Modeling regional and psychophysiologic interactions in fMRI: the importance of hemodynamic deconvolution

An Anisotropic 4D Filtering Approach to Recover Brain Activation From Paradigm-Free Functional MRI Data

CONTEXT

Functional Magnetic Resonance Imaging (fMRI) is a non-invasive imaging technique that provides an indirect view into brain activity via the blood oxygen level dependent (BOLD) response. In particular, resting-state fMRI poses challenges to the recovery of brain activity without prior knowledge on the experimental paradigm, as it is the case for task fMRI. Conventional methods to infer brain activity from the fMRI signals, for example, the general linear model (GLM), require the knowledge of the experimental paradigm to define regressors and estimate the contribution of each voxel's time course to the task. To overcome this limitation, approaches to deconvolve the BOLD response and recover the underlying neural activations without a priori information on the task have been proposed. State-of-the-art techniques, and in particular the total activation (TA), formulate the deconvolution as an optimization problem with decoupled spatial and temporal regularization and an optimization strategy that alternates between the constraints.

APPROACH

In this work, we propose a paradigm-free regularization algorithm named Anisotropic 4D-fMRI (A4D-fMRI) that is applied on the 4D fMRI image, acting simultaneously in the 3D space and 1D time dimensions. Based on the idea that large image variations should be preserved as they occur during brain activations, whereas small variations considered as noise should be removed, the A4D-fMRI applies an anisotropic regularization, thus recovering the location and the duration of brain activations.

RESULTS

Using the experimental paradigm as ground truth, the A4D-fMRI is validated on synthetic and real task-fMRI data from 51 subjects, and its performance is compared to the TA. Results show higher correlations of the recovered time courses with the ground truth compared to the TA and lower computational times. In addition, we show that the A4D-fMRI recovers activity that agrees with the GLM, without requiring or using any knowledge of the experimental paradigm.

Whole-brain connectivity during encoding: age-related differences and associations with cognitive and brain structural decline

There is a limited understanding of age differences in functional connectivity during memory encoding. In the present study, a sample of cognitively healthy adult participants (n = 488, 18-81 years), a subsample of whom had longitudinal cognitive and brain structural data spanning on average 8 years back, underwent functional magnetic resonance imaging while performing an associative memory encoding task. We investigated (1) age-related differences in whole-brain connectivity during memory encoding; (2) whether encoding connectivity patterns overlapped with the activity signatures of specific cognitive processes, and (3) whether connectivity associated with memory encoding related to longitudinal brain structural and cognitive changes. Age was associated with lower intranetwork connectivity among cortical networks and higher internetwork connectivity between networks supporting higher level cognitive functions and unimodal and attentional areas during encoding. Task-connectivity between mediotemporal and posterior parietal regions-which overlapped with areas involved in mental imagery-was related to better memory performance only in older age. The connectivity patterns supporting memory performance in older age reflected preservation of thickness of the medial temporal cortex. The results are more in accordance with a maintenance rather than a compensation account.

The motor inhibitory network in patients with asymmetrical Parkinson's disease: An fMRI study

Recent imaging studies with the stop-signal task in healthy individuals indicate that the subthalamic nucleus, the pre-supplementary motor area and the inferior frontal gyrus are key components of the right hemisphere “inhibitory network”. Limited information is available regarding neural substrates of inhibitory processing in patients with asymmetric Parkinson’s disease. The aim of the current fMRI study was to identify the neural changes underlying deficient inhibitory processing on the stop-signal task in patients with predominantly left-sided Parkinson’s disease. Fourteen patients and 23 healthy controls performed a stop-signal task with the left and right hands. Behaviorally, patients showed delayed response inhibition with either hand compared to controls. We found small imaging differences for the right hand, however for the more affected left hand when behavior was successfully inhibited we found reduced activation of the inferior frontal gyrus bilaterally and the insula. Using the stop-signal delay as regressor, contralateral underactivation in the right dorsolateral prefrontal cortex, inferior frontal and anterior putamen were found in patients. This finding indicates dysfunction of the right inhibitory network in left-sided Parkinson’s disease. Functional connectivity analysis of the left subthalamic nucleus showed a significant increase of connectivity with bilateral insula. In contrast, the right subthalamic nucleus showed increased connectivity with visuomotor and sensorimotor regions of the cerebellum. We conclude that altered inhibitory control in left-sided Parkinson’s disease is associated with reduced activation in regions dedicated to inhibition in healthy controls, which requires engagement of additional regions, not observed in controls, to successfully stop ongoing actions.

The effects of stimulus inversion on the neural representations of Chinese character and face recognition

This study investigates whether stimulus inversion influences neural responses of Chinese character recognition similarly to its effect on face recognition in category-selective and object-related brain areas using functional magnetic resonance imaging. Participants performed a one-back matching task for simple (one radical) and compound (two radicals) Chinese characters and faces with upright and inverted orientations. Inverted stimuli produced slower response times with stronger activity within the fusiform gyrus (FG) than upright stimuli for faces and Chinese characters. While common inversion-related activation was identified in the left FG among stimulus types, we observed a significant inter-regional correlation between the left FG and the intraparietal sulcus for face inversion. Importantly, analyses of region-of-interest (ROI) multivariate pattern classification showed that classifiers trained on face inversion can decode the representations of character inversion in the character-selective ROI. However, this was not true for face inversion in face-selective ROIs when the classifiers were trained on characters. Similar activity patterns for character and face inversion were observed in the object-related ROIs. We also showed higher decoding accuracy for upright stimuli in the face-selective ROI than in the character-selective ROI but this was not true for inverted ones or when patterns were examined in the object-related ROIs. Together, our results support shared and distinct configural representations for character and face recognition in category-selective and object-related brain areas.

Topography of hippocampal connectivity with sensorimotor cortex revealed by optimizing smoothing kernel and voxel size

Studies of the hippocampus use smaller voxel sizes and smoothing kernels than cortical activation studies, typically using a multivoxel seed with specified radius for connectivity analysis. This study identified optimal processing parameters for evaluating hippocampal connectivity with sensorimotor cortex (SMC), comparing effectiveness by varying parameters during both activation and connectivity analysis. Using both 3mm and 4mm isovoxels, smoothing kernels of 0-10mm were evaluated on the amplitude and extent of motor activation and hippocampal connectivity with SMC. Psychophysiological interactions (PPI) identified hippocampal connectivity with SMC during volitional movements, and connectivity effects from multivoxel seeds were compared with alternate methods; a structural seed represented the mean connectivity map from all voxels within a region, whereas a functional seed represented the regional voxel with maximal SMC connectivity. With few exceptions, the same parameters were optimal for activation and connectivity. Larger isovoxels showed larger activation volumes in both SMC and the hippocampus; connectivity volumes from structural seeds were also larger, except from the posterior hippocampus. Regardless of voxel size, the 10mm smoothing kernel generated larger activation and connectivity volumes from structural seeds, as well as larger beta estimates at connectivity maxima; structural seeds also produced larger connectivity volumes than multivoxel seeds. Functional seeds showed lesser effects from voxel size and smoothing kernels. Optimal parameters revealed topography in structural seed connectivity along both the longitudinal axis and mediolateral axis of the hippocampus. These results indicate larger voxels and smoothing kernels can improve sensitivity for detecting both cortical activation and hippocampal connectivity.

From Counting to Retrieving: Neural Networks Underlying Alphabet Arithmetic Learning

This fMRI study aimed at unraveling the neural basis of learning alphabet arithmetic facts, as a proxy of the transition from slow and effortful procedural counting-based processing to fast and effortless processing as it occurs in learning addition arithmetic facts. Neural changes were tracked while participants solved alphabet arithmetic problems in a verification task (e.g., F + 4 = J). Problems were repeated across four learning blocks. Two neural networks with opposed learning-related changes were identified. Activity in a network consisting of basal ganglia and parieto-frontal areas decreased with learning, which is in line with a reduction of the involvement of procedure-based processing. Conversely, activity in a network involving the left angular gyrus and, to a lesser extent, the hippocampus gradually increases with learning, evidencing the gradual involvement of retrieval-based processing. Connectivity analyses gave insight in the functional relationship between the two networks. Despite the opposing learning-related trajectories, it was found that both networks become more integrated. Taking alphabet arithmetic as a proxy for learning arithmetic, the present results have implications for current theories of learning arithmetic facts and can give direction to future developments.

Functional Connectivity Basis and Underlying Cognitive Mechanisms for Gender Differences in Guilt Aversion

Prosocial behavior is pivotal to our society. Guilt aversion, which describes the tendency to reduce the discrepancy between a partner's expectation and his/her actual outcome, drives human prosocial behavior as does well-known inequity aversion. Although women are reported to be more inequity averse than men, gender differences in guilt aversion remain unexplored. Here, we conducted a functional magnetic resonance imaging (fMRI) study (n = 52) and a large-scale online behavioral study (n = 4723) of a trust game designed to investigate guilt and inequity aversions. The fMRI study demonstrated that men exhibited stronger guilt aversion and recruited right dorsolateral prefrontal cortex (DLPFC)-ventromedial PFC (VMPFC) connectivity more for guilt aversion than women, while VMPFC-dorsal medial PFC (DMPFC) connectivity was commonly used in both genders. Furthermore, our regression analysis of the online behavioral data collected with Big Five and demographic factors replicated the gender differences and revealed that Big Five Conscientiousness (rule-based decision) correlated with guilt aversion only in men, but Agreeableness (empathetic consideration) correlated with guilt aversion in both genders. Thus, this study suggests that gender differences in prosocial behavior are heterogeneous depending on underlying motives in the brain and that the consideration of social norms plays a key role in the stronger guilt aversion in men.

Sniffing the human body volatile hexadecanal blocks aggression in men but triggers aggression in women

In terrestrial mammals, body volatiles can effectively trigger or block conspecific aggression. Here, we tested whether hexadecanal (HEX), a human body volatile implicated as a mammalian-wide social chemosignal, affects human aggression. Using validated behavioral paradigms, we observed a marked dissociation: Sniffing HEX blocked aggression in men but triggered aggression in women. Next, using functional brain imaging, we uncovered a pattern of brain activity mirroring behavior: In both men and women, HEX increased activity in the left angular gyrus, an area implicated in perception of social cues. HEX then modulated functional connectivity between the angular gyrus and a brain network implicated in social appraisal (temporal pole) and aggressive execution (amygdala and orbitofrontal cortex) in a sex-dependent manner consistent with behavior: increasing connectivity in men but decreasing connectivity in women. These findings implicate sex-specific social chemosignaling at the mechanistic heart of human aggressive behavior.

Offline tDCS modulates prefrontal-cortical-subcortical-cerebellar fear pathways in delayed fear extinction

Transcranial direct current stimulation (tDCS) has been studied to enhance extinction-based treatments for anxiety disorders. However, the field shows conflicting results about its anxiolytic effect and only a few studies have observed the extinction of consolidated memories. We looked to study the effect of offline 1 mA tDCS over the right dorsolateral pre-frontal cortex across the fear pathways, in consolidated fear response during delayed extinction. Participants (N = 34 women) underwent in a two-day fear conditioning procedure. On day 1, participants were assigned to the control group (N = 18) or the tDCS group (N = 16) and went through a fear acquisition procedure. On day 2, the tDCS group received 20 min tDCS before extinction and while inside the MRI scanner. The control group completed the extinction procedure only. The tDCS session (for the tDCS group) and the fMRI scan (for both groups) were completed just on the second day. Univariate fMRI analysis showed stimulation-dependent activity during late extinction with the tDCS group showing decreased neural activity during the processing of threat cues (CS +) and increased activity during the processing of safety cues (CS -), in prefrontal, postcentral and paracentral regions, during late extinction. ROI to whole-brain psychophysiological interaction (PPI) analysis showed the tDCS effect on the connectivity between the left dorsolateral prefrontal cortex three cortical-amygdalo-hippocampal-cerebellar pathway clusters during the processing of the CS + in late extinction (TFCE corrected; p < 0.05). Increased neuronal activity during the processing of safety cues and stronger coupling during the processing of threat cues might be the mechanisms by which tDCS contributes to stimuli discrimination.

Functional Interactions Between Neural Substrates of Socio-cognitive Mechanisms Involved in Simple Deception and Manipulative Truth

Introduction: Deceptive intentions may be realized by imparting false (simple deception) or true (manipulative truth) information. Both forms of deception require inferring others' thoughts and are underpinned by the theory of mind (TOM) neural system. Manipulative truth is thought to more strongly recruit these processes. However, the organization of functional interactions underlying simple deception and manipulative truth remains unclear. Materials and Methods: We performed psychophysiological interaction analysis for a key node in the TOM system, the right temporoparietal junction (rTPJ), using functional MRI data obtained from 23 volunteers (14 men and 9 women, age range 18-45 years) during the sender-receiver game. During the game, participants sent true, simple deceptive, or manipulative truthful messages to another player according to their own choice. A Bayesian approach to statistics was employed to perform statistical inference and define voxels with significant changes in functional interactions. Results: We observed functional interactions between nodes of the TOM system (bilateral TPJ, left precuneus, left dorsomedial prefrontal cortex, and right superior temporal sulcus) characterizing both forms of deception. We identified an increment in functional interactions of the rTPJ with the left TPJ (lTPJ) and right precuneus associated with manipulative truth. Furthermore, we demonstrated that a higher rate of manipulative truthful actions was associated with weaker functional interactions between the rTPJ and lTPJ, left precuneus, and left dorsomedial prefrontal cortex. Discussion: Compared with simple deception, manipulative truth is associated with a higher demand for socio-cognitive processes that contributes to the cognitive load of this form of deception.

Functional specificity and neural integration in the aesthetic appreciation of artworks with implied motion

Although there is growing interest in the neural foundations of aesthetic experience, it remains unclear how particular mental subsystems (e.g. perceptual, affective and cognitive) are involved in different types of aesthetic judgements. Here, we use fMRI to investigate the involvement of different neural networks during aesthetic judgements of visual artworks with implied motion cues. First, a behavioural experiment (N = 45) confirmed a preference for paintings with implied motion over static cues. Subsequently, in a preregistered fMRI experiment (N = 27), participants made aesthetic and motion judgements towards paintings representing human bodies in dynamic and static postures. Using functional region-of-interest and Bayesian multilevel modelling approaches, we provide no compelling evidence for unique sensitivity within or between neural systems associated with body perception, motion and affective processing during the aesthetic evaluation of paintings with implied motion. However, we show suggestive evidence that motion and body-selective systems may integrate signals via functional connections with a separate neural network in dorsal parietal cortex, which may act as a relay or integration site. Our findings clarify the roles of basic visual and affective brain circuitry in evaluating a central aesthetic feature-implied motion-while also pointing towards promising future research directions, which involve modelling aesthetic preferences as hierarchical interplay between visual and affective circuits and integration processes in frontoparietal cortex.

Reduced Hippocampal-Striatal Interactions during Formation of Durable Episodic Memories in Aging

Encoding of durable episodic memories requires cross-talk between the hippocampus and multiple brain regions. Changes in these hippocampal interactions could contribute to age-related declines in the ability to form memories that can be retrieved after extended time intervals. Here we tested whether hippocampal–neocortical– and subcortical functional connectivity (FC) observed during encoding of durable episodic memories differed between younger and older adults. About 48 younger (20–38 years; 25 females) and 43 older (60–80 years; 25 females) adults were scanned with fMRI while performing an associative memory encoding task. Source memory was tested ~20 min and ~6 days postencoding. Associations recalled after 20 min but later forgotten were classified as transient, whereas memories retained after long delays were classified as durable. Results demonstrated that older adults showed a reduced ability to form durable memories and reduced hippocampal–caudate FC during encoding of durable memories. There was also a positive relationship between hippocampal–caudate FC and higher memory performance among the older adults. No reliable age group differences in durable memory–encoding activity or hippocampal–neocortical connectivity were observed. These results support the classic theory of striatal alterations as one cause of cognitive decline in aging and highlight that age-related changes in episodic memory extend beyond hippocampal–neocortical connections.

An fMRI investigation of the intention-outcome interactions in second- and third-party punishment

Second-party punishment (SPP) and third-party punishment (TPP) are two basic forms of costly punishment that play an essential role in maintaining social orders. Despite scientific breakthroughs in understanding that costly punishment is driven by an integration of the wrongdoers' intention and the outcome of their actions, so far, few studies have compared the neurocognitive processes associated with the intention-outcome integration between SPP and TPP. Here, we combined economic exchange games measuring SPP and TPP with functional magnetic resonance imaging (fMRI) to compare the neuropsychological architectures underlying the intention-outcome integration during one-shot interactions with anonymous partners across four types of norm violations (no norm, accidental, attempted, and intentional violations). Our behavioral findings showed that third-parties punished only attempted norm violations less frequently than second-parties. Our neuroimaging findings revealed higher activities in the right temporoparietal junction (TPJ) and dorsolateral prefrontal cortex (dlPFC) for attempted norm violations during TPP relative to SPP; more activities in these regions with less punishment frequency; and enhancement of functional connectivity of the right TPJ with the right dlPFC and dorsomedial PFC. Our findings demonstrated specific psychological and neural mechanisms of intention-outcome interactions between SPP and TPP -helping to unravel the complex neurocognitive processes of costly punishment.

Aberrant Cerebello-Cortical Connectivity in Pianists With Focal Task-Specific Dystonia

Musician's dystonia is a type of focal task-specific dystonia (FTSD) characterized by abnormal muscle hypercontraction and loss of fine motor control specifically during instrument playing. Although the neuropathophysiology of musician's dystonia remains unclear, it has been suggested that maladaptive functional abnormalities in subcortical and cortical regions may be involved. Here, we hypothesized that aberrant effective connectivity between the cerebellum (subcortical) and motor/somatosensory cortex may underlie the neuropathophysiology of musician's dystonia. Using functional magnetic resonance imaging, we measured the brain activity of 30 pianists with or without FTSD as they played a magnetic resonance imaging-compatible piano-like keyboard, which elicited dystonic symptoms in many but not all pianists with FTSD. Pianists with FTSD showed greater activation of the right cerebellum during the task than healthy pianists. Furthermore, patients who reported dystonic symptoms during the task demonstrated greater cerebellar activation than those who did not, establishing a link between cerebellar activity and overt dystonic symptoms. Using multivoxel pattern analysis, moreover, we found that dystonic and healthy pianists differed in the task-related effective connectivity between the right cerebellum and left premotor/somatosensory cortex. The present study indicates that abnormal cerebellar activity and cerebello-cortical connectivity may underlie the pathophysiology of FTSD in musicians.

Hippocampal and striatal responses during motor learning are modulated by prefrontal cortex stimulation

While it is widely accepted that motor sequence learning (MSL) is supported by a prefrontal-mediated interaction between hippocampal and striatal networks, it remains unknown whether the functional responses of these networks can be modulated in humans with targeted experimental interventions. The present proof-of-concept study employed a multimodal neuroimaging approach, including functional magnetic resonance (MR) imaging and MR spectroscopy, to investigate whether individually-tailored theta-burst stimulation of the dorsolateral prefrontal cortex can modulate responses in the hippocampus and the basal ganglia during motor learning. Our results indicate that while stimulation did not modulate motor performance nor task-related brain activity, it influenced connectivity patterns within hippocampo-frontal and striatal networks. Stimulation also altered the relationship between the levels of gamma-aminobutyric acid (GABA) in the stimulated prefrontal cortex and learning-related changes in both activity and connectivity in fronto-striato-hippocampal networks. This study provides the first experimental evidence, to the best of our knowledge, that brain stimulation can alter motor learning-related functional responses in the striatum and hippocampus.

Continuous-time deconvolutional regression for psycholinguistic modeling

The influence of stimuli in psycholinguistic experiments diffuses across time because the human response to language is not instantaneous. The linear models typically used to analyze psycholinguistic data are unable to account for this phenomenon due to strong temporal independence assumptions, while existing deconvolutional methods for estimating diffuse temporal structure model time discretely and therefore cannot be directly applied to natural language stimuli where events (words) have variable duration. In light of evidence that continuous-time deconvolutional regression (CDR) can address these issues (Shain & Schuler, 2018), this article motivates the use of CDR for many experimental settings, exposits some of its mathematical properties, and empirically evaluates the influence of various experimental confounds (noise, multicollinearity, and impulse response misspecification), hyperparameter settings, and response types (behavioral and fMRI). Results show that CDR (1) yields highly consistent estimates across a variety of hyperparameter configurations, (2) faithfully recovers the data-generating model on synthetic data, even under adverse training conditions, and (3) outperforms widely-used statistical approaches when applied to naturalistic reading and fMRI data. In addition, procedures for testing scientific hypotheses using CDR are defined and demonstrated, and empirically-motivated best-practices for CDR modeling are proposed. Results support the use of CDR for analyzing psycholinguistic time series, especially in a naturalistic experimental paradigm.

Decreased thalamo-cortico connectivity during an implicit sequence motor learning task and 7 days escitalopram intake

Evidence suggests that selective serotonin reuptake inhibitors (SSRIs) reorganize neural networks via a transient window of neuroplasticity. While previous findings support an effect of SSRIs on intrinsic functional connectivity, little is known regarding the influence of SSRI-administration on connectivity during sequence motor learning. To investigate this, we administered 20 mg escitalopram or placebo for 1-week to 60 healthy female participants undergoing concurrent functional magnetic resonance imaging and sequence motor training in a double-blind randomized controlled design. We assessed task-modulated functional connectivity with a psycho-physiological interaction (PPI) analysis in the thalamus, putamen, cerebellum, dorsal premotor, primary motor, supplementary motor, and dorsolateral prefrontal cortices. Comparing an implicit sequence learning condition to a control learning condition, we observed decreased connectivity between the thalamus and bilateral motor regions after 7 days of escitalopram intake. Additionally, we observed a negative correlation between plasma escitalopram levels and PPI connectivity changes, with higher escitalopram levels being associated with greater thalamo-cortico decreases. Our results suggest that escitalopram enhances network-level processing efficiency during sequence motor learning, despite no changes in behaviour. Future studies in more diverse samples, however, with quantitative imaging of neurochemical markers of excitation and inhibition, are necessary to further assess neural responses to escitalopram.

Multivariate semi-blind deconvolution of fMRI time series

Whole brain estimation of the haemodynamic response function (HRF) in functional magnetic resonance imaging (fMRI) is critical to get insight on the global status of the neurovascular coupling of an individual in healthy or pathological condition. Most of existing approaches in the literature works on task-fMRI data and relies on the experimental paradigm as a surrogate of neural activity, hence remaining inoperative on resting-stage fMRI (rs-fMRI) data. To cope with this issue, recent works have performed either a two-step analysis to detect large neural events and then characterize the HRF shape or a joint estimation of both the neural and haemodynamic components in an univariate fashion. In this work, we express the neural activity signals as a combination of piece-wise constant temporal atoms associated with sparse spatial maps and introduce an haemodynamic parcellation of the brain featuring a temporally dilated version of a given HRF model in each parcel with unknown dilation parameters. We formulate the joint estimation of the HRF shapes and spatio-temporal neural representations as a multivariate semi-blind deconvolution problem in a paradigm-free setting and introduce constraints inspired from the dictionary learning literature to ease its identifiability. A fast alternating minimization algorithm, along with its efficient implementation, is proposed and validated on both synthetic and real rs-fMRI data at the subject level. To demonstrate its significance at the population level, we apply this new framework to the UK Biobank data set, first for the discrimination of haemodynamic territories between balanced groups (n=24 individuals in each) patients with an history of stroke and healthy controls and second, for the analysis of normal aging on the neurovascular coupling. Overall, we statistically demonstrate that a pathology like stroke or a condition like normal brain aging induce longer haemodynamic delays in certain brain areas (e.g. Willis polygon, occipital, temporal and frontal cortices) and that this haemodynamic feature may be predictive with an accuracy of 74 % of the individual's age in a supervised classification task performed on n=459 subjects.

Brain reactivity during aggressive response in women with premenstrual dysphoric disorder treated with a selective progesterone receptor modulator

Premenstrual dysphoric disorder (PMDD) is a psychiatric condition characterized by late luteal phase affective, cognitive, and physical impairment. The disorder causes significant suffering in about 5% of women in their reproductive age. Altered sensitivity of cognitive-affective brain circuits to progesterone and its downstream metabolite allopregnanolone is suggested to underlie PMDD symptomatology. Core mood symptoms include irritability and anger, with aggression being the behavioral outcome of these symptoms. The present study sought to investigate the neural correlates of reactive aggression during the premenstrual phase in women with PMDD, randomized to a selective progesterone receptor modulator (SPRM) or placebo. Self-reports on the Daily Record of Severity of Problems were used to assess PMDD symptoms and gonadal hormone levels were measured by liquid chromatography tandem mass spectrometry. Functional magnetic resonance imaging was performed in 30 women with PMDD, while performing the point subtraction aggression paradigm. Overall, a high SPRM treatment response rate was attained (93%), in comparison with placebo (53.3%). Women with PMDD randomized to SPRM treatment had enhanced brain reactivity in the dorsal anterior cingulate cortex and dorsomedial prefrontal cortex during the aggressive response condition. The fronto-cingulate reactivity during aggressive responses depended on treatment, with a negative relationship between brain reactivity and task-related aggressiveness found in the placebo but not the SPRM group. The findings contribute to define the role of progesterone in PMDD symptomatology, suggesting a beneficial effect of progesterone receptor antagonism, and consequent anovulation, on top-down emotion regulation, i.e., greater fronto-cingulate activity in response to provocation stimuli.

Incidental Verbal Semantic Processing Recruits the Fronto-temporal Semantic Control Network

The frontoparietal semantic network, encompassing the inferior frontal gyrus and the posterior middle temporal cortex, is considered to be involved in semantic control processes. The explicit versus implicit nature of these control processes remains however poorly understood. The present study examined this question by assessing regional brain responses to the semantic attributes of an unattended stream of auditory words while participants' top-down attentional control processes were absorbed by a demanding visual search task. Response selectivity to semantic aspects of verbal stimuli was assessed via a functional magnetic resonance imaging response adaptation paradigm. We observed that implicit semantic processing of an unattended verbal stream recruited not only unimodal and amodal cortices in posterior supporting semantic knowledge areas, but also inferior frontal and posterior middle temporal areas considered to be part of the semantic control network. These results indicate that frontotemporal semantic networks support incidental semantic (control) processes.

Task-Dependent Functional and Effective Connectivity during Conceptual Processing

Conceptual knowledge is central to cognition. Previous neuroimaging research indicates that conceptual processing involves both modality-specific perceptual-motor areas and multimodal convergence zones. For example, our previous functional magnetic resonance imaging (fMRI) study revealed that both modality-specific and multimodal regions respond to sound and action features of concepts in a task-dependent fashion (Kuhnke P, Kiefer M, Hartwigsen G. 2020b. Task-dependent recruitment of modality-specific and multimodal regions during conceptual processing. Cereb Cortex. 30:3938–3959.). However, it remains unknown whether and how modality-specific and multimodal areas interact during conceptual tasks. Here, we asked 1) whether multimodal and modality-specific areas are functionally coupled during conceptual processing, 2) whether their coupling depends on the task, 3) whether information flows top-down, bottom-up or both, and 4) whether their coupling is behaviorally relevant. We combined psychophysiological interaction analyses with dynamic causal modeling on the fMRI data of our previous study. We found that functional coupling between multimodal and modality-specific areas strongly depended on the task, involved both top-down and bottom-up information flow, and predicted conceptually guided behavior. Notably, we also found coupling between different modality-specific areas and between different multimodal areas. These results suggest that functional coupling in the conceptual system is extensive, reciprocal, task-dependent, and behaviorally relevant. We propose a new model of the conceptual system that incorporates task-dependent functional interactions between modality-specific and multimodal areas.

Brain-based sex differences in autism spectrum disorder across the lifespan: A systematic review of structural MRI, fMRI, and DTI findings

Females with autism spectrum disorder (ASD) have been long overlooked in neuroscience research, but emerging evidence suggests they show distinct phenotypic trajectories and age-related brain differences. Sex-related biological factors (e.g., hormones, genes) may play a role in ASD etiology and have been shown to influence neurodevelopmental trajectories. Thus, a lifespan approach is warranted to understand brain-based sex differences in ASD. This systematic review on MRI-based sex differences in ASD was conducted to elucidate variations across the lifespan and inform biomarker discovery of ASD in females We identified articles through two database searches. Fifty studies met criteria and underwent integrative review. We found that regions expressing replicable sex-by-diagnosis differences across studies overlapped with regions showing sex differences in neurotypical cohorts. Furthermore, studies investigating age-related brain differences across a broad age-span suggest distinct neurodevelopmental patterns in females with ASD. Qualitative comparison across youth and adult studies also supported this hypothesis. However, many studies collapsed across age, which may mask differences. Furthermore, accumulating evidence supports the female protective effect in ASD, although only one study examined brain circuits implicated in "protection." When synthesized with the broader literature, brain-based sex differences in ASD may come from various sources, including genetic and endocrine processes involved in brain "masculinization" and "feminization" across early development, puberty, and other lifespan windows of hormonal transition. Furthermore, sex-related biology may interact with peripheral processes, in particular the stress axis and brain arousal system, to produce distinct neurodevelopmental patterns in males and females with ASD. Future research on neuroimaging-based sex differences in ASD would benefit from a lifespan approach in well-controlled and multivariate studies. Possible relationships between behavior, sex hormones, and brain development in ASD remain largely unexamined.

A Preferential Role for Ventromedial Prefrontal Cortex in Assessing "the Value of the Whole" in Multiattribute Object Evaluation

Everyday decision-making commonly involves assigning values to complex objects with multiple value-relevant attributes. Drawing on object recognition theories, we hypothesized two routes to multiattribute evaluation: assessing the value of the whole object based on holistic attribute configuration or summing individual attribute values. In two samples of healthy human male and female participants undergoing eye tracking and functional magnetic resonance imaging (fMRI) while evaluating novel pseudo objects, we found evidence for both forms of evaluation. Fixations to and transitions between attributes differed systematically when the value of pseudo objects was associated with individual attributes or attribute configurations. Ventromedial prefrontal cortex (vmPFC) and perirhinal cortex were engaged when configural processing was required. These results converge with our recent findings that individuals with vmPFC lesions were impaired in decisions requiring configural evaluation but not when evaluating the sum of the parts. This suggests that multiattribute decision-making engages distinct evaluation mechanisms relying on partially dissociable neural substrates, depending on the relationship between attributes and value.SIGNIFICANCE STATEMENT Decision neuroscience has only recently begun to address how multiple choice-relevant attributes are brought together during evaluation and choice among complex options. Object recognition research makes a crucial distinction between individual attribute and holistic/configural object processing, but how the brain evaluates attributes and whole objects remains unclear. Using fMRI and eye tracking, we found that the vmPFC and the perirhinal cortex contribute to value estimation specifically when value was related to whole objects, that is, predicted by the unique configuration of attributes and not when value was predicted by the sum of individual attribute values. This perspective on the interactions between subjective value and object processing mechanisms provides a novel bridge between the study of object recognition and reward-guided decision-making.

Multiple parietal pathways are associated with rTMS-induced hippocampal network enhancement and episodic memory changes

Repetitive transcranial magnetic stimulation (rTMS) of the inferior parietal cortex (IPC) increases resting-state functional connectivity (rsFC) of the hippocampus with the precuneus and other posterior cortical areas and causes proportional improvement of episodic memory. The anatomical pathway(s) responsible for the propagation of these effects from the IPC is unknown and may not be direct. In order to assess the relative contributions of candidate pathways from the IPC to the MTL via the parahippocampal cortex and precuneus, to the effects of rTMS on rsFC and memory improvement, we used diffusion tensor imaging to measure the extent to which individual differences in fractional anisotropy (FA) in these pathways accounted for individual differences in response. FA in the IPC-parahippocampal pathway and several MTL pathways predicted changes in rsFC. FA in both parahippocampal and hippocampal pathways was related to changes in episodic, but not procedural, memory. These results implicate pathways to the MTL in the enhancing effect of parietal rTMS on hippocampal rsFC and memory.

Neural correlates of RDoC-specific cognitive processes in a high-functional autistic patient: a statistically validated case report

The level of functioning of individuals with autism spectrum disorder (ASD) varies widely. To better understand the neurobiological mechanism associated with high-functioning ASD, we studied the rare case of a female patient with an exceptional professional career in the highly competitive academic field of Mathematics. According to the Research Domain Criteria (RDoC) approach, which proposes to describe the basic dimensions of functioning by integrating different levels of information, we conducted four fMRI experiments targeting the (1) social processes domain (Theory of mind (ToM) and face matching), (2) positive valence domain (reward processing), and (3) cognitive domain (N-back). Patient’s data were compared to data of 14 healthy controls (HC). Additionally, we assessed the subjective experience of our case during the experiments. The patient showed increased response times during face matching and achieved a higher total gain in the Reward task, whereas her performance in N-back and ToM was similar to HC. Her brain function differed mainly in the positive valence and cognitive domains. During reward processing, she showed reduced activity in a left-hemispheric frontal network and cortical midline structures but increased connectivity within this network. During the working memory task patients’ brain activity and connectivity in left-hemispheric temporo-frontal regions were elevated. In the ToM task, activity in posterior cingulate cortex and temporo-parietal junction was reduced. We suggest that the high level of functioning in our patient is rather related to the effects in brain connectivity than to local cortical information processing and that subjective report provides a fruitful framework for interpretation.

Hemodynamic matrix factorization for functional magnetic resonance imaging

The General Linear Model (GLM) used in task-fMRI relates activated brain areas to extrinsic task conditions. The translation of resulting neural activation into a hemodynamic response is commonly approximated with a linear convolution model using a hemodynamic response function (HRF). There are two major limitations in GLM analysis. Firstly, the GLM assumes that neural activation is either on or off and matches the exact stimulus duration in the corresponding task timings. Secondly, brain networks observed in resting-state fMRI experiments present also during task experiments, but the GLM approach models these task-unrelated brain activity as noise. A novel kernel matrix factorization approach, called hemodynamic matrix factorization (HMF), is therefore proposed that addresses both limitations by assuming that task-related and task-unrelated brain activity can be modeled with the same convolution model as in GLM analysis. By contrast to the GLM, the proposed HMF is a blind source separation (BSS) technique, which decomposes fMRI data into modes. Each mode comprises of a neural activation time course and a spatial mapping. Two versions of HMF are proposed in which the neural activation time course of each mode is convolved with either the canonical HRF or predetermined subject-specific HRFs. Firstly, HMF with the canonical HRF is applied to two open-source cohorts. These cohorts comprise of several task experiments including motor, incidental memory, spatial coherence discrimination, verbal discrimination task and a very short localization task, engaging multiple parts of the eloquent cortex. HMF modes were obtained whose neural activation time course followed original task timings and whose corresponding spatial map matched cortical areas known to be involved in the respective task processing. Secondly, the alignment of these neural activation time courses to task timings were further improved by replacing the canonical HRF with subject-specific HRFs during HMF mode computation. In addition to task-related modes, HMF also produced seemingly task-unrelated modes whose spatial maps matched known resting-state networks. The validity of a fMRI task experiment relies on the assumption that the exposure to a stimulus for a given time causes an imminent increase in neural activation of equal duration. The proposed HMF is an attempt to falsify this assumption and allows to identify subject task participation that does not comply with the experiment instructions.

Reach-relevant somatosensory signals modulate activity in the tactile suppression network

Somatosensory signals on a moving limb are typically suppressed. This results mainly from a predictive mechanism that generates an efference copy, and attenuates the predicted sensory consequences of that movement. Sensory feedback is, however, important for movement control. Behavioral studies show that the strength of suppression on a moving limb increases during somatosensory reaching, when reach-relevant somatosensory signals from the target limb can be additionally used to plan and guide the movement, leading to increased reliability of sensorimotor predictions. It is still unknown how this suppression is neurally implemented. In this fMRI study, participants reached to a somatosensory (static finger) or an external target (touch-screen) without vision. To probe suppression, participants detected brief vibrotactile stimuli on their moving finger shortly before reach onset. As expected, sensitivity to probes was reduced during reaching compared to baseline (resting), and this suppression was stronger during somatosensory than external reaching. BOLD activation associated with suppression was also modulated by the reach target: relative to baseline, processing of probes during somatosensory reaching led to distinct BOLD deactivations in somatosensory regions (postcentral gyrus, supramarginal gyrus-SMG) whereas probes during external reaching led to deactivations in the cerebellum. In line with the behavioral results, we also found additional deactivations during somatosensory relative to external reaching in the supplementary motor area, a region linked with sensorimotor prediction. Somatosensory reaching was also linked with increased functional connectivity between the left SMG and the right parietal operculum along with the right anterior insula. We show that somatosensory processing on a moving limb is reduced when additional reach-relevant feedback signals from the target limb contribute to the movement, by down-regulating activation in regions associated with predictive and feedback processing.

Understanding psychophysiological interaction and its relations to beta series correlation

Psychophysiological interaction (PPI) was proposed 20 years ago for study of task modulated connectivity on functional MRI (fMRI) data. A few modifications have since been made, but there remain misunderstandings on the method, as well as on its relations to a similar method named beta series correlation (BSC). Here, we explain what PPI measures and its relations to BSC. We first clarify that the interpretation of a regressor in a general linear model depends on not only itself but also on how other effects are modeled. In terms of PPI, it always reflects differences in connectivity between conditions, when the physiological variable is included as a covariate. Secondly, when there are multiple conditions, we explain how PPI models calculated from direct contrast between conditions could generate identical results as contrasting separate PPIs of each condition (a.k.a. "generalized" PPI). Thirdly, we explicit the deconvolution process that is used for PPI calculation, and how is it related to the trial-by-trial modeling for BSC, and illustrate the relations between PPI and those based upon BSC. In particular, when context sensitive changes in effective connectivity are present, they manifest as changes in correlations of observed trial-by-trial activations or functional connectivity. Therefore, BSC and PPI can detect similar connectivity differences. Lastly, we report empirical analyses using PPI and BSC on fMRI data of an event-related stop signal task to illustrate our points.

Investigating the neural substrates of Antagonistic Externalizing and social-cognitive Theory of Mind: an fMRI examination of functional activity and synchrony

Recently developed quantitative models of psychopathology (i.e., Hierarchical Taxonomy of Psychopathology) identify an Antagonistic Externalizing spectrum that captures the psychological disposition toward criminal and antisocial behavior. The purpose of the present study was to examine relations between Antagonistic psychopathology (and associated Five-Factor model Antagonism/Agreeableness) and neural functioning related to social-cognitive Theory of Mind using a large sample (N = 973) collected as part of the Human Connectome Project (Van Essen et al., 2013a). No meaningful relations between Antagonism/Antagonistic Externalizing and Theory of Mind-related neural activity or synchrony were observed (p < .005). We conclude by outlining methodological considerations (e.g., validity of social cognition task and low test-retest reliability of functional biomarkers) that may account for these null results, and present recommendations for future research.

Stress Modulates the Balance between Hippocampal and Motor Networks during Motor Memory Processing

The functional interaction between hippocampo- and striato-cortical regions during motor sequence learning is essential to trigger optimal memory consolidation. Based on previous evidence from other memory domains that stress alters the balance between these systems, we investigated whether exposure to stress prior to motor learning modulates motor memory processes. Seventy-two healthy young individuals were exposed to a stressful or nonstressful control intervention prior to training on a motor sequence learning task in a magnetic resonance imaging (MRI) scanner. Consolidation was assessed with an MRI retest after a sleep episode. Behavioral results indicate that stress prior to learning did not influence motor performance. At the neural level, stress induced both a larger recruitment of sensorimotor regions and a greater disengagement of hippocampo-cortical networks during training. Brain-behavior regression analyses showed that while this stress-induced shift from (hippocampo-)fronto-parietal to motor networks was beneficial for initial performance, it was detrimental for consolidation. Our results provide the first experimental evidence that stress modulates the neural networks recruited during motor memory processing and therefore effectively unify concepts and mechanisms from diverse memory fields. Critically, our findings suggest that intersubject variability in brain responses to stress determines the impact of stress on motor learning and subsequent consolidation.

Neural Mechanisms of Parental Communicative Adjustments in Spoken Language

During cultural transmission, caregivers typically adjust their form of speech according to the presumed characteristics of an infant/child, a phenomenon known as infant/child directed speech (IDS/CDS) or "parentese." Although ventromedial prefrontal cortex (vmPFC) damage was previously found to be associated with failure in adjusting non-verbal communicative behaviors, little is known about the neural mechanisms of verbal communicative adjustments, such as IDS/CDS. In the current study, 30 healthy mothers with preschool-age children underwent functional magnetic resonance imaging (fMRI) while performing a picture naming task which required them to name an object for either a child or an adult. In the picture naming task, mothers exhibited a longer naming duration in the toward-child condition than the toward-adult control condition. Naming an object for a child, compared with naming it for an adult, resulted in greater involvement in the vmPFC and other regions (e.g., cerebellum) in the global caregiving network. In particular, the vmPFC exhibited task-related deactivation and decreased functional connectivity with the supplementary motor, precentral, postcentral, and supramarginal regions. These findings suggest that the vmPFC, which is included in the default mode network, is involved in optimizing communicative behaviors for the inter-generational transmission of knowledge. This function of the vmPFC may be considered as a prosocial drive to lead to prosocial communicative behaviors depending on the context. This study provides a better understanding of the neural mechanisms involved in communicative adjustments for children and insight into related applied research fields such as parenting, pedagogy, and education.

Signed Reward Prediction Errors in the Ventral Striatum Drive Episodic Memory

Recent behavioral evidence implicates reward prediction errors (RPEs) as a key factor in the acquisition of episodic memory. Yet, important neural predictions related to the role of RPEs in episodic memory acquisition remain to be tested. Humans (both sexes) performed a novel variable-choice task where we experimentally manipulated RPEs and found support for key neural predictions with fMRI. Our results show that in line with previous behavioral observations, episodic memory accuracy increases with the magnitude of signed (i.e., better/worse-than-expected) RPEs (SRPEs). Neurally, we observe that SRPEs are encoded in the ventral striatum (VS). Crucially, we demonstrate through mediation analysis that activation in the VS mediates the experimental manipulation of SRPEs on episodic memory accuracy. In particular, SRPE-based responses in the VS (during learning) predict the strength of subsequent episodic memory (during recollection). Furthermore, functional connectivity between task-relevant processing areas (i.e., face-selective areas) and hippocampus and ventral striatum increased as a function of RPE value (during learning), suggesting a central role of these areas in episodic memory formation. Our results consolidate reinforcement learning theory and striatal RPEs as key factors subtending the formation of episodic memory.SIGNIFICANCE STATEMENT Recent behavioral research has shown that reward prediction errors (RPEs), a key concept of reinforcement learning theory, are crucial to the formation of episodic memories. In this study, we reveal the neural underpinnings of this process. Using fMRI, we show that signed RPEs (SRPEs) are encoded in the ventral striatum (VS), and crucially, that SRPE VS activity is responsible for the subsequent recollection accuracy of one-shot learned episodic memory associations.

Oscillatory brain activity and maintenance of verbal and visual working memory: A systematic review

Brain oscillations likely play a significant role in the storage of information in working memory (WM). Despite the wide popularity of the topic, current attempts to summarize the research in the field are narrative reviews. We address this gap by providing a descriptive systematic review, in which we investigated oscillatory correlates of maintenance of verbal and visual information in WM. The systematic approach enabled us to challenge some common views popularized by previous research. The identified literature (100 EEG/MEG studies) highlighted the importance of theta oscillations in verbal WM: frontal midline theta enhanced with load in most verbal studies, while more equivocal results have been obtained in visual studies. Increasing WM load affected alpha activity in most studies, but the direction of the effect was inconsistent: the ratio of studies that found alpha increase versus decrease with increasing load was 80/20% in the verbal WM domain and close to 60/40% in the visual domain. Alpha asymmetry (left < right) was a common finding in both verbal and visual WM studies. Beta and gamma activity studies yielded the least convincing data: a diversity in the spatial and frequency distribution of beta activity prevented us from making a coherent conclusion; gamma rhythm was virtually neglected in verbal WM studies with no systematic support for sustained gamma changes during the delay in EEG studies in general.

Distraction decreases rIFG-putamen connectivity during goal-directed effort for food rewards

Distracted eating can lead to increased food intake, but it is unclear how. We aimed to assess how distraction affects motivated, goal-directed responses for food reward after satiation. Thirty-eight healthy normal-weight participants (28F; 10M) performed a visual detection task varying in attentional load (high vs. low distraction) during fMRI. Simultaneously, they exerted effort for sweet and savory food rewards by repeated button presses. Two fMRI runs were separated by sensory-specific satiation (outcome devaluation) of one of the (sweet or savory) reward outcomes, to assess outcome-sensitive, goal-directed, responses (valued vs. devalued reward, post vs. pre satiation). We could not verify our primary hypothesis that more distraction leads to less activation in ventromedial prefrontal cortex (vmPFC) during goal-directed effort. Behaviorally, distraction also did not affect effort for food reward following satiation across subjects. For our secondary hypothesis, we assessed whether distraction affected other fronto-striatal regions during goal-directed effort. We did not obtain such effects at our whole-brain corrected threshold, but at an exploratory uncorrected threshold (p < 0.001), distraction decreased goal-directed responses (devalued vs. valued) in the right inferior frontal gyrus (rIFG). We continued with this rIFG region for the next secondary hypothesis; specifically, that distraction would reduce functional connectivity with the fronto-striatal regions found in the previous analyses. Indeed, distraction decreased functional connectivity between the rIFG and left putamen for valued versus devalued food rewards (pFWE(cluster) < 0.05). In an exploratory brain-behavior analysis, we showed that distraction-sensitive rIFG-responses correlated negatively (r = - 0.40; p = 0.014) with the effect of distraction on effort. Specifically, decreased distraction-related rIFG-responses were associated with increased effort for food reward after satiation. We discuss the absence of distraction effects on goal-directed responses in vmPFC and in behavior across participants. Moreover, based on our significant functional connectivity and brain-behavior results, we suggest that distraction might attenuate the ability to inhibit responses for food reward after satiation by affecting the rIFG and its connection to the putamen.

The neural network underpinning social feedback contingent upon one's action: An fMRI study

Praise enhances motor performance; however, the underlying feedback pathway is unknown. Here, we hypothesized that the social evaluation feedback to the motor system is modified by the top-down effect of the social contingency valuation system, such as the anterior rostral medial prefrontal cortex (arMPFC). We developed a pseudo-interactive task that simplified a conversational student-teacher interaction and conducted a functional magnetic resonance imaging study with 33 participants (13 men, 20 women; mean age = 21.7 years; standard deviation = 2.0 years). The participant inside the scanner uttered the pseudo-English word to the English teacher outside the scanner. The teacher provided feedback of acceptance or rejection by either gestures or words, through video. As a control condition, the pseudo-word was read aloud by a computer. Approval from the teacher enhanced the participants' pleasure rate. Feedback to the participants' utterance, either rejection or acceptance, activated the arMPFC. Irrespective of the preceding utterance by self or computer, acceptance compared with rejection activated the right primary visual cortex (V1), and the reverse activated the left V1. This valence-dependent laterality of V1 activation indicates that the effect is not the domain-general modulation of visual processing. Instead, the early visual cortices are part of the valence-specific representation of the social signal. Physio-physiological interaction analysis with the seed regions in the right and left V1 and the modulator region in the arMPFC showed enhanced connectivity with the bilateral primary motor cortex. These findings indicate that the socially contingent, self-relevant signals from others act as feedback to the motor control system, and this process is mediated by the early visual cortex.

High-Expanding Regions in Primate Cortical Brain Evolution Support Supramodal Cognitive Flexibility

Primate cortical evolution has been characterized by massive and disproportionate expansion of a set of specific regions in the neocortex. The associated increase in neocortical neurons comes with a high metabolic cost, thus the functions served by these regions must have conferred significant evolutionary advantage. In the present series of analyses, we show that evolutionary high-expanding cortex - as estimated from patterns of surface growth from several primate species - shares functional connections with different brain networks in a context-dependent manner. Specifically, we demonstrate that high-expanding cortex is characterized by high internetwork functional connectivity; is recruited flexibly over many different cognitive tasks; and changes its functional coupling pattern between rest and a multimodal task-state. The capacity of high-expanding cortex to connect flexibly with various specialized brain networks depending on particular cognitive requirements suggests that its selective growth and sustainment in evolution may have been linked to an involvement in supramodal cognition. In accordance with an evolutionary-developmental view, we find that this observed ability of high-expanding regions - to flexibly modulate functional connections as a function of cognitive state - emerges gradually through childhood, with a prolonged developmental trajectory plateauing in young adulthood.

Neural correlates of conscious tactile perception: An analysis of BOLD activation patterns and graph metrics

Theories of human consciousness substantially vary in the proposed spatial extent of brain activity associated with conscious perception as well as in the assumed functional alterations within the involved brain regions. Here, we investigate which local and global changes in brain activity accompany conscious somatosensory perception following electrical finger nerve stimulation, and whether there are whole-brain functional network alterations by means of graph metrics. Thirty-eight healthy participants performed a somatosensory detection task and reported their decision confidence during fMRI. For conscious tactile perception in contrast to undetected near-threshold trials (misses), we observed increased BOLD activity in the precuneus, the intraparietal sulcus, the insula, the nucleus accumbens, the inferior frontal gyrus and the contralateral secondary somatosensory cortex. For misses compared to correct rejections, bilateral secondary somatosensory cortices, supplementary motor cortex and insula showed greater activations. The analysis of whole-brain functional network topology for hits, misses and correct rejections, did not result in any significant differences in modularity, participation, clustering or path length, which was supported by Bayes factor statistics. In conclusion, for conscious somatosensory perception, our results are consistent with an involvement of (probably) domain-general brain areas (precuneus, insula, inferior frontal gyrus) in addition to somatosensory regions; our data do not support the notion of specific changes in graph metrics associated with conscious experience. For the employed somatosensory submodality of fine electrical current stimulation, this speaks for a global broadcasting of sensory content across the brain without substantial reconfiguration of the whole-brain functional network resulting in an integrative conscious experience.

Lateralized effects of post-learning transcranial direct current stimulation on motor memory consolidation in older adults: An fMRI investigation

Previous research has consistently demonstrated that older adults have difficulties transforming recently learned movements into robust, long-lasting memories (i.e., motor memory consolidation). One potential avenue to enhance consolidation in older individuals is the administration of transcranial direct current stimulation (tDCS) to task-relevant brain regions after initial learning. Although this approach has shown promise, the underlying cerebral correlates have yet to be revealed. Moreover, it is unknown whether the effects of tDCS are lateralized, an open question with implications for rehabilitative approaches following predominantly unilateral neurological injuries. In this research, healthy older adults completed a sequential motor task before and 6 h after receiving anodal or sham stimulation to right or left primary motor cortex (M1) while functional magnetic resonance images were acquired. Unexpectedly, anodal stimulation to right M1 following left-hand sequence learning significantly hindered consolidation as compared to a sham control, whereas no differences were observed with left M1 stimulation following right-hand learning. Impaired performance following right M1 stimulation was paralleled by sustained engagement of regions known to be critical for early learning stages, including the caudate nucleus and the premotor and parietal cortices. Thus, post-learning tDCS in older adults not only exerts heterogenous effects across the two hemispheres but can also disrupt ongoing memory processing.

Quality and denoising in real-time functional magnetic resonance imaging neurofeedback: A methods review

Neurofeedback training using real-time functional magnetic resonance imaging (rtfMRI-NF) allows subjects voluntary control of localised and distributed brain activity. It has sparked increased interest as a promising non-invasive treatment option in neuropsychiatric and neurocognitive disorders, although its efficacy and clinical significance are yet to be determined. In this work, we present the first extensive review of acquisition, processing and quality control methods available to improve the quality of the neurofeedback signal. Furthermore, we investigate the state of denoising and quality control practices in 128 recently published rtfMRI-NF studies. We found: (a) that less than a third of the studies reported implementing standard real-time fMRI denoising steps, (b) significant room for improvement with regards to methods reporting and (c) the need for methodological studies quantifying and comparing the contribution of denoising steps to the neurofeedback signal quality. Advances in rtfMRI-NF research depend on reproducibility of methods and results. Notably, a systematic effort is needed to build up evidence that disentangles the various mechanisms influencing neurofeedback effects. To this end, we recommend that future rtfMRI-NF studies: (a) report implementation of a set of standard real-time fMRI denoising steps according to a proposed COBIDAS-style checklist (https://osf.io/kjwhf/), (b) ensure the quality of the neurofeedback signal by calculating and reporting community-informed quality metrics and applying offline control checks and (c) strive to adopt transparent principles in the form of methods and data sharing and support of open-source rtfMRI-NF software. Code and data for reproducibility, as well as an interactive environment to explore the study data, can be accessed at https://github.com/jsheunis/quality-and-denoising-in-rtfmri-nf.

Tools of the trade: estimating time-varying connectivity patterns from fMRI data

Given the dynamic nature of the brain, there has always been a motivation to move beyond 'static' functional connectivity, which characterizes functional interactions over an extended period of time. Progress in data acquisition and advances in analytical neuroimaging methods now allow us to assess the whole brain's dynamic functional connectivity (dFC) and its network-based analog, dynamic functional network connectivity at the macroscale (mm) using fMRI. This has resulted in the rapid growth of analytical approaches, some of which are very complex, requiring technical expertise that could daunt researchers and neuroscientists. Meanwhile, making real progress toward understanding the association between brain dynamism and brain disorders can only be achieved through research conducted by domain experts, such as neuroscientists and psychiatrists. This article aims to provide a gentle introduction to the application of dFC. We first explain what dFC is and the circumstances under which it can be used. Next, we review two major categories of analytical approaches to capture dFC. We discuss caveats and considerations in dFC analysis. Finally, we walk readers through an openly accessible toolbox to capture dFC properties and briefly review some of the dynamic metrics calculated using this toolbox.

Antero-Posterior vs. Lateral Vestibular Input Processing in Human Visual Cortex

Visuo-vestibular integration is crucial for locomotion, yet the cortical mechanisms involved remain poorly understood. We combined binaural monopolar galvanic vestibular stimulation (GVS) and functional magnetic resonance imaging (fMRI) to characterize the cortical networks activated during antero-posterior and lateral stimulations in humans. We focused on functional areas that selectively respond to egomotion-consistent optic flow patterns: the human middle temporal complex (hMT+), V6, the ventral intraparietal (VIP) area, the cingulate sulcus visual (CSv) area and the posterior insular cortex (PIC). Areas hMT+, CSv, and PIC were equivalently responsive during lateral and antero-posterior GVS while areas VIP and V6 were highly activated during antero-posterior GVS, but remained silent during lateral GVS. Using psychophysiological interaction (PPI) analyses, we confirmed that a cortical network including areas V6 and VIP is engaged during antero-posterior GVS. Our results suggest that V6 and VIP play a specific role in processing multisensory signals specific to locomotion during navigation.

Stability-Based Sparse Paradigm Free Mapping Algorithm for Deconvolution of Functional MRI Data

Neuronal-related activity can be estimated from functional magnetic resonance imaging (fMRI) data with no knowledge of the timings of blood oxygenation level-dependent (BOLD) events by means of deconvolution with regularized least-squares. This work proposes two improvements on the deconvolution algorithm of sparse paradigm free mapping (SPFM): a new formulation that enables the estimation of neuronal events with long, sustained activity; and the implementation of a subsampling approach based on stability selection that avoids the choice of any regularization parameter. The proposed method is evaluated on real fMRI data and compared with both the original SPFM algorithm and conventional analysis with a general linear model (GLM) that is aware of the temporal model of the neuronal-related activity. We demonstrate that the novel stability-based SPFM algorithm yields activation maps with higher resemblance to the maps obtained with GLM analyses and offers improved detection of neuronal-related events over SPFM, particularly in scenarios with low contrast-to-noise ratio.

Emotion self-regulation training in major depressive disorder using simultaneous real-time fMRI and EEG neurofeedback

Simultaneous real-time fMRI and EEG neurofeedback (rtfMRI-EEG-nf) is an emerging neuromodulation approach, that enables simultaneous volitional regulation of both hemodynamic (BOLD fMRI) and electrophysiological (EEG) brain activities. Here we report the first application of rtfMRI-EEG-nf for emotion self-regulation training in patients with major depressive disorder (MDD). In this proof-of-concept study, MDD patients in the experimental group (n = 16) used rtfMRI-EEG-nf during a happy emotion induction task to simultaneously upregulate two fMRI and two EEG activity measures relevant to MDD. The target measures included BOLD activities of the left amygdala (LA) and left rostral anterior cingulate cortex (rACC), and frontal EEG asymmetries in the alpha band (FAA, [7.5-12.5] Hz) and high-beta band (FBA, [21-30] Hz). MDD patients in the control group (n = 8) were provided with sham feedback signals. An advanced procedure for improved real-time EEG-fMRI artifact correction was implemented. The experimental group participants demonstrated significant upregulation of the LA BOLD activity, FAA, and FBA during the rtfMRI-EEG-nf task, as well as significant enhancement in fMRI connectivity between the LA and left rACC. Average individual FAA changes during the rtfMRI-EEG-nf task positively correlated with depression and anhedonia severities, and negatively correlated with after-vs-before changes in depressed mood ratings. Temporal correlations between the FAA and FBA time courses and the LA BOLD activity were significantly enhanced during the rtfMRI-EEG-nf task. The experimental group participants reported significant mood improvements after the training. Our results suggest that the rtfMRI-EEG-nf may have potential for treatment of MDD.

Baseline sensorimotor GABA levels shape neuroplastic processes induced by motor learning in older adults

Previous research in young adults has demonstrated that both motor learning and transcranial direct current stimulation (tDCS) trigger decreases in the levels of gamma-aminobutyric acid (GABA) in the sensorimotor cortex, and these decreases are linked to greater learning. Less is known about the role of GABA in motor learning in healthy older adults, a knowledge gap that is surprising given the established aging-related reductions in sensorimotor GABA. Here, we examined the effects of motor learning and subsequent tDCS on sensorimotor GABA levels and resting-state functional connectivity in the brains of healthy older participants. Thirty-six older men and women completed a motor sequence learning task before receiving anodal or sham tDCS to the sensorimotor cortex. GABA-edited magnetic resonance spectroscopy of the sensorimotor cortex and resting-state (RS) functional magnetic resonance imaging data were acquired before and after learning/stimulation. At the group level, neither learning nor anodal tDCS significantly modulated GABA levels or RS connectivity among task-relevant regions. However, changes in GABA levels from the baseline to post-learning session were significantly related to motor learning magnitude, age, and baseline GABA. Moreover, the change in functional connectivity between task-relevant regions, including bilateral motor cortices, was correlated with baseline GABA levels. These data collectively indicate that motor learning-related decreases in sensorimotor GABA levels and increases in functional connectivity are limited to those older adults with higher baseline GABA levels and who learn the most. Post-learning tDCS exerted no influence on GABA levels, functional connectivity or the relationships among these variables in older adults.

Semantic and attentional networks in bilingual processing: fMRI connectivity signatures of translation directionality

Comparisons between backward and forward translation (BT, FT) have long illuminated the organization of bilingual memory, with neuroscientific evidence indicating that FT would involve greater linguistic and attentional demands. However, no study has directly assessed the functional interaction between relevant mechanisms. Against this background, we conducted the first fMRI investigation of functional connectivity (FC) differences between BT and FT. In addition to yielding lower behavioral outcomes, FT was characterized by increased FC between a core semantic hub (the left anterior temporal lobe, ATL) and key nodes of attentional and vigilance networks (left inferior frontal, left orbitofrontal, and bilateral parietal clusters). Instead, distinct FC patterns for BT emerged only between the left ATL and the right thalamus, a region implicated in automatic relaying of sensory information to cortical regions. Therefore, FT seems to involve enhanced coupling between semantic and attentional mechanisms, suggesting that asymmetries in cross-language processing reflect dynamic interactions between linguistic and domain-general systems.

Toward Task Connectomics: Examining Whole-Brain Task Modulated Connectivity in Different Task Domains

Human brain anatomical and resting-state functional connectivity have been comprehensively portrayed using MRI, which are termed anatomical and functional connectomes. A systematic examination of tasks modulated whole brain functional connectivity, which we term as task connectome, is still lacking. We analyzed 6 block-designed and 1 event-related designed functional MRI data, and examined whole-brain task modulated connectivity in various task domains, including emotion, reward, language, relation, social cognition, working memory, and inhibition. By using psychophysiological interaction between pairs of regions from the whole brain, we identified statistically significant task modulated connectivity in 4 tasks between their experimental and respective control conditions. Task modulated connectivity was found not only between regions that were activated during the task but also regions that were not activated or deactivated, suggesting a broader involvement of brain regions in a task than indicated by simple regional activations. Decreased functional connectivity was observed in all the 4 tasks and sometimes reduced connectivity was even between regions that were both activated during the task. This suggests that brain regions that are activated together do not necessarily work together. The current study demonstrates the comprehensive task connectomes of 4 tasks, and suggested complex relationships between regional activations and connectivity changes.

Identification of an Amygdala-Thalamic Circuit That Acts as a Central Gain Mechanism in Taste Perceptions

Peripheral sources of individual variation in taste intensity perception have been well described. The existence of a central source has been proposed but remains unexplored. Here we used functional magnetic resonance imaging in healthy human participants (20 women, 8 men) to evaluate the hypothesis that the amygdala exerts an inhibitory influence that affects the "gain" of the gustatory system during tasting. Consistent with the existence of a central gain mechanism (CGM), we found that central amygdala response was correlated with mean intensity ratings across multiple tastants. In addition, psychophysiological and dynamic causal modeling analyses revealed that the connection strength between inhibitory outputs from amygdala to medial dorsal and ventral posterior medial thalamus predicted individual differences in responsiveness to taste stimulation. These results imply that inhibitory inputs from the amygdala to the thalamus act as a CGM that influences taste intensity perception.SIGNIFICANCE STATEMENT Whether central circuits contribute to individual variation in taste intensity perception is unknown. Here we used functional magnetic resonance imaging in healthy human participants to identify an amygdala-thalamic circuit where network dynamics and connectivity strengths during tasting predict individual variation in taste intensity ratings. This finding implies that individual differences in taste intensity perception do not arise solely from variation in peripheral gustatory factors.

Effects of distraction on taste-related neural processing: a cross-sectional fMRI study

BACKGROUND

In the current obesogenic environment we often eat while electronic devices, such as smart phones, computers, or the television, distract us. Such "distracted eating" is associated with increased food intake and overweight. However, the underlying neurocognitive mechanisms of this phenomenon are unknown.

OBJECTIVE

Our aim was to elucidate these mechanisms by investigating whether distraction attenuates processing in the primary and secondary taste cortices, located in the insula and orbitofrontal cortex (OFC), respectively.

METHODS

Forty-one healthy, normal-weight participants received fixed amounts of higher- and lower-sweetness isocaloric chocolate milk while performing a high- or low-distracting detection task during fMRI in 2 test sessions. Subsequently, we measured ad libitum food intake.

RESULTS

As expected, a primary taste cortex region in the right insula responded more to the sweeter drink (P < 0.001, uncorrected). Distraction did not affect this insular sweetness response across the group, but did weaken sweetness-related connectivity of this region to a secondary taste region in the right OFC (P-family-wise error, cluster, small-volume corrected = 0.020). Moreover, individual differences in distraction-related attenuation of taste activation in the insula predicted increased subsequent ad libitum food intake after distraction (r = 0.36).

CONCLUSIONS

These results reveal a mechanism explaining how distraction during consumption attenuates neural taste processing. Moreover, our study shows that such distraction-induced decreases in neural taste processing contribute to individual differences in the susceptibility for overeating. Thus, being mindful about the taste of food during consumption could perhaps be part of successful prevention and treatment of overweight and obesity, which should be further tested in these target groups. This study was preregistered at the Open Science Framework as https://bit.ly/31RtDHZ.