Varieties of semantic cognition revealed through simultaneous decomposition of intrinsic brain connectivity and behaviour

Distinguishable neural circuit mechanisms associated with the clinical efficacy of rTMS in aMCI patients

Repetitive transcranial magnetic stimulation is used in early-stage Alzheimer's disease to slow progression, but heterogeneity in response results in different treatment outcomes. The mechanisms underlying this heterogeneity are unclear. This study used resting-state neuroimaging to investigate the variability in episodic memory improvement from angular gyrus repetitive transcranial magnetic stimulation and tracked the neural circuits involved. Thirty-four amnestic mild cognitive impairment patients underwent angular gyrus repetitive transcranial magnetic stimulation (4 weeks, 20 Hz, 100% resting motor threshold) and were divided into high-response and low-response groups based on minimal clinically important differences in auditory verbal learning test scores. Baseline and pre/post-treatment neural circuit activities were compared. Results indicated that the orbital middle frontal gyrus in the orbitofrontal cortex network and the precuneus in the default mode network had higher local activity in the low-response group. After treatment, changes in local and remote connectivity within brain regions of the orbitofrontal cortex, default mode network, visual network, and sensorimotor network showed opposite trends and were related to treatment effects. This suggests that the activity states of brain regions within the orbitofrontal cortex and default mode network could serve as imaging markers for early cognitive compensation in amnestic mild cognitive impairment patients and predict the aftereffects of repetitive transcranial magnetic stimulation response.

Predicting creative behavior using resting-state electroencephalography

Neuroscience research has shown that specific brain patterns can relate to creativity during multiple tasks but also at rest. Nevertheless, the electrophysiological correlates of a highly creative brain remain largely unexplored. This study aims to uncover resting-state networks related to creative behavior using high-density electroencephalography (HD-EEG) and to test whether the strength of functional connectivity within these networks could predict individual creativity in novel subjects. We acquired resting state HD-EEG data from 90 healthy participants who completed a creative behavior inventory. We then employed connectome-based predictive modeling; a machine-learning technique that predicts behavioral measures from brain connectivity features. Using a support vector regression, our results reveal functional connectivity patterns related to high and low creativity, in the gamma frequency band (30-45 Hz). In leave-one-out cross-validation, the combined model of high and low networks predicts individual creativity with very good accuracy (r = 0.36, p = 0.00045). Furthermore, the model's predictive power is established through external validation on an independent dataset (N = 41), showing a statistically significant correlation between observed and predicted creativity scores (r = 0.35, p = 0.02). These findings reveal large-scale networks that could predict creative behavior at rest, providing a crucial foundation for developing HD-EEG-network-based markers of creativity.

Registered report: Age-preserved semantic memory and the CRUNCH effect manifested as differential semantic control networks: An fMRI study

Semantic memory representations are generally well maintained in aging, whereas semantic control is thought to be more affected. To explain this phenomenon, this study tested the predictions of the Compensation-Related Utilization of Neural Circuits Hypothesis (CRUNCH), focusing on task demands in aging as a possible framework. The CRUNCH effect would manifest itself in semantic tasks through a compensatory increase in neural activation in semantic control network regions but only up to a certain threshold of task demands. This study compares 39 younger (20-35 years old) with 39 older participants (60-75 years old) in a triad-based semantic judgment task performed in an fMRI scanner while manipulating task demand levels (low versus high) through semantic distance. In line with the CRUNCH predictions, differences in neurofunctional activation and behavioral performance (accuracy and response times) were expected in younger versus older participants in the low- versus high-demand conditions, which should be manifested in semantic control Regions of Interest (ROIs). Our older participants had intact behavioral performance, as proposed in the literature for semantic memory tasks (maintained accuracy and slower response times (RTs)). Age-invariant behavioral performance in the older group compared to the younger one is necessary to test the CRUNCH predictions. The older adults were also characterized by high cognitive reserve, as our neuropsychological tests showed. Our behavioral results confirmed that our task successfully manipulated task demands: error rates, RTs and perceived difficulty increased with increasing task demands in both age groups. We did not find an interaction between age group and task demand, or a statistically significant difference in activation between the low- and high-demand conditions for either RTs or accuracy. As for brain activation, we did not find the expected age group by task demand interaction, or a significant main effect of task demand. Overall, our results are compatible with some neural activation in the semantic network and the semantic control network, largely in frontotemporoparietal regions. ROI analyses demonstrated significant effects (but no interactions) of task demand in the left and right inferior frontal gyrus, the left posterior middle temporal gyrus, the posterior inferior temporal gyrus and the prefrontal gyrus. Overall, our test did not confirm the CRUNCH predictions.

How the intrinsic functional connectivity patterns of the semantic network support semantic processing

Semantic processing, a core of language comprehension, involves the activation of brain regions dispersed extensively across the frontal, temporal, and parietal cortices that compose the semantic network. To comprehend the functional structure of this semantic network and how it prepares for semantic processing, we investigated its intrinsic functional connectivity (FC) and the relation between this pattern and semantic processing ability in a large sample from the Human Connectome Project (HCP) dataset. We first defined a well-studied brain network for semantic processing, and then we characterized the within-network connectivity (WNC) and the between-network connectivity (BNC) within this network using a voxel-based global brain connectivity (GBC) method based on resting-state functional magnetic resonance imaging (fMRI). The results showed that 97.73% of the voxels in the semantic network displayed considerably greater WNC than BNC, demonstrating that the semantic network is a fairly encapsulated network. Moreover, multiple connector hubs in the semantic network were identified after applying the criterion of WNC > 1 SD above the mean WNC of the semantic network. More importantly, three of these connector hubs (i.e., the left anterior temporal lobe, angular gyrus, and orbital part of the inferior frontal gyrus) were reliably associated with semantic processing ability. Our findings suggest that the three identified regions use WNC as the central mechanism for supporting semantic processing and that task-independent spontaneous connectivity in the semantic network is essential for semantic processing.

Ventral and dorsal aspects of the inferior frontal-occipital fasciculus support verbal semantic access and visually-guided behavioural control

The Inferior Frontal Occipital Fasciculus (IFOF) is a major anterior-to-posterior white matter pathway in the ventral human brain that connects parietal, temporal and occipital regions to frontal cortex. It has been implicated in a range of functions, including language, semantics, inhibition and the control of action. The recent research shows that the IFOF can be sub-divided into a ventral and dorsal branch, but the functional relevance of this distinction, as well as any potential hemispheric differences, are poorly understood. Using DTI tractography, we investigated the involvement of dorsal and ventral subdivisions of the IFOF in the left and right hemisphere in a response inhibition task (Go/No-Go), where the decision to respond or to withhold a prepotent response was made on the basis of semantic or non-semantic aspects of visual inputs. The task also varied the presentation modality (whether concepts were presented as written words or images). The results showed that the integrity of both dorsal and ventral IFOF in the left hemisphere were associated with participants' inhibition performance when the signal to stop was meaningful and presented in the verbal modality. This effect was absent in the right hemisphere. The integrity of dorsal IFOF was also associated with participants' inhibition efficiency in difficult perceptually guided decisions. This pattern of results indicates that left dorsal IFOF is implicated in the domain-general control of visually-guided behaviour, while the left ventral branch might interface with the semantic system to support the control of action when the inhibitory signal is based on meaning.

Task-based activation and resting-state connectivity predict individual differences in semantic capacity for complex semantic knowledge

Our ability to know and access complex factual information has far reaching effects, influencing our scholastic, professional and social lives. Here we employ functional MRI to assess the relationship between individual differences in semantic aptitude in the task-based activation and resting-state functional connectivity. Using psychometric and behavioural measures, we quantified the semantic and executive aptitude of individuals and had them perform a general-knowledge semantic-retrieval task (N = 41) and recorded resting-state data (N = 43). During the semantic-retrieval task, participants accessed general-knowledge facts drawn from four different knowledge-domains (people, places, objects and 'scholastic'). Individuals with greater executive capacity more strongly recruit anterior sections of prefrontal cortex (PFC) and the precuneus, and individuals with lower semantic capacity more strongly activate a posterior section of the dorsomedial PFC (dmPFC). The role of these regions in semantic processing was validated by analysis of independent resting-state data, where increased connectivity between a left anterior PFC and the precuneus predict higher semantic aptitude, and increased connectivity between left anterior PFC and posterior dmPFC predict lower semantic aptitude. Results suggest that coordination between core semantic regions in the precuneus and anterior prefrontal regions associated with executive processes support greater semantic aptitude.

A dorsomedial prefrontal cortex-based dynamic functional connectivity model of rumination

Rumination is a cognitive style characterized by repetitive thoughts about one's negative internal states and is a common symptom of depression. Previous studies have linked trait rumination to alterations in the default mode network, but predictive brain markers of rumination are lacking. Here, we adopt a predictive modeling approach to develop a neuroimaging marker of rumination based on the variance of dynamic resting-state functional connectivity and test it across 5 diverse subclinical and clinical samples (total n = 288). A whole-brain marker based on dynamic connectivity with the dorsomedial prefrontal cortex (dmPFC) emerges as generalizable across the subclinical datasets. A refined marker consisting of the most important features from a virtual lesion analysis further predicts depression scores of adults with major depressive disorder (n = 35). This study highlights the role of the dmPFC in trait rumination and provides a dynamic functional connectivity marker for rumination.

Posterior superior temporal cortex connectivity is related to social communication in toddlers

The second year of life is a time when social communication skills typically develop, but this growth may be slower in toddlers with language delay. In the current study, we examined how brain functional connectivity is related to social communication abilities in a sample of 12-24 month-old toddlers including those with typical development (TD) and those with language delays (LD). We used an a-priori, seed-based approach to identify regions forming a functional network with the left posterior superior temporal cortex (LpSTC), a region associated with language and social communication in older children and adults. Social communication and language abilities were assessed using the Communication and Symbolic Behavior Scales (CSBS) and Mullen Scales of Early Learning. We found a significant association between concurrent CSBS scores and functional connectivity between the LpSTC and the right posterior superior temporal cortex (RpSTC), with greater connectivity between these regions associated with better social communication abilities. However, functional connectivity was not related to rate of change or language outcomes at 36 months of age. These data suggest an early marker of low communication abilities may be decreased connectivity between the left and right pSTC. Future longitudinal studies should test whether this neurobiological feature is predictive of later social or communication impairments.

Uncovering the biological basis of control energy: Structural and metabolic correlates of energy inefficiency in temporal lobe epilepsy

Network control theory is increasingly used to profile the brain's energy landscape via simulations of neural dynamics. This approach estimates the control energy required to simulate the activation of brain circuits based on structural connectome measured using diffusion magnetic resonance imaging, thereby quantifying those circuits' energetic efficiency. The biological basis of control energy, however, remains unknown, hampering its further application. To fill this gap, investigating temporal lobe epilepsy as a lesion model, we show that patients require higher control energy to activate the limbic network than healthy volunteers, especially ipsilateral to the seizure focus. The energetic imbalance between ipsilateral and contralateral temporolimbic regions is tracked by asymmetric patterns of glucose metabolism measured using positron emission tomography, which, in turn, may be selectively explained by asymmetric gray matter loss as evidenced in the hippocampus. Our investigation provides the first theoretical framework unifying gray matter integrity, metabolism, and energetic generation of neural dynamics.

Generalizable predictive modeling of semantic processing ability from functional brain connectivity

Semantic processing (SP) is one of the critical abilities of humans for representing and manipulating conceptual and meaningful information. Neuroimaging studies of SP typically collapse data from many subjects, but its neural organization and behavioral performance vary between individuals. It is not yet understood whether and how the individual variabilities in neural network organizations contribute to the individual differences in SP behaviors. We aim to identify the neural signatures underlying SP variabilities by analyzing functional connectivity (FC) patterns based on a large‐sample Human Connectome Project (HCP) dataset and rigorous predictive modeling. We used a two‐stage predictive modeling approach to build an internally cross‐validated model and to test the model's generalizability with unseen data from different HCP samples and other out‐of‐sample datasets. FC patterns within a putative semantic brain network were significantly predictive of individual SP scores summarized from five SP‐related behavioral tests. This cross‐validated model can be used to predict unseen HCP data. The model generalizability was enhanced in the language task compared with other tasks used during scanning and was better for females than males. The model constructed from the HCP dataset can be partially generalized to two independent cohorts that participated in different semantic tasks. FCs connecting to the Perisylvian language network show the most reliable contributions to predictive modeling and the out‐of‐sample generalization. These findings contribute to our understanding of the neural sources of individual differences in SP, which potentially lay the foundation for personalized education for healthy individuals and intervention for SP and language deficits patients.

OUP accepted manuscript

Working memory (WM) allows goal-relevant information to be encoded and maintained in mind, even when the contents of WM are incongruent with the immediate environment. While regions of heteromodal cortex are important for WM, the neural mechanisms that relate to individual differences in the encoding and maintenance of goal-relevant information remain unclear. Here, we used behavioral correlates of two large-scale heteromodal networks at rest, the default mode (DMN) and frontoparietal (FPN) networks, to understand their contributions to distinct features of WM. We assessed each individual’s ability to resist distracting information during the encoding and maintenance phases of a visuospatial WM task. Individuals with stronger connectivity of DMN with medial visual and retrosplenial cortex were less affected by encoding distraction. Conversely, weaker connectivity of both DMN and FPN with visual regions was associated with better WM performance when target information was no longer in the environment and distractors were presented in the maintenance phase. Our study suggests that stronger coupling between heteromodal cortex and visual–spatial regions supports WM encoding by reducing the influence of concurrently presented distractors, while weaker visual coupling is associated with better maintenance of goal-relevant information because it relates to the capacity to ignore task-irrelevant changes in the environment.

EEG functional brain connectivity strengthens with age during attentional processing to faces in children

Studying functional connectivity may generate clues to the maturational changes that occur in children, expressed by the dynamical organization of the functional network assessed by electroencephalographic recordings (EEG). In the present study, we compared the EEG functional connectivity pattern estimated by linear cross-correlations of the electrical brain activity of three groups of children (6, 8, and 10 years of age) while performing odd-ball tasks containing facial stimuli that are chosen considering their importance in socioemotional contexts in everyday life. On the first task, the children were asked to identify the sex of faces, on the second, the instruction was to identify the happy expressions of the faces. We estimated the stable correlation pattern (SCP) by the average cross-correlation matrix obtained separately for the resting state and the task conditions and quantified the similarity of these average matrices comparing the different conditions. The accuracy improved with higher age. Although the topology of the SCPs showed high similarity across all ages, the two older groups showed a higher correlation between regions associated with the attentional and face processing networks compared to the youngest group. Only in the youngest group, the similarity metric decreased during the sex condition. In general, correlation values strengthened with age and during task performance compared to rest. Our findings indicate that there is a spatially extended stable brain network organization in children like that reported in adults. Lower similarity scores between several regions in the youngest children might indicate a lesser ability to cope with tasks. The brain regions associated with the attention and face networks presented higher synchronization across regions with increasing age, modulated by task demands.

Intrinsic connectivity of left ventrolateral prefrontal cortex predicts individual differences in controlled semantic retrieval

Control processes allow us to constrain the retrieval of semantic information from long-term memory so that it is appropriate for the task or context. Control demands are influenced by the strength of the target information itself and by the circumstances in which it is retrieved, with more control needed when relatively weak aspects of knowledge are required and after the sustained retrieval of related concepts. To investigate the neurocognitive basis of individual differences in these aspects of semantic control, we used resting-state fMRI to characterise the intrinsic connectivity of left ventrolateral prefrontal cortex (VLPFC), implicated in controlled retrieval, and examined associations on a paced serial semantic task, in which participants were asked to detect category members amongst distractors. This task manipulated both the strength of target associations and the requirement to sustain retrieval within a narrow semantic category over time. We found that individuals with stronger connectivity between VLPFC and medial prefrontal cortex within the default mode network (DMN) showed better retrieval of strong associations (which are thought to be recalled more automatically). Stronger connectivity between the same VLPFC seed and another DMN region in medial parietal cortex was associated with larger declines in retrieval over the course of the category. In contrast, participants with stronger connectivity between VLPFC and cognitive control regions within the ventral attention network (VAN) had better controlled retrieval of weak associations and were better able to sustain their comprehension throughout the category. These effects overlapped in left insular cortex within the VAN, indicating that a common pattern of connectivity is associated with different aspects of controlled semantic retrieval induced by both the structure of long-term knowledge and the sustained retrieval of related information.

Pubertal timing and functional neurodevelopmental alterations independently mediate the effect of family conflict on adolescent psychopathology

This study tested the hypothesis that early life adversity (ELA) heightens psychopathology risk by concurrently altering pubertal and neurodevelopmental timing, and associated gene transcription signatures. Analyses focused on threat- (family conflict/neighbourhood crime) and deprivation-related ELAs (parental inattentiveness/unmet material needs), using longitudinal data from 1514 biologically unrelated youths in the Adolescent Brain and Cognitive Development (ABCD) study. Typical developmental changes in white matter microstructure corresponded to widespread BOLD signal variability (BOLDsv) increases (linked to cell communication and biosynthesis genes) and region-specific task-related BOLDsv increases/decreases (linked to signal transduction, immune and external environmental response genes). Increasing resting-state (RS), but decreasing task-related BOLDsv predicted normative functional network segregation. Family conflict was the strongest concurrent and prospective contributor to psychopathology, while material deprivation constituted an additive risk factor. ELA-linked psychopathology was predicted by higher Time 1 threat-evoked BOLDSV (associated with axonal development, myelination, cell differentiation and signal transduction genes), reduced Time 2 RS BOLDsv (associated with cell metabolism and attention genes) and greater Time 1 to Time 2 control/attention network segregation. Earlier pubertal timing and neurodevelopmental alterations independently mediated ELA effects on psychopathology. Our results underscore the differential roles of the immediate and wider external environment(s) in concurrent and longer-term ELA consequences.

Impaired emotion perception and categorization in semantic aphasia

According to a constructionist model of emotion, conceptual knowledge plays a foundational role in emotion perception; reduced availability of relevant conceptual knowledge should therefore impair emotion perception. Conceptual deficits can follow both degradation of semantic knowledge (e.g., semantic 'storage' deficits in semantic dementia) and deregulation of retrieval (e.g., semantic 'access' deficits in semantic aphasia). While emotion recognition deficits are known to accompany degraded conceptual knowledge, less is known about the impact of semantic access deficits. Here, we examined emotion perception and categorization tasks in patients with semantic aphasia, who have difficulty accessing semantic information in a flexible and controlled fashion following left hemisphere stroke. In Study 1, participants were asked to sort faces according to the emotion they portrayed - with numbers, written labels and picture examples each provided as category anchors across tasks. Semantic aphasia patients made more errors and showed a larger benefit from word anchors that reduced the need to internally constrain categorization than comparison participants. They successfully sorted portrayals that differed in valence (positive vs. negative) but had difficulty categorizing different negative emotions. They were unimpaired on a control task that involved sorting faces by identity. In Study 2, participants matched facial emotion portrayals to written labels following vocal emotion prosody cues, miscues, or no cues. Patients presented with overall poorer performance and benefited from cue trials relative to within-valence miscue trials. This same effect was seen in comparison participants, who also showed deleterious effects of within-valence miscue relative to no cue trials. Overall, we found that patients with deregulated semantic retrieval have deficits in emotional perception but that word anchors and cue conditions can facilitate emotion perception by increasing access to relevant emotion concepts and reducing reliance on semantic control. Semantic control may be of particular importance in emotion perception when it is necessary to interpret ambiguous inputs, or when there is interference between conceptually similar emotional states. These findings extend constructionist accounts of emotion to encompass difficulties in controlled semantic retrieval.

A tale of two gradients: differences between the left and right hemispheres predict semantic cognition

Decomposition of whole-brain functional connectivity patterns reveals a principal gradient that captures the separation of sensorimotor cortex from heteromodal regions in the default mode network (DMN). Functional homotopy is strongest in sensorimotor areas, and weakest in heteromodal cortices, suggesting there may be differences between the left and right hemispheres (LH/RH) in the principal gradient, especially towards its apex. This study characterised hemispheric differences in the position of large-scale cortical networks along the principal gradient, and their functional significance. We collected resting-state fMRI and semantic, working memory and non-verbal reasoning performance in 175 + healthy volunteers. We then extracted the principal gradient of connectivity for each participant, tested which networks showed significant hemispheric differences on the gradient, and regressed participants’ behavioural efficiency in tasks outside the scanner against interhemispheric gradient differences for each network. LH showed a higher overall principal gradient value, consistent with its role in heteromodal semantic cognition. One frontotemporal control subnetwork was linked to individual differences in semantic cognition: when it was nearer heteromodal DMN on the principal gradient in LH, participants showed more efficient semantic retrieval—and this network also showed a strong hemispheric difference in response to semantic demands but not working memory load in a separate study. In contrast, when a dorsal attention subnetwork was closer to the heteromodal end of the principal gradient in RH, participants showed better visual reasoning. Lateralization of function may reflect differences in connectivity between control and heteromodal regions in LH, and attention and visual regions in RH.

Network Analysis of Human Brain Connectivity Reveals Neural Fingerprints of a Compositionality Bias in Signaling Systems

Compositionality is a hallmark of human language and other symbolic systems: a finite set of meaningful elements can be systematically combined to convey an open-ended array of ideas. Compositionality is not uniformly distributed over expressions in a language or over individuals' communicative behavior: at both levels, variation is observed. Here, we investigate the neural bases of interindividual variability by probing the relationship between intrinsic characteristics of brain networks and compositional behavior. We first collected functional resting-state and diffusion magnetic resonance imaging data from a large participant sample (N = 51). Subsequently, participants took part in two signaling games. They were instructed to learn and reproduce an auditory symbolic system of signals (tone sequences) associated with affective meanings (human faces expressing emotions). Signal-meaning mappings were artificial and had to be learned via repeated signaling interactions. We identified a temporoparietal network in which connection length was related to the degree of compositionality introduced in a signaling system by each player. Graph-theoretic analysis of resting-state functional connectivity revealed that, within that network, compositional behavior was associated with integration measures in 2 semantic hubs: the left posterior cingulate cortex and the left angular gyrus. Our findings link individual variability in compositional biases to variation in the anatomy of semantic networks and in the functional topology of their constituent units.

Stimulus-independent neural coding of event semantics: Evidence from cross-sentence fMRI decoding

Multivariate neuroimaging studies indicate that the brain represents word and object concepts in a format that readily generalises across stimuli. Here we investigated whether this was true for neural representations of simple events described using sentences. Participants viewed sentences describing four events in different ways. Multivariate classifiers were trained to discriminate the four events using a subset of sentences, allowing us to test generalisation to novel sentences. We found that neural patterns in a left-lateralised network of frontal, temporal and parietal regions discriminated events in a way that generalised successfully over changes in the syntactic and lexical properties of the sentences used to describe them. In contrast, decoding in visual areas was sentence-specific and failed to generalise to novel sentences. In the reverse analysis, we tested for decoding of syntactic and lexical structure, independent of the event being described. Regions displaying this coding were limited and largely fell outside the canonical semantic network. Our results indicate that a distributed neural network represents the meaning of event sentences in a way that is robust to changes in their structure and form. They suggest that the semantic system disregards the surface properties of stimuli in order to represent their underlying conceptual significance.

Age-preserved semantic memory and the CRUNCH effect manifested as differential semantic control networks: An fMRI study

Semantic memory representations are overall well-maintained in aging whereas semantic control is thought to be more affected. To explain this phenomenon, this study aims to test the predictions of the Compensation Related Utilization of Neural Circuits Hypothesis (CRUNCH) focusing on task demands in aging as a possible framework. The CRUNCH effect would manifest itself in semantic tasks through a compensatory increase in neural activation in semantic control network regions but only up to a certain threshold of task demands. This study will compare 40 young (20-35 years old) with 40 older participants (60-75 years old) in a triad-based semantic judgment task performed in an fMRI scanner while manipulating levels of task demands (low vs. high) through semantic distance. In line with the CRUNCH predictions, differences in neurofunctional activation and behavioral performance (accuracy and response times) are expected in young vs. old participants in the low- vs. high-demand conditions manifested in semantic control Regions of Interest.

Brain-environment alignment during movie watching predicts fluid intelligence and affective function in adulthood

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Functional brain connectivity (FC) patterns vary with changes in the environment.

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Adult FC variability is linked to age-specific network communication profiles.

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Across adulthood, the younger network interaction profile predicts higher fluid IQ.

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Yoked FC-concrete environmental changes predict poorer fluid IQ and anxiety.

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Brain areas linked to episodic memory underpin FC changes at multiple timescales.

BOLD fMRI studies have provided compelling evidence that the human brain demonstrates substantial moment-to-moment fluctuations in both activity and functional connectivity (FC) patterns. While the role of brain signal variability in fostering cognitive adaptation to ongoing environmental demands is well-documented, the relevance of moment-to-moment changes in FC patterns is still debated. Here, we adopt a graph theoretical approach in order to shed light on the cognitive-affective implications of FC variability and associated profiles of functional network communication in adulthood. Our goal is to identify brain communication pathways underlying FC reconfiguration at multiple timescales, thereby improving understanding of how faster perceptually bound versus slower conceptual processes shape neural tuning to the dynamics of the external world and, thus, indirectly, mold affective and cognitive responding to the environment. To this end, we used neuroimaging and behavioural data collected during movie watching by the Cambridge Center for Ageing and Neuroscience (N = 642, 326 women) and the Human Connectome Project (N = 176, 106 women). FC variability evoked by changes to both the concrete perceptual and the more abstract conceptual representation of an ongoing situation increased from young to older adulthood. However, coupling between variability in FC patterns and concrete environmental features was stronger at younger ages. FC variability (both moment-to-moment/concrete featural and abstract conceptual boundary-evoked) was associated with age-distinct profiles of network communication, specifically, greater functional integration of the default mode network in older adulthood, but greater informational flow across neural networks implicated in environmentally driven attention and control (cingulo-opercular, salience, ventral attention) in younger adulthood. Whole-brain communication pathways anchored in default mode regions relevant to episodic and semantic context creation (i.e., angular and middle temporal gyri) supported FC reconfiguration in response to changes in the conceptual representation of an ongoing situation (i.e., narrative event boundaries), as well as stronger coupling between moment-to-moment fluctuations in FC and concrete environmental features. Fluid intelligence/abstract reasoning was directly linked to levels of brain-environment alignment, but only indirectly associated with levels of FC variability. Specifically, stronger coupling between moment-to-moment FC variability and concrete environmental features predicted poorer fluid intelligence and greater affectively driven environmental vigilance. Complementarily, across the adult lifespan, higher fluid (but not crystallised) intelligence was related to stronger expression of the network communication profile underlying momentary and event boundary-based FC variability during youth. Our results indicate that the adaptiveness of dynamic FC reconfiguration during naturalistic information processing changes across the lifespan due to the associated network communication profiles. Moreover, our findings on brain-environment alignment complement the existing literature on the beneficial consequences of modulating brain signal variability in response to environmental complexity. Specifically, they imply that coupling between moment-to-moment FC variability and concrete environmental features may index a bias towards perceptually-bound, rather than conceptual processing, which hinders affective functioning and strategic cognitive engagement with the external environment.

Varying demands for cognitive control reveals shared neural processes supporting semantic and episodic memory retrieval

The categorisation of long-term memory into semantic and episodic systems has been an influential catalyst for research on human memory organisation. However, the impact of variable cognitive control demands on this classical distinction remains to be elucidated. Across two independent experiments, here we directly compare neural processes for the controlled versus automatic retrieval of semantic and episodic memory. In a multi-session functional magnetic resonance imaging experiment, we first identify a common cluster of cortical activity centred on the left inferior frontal gyrus and anterior insular cortex for the retrieval of both weakly-associated semantic and weakly-encoded episodic memory traces. In an independent large-scale individual difference study, we further reveal a common neural circuitry in which reduced functional interaction between the identified cluster and ventromedial prefrontal cortex, a default mode network hub, is linked to better performance across both memory types. Our results provide evidence for shared neural processes supporting the controlled retrieval of information from functionally distinct long-term memory systems.

Making sense of the world around us often requires flexible access to information from both semantic and episodic memory systems. Here, the authors show that controlled retrieval from functionally distinct long-term memory stores is supported by shared neural processes in the human brain.

The neural correlates of ongoing conscious thought

A core goal in cognitive neuroscience is identifying the physical substrates of the patterns of thought that occupy our daily lives. Contemporary views suggest that the landscape of ongoing experience is heterogeneous and can be influenced by features of both the person and the context. This perspective piece considers recent work that explicitly accounts for both the heterogeneity of the experience and context dependence of patterns of ongoing thought. These studies reveal that systems linked to attention and control are important for organizing experience in response to changing environmental demands. These studies also establish a role of the default mode network beyond task-negative or purely episodic content, for example, implicating it in the level of vivid detail in experience in both task contexts and in spontaneous self-generated experiential states. Together, this work demonstrates that the landscape of ongoing thought is reflected in the activity of multiple neural systems, and it is important to distinguish between processes contributing to how the experience unfolds from those linked to how these experiences are regulated.

Knowing what you need to know in advance: The neural processes underpinning flexible semantic retrieval of thematic and taxonomic relations

Semantic retrieval is flexible, allowing us to focus on subsets of features and associations that are relevant to the current task or context: for example, we use taxonomic relations to locate items in the supermarket (carrots are a vegetable), but thematic associations to decide which tools we need when cooking (carrot goes with peeler). We used fMRI to investigate the neural basis of this form of semantic flexibility; in particular, we asked how retrieval unfolds differently when participants have advanced knowledge of the type of link to retrieve between concepts (taxonomic or thematic). Participants performed a semantic relatedness judgement task: on half the trials, they were cued to search for a taxonomic or thematic link, while on the remaining trials, they judged relatedness without knowing which type of semantic relationship would be relevant. Left inferior frontal gyrus showed greater activation when participants knew the trial type in advance. An overlapping region showed a stronger response when the semantic relationship between the items was weaker, suggesting this structure supports both top-down and bottom-up forms of semantic control. Multivariate pattern analysis further revealed that the neural response in left inferior frontal gyrus reflects goal information related to different conceptual relationships. Top-down control specifically modulated the response in visual cortex: when the goal was unknown, there was greater deactivation to the first word, and greater activation to the second word. We conclude that top-down control of semantic retrieval is primarily achieved through the gating of task-relevant 'spoke' regions.

Interactions between the neural correlates of dispositional internally directed thought and visual imagery

Cognition is not always directed to the events in the here and now and we often self-generate thoughts and images in imagination. Important aspects of these self-generated experiences are associated with various dispositional traits. In this study, we explored whether these psychological associations relate to a common underlying neurocognitive mechanism. We acquired resting state functional magnetic resonance imaging data from a large cohort of participants and asked them to retrospectively report their experience during the scan. Participants also completed questionnaires reflecting a range of dispositional traits. We found thoughts emphasizing visual imagery at rest were associated with dispositional tendency towards internally directed attention (self-consciousness and attentional problems) and linked to a stronger correlation between a posterior parietal network and a lateral fronto-temporal network. Furthermore, decoupling between the brainstem and a lateral visual network was associated with dispositional internally directed attention. Critically, these brain-cognition associations were related: the correlation between parietal-frontal regions and reports of visual imagery was stronger for individuals with increased connectivity between brainstem and visual cortex. Our results highlight neural mechanisms linked to the dispositional basis for patterns of self-generated thought, and suggest that accounting for dispositional traits is important when exploring the neural substrates of self-generated experience (and vice versa). This article is part of the theme issue 'Offline perception: voluntary and spontaneous perceptual experiences without matching external stimulation'.

Functional Connectivity of Successful Picture-Naming: Age-Specific Organization and the Effect of Engaging in Stimulating Activities

Aging is a lifelong process that starts at birth. Throughout the course of their life, individuals are exposed to various levels of stimulating activities. A higher level of engagement in such activities is suspected to protect against the normal course of cognitive aging or the cognitive manifestations of age-related brain diseases. However, the exact mechanism underlying such protective action remains unclear. The concept of the neurocognitive reserve was introduced to refer to the hypothesis that engagement in stimulating activities shapes brain structure and function, thus indirectly allowing for better preserved cognitive abilities. Although it is known that word production is among the best-preserved cognitive abilities in aging, the underlying neurofunctional mechanisms that allow this relative preservation are still unknown, and it is still unclear how engagement in stimulating activities affects these processes. The objective of this study is to describe the brain functional connectivity patterns associated with picture-naming abilities in younger and older adults with varying levels of engagement in stimulating activities, as a proxy for neurocognitive reserve. A mediation analysis was applied to determine whether the association between reserve proxies and naming accuracy is dependent on task FC. Results show that naming accuracy depends on the posterior cingulate cortex (PCC) functional decoupling in both younger and older adults but through different pathways. While high-performing older adults rely on the asynchronization of this area from motor speech regions’ activity, the best-performing younger adults rely on the functional decoupling with language-related regions. Mediation analysis reveals that the PCC decoupling mediates the relationship between the level of engagement in stimulating activities and naming accuracy in younger adults, but not in older adults. These findings suggest that reserve-related mechanisms may be more critical for naming in early adult life, while older adults’ neurofunctional organization may benefit more from a lifetime of acquired knowledge.

Intrinsic connectivity of anterior temporal lobe relates to individual differences in semantic retrieval for landmarks

Contemporary neuroscientific accounts suggest that ventral anterior temporal lobe (ATL) acts as a bilateral heteromodal semantic hub, which is particularly critical for the specific-level knowledge needed to recognise unique entities, such as familiar landmarks and faces. There may also be graded functional differences between left and right ATL, relating to effects of modality (linguistic versus non-linguistic) and category (e.g., knowledge of people and places). Individual differences in intrinsic connectivity from left and right ATL might be associated with variation in semantic categorisation performance across these categories and modalities. We recorded resting-state fMRI in 74 individuals and, in a separate session, examined semantic categorisation. People with greater connectivity between left and right ATL were more efficient at categorising landmarks (e.g., Eiffel Tower), especially when these were presented visually. In addition, participants who showed stronger connectivity from right than left ATL to medial occipital cortex showed more efficient semantic categorisation of landmarks regardless of modality of presentation. These results can be interpreted in terms of graded differences in the patterns of connectivity across left and right ATL, which give rise to a bilateral yet partially segregated semantic 'hub'. More specifically, right ATL connectivity supports the efficient semantic categorisation of landmarks.

A gradient from long-term memory to novel cognition: Transitions through default mode and executive cortex

Human cognition flexibly guides decision-making in familiar and novel situations. Although these decisions are often treated as dichotomous, in reality, situations are neither completely familiar, nor entirely new. Contemporary accounts of brain organization suggest that neural function is organized along a connectivity gradient from unimodal regions of sensorimotor cortex, through executive regions to transmodal default mode network. We examined whether this graded view of neural organization helps to explain how decision-making changes across situations that vary in their alignment with long-term knowledge. We used a semantic judgment task, which parametrically varied the global semantic similarity of items within a feature matching task to create a 'task gradient', from conceptual combinations that were highly overlapping in long-term memory to trials that only shared the goal-relevant feature. We found the brain's response to the task gradient varied systematically along the connectivity gradient, with the strongest response in default mode network when the probe and target items were highly overlapping conceptually. This graded functional change was seen in multiple brain regions and within individual brains, and was not readily explained by task difficulty. Moreover, the gradient captured the spatial layout of networks involved in semantic processing, providing an organizational principle for controlled semantic cognition across the cortex. In this way, the cortex is organized to support semantic decision-making in both highly familiar and less familiar situations.

Missing the forest because of the trees: slower alternations during binocular rivalry are associated with lower levels of visual detail during ongoing thought

Conscious awareness of the world fluctuates, either through variation in how vividly we perceive the environment, or when our attentional focus shifts away from information in the external environment towards information that we generate via imagination. Our study combined individual differences in experience sampling, psychophysical reports of perception and neuroimaging descriptions of structural connectivity to better understand these changes in conscious awareness. In particular, we examined (i) whether aspects of ongoing thought—indexed via multi-dimensional experience sampling during a sustained attention task—are associated with the white matter fibre organization of the cortex as reflected by their relative degree of anisotropic diffusion and (ii) whether these neurocognitive descriptions of ongoing experience are related to a more constrained measure of visual consciousness through analysis of bistable perception during binocular rivalry. Individuals with greater fractional anisotropy in right hemisphere white matter regions involving the inferior fronto-occipital fasciculus, the superior longitudinal fasciculus and the cortico-spinal tract, described their ongoing thoughts as lacking external details. Subsequent analysis indicated that the combination of low fractional anisotropy in these right hemisphere regions, with reports of thoughts with high levels of external details, was associated with the shortest periods of dominance during binocular rivalry. Since variation in binocular rivalry reflects differences between bottom-up and top-down influences on vision, our study suggests that reports of ongoing thoughts with vivid external details may occur when conscious precedence is given to bottom-up representation of perceptual information.

A technical review of canonical correlation analysis for neuroscience applications

Collecting comprehensive data sets of the same subject has become a standard in neuroscience research and uncovering multivariate relationships among collected data sets have gained significant attentions in recent years. Canonical correlation analysis (CCA) is one of the powerful multivariate tools to jointly investigate relationships among multiple data sets, which can uncover disease or environmental effects in various modalities simultaneously and characterize changes during development, aging, and disease progressions comprehensively. In the past 10 years, despite an increasing number of studies have utilized CCA in multivariate analysis, simple conventional CCA dominates these applications. Multiple CCA-variant techniques have been proposed to improve the model performance; however, the complicated multivariate formulations and not well-known capabilities have delayed their wide applications. Therefore, in this study, a comprehensive review of CCA and its variant techniques is provided. Detailed technical formulation with analytical and numerical solutions, current applications in neuroscience research, and advantages and limitations of each CCA-related technique are discussed. Finally, a general guideline in how to select the most appropriate CCA-related technique based on the properties of available data sets and particularly targeted neuroscience questions is provided.

Neurocognitive patterns dissociating semantic processing from executive control are linked to more detailed off-task mental time travel

Features of ongoing experience are common across individuals and cultures. However, certain people express specific patterns of thought to a greater extent than others. Contemporary psychological theory assumes that individual differences in thought patterns occur because different types of experience depend on the expression of different neurocognitive processes. Consequently, individual variation in the underlying neurocognitive architecture is hypothesised to determine the ease with which certain thought patterns are generated or maintained. Our study (N = 178) tested this hypothesis using multivariate pattern analysis to infer shared variance among measures of cognitive function and neural organisation and examined whether these latent variables explained reports of the patterns of on-going thoughts people experienced in the lab. We found that relatively better performance on tasks relying primarily on semantic knowledge, rather than executive control, was linked to a neural functional organisation associated, via meta-analysis, with task labels related to semantic associations (sentence processing, reading and verbal semantics). Variability of this functional mode predicted significant individual variation in the types of thoughts that individuals experienced in the laboratory: neurocognitive patterns linked to better performance at tasks that required guidance from semantic representation, rather than those dependent on executive control, were associated with patterns of thought characterised by greater subjective detail and a focus on time periods other than the here and now. These relationships were consistent across different days and did not vary with level of task demands, indicating they are relatively stable features of an individual’s cognitive profile. Together these data confirm that individual variation in aspects of ongoing experience can be inferred from hidden neurocognitive architecture and demonstrate that performance trade-offs between executive control and long-term semantic knowledge are linked to a person’s tendency to imagine situations that transcend the here and now.

Approaches to Defining Common and Dissociable Neurobiological Deficits Associated With Psychopathology in Youth

Psychiatric disorders show high rates of comorbidity and nonspecificity of presenting clinical symptoms, while demonstrating substantial heterogeneity within diagnostic categories. Notably, many of these psychiatric disorders first manifest in youth. We review progress and next steps in efforts to parse heterogeneity in psychiatric symptoms in youths by identifying abnormalities within neural circuits. To address this fundamental challenge in psychiatry, a number of methods have been proposed. We provide an overview of these methods, broadly organized into dimensional versus categorical approaches and single-view versus multiview approaches. Dimensional approaches including factor analysis and canonical correlation analysis aim to capture dimensional associations between psychopathology and brain measures across a continuous spectrum from health to disease. In contrast, categorical approaches, such as clustering and community detection, aim to identify subtypes of individuals within a class of symptoms or brain features. We highlight several studies that apply these methods to samples of youths and discuss issues to consider when using these approaches. Finally, we end by highlighting avenues for future research.

Distinct patterns of thought mediate the link between brain functional connectomes and well-being

Ongoing thought patterns constitute important aspects of both healthy and abnormal human cognition. However, the neural mechanisms behind these daily experiences and their contribution to well-being remain a matter of debate. Here, using resting-state fMRI and retrospective thought sampling in a large neurotypical cohort (n = 211), we identified two distinct patterns of thought, broadly describing the participants' current concerns and future plans, that significantly explained variability in the individual functional connectomes. Consistent with the view that ongoing thoughts are an emergent property of multiple neural systems, network-based analysis highlighted the central importance of both unimodal and transmodal cortices in the generation of these experiences. Importantly, while state-dependent current concerns predicted better psychological health, mediating the effect of functional connectomes, trait-level future plans were related to better social health, yet with no mediatory influence. Collectively, we show that ongoing thoughts can influence the link between brain physiology and well-being.

The Neural Dynamics of Individual Differences in Episodic Autobiographical Memory

The ability to mentally travel to specific events from one's past, dubbed episodic autobiographical memory (E-AM), contributes to adaptive functioning. Nonetheless, the mechanisms underlying its typical interindividual variation remain poorly understood. To address this issue, we capitalize on existing evidence that successful performance on E-AM tasks draws on the ability to visualize past episodes and reinstate their unique spatiotemporal context. Hence, here, we test whether features of the brain's functional architecture relevant to perceptual versus conceptual processes shape individual differences in both self-rated E-AM and laboratory-based episodic memory (EM) for random visual scene sequences (visual EM). We propose that superior subjective E-AM and visual EM are associated with greater similarity in static neural organization patterns, potentially indicating greater efficiency in switching, between rest and mental states relevant to encoding perceptual information. Complementarily, we postulate that impoverished subjective E-AM and visual EM are linked to dynamic brain organization patterns implying a predisposition towards semanticizing novel perceptual information. Analyses were conducted on resting state and task-based fMRI data from 329 participants (160 women) in the Human Connectome Project (HCP) who completed visual and verbal EM assessments, and an independent gender diverse sample (N = 59) who self-rated their E-AM. Interindividual differences in subjective E-AM were linked to the same neural mechanisms underlying visual, but not verbal, EM, in general agreement with the hypothesized static and dynamic brain organization patterns. Our results suggest that higher E-AM entails more efficient processing of temporally extended information sequences, whereas lower E-AM entails more efficient semantic or gist-based processing.

Finding the needle in a high-dimensional haystack: Canonical correlation analysis for neuroscientists

The 21st century marks the emergence of "big data" with a rapid increase in the availability of datasets with multiple measurements. In neuroscience, brain-imaging datasets are more commonly accompanied by dozens or hundreds of phenotypic subject descriptors on the behavioral, neural, and genomic level. The complexity of such "big data" repositories offer new opportunities and pose new challenges for systems neuroscience. Canonical correlation analysis (CCA) is a prototypical family of methods that is useful in identifying the links between variable sets from different modalities. Importantly, CCA is well suited to describing relationships across multiple sets of data, such as in recently available big biomedical datasets. Our primer discusses the rationale, promises, and pitfalls of CCA.

Linking individual differences in semantic cognition to white matter microstructure

Semantic cognition is thought to involve the interaction of heteromodal conceptual representations with control processes that (i) focus retrieval on currently-relevant information, and (ii) suppress dominant yet irrelevant features and associations. Research suggests that semantic control demands are higher when retrieving a link between weakly-associated word pairs, since there is a mismatch between the pattern of semantic retrieval required by the task and the dominant associations of individual words. In addition, given that heteromodal concepts are thought to reflect the integration of vision, audition, valence and other features, the control demands of semantic tasks should be higher when there is less consistency between these features. In the present study, 62 volunteers completed a semantic decision task, where association strength and semantic-affective congruence were manipulated. We used diffusion tensor magnetic resonance imaging to obtain fractional anisotropy (FA) measures of white matter tracts hypothesized to be part of the semantic network. The behavioural data revealed an interaction between semantic-affective congruence and strength of association, suggesting these manipulations both contribute to semantic control demands. Next we considered how individual differences in these markers of semantic control relate to the microstructure of canonical white matter tracts, complementing previous studies that have largely focused on measures of intrinsic functional connectivity. Repeated-measures analysis of covariance showed opposing interactions between semantic control markers and FA of two tracts: left inferior longitudinal fasciculus (ILF) and right inferior fronto-occipital fasciculus (IFOF). Participants with higher FA in left ILF showed more efficient retrieval of weak associations, and more accurate performance for weak associations when meaning and valence were incongruent, consistent with the hypothesis that this left hemisphere tract supports semantic control. In contrast, participants with higher FA in right IFOF were more accurate for trials in which meaning and valence were congruent, and consequently when semantic control demands were minimised. These findings are consistent with recent studies showing that semantic control processes are strongly left-lateralised. In contrast, long-range connections from vision to semantic regions in the right hemisphere might support relatively automatic patterns of semantic retrieval.

Distinct individual differences in default mode network connectivity relate to off-task thought and text memory during reading

Often, as we read, we find ourselves thinking about something other than the text; this tendency to mind-wander is linked to poor comprehension and reduced subsequent memory for texts. Contemporary accounts argue that periods of off-task thought are related to the tendency for attention to be decoupled from external input. We used fMRI to understand the neural processes that underpin this phenomenon. First, we found that individuals with poorer text-based memory tend to show reduced recruitment of left middle temporal gyrus in response to orthographic input, within a region located at the intersection of default mode, dorsal attention and frontoparietal networks. Voxels within these networks were taken as seeds in a subsequent resting-state study. The default mode network region (i) had greater connectivity with medial prefrontal cortex, falling within the same network, for individuals with better text-based memory, and (ii) was more decoupled from medial visual regions in participants who mind-wandered more frequently. These findings suggest that stronger intrinsic connectivity within the default mode network is linked to better text processing, while reductions in default mode network coupling to the visual system may underpin individual variation in the tendency for our attention to become disengaged from what we are reading.

Imagining Sounds and Images: Decoding the Contribution of Unimodal and Transmodal Brain Regions to Semantic Retrieval in the Absence of Meaningful Input

In the absence of sensory information, we can generate meaningful images and sounds from representations in memory. However, it remains unclear which neural systems underpin this process and whether tasks requiring the top–down generation of different kinds of features recruit similar or different neural networks. We asked people to internally generate the visual and auditory features of objects, either in isolation (car, dog) or in specific and complex meaning-based contexts (car/dog race). Using an fMRI decoding approach, in conjunction with functional connectivity analysis, we examined the role of auditory/visual cortex and transmodal brain regions. Conceptual retrieval in the absence of external input recruited sensory and transmodal cortex. The response in transmodal regions—including anterior middle temporal gyrus—was of equal magnitude for visual and auditory features yet nevertheless captured modality information in the pattern of response across voxels. In contrast, sensory regions showed greater activation for modality-relevant features in imagination (even when external inputs did not differ). These data are consistent with the view that transmodal regions support internally generated experiences and that they play a role in integrating perceptual features encoded in memory.

Distinct neural response to visual perspective and body size in the extrastriate body area

Neuroimaging research has independently implicated the extrastriate body area (EBA) in distinguishing between different visual perspectives and morphologies of bodies within visual processing. However, the combined processing of these physical attributes towards neural EBA response remains unclear, and may be crucial in influencing higher-order, aesthetic evaluation of bodies. Indeed, EBA alterations amongst eating disorder patients have been associated with disturbances in body image, and disruption to EBA activity amongst healthy individuals has been shown to influence aesthetic evaluations made towards bodies. Therefore, the present study used images of slim and large female bodies viewed from egocentric and allocentric perspectives, to investigate neural EBA response amongst healthy females (N = 30). In addition, participants provided behavioural aesthetic and weight evaluations of all model stimuli. Results revealed an interaction, bilaterally, between visual perspective and body size towards EBA activity, with multi-voxel pattern analysis revealing distinct neural patterns between the four conditions. However, EBA activity did not relate to non-clinical eating disorder psychopathology. No direct relationship was found between EBA activity and behavioural evaluations of model stimuli; however, a whole brain analysis revealed that higher-order, prefrontal regions were associated with cognitive evaluations of large bodies. Taken together, our results suggest that the EBA is an integral core region in discriminating between multiple physical attributes of the body, which is likely to provide important information to higher-order brain regions which make aesthetic evaluations towards bodies.

Divergent effects of healthy ageing on semantic knowledge and control: Evidence from novel comparisons with semantically impaired patients

Effective use of semantic knowledge requires a set of conceptual representations and control processes which ensure that currently relevant aspects of this knowledge are retrieved and selected. It is well-established that levels of semantic knowledge increase across the lifespan. However, the effects of ageing on semantic control processes have not been assessed. I addressed this issue by comparing the performance profiles of young and older people on a verbal comprehension test. Two sets of variables were used to predict accuracy and RT in each group: (1) the psycholinguistic properties of words probed in each trial and (2) the performance on each trial by two groups of semantically impaired neuropsychological patients. Young people demonstrated poor performance for low-frequency and abstract words, suggesting that they had difficulty processing words with intrinsically weak semantic representations. Indeed, performance in this group was strongly predicted by the performance of patients with semantic dementia, who suffer from degradation of semantic knowledge. In contrast, older adults performed poorly on trials where the target semantic relationship was weak and distractor relationships strong - conditions which require high levels of controlled processing. Their performance was not predicted by the performance of semantic dementia patients, but was predicted by the performance of patients with semantic control deficits. These findings indicate that the effects of ageing on semantic cognition are more complex than has previously been assumed. While older people have larger stores of knowledge than young people, they appear to be less skilled at exercising control over the activation of this knowledge.

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.

Electroconvulsive therapy "corrects" the neural architecture of visuospatial memory: Implications for typical cognitive-affective functioning

Although electroconvulsive therapy (ECT) is a widely used and effective treatment for refractory depression, the neural underpinnings of its therapeutic effects remain poorly understood. To address this issue, here, we focused on a core cognitive deficit associated with depression, which tends to be reliably ameliorated through ECT, specifically, the ability to learn visuospatial information. Thus, we pursued three goals. First, we tested whether ECT can “normalize” the functional brain organization patterns associated with visuospatial memory and whether such corrections would predict post-ECT improvements in learning visuospatial information. Second, we investigated whether, among healthy individuals, stronger expression of the neural pattern, susceptible to adjustments through ECT, would predict reduced incidence of depression-relevant cognition and affect. Third, we sought to quantify the heritability of the ECT-correctable neural profile. Thus, in a task fMRI study with a clinical and a healthy comparison sample, we characterized two functional connectome patterns: one that typifies trait depression (i.e., differentiates patients from healthy individuals) and another that is susceptible to “normalization” through ECT. Both before and after ECT, greater expression of the trait depression neural profile was associated with more frequent repetitive thinking about past personal events (affective persistence), a hallmark of depressogenic cognition. Complementarily, post-treatment, stronger expression of the ECT-corrected neural profile was linked to improvements in visuospatial learning, a mental ability which is markedly impaired in depression. Subsequently, using data from the Human Connectome Project (HCP) (N = 333), we demonstrated that the functional brain organization of healthy participants with greater levels of subclinical depression and higher incidence of its associated cognitive deficits (affective persistence, impaired learning) shows greater similarity to the trait depression neural profile and reduced similarity to the ECT-correctable neural profile, as identified in the patient sample. These results tended to be specific to learning-relevant task contexts (working memory, perceptual relational processing). Genetic analyses based on HCP twin data (N = 128 pairs) suggested that, among healthy individuals, a functional brain organization similar to the one normalized by ECT in the patient sample is endogenous to cognitive contexts that require visuospatial processing that extends beyond the here-and-now. Broadly, the present findings supported our hypothesis that some of the therapeutic effects of ECT may be due to its correcting the expression of a naturally occurring pattern of functional brain organization that facilitates integration of internal and external cognition beyond the immediate present. Given their substantial susceptibility to both genetic and environmental effects, such mechanisms may be useful both for identifying at risk individuals and for monitoring progress of interventions targeting mood-related pathology.

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Trait depression and ECT-correctable neural profiles were described in patients.

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The former was related to rumination and the latter to improved learning after ECT.

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Their relative expression was linked to subclinical depression in a healthy sample.

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Twin analyses implied that both profiles are endogenous to working memory contexts.

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 posterior cingulate cortex: Insights from structure and function

The posterior cingulate cortex (PCC) (Brodmann areas 23/31) is one of the least well-understood regions of the cortex. The PCC has very high levels of metabolic consumption, and network analyses of functional and structural data suggest it is a core hub in the human connectome; however, contemporary neuroscience lacks a clear account of its functional significance. Consequently, many studies over the last decade have focused on understanding the role this region plays in cognition, particularly given its apparent tendency to deactivate during demanding external tasks. Consistent with the cytoarchitecture, recent work, leveraging complex analytical approaches, highlight that the connections the PCC forms with other regions are heterogeneous, going beyond a single network, while recent studies of its function highlight a role in a wide range of complex forms of cognition including memory, navigation, and narrative comprehension. This constellation of observations highlights a role for PCC in a set of cognitive processes that are supported by internal representations but may lack a common type of representational content. Together, these structural and functional studies contribute to an emerging view of the PCC as contributing to how cognition unfolds rather than what it is focused on.

Stable between-subject statistical inference from unstable within-subject functional connectivity estimates

Spatial or temporal aspects of neural organization are known to be important indices of how cognition is organized. However, measurements and estimations are often noisy and many of the algorithms used are probabilistic, which in combination have been argued to limit studies exploring the neural basis of specific aspects of cognition. Focusing on static and dynamic functional connectivity estimations, we propose to leverage this variability to improve statistical efficiency in relating these estimations to behavior. To achieve this goal, we use a procedure based on permutation testing that provides a way of combining the results from many individual tests that refer to the same hypothesis. This is needed when testing a measure whose value is obtained from a noisy process, which can be repeated multiple times, referred to as replications. Focusing on functional connectivity, this noisy process can be: (a) computational, for example, when using an approximate inference algorithm for which different runs can produce different results or (b) observational, if we have the capacity to acquire data multiple times, and the different acquired data sets can be considered noisy examples of some underlying truth. In both cases, we are not interested in the individual replications but on the unobserved process generating each replication. In this note, we show how results can be combined instead of choosing just one of the estimated models. Using both simulations and real data, we show the benefits of this approach in practice.