Distributed representations of prediction error signals across the cortical hierarchy are synergistic.

A relevant question concerning inter-areal communication in the cortex is whether these interactions are synergistic. Synergy refers to the complementary effect of multiple brain signals conveying more information than the sum of each isolated signal. Redundancy, on the other hand, refers to the common information shared between brain signals. Here, we dissociated cortical interactions encoding complementary information (synergy) from those sharing common information (redundancy) during prediction error (PE) processing. We analyzed auditory and frontal electrocorticography (ECoG) signals in five common awake marmosets performing two distinct auditory oddball tasks and investigated to what extent event-related potentials (ERP) and broadband (BB) dynamics encoded synergistic and redundant information about PE processing. The information conveyed by ERPs and BB signals was synergistic even at lower stages of the hierarchy in the auditory cortex and between auditory and frontal regions. Using a brain-constrained neural network, we simulated the synergy and redundancy observed in the experimental results and demonstrated that the emergence of synergy between auditory and frontal regions requires the presence of strong, long-distance, feedback, and feedforward connections. These results indicate that distributed representations of PE signals across the cortical hierarchy can be highly synergistic.

Consensus-building conversation leads to neural alignment.

Conversation is a primary means of social influence, but its effects on brain activity remain unknown. Previous work on conversation and social influence has emphasized public compliance, largely setting private beliefs aside. Here, we show that consensus-building conversation aligns future brain activity within groups, with alignment persisting through novel experiences participants did not discuss. Participants watched ambiguous movie clips during fMRI scanning, then conversed in groups with the goal of coming to a consensus about each clip's narrative. After conversation, participants' brains were scanned while viewing the clips again, along with novel clips from the same movies. Groups that reached consensus showed greater similarity of brain activity after conversation. Participants perceived as having high social status spoke more and signaled disbelief in others, and their groups had unequal turn-taking and lower neural alignment. By contrast, participants with central positions in their real-world social networks encouraged others to speak, facilitating greater group neural alignment. Socially central participants were also more likely to become neurally aligned to others in their groups.

Decreased brain iron deposition based on quantitative susceptibility mapping correlates with reduced neurodevelopmental status in children with autism spectrum disorder.

To investigate potential correlations between the susceptibility values of certain brain regions and the severity of disease or neurodevelopmental status in children with autism spectrum disorder (ASD), 18 ASD children and 15 healthy controls (HCs) were recruited. The neurodevelopmental status was assessed by the Gesell Developmental Schedules (GDS) and the severity of the disease was evaluated by the Autism Behavior Checklist (ABC). Eleven brain regions were selected as regions of interest and the susceptibility values were measured by quantitative susceptibility mapping. To evaluate the diagnostic capacity of susceptibility values in distinguishing ASD and HC, the receiver operating characteristic (ROC) curve was computed. Pearson and Spearman partial correlation analysis were used to depict the correlations between the susceptibility values, the ABC scores, and the GDS scores in the ASD group. ROC curves showed that the susceptibility values of the left and right frontal white matter had a larger area under the curve in the ASD group. The susceptibility value of the right globus pallidus was positively correlated with the GDS-fine motor scale score. These findings indicated that the susceptibility value of the right globus pallidus might be a viable imaging biomarker for evaluating the neurodevelopmental status of ASD children.

Loss, gain and choice difficulty in gambling patients: Neural and behavioural processes.

Impaired decision-making is often displayed by individuals suffering from gambling disorder (GD). Since there are a variety of different phenomena influencing decision-making, we focused in this study on the effects of GD on neural and behavioural processes related to loss aversion and choice difficulty. Behavioural responses as well as brain images of 23 patients with GD and 20 controls were recorded while they completed a mixed gambles task, where they had to decide to either accept or reject gambles with different amounts of potential gain and loss. We found no behavioural loss aversion in either group and no group differences regarding loss and gain-related choice behaviour, but there was a weaker relation between choice difficulty and decision time in patients with GD. Similarly, we observed no group differences in processing of losses or gains, but choice difficulty was weaker associated with brain activity in the right anterior insula and anterior cingulate cortex in patients with GD. Our results showed for the first time the effects of GD on neural processes related to choice difficulty. In addition, our findings on choice difficulty give new insights on the psychopathology of GD and on neural processes related to impaired decision-making in GD.

Forming cognitive maps for abstract spaces: the roles of the human hippocampus and orbitofrontal cortex.

How does the human brain construct cognitive maps for decision-making and inference? Here, we conduct an fMRI study on a navigation task in multidimensional abstract spaces. Using a deep neural network model, we assess learning levels and categorized paths into exploration and exploitation stages. Univariate analyses show higher activation in the bilateral hippocampus and lateral prefrontal cortex during exploration, positively associated with learning level and response accuracy. Conversely, the bilateral orbitofrontal cortex (OFC) and retrosplenial cortex show higher activation during exploitation, negatively associated with learning level and response accuracy. Representational similarity analysis show that the hippocampus, entorhinal cortex, and OFC more accurately represent destinations in exploitation than exploration stages. These findings highlight the collaboration between the medial temporal lobe and prefrontal cortex in learning abstract space structures. The hippocampus may be involved in spatial memory formation and representation, while the OFC integrates sensory information for decision-making in multidimensional abstract spaces.

Comprehensive mapping of histamine H1 receptor mRNA in the mouse brain.

Histamine H1 receptor (H1R) in the central nervous system plays an important role in various functions, including learning and memory, aggression, feeding behaviors, and wakefulness, as evidenced by studies utilizing H1R knockout mice and pharmacological interventions. Although previous studies have reported the widespread distribution of H1R in the brains of rats, guinea pigs, monkeys, and humans, the detailed distribution in the mouse brain remains unclear. This study provides a comprehensive description of the distribution of H1R mRNA in the mouse brain using two recently developed techniques: RNAscope and in situ hybridization chain reaction, both of which offer enhanced sensitivity and resolution compared to traditional methodologies such as radioisotope labeling, which were used in previous studies. The H1R mRNA expression was observed throughout the entire brain, including key regions implicated in sleep-wake regulatory functions, such as the pedunculopontine tegmental nucleus and dorsal raphe. Additionally, strong H1R mRNA signals were identified in the paraventricular hypothalamus and ventromedial hypothalamus, which may explain the potential mechanisms underlying histamine-mediated feeding regulation. Notably, we identified strong H1R mRNA expression in previously unreported cerebral regions, such as the dorsal endopiriform nucleus, bed nucleus of the accessory olfactory tract, and postsubiculum. These findings significantly contribute to our understanding of the multifaceted roles of H1R in diverse brain functions.

The vmPFC-IPL functional connectivity as the neural basis of future self-continuity impacted procrastination: the mediating role of anticipated positive outcomes.

Procrastination is universally acknowledged as a problematic behavior with wide-ranging consequences impacting various facets of individuals' lives, including academic achievement, social accomplishments, and mental health. Although previous research has indicated that future self-continuity is robustly negatively correlated with procrastination, it remains unknown about the neural mechanisms underlying the impact of future self-continuity on procrastination. To address this issue, we employed a free construction approach to collect individuals' episodic future thinking (EFT) thoughts regarding specific procrastination tasks. Next, we conducted voxel-based morphometry (VBM) and resting-state functional connectivity (RSFC) analysis to explore the neural substrates underlying future self-continuity. Behavior results revealed that future self-continuity was significantly negatively correlated with procrastination, and positively correlated with anticipated positive outcome. The VBM analysis showed a positive association between future self-continuity and gray matter volumes in the right ventromedial prefrontal cortex (vmPFC). Furthermore, the RSFC results indicated that the functional connectivity between the right vmPFC and the left inferior parietal lobule (IPL) was positively correlated with future self-continuity. More importantly, the mediation analysis demonstrated that anticipated positive outcome can completely mediate the relationship between the vmPFC-IPL functional connectivity and procrastination. These findings suggested that vmPFC-IPL functional connectivity might prompt anticipated positive outcome about the task and thereby reduce procrastination, which provides a new perspective to understand the relationship between future self-continuity and procrastination.

A cautionary tale on the effects of different covariance structures in linear mixed effects modeling of fMRI data.

With the steadily increasing abundance of longitudinal neuroimaging studies with large sample sizes and multiple repeated measures, questions arise regarding the appropriate modeling of variance and covariance. The current study examined the influence of standard classes of variance-covariance structures in linear mixed effects (LME) modeling of fMRI data from patients with pediatric mild traumatic brain injury (pmTBI; N = 181) and healthy controls (N = 162). During two visits, participants performed a cognitive control fMRI paradigm that compared congruent and incongruent stimuli. The hemodynamic response function was parsed into peak and late peak phases. Data were analyzed with a 4-way (GROUP×VISIT×CONGRUENCY×PHASE) LME using AFNI's 3dLME and compound symmetry (CS), autoregressive process of order 1 (AR1), and unstructured (UN) variance-covariance matrices. Voxel-wise results dramatically varied both within the cognitive control network (UN>CS for CONGRUENCY effect) and broader brain regions (CS>UN for GROUP:VISIT) depending on the variance-covariance matrix that was selected. Additional testing indicated that both model fit and estimated standard error were superior for the UN matrix, likely as a result of the modeling of individual terms. In summary, current findings suggest that the interpretation of results from complex designs is highly dependent on the selection of the variance-covariance structure using LME modeling.

Gender differences in the functional language networks at birth: a resting-state fNIRS study.

Numerous studies reported inconsistent results concerning gender influences on the functional organization of the brain for language in children and adults. However, data for the gender differences in the functional language networks at birth are sparse. Therefore, we investigated gender differences in resting-state functional connectivity in the language-related brain regions in newborns using functional near-infrared spectroscopy. The results revealed that female newborns demonstrated significantly stronger functional connectivities between the superior temporal gyri and middle temporal gyri, the superior temporal gyri and the Broca's area in the right hemisphere, as well as between the right superior temporal gyri and left Broca's area. Nevertheless, statistical analysis failed to reveal functional lateralization of the language-related brain areas in resting state in both groups. Together, these results suggest that the onset of language system might start earlier in females, because stronger functional connectivities in the right brain in female neonates were probably shaped by the processing of prosodic information, which mainly constitutes newborns' first experiences of speech in the womb. More exposure to segmental information after birth may lead to strengthened functional connectivities in the language system in both groups, resulting in a stronger leftward lateralization in males and a more balanced or leftward dominance in females.

Identifying ADHD-Related Abnormal Functional Connectivity with a Graph Convolutional Neural Network.

Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder that is characterized by inattention, hyperactivity, and impulsivity. The neural mechanisms underlying ADHD remain inadequately understood, and current approaches do not well link neural networks and attention networks within brain networks. Our objective is to investigate the neural mechanisms related to attention and explore neuroimaging biological tags that can be generalized within the attention networks. In this paper, we utilized resting-state functional magnetic resonance imaging data to examine the differential functional connectivity network between ADHD and typically developing individuals. We employed a graph convolutional neural network model to identify individuals with ADHD. After classification, we visualized brain regions with significant contributions to the classification results. Our results suggest that the frontal, temporal, parietal, and cerebellar regions are likely the primary areas of dysfunction in individuals with ADHD. We also explored the relationship between regions of interest and attention networks, as well as the connection between crucial nodes and the distribution of positively and negatively correlated connections. This analysis allowed us to pinpoint the most discriminative brain regions, including the right orbitofrontal gyrus, the left rectus gyrus and bilateral insula, the right inferior temporal gyrus and bilateral transverse temporal gyrus in the temporal region, and the lingual gyrus of the occipital lobe, multiple regions of the basal ganglia and the upper cerebellum. These regions are primarily involved in the attention executive control network and the attention orientation network. Dysfunction in the functional connectivity of these regions may contribute to the underlying causes of ADHD.

Charitable crowdfunding donation-intention estimation depending on emotional project images using fNIRS-based functional connectivity.

Charitable fundraising increasingly relies on online crowdfunding platforms. Project images of charitable crowdfunding use emotional appeals to promote helping behavior. Negative emotions are commonly used to motivate helping behavior because the image of a happy child may not motivate donors to donate as willingly. However, some research has found that happy images can be more beneficial. These contradictory results suggest that the emotional valence of project imagery and how fundraisers frame project images effectively remain debatable. Thus, we compared and analyzed brain activation differences in the prefrontal cortex governing human emotions depending on donation decisions using functional near-infrared spectroscopy, a neuroimaging device. We advance existing theory on charitable behavior by demonstrating that little correlation exists in donation intentions and brain activity between negative and positive project images, which is consistent with survey results on donation intentions by victim image. We also discovered quantitative brain hemodynamic signal variations between donors and nondonors, which can predict and detect donor mental brain functioning using functional connectivity, that is, the statistical dependence between the time series of electrophysiological activity and oxygenated hemodynamic levels in the prefrontal cortex. These findings are critical in developing future marketing strategies for online charitable crowdfunding platforms, especially project images.

Mapping brain function in adults and young children during naturalistic viewing with high-density diffuse optical tomography.

Human studies of early brain development have been limited by extant neuroimaging methods. MRI scanners present logistical challenges for imaging young children, while alternative modalities like functional near-infrared spectroscopy have traditionally been limited by image quality due to sparse sampling. In addition, conventional tasks for brain mapping elicit low task engagement, high head motion, and considerable participant attrition in pediatric populations. As a result, typical and atypical developmental trajectories of processes such as language acquisition remain understudied during sensitive periods over the first years of life. We evaluate high-density diffuse optical tomography (HD-DOT) imaging combined with movie stimuli for high resolution optical neuroimaging in awake children ranging from 1 to 7 years of age. We built an HD-DOT system with design features geared towards enhancing both image quality and child comfort. Furthermore, we characterized a library of animated movie clips as a stimulus set for brain mapping and we optimized associated data analysis pipelines. Together, these tools could map cortical responses to movies and contained features such as speech in both adults and awake young children. This study lays the groundwork for future research to investigate response variability in larger pediatric samples and atypical trajectories of early brain development in clinical populations.

Verbal memory network mapping in individual patients predicts postoperative functional impairments.

Verbal memory decline is a significant concern following temporal lobe surgeries in patients with epilepsy, emphasizing the need for precision presurgical verbal memory mapping to optimize functional outcomes. However, the inter-individual variability in functional networks and brain function-structural dissociations pose challenges when relying solely on group-level atlases or anatomical landmarks for surgical guidance. Here, we aimed to develop and validate a personalized functional mapping technique for verbal memory using precision resting-state functional MRI (rs-fMRI) and neurosurgery. A total of 38 patients with refractory epilepsy scheduled for surgical interventions were enrolled and 28 patients were analyzed in the study. Baseline 30-min rs-fMRI scanning, verbal memory and language assessments were collected for each patient before surgery. Personalized verbal memory networks (PVMN) were delineated based on preoperative rs-fMRI data for each patient. The accuracy of PVMN was assessed by comparing post-operative functional impairments and the overlapping extent between PVMN and surgical lesions. A total of 14 out of 28 patients experienced clinically meaningful declines in verbal memory after surgery. The personalized network and the group-level atlas exhibited 100% and 75.0% accuracy in predicting postoperative verbal memory declines, respectively. Moreover, six patients with extra-temporal lesions that overlapped with PVMN showed selective impairments in verbal memory. Furthermore, the lesioned ratio of the personalized network rather than the group-level atlas was significantly correlated with postoperative declines in verbal memory (personalized networks: r = -0.39, p = .038; group-level atlas: r = -0.19, p = .332). In conclusion, our personalized functional mapping technique, using precision rs-fMRI, offers valuable insights into individual variability in the verbal memory network and holds promise in precision verbal memory network mapping in individuals.

Have you been there before? Decoding recognition of spatial scenes from fMRI signals in precuneus.

One potential application of forensic "brain reading" is to test whether a suspect has previously experienced a crime scene. Here, we investigated whether it is possible to decode real life autobiographic exposure to spatial locations using fMRI. In the first session, participants visited four out of eight possible rooms on a university campus. During a subsequent scanning session, subjects passively viewed pictures and videos from these eight possible rooms (four old, four novel) without giving any responses. A multivariate searchlight analysis was employed that trained a classifier to distinguish between "seen" versus "unseen" stimuli from a subset of six rooms. We found that bilateral precuneus encoded information that can be used to distinguish between previously seen and unseen rooms and that also generalized to the two stimuli left out from training. We conclude that activity in bilateral precuneus is associated with the memory of previously visited rooms, irrespective of the identity of the room, thus supporting a parietal contribution to episodic memory for spatial locations. Importantly, we could decode whether a room was visited in real life without the need of explicit judgments about the rooms. This suggests that recognition is an automatic response that can be decoded from fMRI data, thus potentially supporting forensic applications of concealed information tests for crime scene recognition.

Detecting language network alterations in mild cognitive impairment using task-based fMRI and resting-state fMRI: A comparative study.

OBJECTIVE: The objective of this study was to investigate the functional changes associated with mild cognitive impairment (MCI) using independent component analysis (ICA) with the word generation task functional magnetic resonance imaging (fMRI) and resting-state fMRI. METHODS: In this study 17 patients with MCI and age and education-matched 17 healthy individuals as control group are investigated. All participants underwent resting-state fMRI and task-based fMRI while performing the word generation task. ICA was used to identify the appropriate independent components (ICs) and their associated networks. The Dice Coefficient method was used to determine the relevance of the ICs to the networks of interest. RESULTS: IC-14 was found relevant to language network in both resting-state and task-based fMRI, IC-4 to visual, and IC-28 to dorsal attention network (DAN) in word generation task-based fMRI by Sorento-Dice Coefficient. ICA showed increased activation in language network, which had a larger voxel size in resting-state functional MRI than word generation task-based fMRI in the bilateral lingual gyrus. Right temporo-occipital fusiform cortex, right hippocampus, and right thalamus were also activated in the task-based fMRI. Decreased activation was found in DAN and visual network MCI patients in word generation task-based fMRI. CONCLUSION: Task-based fMRI and ICA are more sophisticated and reliable tools in evaluation cognitive impairments in language processing. Our findings support the neural mechanisms of the cognitive impairments in MCI.

Re-awakening the brain: Forcing transitions in disorders of consciousness by external in silico perturbation.

A fundamental challenge in neuroscience is accurately defining brain states and predicting how and where to perturb the brain to force a transition. Here, we investigated resting-state fMRI data of patients suffering from disorders of consciousness (DoC) after coma (minimally conscious and unresponsive wakefulness states) and healthy controls. We applied model-free and model-based approaches to help elucidate the underlying brain mechanisms of patients with DoC. The model-free approach allowed us to characterize brain states in DoC and healthy controls as a probabilistic metastable substate (PMS) space. The PMS of each group was defined by a repertoire of unique patterns (i.e., metastable substates) with different probabilities of occurrence. In the model-based approach, we adjusted the PMS of each DoC group to a causal whole-brain model. This allowed us to explore optimal strategies for promoting transitions by applying off-line in silico probing. Furthermore, this approach enabled us to evaluate the impact of local perturbations in terms of their global effects and sensitivity to stimulation, which is a model-based biomarker providing a deeper understanding of the mechanisms underlying DoC. Our results show that transitions were obtained in a synchronous protocol, in which the somatomotor network, thalamus, precuneus and insula were the most sensitive areas to perturbation. This motivates further work to continue understanding brain function and treatments of disorders of consciousness.

Role of the left posterior middle temporal gyrus in shape recognition and its reconstruction during drawing: A study combining transcranial magnetic stimulation and functional near infrared spectroscopy.

There are numerous reports of enhanced or emerged visual arts abilities in patients with semantic impairment. These reports led to the theory that a loss of function on the language side of the brain can result in changes of ability to draw and/or to paint. Further, the left posterior middle temporal gyrus (l-pMTG) has been revealed to contribute to the higher control semantic mechanisms with objects recognition and integration of visual information, within a widely distributed network of the left hemisphere. Nevertheless, the theory has not been fully studied in neural bases. The aim of this study is to examine role of the l-pMTG on shape recognition and its reconstruction within drawing behavior, by using a combining method of the repetitive transcranial magnetic stimulation (rTMS) and functional near-infrared spectroscopy (fNIRS). Eighteen healthy participants received a low frequency inhibitory rTMS to their l-pMTG during the drawing task of the Benton Visual Retention Test (BVRT). There was a significant decrease of the mean accuracy of reproductions in the Complex designs of the BVRT, compared to the Simple and Medium designs. The fNIRS data showed strong negative correlations with the results of the BVRT. Though our hypothesis had a contradiction that rTMS would have inhibited the brain activity in the stimulated site, the results suggest that shape recognition and its reconstruction such as the BVRT require neural activations of the l-TL as well as that of the l-pMTG.

Lessons learned from an fMRI-guided rTMS study on performance in a numerical Stroop task.

The Stroop task is a well-established tool to investigate the influence of competing visual categories on decision making. Neuroimaging as well as rTMS studies have demonstrated the involvement of parietal structures, particularly the intraparietal sulcus (IPS), in this task. Given its reliability, the numerical Stroop task was used to compare the effects of different TMS targeting approaches by Sack and colleagues (Sack AT 2009), who elegantly demonstrated the superiority of individualized fMRI targeting. We performed the present study to test whether fMRI-guided rTMS effects on numerical Stroop task performance could still be observed while using more advanced techniques that have emerged in the last decade (e.g., electrical sham, robotic coil holder system, etc.). To do so we used a traditional reaction time analysis and we performed, post-hoc, a more advanced comprehensive drift diffusion modeling approach. Fifteen participants performed the numerical Stroop task while active or sham 10 Hz rTMS was applied over the region of the right intraparietal sulcus (IPS) showing the strongest functional activation in the Incongruent > Congruent contrast. This target was determined based on individualized fMRI data collected during a separate session. Contrary to our assumption, the classical reaction time analysis did not show any superiority of active rTMS over sham, probably due to confounds such as potential cumulative rTMS effects, and the effect of practice. However, the modeling approach revealed a robust effect of rTMS on the drift rate variable, suggesting differential processing of congruent and incongruent properties in perceptual decision-making, and more generally, illustrating that more advanced computational analysis of performance can elucidate the effects of rTMS on the brain where simpler methods may not.

Neural processing of speech comprehension in noise predicts individual age using fNIRS-based brain-behavior models.

Speech comprehension in noise depends on complex interactions between peripheral sensory and central cognitive systems. Despite having normal peripheral hearing, older adults show difficulties in speech comprehension. It remains unclear whether the brain's neural responses could indicate aging. The current study examined whether individual brain activation during speech perception in different listening environments could predict age. We applied functional near-infrared spectroscopy to 93 normal-hearing human adults (20 to 70 years old) during a sentence listening task, which contained a quiet condition and 4 different signal-to-noise ratios (SNR = 10, 5, 0, -5 dB) noisy conditions. A data-driven approach, the region-based brain-age predictive modeling was adopted. We observed a significant behavioral decrease with age under the 4 noisy conditions, but not under the quiet condition. Brain activations in SNR = 10 dB listening condition could successfully predict individual's age. Moreover, we found that the bilateral visual sensory cortex, left dorsal speech pathway, left cerebellum, right temporal-parietal junction area, right homolog Wernicke's area, and right middle temporal gyrus contributed most to prediction performance. These results demonstrate that the activations of regions about sensory-motor mapping of sound, especially in noisy conditions, could be sensitive measures for age prediction than external behavior measures.