Experiment 1), describe the details about them (Experiment 2) or imagine scenes associated with them (Experiment 3). After intervals of 10 minutes, one day, one week and one month, gist and detailed memories of the pictures were tested and assessed using a remember/know/guess judgement. The results showed that after the naming task, gist and detailed memories were forgotten at a similar rate, but after the description and the imagination tasks, detailed memory was forgotten at a slower rate than gist memory. The forgetting rate of gist memory was the slowest after the naming task, while that of detailed memory was the slowest after the description task. In addition, when three experiments were compared, the naming task enhanced the contributions of recollection and familiarity for gist memory, while the description task enhanced the contribution of familiarity for detailed memory. These results reveal the importance of the encoding task in the forgetting of gist and detailed information, and suggest a possible way to maintain perceptual details of objects at longer intervals.

Reading direct speech quotes increases theta phase-locking: Evidence for cortical tracking of inner speech?

Growing evidence shows that theta-band (4-7 Hz) activity in the auditory cortex phase-locks to rhythms of overt speech. Does theta activity also encode the rhythmic dynamics of inner speech? Previous research established that silent reading of direct speech quotes (e.g., Mary said: "This dress is lovely!") elicits more vivid inner speech than indirect speech quotes (e.g., Mary said that the dress was lovely). As we cannot directly track the phase alignment between theta activity and inner speech over time, we used EEG to measure the brain's phase-locked responses to the onset of speech quote reading. We found that direct (vs. indirect) quote reading was associated with increased theta phase synchrony over trials at 250-500 ms post-reading onset, with sources of the evoked activity estimated in the speech processing network. An eye-tracking control experiment confirmed that increased theta phase synchrony in direct quote reading was not driven by eye movement patterns, and more likely reflects synchronous phase resetting at the onset of inner speech. These findings suggest a functional role of theta phase modulation in reading-induced inner speech.

Nonlinear manifold learning in functional magnetic resonance imaging uncovers a low-dimensional space of brain dynamics.

Large-scale brain dynamics are believed to lie in a latent, low-dimensional space. Typically, the embeddings of brain scans are derived independently from different cognitive tasks or resting-state data, ignoring a potentially large-and shared-portion of this space. Here, we establish that a shared, robust, and interpretable low-dimensional space of brain dynamics can be recovered from a rich repertoire of task-based functional magnetic resonance imaging (fMRI) data. This occurs when relying on nonlinear approaches as opposed to traditional linear methods. The embedding maintains proper temporal progression of the tasks, revealing brain states and the dynamics of network integration. We demonstrate that resting-state data embeds fully onto the same task embedding, indicating similar brain states are present in both task and resting-state data. Our findings suggest analysis of fMRI data from multiple cognitive tasks in a low-dimensional space is possible and desirable.