An In-depth Exploration of the Interplay between fMRI Methods and Theory in Cognitive Neuroscience.

Functional magnetic resonance imaging (fMRI) has been a cornerstone of cognitive neuroscience since its invention in the 1990s. The methods that we use for fMRI data analysis allow us to test different theories of the brain, thus different analyses can lead us to different conclusions about how the brain produces cognition. There has been a centuries-long debate about the nature of neural processing, with some theories arguing for functional specialization or localization (e.g., face and scene processing) while other theories suggest that cognition is implemented in distributed representations across many neurons and brain regions. Importantly, these theories have received support via different types of analyses; therefore, having students implement hands-on data analysis to explore the results of different fMRI analyses can allow them to take a firsthand approach to thinking about highly influential theories in cognitive neuroscience. Moreover, these explorations allow students to see that there are not clearcut "right" or "wrong" answers in cognitive neuroscience, rather we effectively instantiate assumptions within our analytical approaches that can lead us to different conclusions. Here, I provide Python code that uses freely available software and data to teach students how to analyze fMRI data using traditional activation analysis and machine-learning-based multivariate pattern analysis (MVPA). Altogether, these resources help teach students about the paramount importance of methodology in shaping our theories of the brain, and I believe they will be helpful for introductory undergraduate courses, graduate-level courses, and as a first analysis for people working in labs that use fMRI.

Alterations in functional brain connectivity associated with developmental dyscalculia.

BACKGROUND AND PURPOSE: In recent years, there has been a growing interest in the study of resting neural networks in different neurological and mental disorders. While previous studies suggest that the default mode network (DMN) may be altered in dyscalculia, the study of resting-state networks in the development of numerical skills, especially in children with developmental dyscalculia (DD), is scarce and relatively recent. Based on this, this study examines differences in resting-state functional connectivity (rs-FC) data of children with DD using functional connectivity multivariate pattern analysis (fc-MVPA), a data-driven methodology that summarizes properties of the entire connectome. METHODS: We performed fc-MVPA on resting-state images of a sample composed of a group of children with DD (n = 19, 8.06 ± 0.87 years) and an age- and sex-matched control group of typically developing children (n = 23, 7.76 ± 0.46 years). RESULTS: Analysis of fc-MVPA showed significant differences between group connectivity profiles in two clusters allocated in both the right and left medial temporal gyrus. Post hoc effect size results revealed a decreased rs-FC between each temporal pole and the DMN in children with DD and an increased rs-FC between each temporal pole and the sensorimotor network. CONCLUSIONS: Our results suggest an aberrant information flow between resting-state networks in children with DD, demonstrating the importance of these networks for arithmetic development.

Enhanced generalization and specialization of brain representations of semantic knowledge in healthy aging.

Aging is often associated with a decrease in cognitive capacities. However, semantic memory appears relatively well preserved in healthy aging. Both behavioral and neuroimaging studies support the view that changes in brain networks contribute to this preservation of semantic cognition. However, little is known about the role of healthy aging in the brain representation of semantic categories. Here we used pattern classification analyses and computational models to examine the neural representations of living and non-living word concepts. The results demonstrate that brain representations of animacy in healthy aging exhibit increased similarity across categories, even across different task contexts. This pattern of results aligns with the neural dedifferentiation hypothesis that proposes that aging is associated with decreased specificity in brain activity patterns and less efficient neural resource allocation. However, the loss in neural specificity for different categories was accompanied by increased dissimilarity of item-based conceptual representations within each category. Taken together, the age-related patterns of increased generalization and specialization in the brain representations of semantic knowledge may reflect a compensatory mechanism that enables a more efficient coding scheme characterized by both compression and sparsity, thereby helping to optimize the limited neural resources and maintain semantic processing in the healthy aging brain.

Similar patterns of brain activity for holistic representation of working memory: a study in children and adults.

Working memory is the fundamental function of the various cognitive processes and abilities in the overall trajectory of development. Significant advances in multivariate analysis of human functional magnetic resonance imaging data have converged functional segregation models toward integrated representation-based models. However, due to the inherent limitations of the multi-voxel pattern analysis method, we are unable to determine whether the underlying neural representations are spatially similar in the brain. Our study attempts to answer this question by examining the spatial similarity of brain activity during the working memory task in children and adults. Our results reveal similar patterns of activity between the regions involved in working memory. This functional network of similar spatial patterns was observed in both normally developing children and adults. However, the between-region similarity was more pronounced in adults than in children and associated with better performance. We propose an exchange of similar information flows through the brain at an integrated level of working memory processes, underpinning the holistic nature of working memory representation.

Optimizing magnetometers arrays and analysis pipelines for multivariate pattern analysis.

BACKGROUND: Multivariate pattern analysis (MVPA) has proven an excellent tool in cognitive neuroscience. It also holds a strong promise when applied to optically-pumped magnetometer-based magnetoencephalography. NEW METHOD: To optimize OPM-MEG systems for MVPA experiments this study examines data from a conventional MEG magnetometer array, focusing on appropriate noise reduction techniques for magnetometers. We determined the least required number of sensors needed for robust MVPA for image categorization experiments. RESULTS: We found that the use of signal space separation (SSS) without a proper regularization significantly lowered the classification accuracy considering a sub-array of 102 magnetometers or a sub-array of 204 gradiometers. We also found that classification accuracy did not improve when going beyond 30 sensors irrespective of whether SSS has been applied. COMPARISON WITH EXISTING METHODS: The power spectra of data filtered with SSS has a substantially higher noise floor that data cleaned with SSP or HFC. Consequently, MVPA decoding results obtained from the SSS-filtered data are significantly lower compared to all other methods employed. CONCLUSIONS: When designing MEG system based on SQUID magnetometers optimized for multivariate analysis for image categorization experiments, about 30 magnetometers are sufficient. We advise against applying SSS filters without a proper regularization to data from MEG and OPM systems prior to performing MVPA as this method, albeit reducing low-frequency external noise contributions, also introduces an increase in broadband noise. We recommend employing noise reduction techniques that either decrease or maintain the noise floor of the data like signal-space projection, homogeneous field correction and gradient noise reduction.

Selective Attention and Decision-Making Have Separable Neural Bases in Space and Time.

Attention and decision-making processes are fundamental to cognition. However, they are usually experimentally confounded, making it difficult to link neural observations to specific processes. Here we separated the effects of selective attention from the effects of decision-making on brain activity obtained from human participants (both sexes), using a two-stage task where the attended stimulus and decision were orthogonal and separated in time. Multivariate pattern analyses of multimodal neuroimaging data revealed the dynamics of perceptual and decision-related information coding through time with magnetoencephalography (MEG), through space with functional magnetic resonance imaging (fMRI), and their combination (MEG-fMRI fusion). Our MEG results showed an effect of attention before decision-making could begin, and fMRI results showed an attention effect in early visual and frontoparietal regions. Model-based MEG-fMRI fusion suggested that attention boosted stimulus information in the frontoparietal and early visual regions before decision-making was possible. Together, our results suggest that attention affects neural stimulus representations in the frontoparietal regions independent of decision-making.

Mindfulness meditation and placebo modulate distinct multivariate neural signatures to reduce pain.

BACKGROUND: Rather than a passive reflection of nociception, pain is shaped by the interplay between one's experiences, current cognitive-affective states, and expectations. The placebo-response, a paradoxical yet reliable phenomenon, is postulated to reduce pain by engaging mechanisms shared with "active" therapies. It has been assumed that mindfulness meditation, practiced by sustaining nonjudgmental awareness of arising sensory events, merely reflects mechanisms evoked by placebo. Recently, brain-based multivariate pattern analysis (MVPA) has been validated to successfully disentangle nociceptive-specific, negative-affective, and placebo-based dimensions of the subjective pain experience. METHODS: To determine if mindfulness meditation engages distinct brain mechanisms from placebo and sham-mindfulness to reduce pain, MVPA pain signatures were applied across two randomized clinical trials that employed overlapping psychophysical pain testing procedures (49°C noxious heat; visual analogue pain scales) and distinct fMRI techniques (blood-oxygen-level dependent; perfusion-based). After baseline pain testing, 115 healthy participants were randomized into a four-session mindfulness meditation (n = 37), placebo-cream conditioning (n = 19), sham-mindfulness meditation (n = 20), or book-listening (n = 39) intervention. After each intervention, noxious heat was administered during fMRI and each manipulation. RESULTS: A double dissociation in the MVPA signatures supporting pain regulation was revealed by mindfulness meditation as compared to placebo-cream. Mindfulness meditation produced significantly greater reductions in pain intensity and pain unpleasantness ratings, nociceptive-specific and negative-affective pain signatures when compared to placebo-cream, sham-mindfulness meditation and controls. Placebo-cream only reduced the placebo-based signature. CONCLUSIONS: Mindfulness meditation and placebo engage distinct neural pain signatures to reduce pain to demonstrate mechanistic granularity between placebo and mindfulness.

Sensory and Perceptual Decisional Processes Underlying the Perception of Reverberant Auditory Environments.

Reverberation, a ubiquitous feature of real-world acoustic environments, exhibits statistical regularities that human listeners leverage to self-orient, facilitate auditory perception, and understand their environment. Despite the extensive research on sound source representation in the auditory system, it remains unclear how the brain represents real-world reverberant environments. Here, we characterized the neural response to reverberation of varying realism by applying multivariate pattern analysis to electroencephalographic (EEG) brain signals. Human listeners (12 males and 8 females) heard speech samples convolved with real-world and synthetic reverberant impulse responses and judged whether the speech samples were in a "real" or "fake" environment, focusing on the reverberant background rather than the properties of speech itself. Participants distinguished real from synthetic reverberation with ∼75% accuracy; EEG decoding reveals a multistage decoding time course, with dissociable components early in the stimulus presentation and later in the perioffset stage. The early component predominantly occurred in temporal electrode clusters, while the later component was prominent in centroparietal clusters. These findings suggest distinct neural stages in perceiving natural acoustic environments, likely reflecting sensory encoding and higher-level perceptual decision-making processes. Overall, our findings provide evidence that reverberation, rather than being largely suppressed as a noise-like signal, carries relevant environmental information and gains representation along the auditory system. This understanding also offers various applications; it provides insights for including reverberation as a cue to aid navigation for blind and visually impaired people. It also helps to enhance realism perception in immersive virtual reality settings, gaming, music, and film production.

Associations of physical activity and soybean product consumption with psychological symptoms: a cross-sectional survey of Chinese university students.

INTRODUCTION: Declining physical activity among university students has become a concern, with increasingly poor dietary behaviors and other unfavorable factors having an impact on the occurrence of psychological symptoms. Previous studies have analyzed the association between moderate-to-vigorous physical activity (MVPA) and psychological symptoms, but few studies have investigated the association between soy product consumption and these symptoms. In addition, the associations between physical activity and soy product consumption with psychological symptoms have not been investigated. METHODS: In this study, 7267 university students from different regions of China were surveyed regarding physical activity, soy product consumption, and psychological symptoms. Binary logistic regression was used to analyze the associations among MVPA, soy product consumption, and psychological symptoms. A generalized linear model (GLM) was applied to further analyze the associations of MVPA and soy product consumption with psychological symptoms in this population. RESULTS: The detection rate of psychological symptoms among Chinese university students was 17.9%, with the rate among female students (18.9%) higher than that among male students (16.6%). The proportion of university students with MVPA < 30 min/d, 30-60 min/d, and > 60 min/d was 76.1%, 19.3%, and 4.6%, respectively, and the proportion with soy product consumption ≤ 2 times/wk, 3-5 times/wk, and ≥ 5 times/wk was 25.8%, 42.4%, and 31.7%, respectively. The GLM showed that compared with university students who had MVPA < 30 min/d and soy product consumption ≤ 2 times/week, those with the lowest risk of developing psychological symptoms had MVPA > 60 min/d and soy product consumption ≥ 6 times/week (OR = 0.198, 95% CI: 0.100-0.393, P < 0.001). This group was followed by university students with MVPA > 60 min/d and soy product consumption 3-5 times/week (OR = 0.221, 95% CI: 0.102-0.479, P < 0.001). CONCLUSION: In terms of research, there is an association between physical activity and soy product consumption and psychological symptoms among university students. The results of our study suggest that integrated intervention for psychological symptoms among university students is needed from the perspectives of physical activity and dietary behavior to promote good mental health in this population.

Impact of Outdoor Play Structures on Moderate to Vigorous Physical Activity in Children during Recess: A Comparative Study.

BACKGROUND/OBJECTIVES: It is believed that outdoor play structures lead to more physical activity for kids during school recess. However, the intensity of this activity remains unknown. This study explored whether access to outdoor play structures during recess interferes with children's physical activity levels. METHODS: Forty-one children (8-10 years old) accessed play structures during the afternoon recess but not in the morning for one entire week. To control for temperature differences, the same number of participants from another school who did not access playground structures were invited to participate. Moderate to Vigorous Physical Activity (MVPA) was determined using heart rate reserve. Heart rate was recorded using the Fitbit Inspire 2 (San Francisco, CA, USA) for at least three full school days. Wilcoxon signed-rank and Mann-Whitney U tests analyzed within- and between-group differences. RESULTS: The findings show no difference in MVPA when accessing or not accessing outdoor play structures, both within groups [(n = 37) median (25th-75th) 16 min (7-30) vs. 14 min (5-22)] and between groups [(n = 22) 16 min (7-26)]. The weekly MVPA for all participants (n = 59) [172 min (117-282)] was the strongest variable associated with MVPA during recess [t(df) = 5.40 (38), 95% CI 0.04-0.09, p < 0.001]. CONCLUSION: accessibility to outdoor play structures does not increase MVPA during recess in children aged 8 to 10. Therefore, schools may need various options for children to play during recess, allowing them to accumulate MVPA.

A Within-Subject Multimodal NIRS-EEG Classifier for Infant Data.

Functional Near Infrared Spectroscopy (fNIRS) and Electroencephalography (EEG) are commonly employed neuroimaging methods in developmental neuroscience. Since they offer complementary strengths and their simultaneous recording is relatively easy, combining them is highly desirable. However, to date, very few infant studies have been conducted with NIRS-EEG, partly because analyzing and interpreting multimodal data is challenging. In this work, we propose a framework to carry out a multivariate pattern analysis that uses an NIRS-EEG feature matrix, obtained by selecting EEG trials presented within larger NIRS blocks, and combining the corresponding features. Importantly, this classifier is intended to be sensitive enough to apply to individual-level, and not group-level data. We tested the classifier on NIRS-EEG data acquired from five newborn infants who were listening to human speech and monkey vocalizations. We evaluated how accurately the model classified stimuli when applied to EEG data alone, NIRS data alone, or combined NIRS-EEG data. For three out of five infants, the classifier achieved high and statistically significant accuracy when using features from the NIRS data alone, but even higher accuracy when using combined EEG and NIRS data, particularly from both hemoglobin components. For the other two infants, accuracies were lower overall, but for one of them the highest accuracy was still achieved when using combined EEG and NIRS data with both hemoglobin components. We discuss how classification based on joint NIRS-EEG data could be modified to fit the needs of different experimental paradigms and needs.

MRI resting-state signature of the propensity to experience meaningful coincidences: a functional coupling analysis.

The propensity to experience meaningful patterns in random arrangements and unrelated events shows considerable interindividual differences. Reduced inhibitory control (over sensory processes) and decreased working memory capacities are associated with this trait, which implies that the activation of frontal as well as posterior brain regions may be altered during rest and working memory tasks. In addition, people experiencing more meaningful coincidences showed reduced gray matter of the left inferior frontal gyrus (IFG), which is linked to the inhibition of irrelevant information in working memory and the control and integration of multisensory information. To study deviations in the functional connectivity of the IFG with posterior associative areas, the present study investigated the fMRI resting state in a large sample of n = 101 participants. We applied seed-to-voxel analysis and found that people who perceive more meaningful coincidences showed negative functional connectivity of the left IFG (i.e. pars triangularis) with areas of the left posterior associative cortex (e.g. superior parietal cortex). A data-driven multivoxel pattern analysis further indicated that functional connectivity of a cluster located in the right cerebellum with a cluster including parts of the left middle frontal gyrus, left precentral gyrus, and the left IFG (pars opercularis) was associated with meaningful coincidences. These findings add evidence to the neurocognitive foundations of the propensity to experience meaningful coincidences, which strengthens the idea that deviations of working memory functions and inhibition of sensory and motor information explain why people experience more meaning in meaningless noise.

The metacontrol of event segmentation-A neurophysiological and behavioral perspective.

During our everyday life, the constant flow of information is divided into discrete events, a process conceptualized in Event Segmentation Theory (EST). How people perform event segmentation and the resulting granularity of encapsulated segments likely depends on their metacontrol style. Yet, the underlying neural mechanisms remain undetermined. The current study examines how the metacontrol style affects event segmentation through the analysis of EEG data using multivariate pattern analysis (MVPA) and source localization analysis. We instructed two groups of healthy participants to either segment a movie as fine-grained as possible (fine-grain group) or provided no such instruction (free-segmentation group). The fine-grain group showed more segments and a higher likelihood to set event boundaries upon scene changes, which supports the notion that cognitive control influences segmentation granularity. On a neural level, representational dynamics were decodable 400 ms prior to the decision to close a segment and open a new one, and especially fronto-polar regions (BA10) were associated with this representational dynamic. Groups differed in their use of this representational dynamics to guide behavior and there was a higher sensitivity to incoming information in the Fine-grain group. Moreover, a higher likelihood to set event boundaries was reflected by activity increases in the insular cortex suggesting an increased monitoring of potentially relevant upcoming events. The study connects the EST with the metacontrol framework and relates these to overarching neural concepts of prefrontal cortex function.

Analysis of the associations between moderate-to-vigorous physical activity and screen time on psychological symptoms among university students: a cross-sectional survey based on six geographic regions in China.

BACKGROUND: Declining physical activity and increasing screen time (ST) among Chinese adolescents have become major concerns shared by scholars, while mental health issues are also on the rise. Previous studies have confirmed the association between physical activity and screen time and psychological symptoms, but it is unclear how their psychological symptoms, especially for Chinese university students who have a high proportion of psychological symptoms, and no research evidence has been found. METHODS: This study investigated physical activity, screen time, and psychological symptoms in 11,173 university students aged 19-22 years in six regions of China. A binary logistic regression analysis was used to analyze the association between moderate-to-vigorous physical activity (MVPA) and screen time and psychological symptoms. And the generalize linear model (GLM) analysis was used to further analyze the association between MVPA and screen time and psychological symptoms. RESULTS: The detection rate of psychological symptoms among Chinese university students was 16.3%, with a higher percentage of female students (17.5%) than male students (14.7%). The proportion of male students (8.2%) with MVPA > 60 min/d was higher than that of female students (2.3%), and the proportion of male students (33.8%) and female students (34.5%) with screen time > 2 h/d was basically the same. The generalize linear model (GLM) analysis showed that university students with MVPA < 30 min/d and screen time > 2 h/d (OR = 1.59, 95% CI: 1.10-2.31) had the highest risk of psychological symptoms (OR = 1.59, 95% CI: 1.10-2.31) compared to university students with MVPA > 60 min/d and screen time < 1 h/d as the reference group. The risk of psychological symptoms was the highest among those with MVPA < 30 min/d and screen time > 2 h/d (OR = 1.59,95% CI: 1.10-2.31). In addition, university students with MVPA > 60 min/d and a screen time of 1-2 h/d (OR = 0.09, 95% CI: 0.03-0.25) had the lowest risk of psychological symptoms (P < 0.001). The same trend was observed for both male and female students. CONCLUSION: Chinese university students have a certain proportion of psychological symptom problems, and there is a significant between MVPA and screen time and psychological symptoms, and the same trend exists for both male and female students. Chinese university students should perform MVPA for not less than 60 min a day, and at the same time control the duration of screen time, and screen time should be controlled between 1 and 2 h a day, which has a better promotion effect on psychological health.

Association of Physical Activity Patterns with the Metabolic Syndrome in Korean Adults: A Nationwide Cross-Sectional Study.

Background: Recent research has focused on a new group called the "weekend warriors". These individuals accumulate their recommended moderate to vigorous physical activity (MVPA) over just 1-2 days, often during weekends, while remaining relatively inactive during the rest of the week. However, the effects of engaging in low-frequency MVPA on the risk of metabolic syndrome (MetS) are not well understood. This study investigated the association between physical activity patterns and the risk of MetS among Korean adults. Methods: This study included 26,197 participants (11,804 male and 14,393 female) aged ≥ 20 years from the Korea National Health and Nutrition Examination Survey. MVPA was measured using a global physical activity questionnaire. MetS was defined as the presence of more than three risk factors. Results: The odds ratio (OR) for MetS was 0.60 (95% confidence interval [CI] = 0.52, 0.70) in the "regularly active" group and 0.82 (95% CI = 0.69, 0.98) in the "weekend warrior" group compared to that in the inactive group (reference), which controlled for all covariates. For sensitivity analyses, the results across all subgroups exhibited similar patterns, with more pronounced effects observed in women, middle-aged individuals, and non-drinkers/light drinkers. Conclusions: Our findings suggest that concentrated bouts of moderate to vigorous physical activity, even if undertaken infrequently, confer health benefits that align with the recommended guidelines. This study contributes to the growing evidence on the relationship between physical activity patterns and MetS risk in Korean adults. The study also emphasizes the potential of different activity patterns in mitigating metabolic risk.

Semantic structures facilitate threat memory integration throughout the medial temporal lobe and medial prefrontal cortex.

Emotional experiences can profoundly impact our conceptual model of the world, modifying how we represent and remember a host of information even indirectly associated with that experienced in the past. Yet, how a new emotional experience infiltrates and spreads across pre-existing semantic knowledge structures (e.g., categories) is unknown. We used a modified aversive sensory preconditioning paradigm in fMRI (n = 35) to investigate whether threat memories integrate with a pre-established category to alter the representation of the entire category. We observed selective but transient changes in the representation of conceptually related items in the amygdala, medial prefrontal cortex, and occipitotemporal cortex following threat conditioning to a simple cue (geometric shape) pre-associated with a different, but related, set of category exemplars. These representational changes persisted beyond 24 h in the hippocampus and perirhinal cortex. Reactivation of the semantic category during threat conditioning, combined with activation of the hippocampus or medial prefrontal cortex, was predictive of subsequent amygdala reactivity toward novel category members at test. This provides evidence for online integration of emotional experiences into semantic categories, which then promotes threat generalization. Behaviorally, threat conditioning by proxy selectively and retroactively enhanced recognition memory and increased the perceived typicality of the semantic category indirectly associated with threat. These findings detail a complex route through which new emotional learning generalizes by modifying semantic structures built up over time and stored in memory as conceptual knowledge.

Aberrant functional hubs and related networks attributed to cognitive impairment in patients with anti­N­methyl­D­aspartate receptor encephalitis.

Anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis results in severe neuropsychiatric symptoms and persistent cognitive impairment; however, the underlying mechanism is still not fully understood. The present study utilized the degree centrality (DC), functional connectivity (FC) and multivariate pattern analysis (MVPA) to further explore neurofunctional symptoms in patients with anti-NMDAR encephalitis. A total of 29 patients with anti-NMDAR encephalitis and 26 healthy controls (HCs) were enrolled for neuropsychological assessment and resting-state functional MRI (rs-fMRI) scans. DC, FC and MVPA were examined to investigate cerebral functional activity and distinguish neuroimaging characteristics between the patient and HC groups based on the rs-fMRI data. Compared with the HCs, the patients exhibited cognitive deficits, anxiety and depression. In the DC analysis, the patients exhibited significantly decreased DC strength in the left rectus gyrus, left caudate nucleus (LCN) and bilateral superior medial frontal gyrus, as well as increased DC strength in the cerebellar anterior lobe, compared with the HCs. In the subsequent FC analysis, the LCN showed decreased FC strength in the bilateral middle frontal gyrus and right precuneus. Furthermore, correlation analysis indicated that disrupted cerebral functional activity was significantly correlated with the alerting effect and Hamilton Depression Scale score. Using DC maps and receiver operating characteristic curve analysis, the MVPA classifier exhibited an area under curve of 0.79, and the accuracy classification rate was 76.36%, with a sensitivity of 79.31% and a specificity of 78.18%. The present study revealed that the disrupted functional activity of hub and related networks in the cerebellum, including the default mode network and executive control network, contributed to deficits in cognition and emotion in patients with anti-NMDAR encephalitis. In conclusion, the present study provided imaging evidence and primary diagnostic markers for pathological and compensatory mechanisms of anti-NMDAR encephalitis, with the aim of improving the understanding of this disease.

Top-Down Task Goals Induce the Retrieval State.

Engaging the retrieval state (Tulving, 1983) impacts processing and behavior (Long and Kuhl, 2019, 2021; Smith et al., 2022), but the extent to which top-down factors-explicit instructions and goals-versus bottom-up factors-stimulus properties such as repetition and similarity-jointly or independently induce the retrieval state is unclear. Identifying the impact of bottom-up and top-down factors on retrieval state engagement is critical for understanding how control of task-relevant versus task-irrelevant brain states influence cognition. We conducted between-subjects recognition memory tasks on male and female human participants in which we varied test phase goals. We recorded scalp electroencephalography and used an independently validated mnemonic state classifier (Long, 2023) to measure retrieval state engagement as a function of top-down task goals (recognize old vs detect new items) and bottom-up stimulus repetition (hits vs correct rejections (CRs)). We find that whereas the retrieval state is engaged for hits regardless of top-down goals, the retrieval state is only engaged during CRs when the top-down goal is to recognize old items. Furthermore, retrieval state engagement is greater for low compared to high confidence hits when the task goal is to recognize old items. Together, these results suggest that top-down demands to recognize old items induce the retrieval state independent from bottom-up factors, potentially reflecting the recruitment of internal attention to enable access of a stored representation.

More than labels: neural representations of emotion words are widely distributed across the brain.

Although emotion words such as "anger," "disgust," "happiness," or "pride" are often thought of as mere labels, increasing evidence points to language as being important for emotion perception and experience. Emotion words may be particularly important for facilitating access to the emotion concepts. Indeed, deficits in semantic processing or impaired access to emotion words interfere with emotion perception. Yet, it is unclear what these behavioral findings mean for affective neuroscience. Thus, we examined the brain areas that support processing of emotion words using representational similarity analysis of functional magnetic resonance imaging data (N = 25). In the task, participants saw 10 emotion words (e.g. "anger," "happiness") while in the scanner. Participants rated each word based on its valence on a continuous scale ranging from 0 (Pleasant/Good) to 1 (Unpleasant/Bad) scale to ensure they were processing the words. Our results revealed that a diverse range of brain areas including prefrontal, midline cortical, and sensorimotor regions contained information about emotion words. Notably, our results overlapped with many regions implicated in decoding emotion experience by prior studies. Our results raise questions about what processes are being supported by these regions during emotion experience.

Decoding N400m Evoked Component: A Tutorial on Multivariate Pattern Analysis for OP-MEG Data.

Multivariate pattern analysis (MVPA) has played an extensive role in interpreting brain activity, which has been applied in studies with modalities such as functional Magnetic Resonance Imaging (fMRI), Magnetoencephalography (MEG) and Electroencephalography (EEG). The advent of wearable MEG systems based on optically pumped magnetometers (OPMs), i.e., OP-MEG, has broadened the application of bio-magnetism in the realm of neuroscience. Nonetheless, it also raises challenges in temporal decoding analysis due to the unique attributes of OP-MEG itself. The efficacy of decoding performance utilizing multimodal fusion, such as MEG-EEG, also remains to be elucidated. In this regard, we investigated the impact of several factors, such as processing methods, models and modalities, on the decoding outcomes of OP-MEG. Our findings indicate that the number of averaged trials, dimensionality reduction (DR) methods, and the number of cross-validation folds significantly affect the decoding performance of OP-MEG data. Additionally, decoding results vary across modalities and fusion strategy. In contrast, decoder type, resampling frequency, and sliding window length exert marginal effects. Furthermore, we introduced mutual information (MI) to investigate how information loss due to OP-MEG data processing affect decoding accuracy. Our study offers insights for linear decoding research using OP-MEG and expand its application in the fields of cognitive neuroscience.