Functional Heterogeneity within the Default Network during Semantic Processing and Speech Production

Graph analysis uncovers an opposing impact of methylphenidate on connectivity patterns within default mode network sub-divisions

BACKGROUND

The Default Mode Network (DMN) is a central neural network, with recent evidence indicating that it is composed of functionally distinct sub-networks. Methylphenidate (MPH) administration has been shown before to modulate impulsive behavior, though it is not yet clear whether these effects relate to MPH-induced changes in DMN connectivity. To address this gap, we assessed the impact of MPH administration on functional connectivity patterns within and between distinct DMN sub-networks and tested putative relations to variability in sub-scales of impulsivity.

METHODS

Fifty-five right-handed healthy adults underwent two resting-state functional MRI (rs-fMRI) scans, following acute administration of either MPH (20 mg) or placebo, via a randomized double-blind placebo-controlled design. Graph modularity analysis was implemented to fractionate the DMN into distinct sub-networks based on the impact of MPH (vs. placebo) on DMN connectivity patterns with other neural networks.

RESULTS

MPH administration led to an overall decreased DMN connectivity, particularly with the auditory, cinguloopercular, and somatomotor networks, and increased connectivity with the parietomedial network. Graph analysis revealed that the DMN could be fractionated into two distinct sub-networks, with one exhibiting MPH-induced increased connectivity and the other decreased connectivity. Decreased connectivity of the DMN sub-network with the cinguloopercular network following MPH administration was associated with elevated impulsivity and non-planning impulsiveness.

CONCLUSION

Current findings highlight the intricate effects of MPH administration on DMN rs-fMRI connectivity, uncovering its opposing impact on distinct DMN sub-divisions. MPH-induced dynamics in DMN connectivity patterns with other neural networks may account for some of the effects of MPH administration on impulsive behavior.

How does the "default mode" network contribute to semantic cognition?

This review examines whether and how the "default mode" network (DMN) contributes to semantic processing. We review evidence implicating the DMN in the processing of individual word meanings and in sentence- and discourse-level semantics. Next, we argue that the areas comprising the DMN contribute to semantic processing by coordinating and integrating the simultaneous activity of local neuronal ensembles across multiple unimodal and multimodal cortical regions, creating a transient, global neuronal ensemble. The resulting ensemble implements an integrated simulation of phenomenological experience - that is, an embodied situation model - constructed from various modalities of experiential memory traces. These situation models, we argue, are necessary not only for semantic processing but also for aspects of cognition that are not traditionally considered semantic. Although many aspects of this proposal remain provisional, we believe it provides new insights into the relationships between semantic and non-semantic cognition and into the functions of the DMN.

Neural Changes in Children With Residual Speech Sound Disorder After Ultrasound Biofeedback Speech Therapy

PURPOSE

Children with residual speech sound disorders (RSSD) have shown differences in neural function for speech production, as compared to their typical peers; however, information about how these differences may change over time and relative to speech therapy is needed. To address this gap, we used functional magnetic resonance imaging (fMRI) to examine functional activation and connectivity on adaptations of the syllable repetition task (SRT-Early Sounds and SRT-Late Sounds) in children with RSSD before and after a speech therapy program.

METHOD

Sixteen children with RSSD completed an fMRI experiment before (Time 1) and after (Time 2) a speech therapy program with ultrasound visual feedback for /ɹ/ misarticulation. Progress in therapy was measured via perceptual ratings of productions of untreated /ɹ/ word probes. To control for practice effects and developmental change in patterns of activation and connectivity, 17 children with typical speech development (TD) completed the fMRI at Time 1 and Time 2. Functional activation was analyzed using a region-of-interest approach and functional connectivity was analyzed using a seed-to-voxel approach.

RESULTS

Children with RSSD showed a range of responses to therapy. After correcting for multiple comparisons, we did not observe any statistically significant cross-sectional differences or longitudinal changes in functional activation. A negative relationship between therapy effect size and functional activation in the left visual association cortex was on the SRT-Late Sounds after therapy, but it did not survive correction for multiple comparisons. Significant longitudinal changes in functional connectivity were observed for the RSSD group on SRT-Early Sounds and SRT-Late Sounds, as well as for the TD group on the SRT-Early Sounds. RSSD and TD groups showed connectivity differences near the left insula on the SRT-Late Sounds at Time 2.

CONCLUSION

RSSD and treatment with ultrasound visual feedback may thus be associated with neural differences in speech motor and visual association processes recruited for speech production.

The intracortical myelin content of impulsive choices: results from T1- and T2-weighted MRI myelin mapping

Delay discounting (DD) refers to a phenomenon that humans tend to choose small-sooner over large-later rewards during intertemporal choices. Steep discounting of delayed outcome is related to a variety of maladaptive behaviors and is considered as a transdiagnostic process across psychiatric disorders. Previous studies have investigated the association between brain structure (e.g. gray matter volume) and DD; however, it is unclear whether the intracortical myelin (ICM) influences DD. Here, based on a sample of 951 healthy young adults drawn from the Human Connectome Project, we examined the relationship between ICM, which was measured by the contrast of T1w and T2w images, and DD and further tested whether the identified associations were mediated by the regional homogeneity (ReHo) of brain spontaneous activity. Vertex-wise regression analyses revealed that steeper DD was significantly associated with lower ICM in the left temporoparietal junction (TPJ) and right middle-posterior cingulate cortex. Region-of-interest analysis revealed that the ReHo values in the left TPJ partially mediated the association of its myelin content with DD. Our findings provide the first evidence that cortical myelination is linked with individual differences in decision impulsivity and suggest that the myelin content affects cognitive performances partially through altered local brain synchrony.

Multiple functions of the angular gyrus at high temporal resolution

Here, the functions of the angular gyrus (AG) are evaluated in the light of current evidence from transcranial magnetic/electric stimulation (TMS/TES) and EEG/MEG studies. 65 TMS/TES and 52 EEG/MEG studies were examined in this review. TMS/TES literature points to a causal role in semantic processing, word and number processing, attention and visual search, self-guided movement, memory, and self-processing. EEG/MEG studies reported AG effects at latencies varying between 32 and 800 ms in a wide range of domains, with a high probability to detect an effect at 300-350 ms post-stimulus onset. A three-phase unifying model revolving around the process of sensemaking is then suggested: (1) early AG involvement in defining the current context, within the first 200 ms, with a bias toward the right hemisphere; (2) attention re-orientation and retrieval of relevant information within 200-500 ms; and (3) cross-modal integration at late latencies with a bias toward the left hemisphere. This sensemaking process can favour accuracy (e.g. for word and number processing) or plausibility (e.g. for comprehension and social cognition). Such functions of the AG depend on the status of other connected regions. The much-debated semantic role is also discussed as follows: (1) there is a strong TMS/TES evidence for a causal semantic role, (2) current EEG/MEG evidence is however weak, but (3) the existing arguments against a semantic role for the AG are not strong. Some outstanding questions for future research are proposed. This review recognizes that cracking the role(s) of the AG in cognition is possible only when its exact contributions within the default mode network are teased apart.

Decreased Default Mode Network Connectivity Following 24 Hours of Capsaicin-induced Pain Persists During Immediate Pain Relief and Facilitation

Prolonged experimental pain models can help assess cortical mechanisms underlying the transition from acute to chronic pain such as resting-state functional connectivity (rsFC), especially in early stages. This crossover study determined the effects of 24-hour-capsaicin-induced pain on the default mode network rsFC, a major network in the dynamic pain connectome. Electroencephalographic rsFC measured by Granger causality was acquired from 24 healthy volunteers (12 women) at baseline, 1hour, and 24hours following the application of a control or capsaicin patch on the right forearm. The control patch was received maximum 1 week before the capsaicin patch. Following 24hours, the patch was cooled and later heated to assess rsFC changes in response to pain relief and facilitation, respectively. Compared to baseline, decreased rsFC at alpha oscillations (8-10Hz) was found following 1hour and 24hours of capsaicin application for connections projecting from medial prefrontal cortex (mPFC) and right angular gyrus (rAG) but not left angular gyrus (lAG) or posterior cingulate cortex (PCC): mPFC-PCC (1hour:P < .001, 24hours:P = .002), mPFC-rAG (1hour:P < .001, 24hours:P = .001), rAG-mPFC (1hour:P < .001, 24hours:P = .001), rAG-PCC (1hour:P < .001, 24hours:P = .004). Comparable decreased rsFC following 1hour and 24hours (P≤0.008) was found at beta oscillations, however, decreased projections from PCC were also found: PCC-rAG (P≤0.005) and PCC-lAG (P≤0.006). Pain NRS scores following 24hours (3.7±0.4) was reduced by cooling (0.3±0.1, P = .004) and increased by heating (4.8±0.6, P = .016). However, neither cooling nor heating altered rsFC. This study shows that 24hours of experimental pain induces a robust decrease in DMN connectivity that persists during pain relief or facilitation suggesting a possible shift to attentional and emotional processing in persistent pain. PERSPECTIVE: This article shows decreased DMN connectivity that might reflect possible attentional and emotional changes during acute and prolonged pain. Understanding these changes could potentially help clinicians in developing therapeutic methods that can better target these attentional and emotional processes before developing into more persistent states.

Task-specific network interactions across key cognitive domains

Human cognition is organized in distributed networks in the brain. Although distinct specialized networks have been identified for different cognitive functions, previous work also emphasizes the overlap of key cognitive domains in higher level association areas. The majority of previous studies focused on network overlap and dissociation during resting states whereas task-related network interactions across cognitive domains remain largely unexplored. A better understanding of network overlap and dissociation during different cognitive tasks may elucidate flexible (re-)distribution of resources during human cognition. The present study addresses this issue by providing a broad characterization of large-scale network dynamics in three key cognitive domains. Combining prototypical tasks of the larger domains of attention, language, and social cognition with whole-brain multivariate activity and connectivity approaches, we provide a spatiotemporal characterization of multiple large-scale, overlapping networks that differentially interact across cognitive domains. We show that network activity and interactions increase with increased cognitive complexity across domains. Interaction patterns reveal a common core structure across domains as well as dissociable domain-specific network activity. The observed patterns of activation and deactivation of overlapping and strongly coupled networks provide insight beyond region-specific activity within a particular cognitive domain toward a network perspective approach across diverse key cognitive functions.

Structural brain network topological alterations in stuttering adults

Persistent developmental stuttering is a speech disorder that primarily affects normal speech fluency but encompasses a complex set of symptoms ranging from reduced sensorimotor integration to socioemotional challenges. Here, we investigated the whole brain structural connectome and its topological alterations in adults who stutter. Diffusion weighted imaging data of 33 subjects (13 adults who stutter and 20 fluent speakers) was obtained along with a stuttering severity evaluation. The structural brain network properties were analyzed using Network-based statistics and graph theoretical measures particularly focusing on community structure, network hubs and controllability. Bayesian power estimation was used to assess the reliability of the structural connectivity differences by examining the effect size. The analysis revealed reliable and wide-spread decreases in connectivity for adults who stutter in regions associated with sensorimotor, cognitive, emotional, and memory-related functions. The community detection algorithms revealed different subnetworks for fluent speakers and adults who stutter, indicating considerable network adaptation in adults who stutter. Average and modal controllability differed between groups in a subnetwork encompassing frontal brain regions and parts of the basal ganglia.

The results revealed extensive structural network alterations and substantial adaptation in neural architecture in adults who stutter well beyond the sensorimotor network. These findings highlight the impact of the neurodevelopmental effects of persistent stuttering on neural organization and the importance of examining the full structural connectome and the network alterations that underscore the behavioral phenotype.

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.

Viewing personalized video clips recommended by TikTok activates default mode network and ventral tegmental area

Cutting-edge recommendation algorithms have been widely used by media platforms to suggest users with personalized content. While such user-specific recommendations may satisfy users' needs to obtain intended information, some users may develop a problematic use pattern manifested by addiction-like undesired behaviors. Using a popular video sharing and recommending platform (TikTok) as an example, the present study first characterized use-related undesired behaviors with a questionnaire, then investigated how personally recommended videos modulated brain activity with an fMRI experiment. We found more undesired symptoms were related to lower self-control ability among young adults, and about 5.9% of TikTok users may have significant problematic use. The fMRI results showed higher brain activations in sub-components of the default mode network (DMN), ventral tegmental area, and discrete regions including lateral prefrontal, anterior thalamus, and cerebellum when viewing personalized videos in contrast to non-personalized ones. Psychophysiological interaction analyses revealed stronger coupling between activated DMN subregions and neural pathways underlying auditory and visual processing, as well as the frontoparietal network. This study highlights the functional heterogeneity of DMN in viewing personalized videos and may shed light on the neural underpinnings of how recommendation algorithms are able to keep the user's attention to suggested contents.

Language Familiarity and Proficiency Leads to Differential Cortical Processing During Translation Between Distantly Related Languages

In the midst of globalization, English is regarded as an international language, or Lingua Franca, but learning it as a second language (L2) remains still difficult to speakers of other languages. This is true especially for the speakers of languages distantly related to English such as Japanese. In this sense, exploring neural basis for translation between the first language (L1) and L2 is of great interest. There have been relatively many previous researches revealing brain activation patterns during translations between L1 and English as L2. These studies, which focused on language translation with close or moderate linguistic distance (LD), have suggested that the Broca area (BA 44/45) and the dorsolateral prefrontal cortex (DLPFC; BA 46) may play an important role on translation. However, the neural mechanism of language translation between Japanese and English, having large LD, has not been clarified. Thus, we used functional near infrared spectroscopy (fNIRS) to investigate the brain activation patterns during word translation between Japanese and English. We also assessed the effects of translation directions and word familiarity. All participants’ first language was Japanese and they were learning English. Their English proficiency was advanced or elementary. We selected English and Japanese words as stimuli based on the familiarity for Japanese people. Our results showed that the brain activation patterns during word translation largely differed depending on their English proficiency. The advanced group elicited greater activation on the left prefrontal cortex around the Broca’s area while translating words with low familiarity, but no activation was observed while translating words with high familiarity. On the other hand, the elementary group evoked greater activation on the left temporal area including the superior temporal gyrus (STG) irrespective of the word familiarity. These results suggested that different cognitive process could be involved in word translation corresponding to English proficiency in Japanese learners of English. These difference on the brain activation patterns between the advanced and elementary group may reflect the difference on the cognitive loads depending on the levels of automatization in one’s language processing.

Changed functional connectivity at rest in functional illiterates after extensive literacy training

Background

About 6.2 million adults in Germany cannot read and write properly despite attending school for several years. They are considered to be functional illiterates (FI). Since the ability to read and write is crucial for being employed and socially accepted, we developed a special literacy training to overcome these deficits.

Methods

In this study, we investigate training-related changes in intrinsic functional connectivity (iFC) at rest in a group of 20 FI and 20 adult normal readers using resting state functional magnetic resonance imaging (rsfMRI). We used independent component analysis (ICA) to define different networks.

Results

Before training, the between group analysis showed increased iFC in FI in a left-fronto-parietal network (LFPN; anterior insula, medial frontal cortex, lateral and frontal parietal regions) and in the Basal Ganglia network (BGN: thalamus, caudate, putamen, pallidum, amygdala, supplementary motor cortex and cingulate gyrus). Furthermore, the Visual Network-1 (VN1; temporal occipital fusiform gyrus, lateral occipital cortex, occipital pole, lingual gyrus, thalamus) showed decreased iFC in FI. After training the FI group showed reversal of the “hyperconnectivity” in middle frontal gyrus and in the frontal orbital cortex and between supramarginal gyrus and the BGN. Furthermore, functional connectivity increased in FI VN1 (lateral occipital cortex, insular cortex). These changes in connectivity correlated with gains in reading speed and spelling accuracy.

Conclusions

These findings show that poor reading and writing abilities are associated with abnormalities in iFC in several brain areas subserving cognitive processes important for reading. Intensive literacy training induces changes in the functional connectivity between and within neural networks important for literacy skills.

Neural and Linguistic Considerations for Assessing Moral Intuitions Using Text-Based Stimuli

This review takes a focused look at neural and linguistic considerations for assessing moral intuitions using text-based stimuli. Relevant neural correlates of moral salience, emotional processing, moral emotions (shame and guilt), semantic processing, implicit stereotype activation (e.g., gender, age, and race stereotypes), and functional brain network development (the default mode network and salience network) are considered insofar as they relate to unique considerations for text-based instruments. What emerge are not only key considerations for researchers assessing moral intuitions using text-based stimuli but also considerations for the study of moral psychology more broadly, especially in developmental and educational contexts.

Impaired naming performance in temporal lobe epilepsy: language fMRI responses are modulated by disease characteristics

OBJECTIVE

To investigate alterations of language networks and their relation to impaired naming performance in temporal lobe epilepsy (TLE) using functional MRI.

METHODS

Seventy-two adult TLE patients (41 left) and 36 controls were studied with overt auditory and picture naming fMRI tasks to assess temporal lobe language areas, and a covert verbal fluency task to probe frontal lobe language regions. Correlation of fMRI activation with clinical naming scores, and alteration of language network patterns in relation to epilepsy duration, age at onset and seizure frequency, were investigated with whole-brain multiple regression analyses.

RESULTS

Auditory and picture naming fMRI activated the left posterior temporal lobe, and stronger activation correlated with better clinical naming scores. Verbal fluency MRI mainly activated frontal lobe regions. In left and right TLE, a later age of epilepsy onset related to stronger temporal lobe activations, while earlier age of onset was associated with impaired deactivation of extratemporal regions. In left TLE patients, longer disease duration and higher seizure frequency were associated with reduced deactivation. Frontal lobe language networks were unaffected by disease characteristics.

CONCLUSIONS

While frontal lobe language regions appear spared, temporal lobe language areas are susceptible to dysfunction and reorganisation, particularly in left TLE. Early onset and long duration of epilepsy, and high seizure frequency, were associated with compromised activation and deactivation patterns of task-associated regions, which might account for impaired naming performance in individuals with TLE.

Frequency-Dependent Intrinsic Electrophysiological Functional Architecture of the Human Verbal Language Network

Functional magnetic resonance imaging (fMRI) allowed the spatial characterization of the resting-state verbal language network (vLN). While other resting-state networks (RSNs) were matched with their electrophysiological equivalents at rest and could be spectrally defined, such correspondence is lacking for the vLN. This magnetoencephalography (MEG) study aimed at defining the spatio-spectral characteristics of the neuromagnetic intrinsic functional architecture of the vLN. Neuromagnetic activity was recorded at rest in 100 right-handed healthy adults (age range: 18-41 years). Band-limited power envelope correlations were performed within and across frequency bands (θ, α, β, and low γ) from a seed region placed in the left Broca's area, using static orthogonalization as leakage correction. K-means clustering was used to segregate spatio-spectral clusters of resting-state functional connectivity (rsFC). Remarkably, unlike other RSNs, within-frequency long-range rsFC from the left Broca's area was not driven by one main carrying frequency but was characterized by a specific spatio-spectral pattern segregated along the ventral (predominantly θ and α) and dorsal (β and low-γ bands) vLN streams. In contrast, spatial patterns of cross-frequency vLN functional integration were spectrally more widespread and involved multiple frequency bands. Moreover, the static intrinsic functional architecture of the neuromagnetic human vLN involved clearly left-hemisphere-dominant vLN interactions as well as cross-network interactions with the executive control network and postero-medial nodes of the DMN. Overall, this study highlighted the involvement of multiple modes of within and cross-frequency power envelope couplings at the basis of long-range electrophysiological vLN functional integration. As such, it lays the foundation for future works aimed at understanding the pathophysiology of language-related disorders.

No title, no theme: The joined neural space between speakers and listeners during production and comprehension of multi-sentence discourse

Speakers and listeners usually interact in larger discourses than single words or even single sentences. The goal of the present study was to identify the neural bases reflecting how the mental representation of the situation denoted in a multi-sentence discourse (situation model) is constructed and shared between speakers and listeners. An fMRI study using a variant of the ambiguous text paradigm was designed. Speakers (n = 15) produced ambiguous texts in the scanner and listeners (n = 27) subsequently listened to these texts in different states of ambiguity: preceded by a highly informative, intermediately informative or no title at all. Conventional BOLD activation analyses in listeners, as well as inter-subject correlation analyses between the speakers' and the listeners' hemodynamic time courses were performed. Critically, only the processing of disambiguated, coherent discourse with an intelligible situation model representation involved (shared) activation in bilateral lateral parietal and medial prefrontal regions. This shared spatiotemporal pattern of brain activation between the speaker and the listener suggests that the process of memory retrieval in medial prefrontal regions and the binding of retrieved information in the lateral parietal cortex constitutes a core mechanism underlying the communication of complex conceptual representations.

Correcting Task fMRI Signals for Variability in Baseline CBF Improves BOLD-Behavior Relationships: A Feasibility Study in an Aging Model

Blood Oxygen Level Dependent (BOLD) functional MRI is a complex neurovascular signal whose magnitude depends on baseline physiological factors such as cerebral blood flow (CBF). Because baseline CBF varies across the brain and is altered with aging, the interpretation of stand-alone aging-related BOLD changes can be misleading. The primary objective of this study was to develop a methodology that combines task fMRI and arterial spin labeling (ASL) techniques to sensitize task-induced BOLD activity by covarying out the baseline physiology (i.e., CBF) in an aging model. We recruited 11 younger and 13 older healthy participants who underwent ASL and an overt language fMRI task (semantic category member generation). We measured in-scanner language performance to investigate the effect of BOLD sensitization on BOLD-behavior relationships. The results demonstrate that our correction approach is effective at enhancing the specificity and sensitivity of the BOLD signal in both groups. In addition, the correction strengthens the statistical association between task BOLD activity and behavioral performance. Although CBF has inherent age dependence, our results show that retaining the age factor within CBF aides in greater sensitization of task fMRI signals. From a cognitive standpoint, compared to young adults, the older participants showed a delayed domain-general language-related task activity possibly due to compromised vessel compliance. Further, assessment of functional evolution of corrected BOLD activity revealed biphasic BOLD dynamics in both groups where BOLD deactivation may reflect greater semantic demand or increased premium on domain general executive functioning in response to task difficulty. Although it was promising to note that the predictability of behavior using the proposed methodology outperforms other methodologies (i.e., no correction and normalization by division), and provides moderate stability and adequate power, further work with a larger cohort and other task designs is necessary to improve the stability of predicting associated behavior. In summary, we recommend correction of task fMRI signals by covarying out baseline CBF especially when comparing groups with different neurovascular properties. Given that ASL and BOLD fMRI are well established and widely employed techniques, our proposed multi-modal methodology can be readily implemented into data processing pipelines to obtain more accurate BOLD activation maps.

Mapping language with resting-state functional magnetic resonance imaging: A study on the functional profile of the language network

Resting-state functional magnetic resonance imaging (rsfMRI) is a promising technique for language mapping that does not require task-execution. This can be an advantage when language mapping is limited by poor task performance, as is common in clinical settings. Previous studies have shown that language maps extracted with rsfMRI spatially match their task-based homologs, but no study has yet demonstrated the direct participation of the rsfMRI language network in language processes. This demonstration is critically important because spatial similarity can be influenced by the overlap of domain-general regions that are recruited during task-execution. Furthermore, it is unclear which processes are captured by the language network: does it map rather low-level or high-level (e.g., syntactic and lexico-semantic) language processes? We first identified the rsfMRI language network and then investigated task-based responses within its regions when processing stimuli of increasing linguistic content: symbols, pseudowords, words, pseudosentences and sentences. The language network responded only to language stimuli (not to symbols), and higher linguistic content elicited larger brain responses. The left fronto-parietal, the default mode, and the dorsal attention networks were examined and yet none showed language involvement. These findings demonstrate for the first time that the language network extracted through rsfMRI is able to map language in the brain, including regions subtending higher-level syntactic and semantic processes.

Pharmaco-fMRI: A Tool to Predict the Response to Antiepileptic Drugs in Epilepsy

Pharmacological treatment with antiepileptic medications (AEDs) in epilepsy is associated with a variety of neurocognitive side effects. However, the mechanisms underlying these side effects, and why certain brain anatomies are more affected still remain poorly understood. Advanced functional magnetic resonance imaging (fMRI) methods, such as pharmaco-fMRI, can investigate medication-related effects on brain activities using task and resting state fMRI and showing reproducible activation and deactivation patterns. This methodological approach has been used successfully to complement neuropsychological studies of AEDs. Here we review pharmaco-fMRI studies in people with epilepsy targeting the most-widely prescribed AEDs. Pharmco-fMRI has advanced our understanding of the impact of AEDs on specific brain networks and thus may provide potential biomarkers to move beyond the current “trial and error” approach when commencing anti-epileptic medication.

Beyond consensus: Embracing heterogeneity in curated neuroimaging meta-analysis

Coordinate-based meta-analysis can provide important insights into mind-brain relationships. A popular approach for curated small-scale meta-analysis is activation likelihood estimation (ALE), which identifies brain regions consistently activated across a selected set of experiments, such as within a functional domain or mental disorder. ALE can also be utilized in meta-analytic co-activation modeling (MACM) to identify brain regions consistently co-activated with a seed region. Therefore, ALE aims to find consensus across experiments, treating heterogeneity across experiments as noise. However, heterogeneity within an ALE analysis of a functional domain might indicate the presence of functional sub-domains. Similarly, heterogeneity within a MACM analysis might indicate the involvement of a seed region in multiple co-activation patterns that are dependent on task contexts. Here, we demonstrate the use of the author-topic model to automatically determine if heterogeneities within ALE-type meta-analyses can be robustly explained by a small number of latent patterns. In the first application, the author-topic modeling of experiments involving self-generated thought (N = 179) revealed cognitive components fractionating the default network. In the second application, the author-topic model revealed that the left inferior frontal junction (IFJ) participated in multiple task-dependent co-activation patterns (N = 323). Furthermore, the author-topic model estimates compared favorably with spatial independent component analysis in both simulation and real data. Overall, the results suggest that the author-topic model is a flexible tool for exploring heterogeneity in ALE-type meta-analyses that might arise from functional sub-domains, mental disorder subtypes or task-dependent co-activation patterns. Code for this study is publicly available (https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/meta-analysis/Ngo2019_AuthorTopic).

Reduced semantic control in older adults is linked to intrinsic DMN connectivity

Ageing provides an interesting window into semantic cognition: while younger adults generally outperform older adults on many cognitive tasks, knowledge continues to accumulate over the lifespan and consequently, the semantic store (i.e., vocabulary size) remains stable (or even improves) during healthy ageing. Semantic cognition involves the interaction of at least two components - a semantic store and control processes that interact to ensure efficient and context-relevant use of representations. Given older adults perform less well on tasks measuring executive control, their ability to access the semantic store in a goal driven manner may be compromised. Older adults also consistently show reductions in intrinsic brain connectivity, and we examined how these brain changes relate to age-related changes in semantic performance. We found that while older participants outperformed their younger counterparts on tests of vocabulary size (i.e., NART), younger participants were faster and more accurate in tasks requiring semantic control, and these age differences correlated with measures of intrinsic connectivity between the anterior temporal lobe (ATL) and medial prefrontal cortex (mPFC), within the default mode network. Higher intrinsic connectivity from right ATL to mPFC at rest related to better performance on verbal (but not picture) semantic tasks, and older adults showed an exaggerated version of this pattern, suggesting that this within-DMN connectivity may become more important for conceptual access from words as we age. However, this appeared to be at the expense of control over semantic retrieval - there was little relationship between connectivity and performance for strong associations in either group, but older adults with stronger connectivity showed particularly inefficient retrieval of weak associations. Older adults may struggle to harness the default mode network to support demanding patterns of semantic retrieval, resulting in a performance cost.

Increased Functional Connectivity of the Angular Gyrus During Imagined Music Performance

The angular gyrus (AG) is a hub of several networks that are involved in various functions, including attention, self-processing, semantic information processing, emotion regulation, and mentalizing. Since these functions are required in music performance, it is likely that the AG plays a role in music performance. Considering that these functions emerge as network properties, this study analyzed the functional connectivity of the AG during the imagined music performance task and the resting condition. Our hypothesis was that the functional connectivity of the AG is modulated by imagined music performance. In the resting condition, the AG had connections with the medial prefrontal cortex (mPFC), posterior cingulate cortex (PCC), and precuneus as well as the superior and inferior frontal gyri and with the temporal cortex. Compared with the resting condition, imagined music performance increased the functional connectivity of the AG with the superior frontal gyrus (SFG), mPFC, precuneus, PCC, hippocampal/parahippocampal gyrus (H/PHG), and amygdala. The anterior cingulate cortex (ACC) and superior temporal gyrus (STG) were newly engaged or added to the AG network during the task. In contrast, the supplementary motor area (SMA), sensorimotor areas, and occipital regions, which were anti-correlated with the AG in the resting condition, were disengaged during the task. These results lead to the conclusion that the functional connectivity of the AG is modulated by imagined music performance, which suggests that the AG plays a role in imagined music performance.

Exploring distinct default mode and semantic networks using a systematic ICA approach

Resting-state networks (RSNs; groups of regions consistently co-activated without an explicit task) are hugely influential in modern brain research. Despite this popularity, the link between specific RSNs and their functions remains elusive, limiting the impact on cognitive neuroscience (where the goal is to link cognition to neural systems). Here we present a series of logical steps to formally test the relationship between a coherent RSN with a cognitive domain. This approach is applied to a challenging and significant test-case; extracting a recently-proposed semantic RSN, determining its relation with a well-known RSN, the default mode network (DMN), and assessing their roles in semantic cognition. Results showed the DMN and semantic network are two distinct coherent RSNs. Assessing the cognitive signature of these spatiotemporally coherent networks directly (and therefore accounting for overlapping networks) showed involvement of the proposed semantic network, but not the DMN, in task-based semantic cognition. Following the steps presented here, researchers could formally test specific hypotheses regarding the function of RSNs, including other possible functions of the DMN.

The evolution of cognitive models: From neuropsychology to neuroimaging and back

This paper provides a historical and future perspective on how neuropsychology and neuroimaging can be used to develop cognitive models of human brain functions. Section 1 focuses on the emergence of cognitive modelling from neuropsychology, why lesion location was considered to be unimportant and the challenges faced when mapping symptoms to impaired cognitive processes. Section 2 describes how established cognitive models based on behavioural data alone cannot explain the complex patterns of distributed brain activity that are observed in functional neuroimaging studies. This has led to proposals for new cognitive processes, new cognitive strategies and new functional ontologies for cognition. Section 3 considers how the integration of data from lesion, behavioural and functional neuroimaging studies of large cohorts of brain damaged patients can be used to determine whether inter-patient variability in behaviour is due to differences in the premorbid function of each brain region, lesion site or cognitive strategy. This combination of neuroimaging and neuropsychology is providing a deeper understanding of how cognitive functions can be lost and re-learnt after brain damage - an understanding that will transform our ability to generate and validate cognitive models that are both physiologically plausible and clinically useful.

Effects of carbamazepine and lamotrigine on functional magnetic resonance imaging cognitive networks

OBJECTIVE

To investigate the effects of sodium channel-blocking antiepileptic drugs (AEDs) on functional magnetic resonance imaging (fMRI) language network activations in patients with focal epilepsy.

METHODS

In a retrospective study, we identified patients who were treated at the time of language fMRI scanning with either carbamazepine (CBZ; n = 42) or lamotrigine (LTG; n = 42), but not another sodium channel-blocking AED. We propensity-matched 42 patients taking levetiracetam (LEV) as "patient-controls" and included further 42 age- and gender-matched healthy controls. After controlling for age, age at onset of epilepsy, gender, and antiepileptic comedications, we compared verbal fluency fMRI activations between groups and out-of-scanner psychometric measures of verbal fluency.

RESULTS

Patients on CBZ performed less well on a verbal fluency tests than those taking LTG or LEV. Compared to either LEV-treated patients or controls, patients taking CBZ showed decreased activations in left inferior frontal gyrus and patients on LTG showed abnormal deactivations in frontal and parietal default mode areas. All patient groups showed fewer activations in the putamen bilaterally compared to controls. In a post hoc analysis, out-of-scanner fluency scores correlated positively with left putamen activation.

SIGNIFICANCE

Our study provides evidence of AED effects on the functional neuroanatomy of language, which might explain subtle language deficits in patients taking otherwise well-tolerated sodium channel-blocking agents. Patients on CBZ showed dysfunctional frontal activation and more pronounced impairment of performance than patients taking LTG, which was associated only with failure to deactivate task-negative networks. As previously shown for working memory, LEV treatment did not affect functional language networks.

Mapping the Neural Dynamics of Korean-English Bilinguals With Medium Proficiency During Auditory Word Processing

Bilingualism is a worldwide phenomenon and provides an opportunity to understand how the brain represents language processing. Although many studies have investigated the neural mechanism of bilingualism, it still remain unclear how brain systems are involved in the second language processing. Here, we examined the neural dynamics of bilinguals with medium proficiency during auditory word processing. Korean–English (K–E) bilinguals were recruited for the study (L1: Korean and L2: English). They performed a word comprehension task on phonological and semantic aspects by hearing words. We compared their task performance, task-induced regional activity, and functional connectivity (FC) between L1 and L2 processing. Brain activation analyses revealed that L2 evoked more widespread and stronger activation in brain regions involved in auditory word processing and the increased regional activity in L2 was prominent during phonological processing. Moreover, L2 evoked up-regulation during semantic processing was associated with L2 proficiency. FC analyses demonstrated that the intra-network connectivity showed stronger in the language network (LN), dorsal attention network (DAN), and default mode network (DMN) in L2 than L1. For the L2 phonological processing, the increased FC within the DAN was positively correlated with individuals’ L2 proficiency. Also, L2 semantic processing induced the enhanced internetwork connectivity between the LN and DMN. Our findings suggest that L2 processing in K–E bilinguals induces dynamic changes in the brain at a regional and network-level and FC analysis can disentangle the different networks involvement in L2 auditory word processing according to two key features: phonology and semantics.

Why People Are Always Thinking about Themselves: Medial Prefrontal Cortex Activity during Rest Primes Self-referential Processing

Humans have a tendency to think about themselves. What generates this self-focus? One clue may come from the observation that the same part of the brain that supports self-reflection—the medial pFC (MPFC/Brodmann's area 10 [BA 10])—also spontaneously engages by default whenever the brain is free from external demands to attention. Here, we test the possibility that the default tendency to engage MPFC/BA 10 primes self-referential thinking. Participants underwent fMRI while alternating between brief periods of rest and experimental tasks in which they thought about their own traits, another person's traits, or another location's traits. Greater default engagement in MPFC/BA 10 during momentary breaks preferentially facilitated task performance on subsequent self-reflection trials on a moment-to-moment basis. These results suggest that reflexively engaging MPFC/BA 10 by default may nudge self-referential thinking, perhaps explaining why humans think about themselves so readily.

Spectral Diversity in Default Mode Network Connectivity Reflects Behavioral State

Default mode network (DMN) functional connectivity is thought to occur primarily in low frequencies (<0.1 Hz), resulting in most studies removing high frequencies during data preprocessing. In contrast, subtractive task analyses include high frequencies, as these are thought to be task relevant. An emerging line of research explores resting fMRI data at higher-frequency bands, examining the possibility that functional connectivity is a multiband phenomenon. Furthermore, recent studies suggest DMN involvement in cognitive processing; however, without a systematic investigation of DMN connectivity during tasks, its functional contribution to cognition cannot be fully understood. We bridged these concurrent lines of research by examining the contribution of high frequencies in the relationship between DMN and dorsal attention network at rest and during task execution. Our findings revealed that the inclusion of high frequencies alters between network connectivity, resulting in reduced anticorrelation and increased positive connectivity between DMN and dorsal attention network. Critically, increased positive connectivity was observed only during tasks, suggesting an important role for high-frequency fluctuations in functional integration. Moreover, within-DMN connectivity during task execution correlated with RT only when high frequencies were included. These results show that DMN does not simply deactivate during task execution and suggest active recruitment while performing cognitively demanding paradigms.

"Neural overlap of L1 and L2 semantic representations across visual and auditory modalities: a decoding approach"

This study investigated whether brain activity in Dutch-French bilinguals during semantic access to concepts from one language could be used to predict neural activation during access to the same concepts from another language, in different language modalities/tasks. This was tested using multi-voxel pattern analysis (MVPA), within and across language comprehension (word listening and word reading) and production (picture naming). It was possible to identify the picture or word named, read or heard in one language (e.g. maan, meaning moon) based on the brain activity in a distributed bilateral brain network while, respectively, naming, reading or listening to the picture or word in the other language (e.g. lune). The brain regions identified differed across tasks. During picture naming, brain activation in the occipital and temporal regions allowed concepts to be predicted across languages. During word listening and word reading, across-language predictions were observed in the rolandic operculum and several motor-related areas (pre- and postcentral, the cerebellum). In addition, across-language predictions during reading were identified in regions typically associated with semantic processing (left inferior frontal, middle temporal cortex, right cerebellum and precuneus) and visual processing (inferior and middle occipital regions and calcarine sulcus). Furthermore, across modalities and languages, the left lingual gyrus showed semantic overlap across production and word reading. These findings support the idea of at least partially language- and modality-independent semantic neural representations.

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Evidence for at least partially language- and modality-independent semantic neural representations.

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With a decoding approach, we tested whether brain activity during the semantic access of individual nouns in one language and modality (e.g. production) allowed predicting the semantic access of the same concepts in the other language and modalities (e.g. word listening, word reading).

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Across modalities and languages, the left lingual gyrus showed semantic overlap across production and word reading.

Anomalous network architecture of the resting brain in children who stutter

PURPOSE

We combined a large longitudinal neuroimaging dataset that includes children who do and do not stutter and a whole-brain network analysis in order to examine the intra- and inter-network connectivity changes associated with stuttering. Additionally, we asked whether whole brain connectivity patterns observed at the initial year of scanning could predict persistent stuttering in later years.

METHODS

A total of 224 high-quality resting state fMRI scans collected from 84 children (42 stuttering, 42 controls) were entered into an independent component analysis (ICA), yielding a number of distinct network connectivity maps ("components") as well as expression scores for each component that quantified the degree to which it is expressed for each child. These expression scores were compared between stuttering and control groups' first scans. In a second analysis, we examined whether the components that were most predictive of stuttering status also predicted persistence in stuttering.

RESULTS

Stuttering status, as well as stuttering persistence, were associated with aberrant network connectivity involving the default mode network and its connectivity with attention, somatomotor, and frontoparietal networks. The results suggest developmental alterations in the balance of integration and segregation of large-scale neural networks that support proficient task performance including fluent speech motor control.

CONCLUSIONS

This study supports the view that stuttering is a complex neurodevelopmental disorder and provides comprehensive brain network maps that substantiate past theories emphasizing the importance of considering situational, emotional, attentional and linguistic factors in explaining the basis for stuttering onset, persistence, and recovery.

Modulation of Speech Motor Learning with Transcranial Direct Current Stimulation of the Inferior Parietal Lobe

The inferior parietal lobe (IPL) is a region of the cortex believed to participate in speech motor learning. In this study, we investigated whether transcranial direct current stimulation (tDCS) of the IPL could influence the extent to which healthy adults (1) adapted to a sensory alteration of their own auditory feedback, and (2) changed their perceptual representation. Seventy subjects completed three tasks: a baseline perceptual task that located the phonetic boundary between the vowels /e/ and /a/; a sensorimotor adaptation task in which subjects produced the word “head” under conditions of altered or unaltered feedback; and a post-adaptation perceptual task identical to the first. Subjects were allocated to four groups which differed in current polarity and feedback manipulation. Subjects who received anodal tDCS to their IPL (i.e., presumably increasing cortical excitability) lowered their first formant frequency (F1) by 10% in opposition to the upward shift in F1 in their auditory feedback. Subjects who received the same stimulation with unaltered feedback did not change their production. Subjects who received cathodal tDCS to their IPL (i.e., presumably decreasing cortical excitability) showed a 5% adaptation to the F1 alteration similar to subjects who received sham tDCS. A subset of subjects returned a few days later to reiterate the same protocol but without tDCS, enabling assessment of any facilitatory effects of the previous tDCS. All subjects exhibited a 5% adaptation effect. In addition, across all subjects and for the two recording sessions, the phonetic boundary was shifted toward the vowel /e/ being repeated, consistently with the selective adaptation effect, but a correlation between perception and production suggested that anodal tDCS had enhanced this perceptual shift. In conclusion, we successfully demonstrated that anodal tDCS could (1) enhance the motor adaptation to a sensory alteration, and (2) potentially affect the perceptual representation of those sounds, but we failed to demonstrate the reverse effect with the cathodal configuration. Overall, tDCS of the left IPL can be used to enhance speech performance but only under conditions in which new or adaptive learning is required.

Modality-independent encoding of individual concepts in the left parietal cortex

The organization of semantic information in the brain has been mainly explored through category-based models, on the assumption that categories broadly reflect the organization of conceptual knowledge. However, the analysis of concepts as individual entities, rather than as items belonging to distinct superordinate categories, may represent a significant advancement in the comprehension of how conceptual knowledge is encoded in the human brain. Here, we studied the individual representation of thirty concrete nouns from six different categories, across different sensory modalities (i.e., auditory and visual) and groups (i.e., sighted and congenitally blind individuals) in a core hub of the semantic network, the left angular gyrus, and in its neighboring regions within the lateral parietal cortex. Four models based on either perceptual or semantic features at different levels of complexity (i.e., low- or high-level) were used to predict fMRI brain activity using representational similarity encoding analysis. When controlling for the superordinate component, high-level models based on semantic and shape information led to significant encoding accuracies in the intraparietal sulcus only. This region is involved in feature binding and combination of concepts across multiple sensory modalities, suggesting its role in high-level representation of conceptual knowledge. Moreover, when the information regarding superordinate categories is retained, a large extent of parietal cortex is engaged. This result indicates the need to control for the coarse-level categorial organization when performing studies on higher-level processes related to the retrieval of semantic information.

Effect of topiramate and zonisamide on fMRI cognitive networks

Objective:

To investigate the effects of topiramate (TPM), zonisamide (ZNS), and levetiracetam (LEV) on cognitive network activations in patients with focal epilepsy using an fMRI language task.

Methods:

In a retrospective, cross-sectional study, we identified patients from our clinical database of verbal fluency fMRI studies who were treated with either TPM (n = 32) or ZNS (n = 51). We matched 62 patients for clinical measures who took LEV but not TPM or ZNS. We entered antiepileptic comedications as nuisance variables and compared out-of-scanner psychometric measures for verbal fluency and working memory between groups.

Results:

Out-of-scanner psychometric data showed overall poorer performance for TPM compared to ZNS and LEV and poorer working memory performance in ZNS-treated patients compared to LEV-treated patients. We found common fMRI effects in patients taking ZNS and TPM, with decreased activations in cognitive frontal and parietal lobe networks compared to those taking LEV. Impaired deactivation was seen only with TPM.

Conclusions:

Our findings suggest that TPM and ZNS are associated with similar dysfunctions of frontal and parietal cognitive networks, which are associated with impaired performance. TPM is also associated with impaired attenuation of language-associated deactivation. These studies imply medication-specific effects on the functional neuroanatomy of language and working memory networks.

Classification of evidence:

This study provides Class III evidence that in patients with focal epilepsy, TPM and ZNS compared to LEV lead to disruption of language and working memory networks.

Pharmaco fMRI: Determining the functional anatomy of the effects of medication

Functional MRI studies have helped to elucidate underlying mechanisms in complex neurological and neuropsychiatric disorders. Disease processes often involve complex large-scale network interactions, extending beyond the presumed main disease focus. Given both the complexity of the clinical phenotype and the underlying dysfunctional brain circuits, so called pharmaco-fMRI (ph-MRI) studies probe pharmacological effects on functional neuro-anatomy, and can help to determine early treatment response, mechanisms of drug efficacy and side effects, and potentially advance CNS drug development. In this review, we discuss recent ph-MRI research in three major neuropsychiatric and neurological disorders and associated network alterations, namely selective serotonin and noradrenergic reuptake inhibitors in affective disorders and emotional processing circuits; antiepileptic drugs in epilepsy and cognitive networks; and stimulants in attention-deficit/hyperactivity disorder and networks of attention control. We conclude that ph-MRI studies show consistent and reproducible changes on disease relevant networks, and prove sensitive to early pharmacological effects on functional anatomy associated with disease. Further CNS drug research and development would benefit greatly from improved disease phenotyping, or biomarkers, using advanced imaging techniques.

Perceived communicative intent in gesture and language modulates the superior temporal sulcus

Behavioral evidence and theory suggest gesture and language processing may be part of a shared cognitive system for communication. While much research demonstrates both gesture and language recruit regions along perisylvian cortex, relatively less work has tested functional segregation within these regions on an individual level. Additionally, while most work has focused on a shared semantic network, less has examined shared regions for processing communicative intent. To address these questions, functional and structural MRI data were collected from 24 adult participants while viewing videos of an experimenter producing communicative, Participant-Directed Gestures (PDG) (e.g., "Hello, come here"), noncommunicative Self-adaptor Gestures (SG) (e.g., smoothing hair), and three written text conditions: (1) Participant-Directed Sentences (PDS), matched in content to PDG, (2) Third-person Sentences (3PS), describing a character's actions from a third-person perspective, and (3) meaningless sentences, Jabberwocky (JW). Surface-based conjunction and individual functional region of interest analyses identified shared neural activation between gesture (PDGvsSG) and language processing using two different language contrasts. Conjunction analyses of gesture (PDGvsSG) and Third-person Sentences versus Jabberwocky revealed overlap within left anterior and posterior superior temporal sulcus (STS). Conjunction analyses of gesture and Participant-Directed Sentences to Third-person Sentences revealed regions sensitive to communicative intent, including the left middle and posterior STS and left inferior frontal gyrus. Further, parametric modulation using participants' ratings of stimuli revealed sensitivity of left posterior STS to individual perceptions of communicative intent in gesture. These data highlight an important role of the STS in processing participant-directed communicative intent through gesture and language. Hum Brain Mapp 37:3444-3461, 2016. © 2016 Wiley Periodicals, Inc.

Self-similarity and recursion as default modes in human cognition

Humans generate recursive hierarchies in a variety of domains, including linguistic, social and visuo-spatial modalities. The ability to represent recursive structures has been hypothesized to increase the efficiency of hierarchical processing. Theoretical work together with recent empirical findings suggests that the ability to represent the self-similar structure of hierarchical recursive stimuli may be supported by internal neural representations that compress raw external information and increase efficiency. In order to explicitly test whether the representation of recursive hierarchies depends on internalized rules we compared the processing of visual hierarchies represented either as recursive or non-recursive, using task-free resting-state fMRI data. We aimed to evaluate the relationship between task-evoked functional networks induced by cognitive representations with the corresponding resting-state architecture. We observed increased connectivity within Default Mode Network (DMN) related brain areas during the representation of recursion, while non-recursive representations yielded increased connectivity within the Fronto-Parietal Control-Network. Our results suggest that human hierarchical information processing using recursion is supported by the DMN. In particular, the representation of recursion seems to constitute an internally-biased mode of information-processing that is mediated by both the core and dorsal-medial subsystems of the DMN. Compressed internal rule representations mediated by the DMN may help humans to represent and process hierarchical structures in complex environments by considerably reducing information processing load.

Does the sound of a barking dog activate its corresponding visual form? An fMRI investigation of modality-specific semantic access

Much remains to be learned about the neural architecture underlying word meaning. Fully distributed models of semantic memory predict that the sound of a barking dog will conjointly engage a network of distributed sensorimotor spokes. An alternative framework holds that modality-specific features additionally converge within transmodal hubs. Participants underwent functional MRI while covertly naming familiar objects versus newly learned novel objects from only one of their constituent semantic features (visual form, characteristic sound, or point-light motion representation). Relative to the novel object baseline, familiar concepts elicited greater activation within association regions specific to the presentation modality. Furthermore, visual form elicited activation within high-level auditory association cortex. Conversely, environmental sounds elicited activation in regions proximal to visual association cortex. Both conditions commonly engaged a putative hub region within lateral anterior temporal cortex. These results support hybrid semantic models in which local hubs and distributed spokes are dually engaged in service of semantic memory.

Functional Connectivity of the Precuneus in Female University Students with Long-Term Musical Training

Conceiving concrete mental imagery is critical for skillful musical expression and performance. The precuneus, a core component of the default mode network (DMN), is a hub of mental image processing that participates in functions such as episodic memory retrieval and imagining future events. The precuneus connects with many brain regions in the frontal, parietal, temporal, and occipital cortices. The aim of this study was to examine the effects of long-term musical training on the resting-state functional connectivity of the precuneus. Our hypothesis was that the functional connectivity of the precuneus is altered in musicians. We analyzed the functional connectivity of the precuneus using resting-state functional magnetic resonance imaging (fMRI) data recorded in female university students majoring in music and nonmusic disciplines. The results show that the music students had higher functional connectivity of the precuneus with opercular/insular regions, which are associated with interoceptive and emotional processing; Heschl’s gyrus (HG) and the planum temporale (PT), which process complex tonal information; and the lateral occipital cortex (LOC), which processes visual information. Connectivity of the precuneus within the DMN did not differ between the two groups. Our finding suggests that functional connections between the precuneus and the regions outside of the DMN play an important role in musical performance. We propose that a neural network linking the precuneus with these regions contributes to translate mental imagery into information relevant to musical performance.

Altered cerebral activity associated with topiramate and its withdrawal in patients with epilepsy with language impairment: An fMRI study using the verb generation task

OBJECTIVE

Topiramate (TPM) is well recognized for its negative effects on language in healthy volunteers and patients with epilepsy. The aim of this study was to investigate the brain activation and deactivation patterns in TPM-treated patients with epilepsy with language impairment and their dynamic alteration during TPM withdrawal using functional magnetic resonance imaging (fMRI) with the verb generation task (VGT).

METHODS

Twelve patients with epilepsy experiencing subjective language disfluency after TPM add-on treatment (TPM-on) and thirty sex- and age-matched healthy controls (HCs) were recruited. All subjects received a battery of neuropsychological tests and an fMRI scan with the VGT. Withdrawal of TPM was attempted in all patients. Only six patients reached complete withdrawal without seizure relapses (TPM-off), and these patients underwent a reassessment of neuropsychological and neuroimaging tests.

RESULT

The neuropsychological tests demonstrated objective language impairments in TPM-on patients. Compared with the HCs, the bilateral medial prefrontal cortex and the posterior midline and lateral parts of the default mode network (DMN) (including the bilateral posterior cingulate cortex (PCC), the right medial prefrontal cortex, the right angular gyrus, the right inferior temporal gyrus, and the bilateral supramarginal gyrus) in TPM-on patients failed to deactivate during the VGT. Their task-induced activation patterns were largely similar to those of the HCs. After TPM withdrawal, partial improvement of both task-induced deactivation of the DMN (the left parahippocampal gyrus and the bilateral PCC) and task-related activation of the language network (the right middle frontal gyrus and the left superior occipital gyrus) was identified along with partial improvement of neuropsychological tests.

CONCLUSION

Task-induced deactivation is a more sensitive neuroimaging biomarker for the impaired language performance in patients administered TPM than task-induced activation. Disruption and reorganization of the balance between the DMN and the cortical language networks are found along with reversible TPM-related language impairment. These results may suggest an underlying brain mechanism by which TPM affects cognitive function.

The Semantics of Syntax: The Grounding of Transitive and Intransitive Constructions

Embodied theories of language maintain that brain areas associated with perception and action are also involved in the processing and representation of word meaning. A number of studies have shown that sentences with action verbs elicit activation within sensory–motor brain regions, arguing that sentence-induced mental simulations provide a means for grounding their lexical-semantic meaning. Constructionist theories argue, however, that form–meaning correspondence is present not only at the lexical level but also at the level of constructions. We investigated whether sentence-induced motor resonance is present for syntactic constructions. We measured the BOLD signal while participants read sentences with (di)transitive (caused motion) or intransitive constructions that contained either action or abstract verbs. The results showed a distinct neuronal signature for caused motion and intransitive syntactic frames. Caused motion frames activated regions associated with reaching and grasping actions, including the left anterior intraparietal sulcus and the parietal reach region. Intransitive frames activated lateral temporal regions commonly associated with abstract word processing. The left pars orbitalis showed an interaction between the syntactic frame and verb class. These findings show that sensory–motor activation elicited by sentences entails both motor resonance evoked by single words as well as at the level of syntactic constructions.

Signal or noise: brain network interactions underlying the experience and training of mindfulness

A broad set of brain regions has been associated with the experience and training of mindfulness. Many of these regions lie within key intrinsic brain networks, including the executive control, salience, and default networks. In this paper, we review the existing literature on the cognitive neuroscience of mindfulness through the lens of network science. We describe the characteristics of the intrinsic brain networks implicated in mindfulness and summarize the relevant findings pertaining to changes in functional connectivity (FC) within and between these networks. Convergence across these findings suggests that mindfulness may be associated with increased FC between two regions within the default network: the posterior cingulate cortex and the ventromedial prefrontal cortex. Additionally, extensive meditation experience may be associated with increased FC between the insula and the dorsolateral prefrontal cortex. However, little consensus has emerged within the existing literature owing to the diversity of operational definitions of mindfulness, neuroimaging methods, and network characterizations. We describe several challenges to develop a coherent cognitive neuroscience of mindfulness and to provide detailed recommendations for future research.

Visualising inter-subject variability in fMRI using threshold-weighted overlap maps

Functional neuroimaging studies are revealing the neural systems sustaining many sensory, motor and cognitive abilities. A proper understanding of these systems requires an appreciation of the degree to which they vary across subjects. Some sources of inter-subject variability might be easy to measure (demographics, behavioural scores, or experimental factors), while others are more difficult (cognitive strategies, learning effects, and other hidden sources). Here, we introduce a simple way of visualising whole-brain consistency and variability in brain responses across subjects using threshold-weighted voxel-based overlap maps. The output quantifies the proportion of subjects activating a particular voxel or region over a wide range of statistical thresholds. The sensitivity of our approach was assessed in 30 healthy adults performing a matching task with their dominant hand. We show how overlap maps revealed many effects that were only present in a subsample of our group; we discuss how overlap maps can provide information that may be missed or misrepresented by standard group analysis, and how this information can help users to understand their data. In particular, we emphasize that functional overlap maps can be particularly useful when it comes to explaining typical (or atypical) compensatory mechanisms used by patients following brain damage.

Multidisciplinary investigation links backward-speech trait and working memory through genetic mutation

Case studies of unusual traits can provide unique snapshots of the effects of modified systems. In this study, we report on an individual from a Serbian family with the ability to rapidly, accurately and voluntarily speak backwards. We consider psychological, neural and genetic correlates of this trait to identify specific relevant neural mechanisms and new molecular pathways for working memory and speech-related tasks. EEG data suggest that the effect of word reversal precedes semantic integration of visually presented backward-words, and that event-related potentials above the frontal lobe are affected by both word reversal and the maintenance of backward-words in working memory. fMRI revealed that the left fusiform gyrus may facilitate the production of backward-speech. Exome sequencing identified three novel coding variants of potential significance in the RIC3, RIPK1 and ZBED5 genes. Taken together, our data suggest that, in this individual, the ability to speak backwards is afforded by an extraordinary working memory capacity. We hypothesise that this is served by cholinergic projections from the basal forebrain to the frontal cortex and supported by visual semantic loops within the left fusiform gyrus and that these neural processes may be mediated by a genetic mutation in RIC3; a chaperone for nicotinic acetylcholine receptors.

Echoes of the Brain: Local-Scale Representation of Whole-Brain Functional Networks within Transmodal Cortex

Transmodal (nonsensory-specific) regions sit at the confluence of different information streams, and play an important role in cognition. These regions are thought to receive and integrate information from multiple functional networks. However, little is known about (1) how transmodal cortices are functionally organized and (2) how this organization might facilitate information processing. In this article, we discuss recent findings that transmodal cortices contain a detailed local functional architecture of adjacent and partially overlapping subregions. These subregions show relative specializations, and contain traces or "echoes" of the activity of different large-scale intrinsic connectivity networks. We propose that this finer-grained organization can (1) explain how the same transmodal region can play a role in multiple tasks and cognitive disorders, (2) provide a mechanism by which different types of signals can be simultaneously segregated and integrated within transmodal regions, and (3) enhance current network- and node-level models of brain function, by showing that non-stationary functional connectivity patterns may be a result of dynamic shifts in subnodal signals. Finally, we propose that LFA may have an important role in regulating neural dynamics and facilitating balanced activity across the cortex to enable efficient and flexible high-level cognition.

The Functional Connectome of Speech Control

In the past few years, several studies have been directed to understanding the complexity of functional interactions between different brain regions during various human behaviors. Among these, neuroimaging research installed the notion that speech and language require an orchestration of brain regions for comprehension, planning, and integration of a heard sound with a spoken word. However, these studies have been largely limited to mapping the neural correlates of separate speech elements and examining distinct cortical or subcortical circuits involved in different aspects of speech control. As a result, the complexity of the brain network machinery controlling speech and language remained largely unknown. Using graph theoretical analysis of functional MRI (fMRI) data in healthy subjects, we quantified the large-scale speech network topology by constructing functional brain networks of increasing hierarchy from the resting state to motor output of meaningless syllables to complex production of real-life speech as well as compared to non-speech-related sequential finger tapping and pure tone discrimination networks. We identified a segregated network of highly connected local neural communities (hubs) in the primary sensorimotor and parietal regions, which formed a commonly shared core hub network across the examined conditions, with the left area 4p playing an important role in speech network organization. These sensorimotor core hubs exhibited features of flexible hubs based on their participation in several functional domains across different networks and ability to adaptively switch long-range functional connectivity depending on task content, resulting in a distinct community structure of each examined network. Specifically, compared to other tasks, speech production was characterized by the formation of six distinct neural communities with specialized recruitment of the prefrontal cortex, insula, putamen, and thalamus, which collectively forged the formation of the functional speech connectome. In addition, the observed capacity of the primary sensorimotor cortex to exhibit operational heterogeneity challenged the established concept of unimodality of this region.

This study uses graph theory to analyze functional MRI data recorded from speakers as they produce single syllables or whole sentences, revealing the complexity of the brain network machinery that controls speech and language.

Speech production is a complex process that requires the orchestration of multiple brain regions. However, our current understanding of the large-scale neural architecture during speaking remains scant, as research has mostly focused on examining distinct brain circuits involved in distinct aspects of speech control. Here, we performed graph theoretical analyses of functional MRI data acquired from healthy subjects in order to reveal how brain regions relate to one another while speaking. We constructed functional brain networks of increasing hierarchy from rest to simple vocal motor output to the production of real-life speech, and compared these to nonspeech control tasks such as finger tapping and pure tone discrimination. We discovered a specialized network of densely connected sensorimotor regions, which formed a common processing core across all conditions. Specifically, the primary sensorimotor cortex participated in multiple functional domains across different networks and modulated long-range connections depending on task content, which challenges the established concept of low-order unimodal function of this region. Compared to other tasks, speech production was characterized by the formation of six distinct neural communities with specialized recruitment of the prefrontal cortex, insula, putamen, and thalamus, which collectively formed the functional speech connectome.

Establishing task- and modality-dependent dissociations between the semantic and default mode networks

The default mode network (DMN) and semantic network (SN) are two of the most extensively studied systems, and both are increasingly used as clinical biomarkers in neurological studies. There are strong theoretical reasons to assume a relationship between the networks, as well as anatomical evidence that they might rely on overlapping cortical regions, such as the anterior temporal lobe (ATL) or angular gyrus (AG). Despite these strong motivations, the relationship between the two systems has received minimal attention. We directly compared the SN and DMN using a large (n = 69) distortion-corrected functional MRI (fMRI) dataset, spanning a range of semantic and nonsemantic tasks that varied input modality. The results showed that both networks fractionate depending on the semantic nature of the task, stimulus type, modality, and task difficulty. Furthermore, despite recent claims that both AG and ATL are semantic hubs, the two areas responded very differently, with results supporting the role of ATL, but not AG, in semantic representation. Specifically, the left ATL was positively activated for all semantic tasks, but deactivated during nonsemantic task performance. In contrast, the left AG was deactivated for all tasks, with the level of deactivation related to task difficulty. Thus, ATL and AG do not share a common interest in semantic tasks, but, rather, a common "disinterest" in nonsemantic tasks. The implications for the variability in the DMN, its cognitive coherence, and interpretation of resting-state fMRI data are discussed.