Evolutionarily novel functional networks in the human brain?

Early life stress, literacy and dyslexia: an evolutionary perspective

Stress and learning co-evolved in parallel, with their interdependence critical to the survival of the species. Even today, the regulation of moderate levels of stress by the central autonomic network (CAN), especially during pre- and post-natal periods, facilitates biological adaptability and is an essential precursor for the cognitive requisites of learning to read. Reading is a remarkable evolutionary achievement of the human brain, mysteriously unusual, because it is not pre-wired with a genetic address to facilitate its acquisition. There is no gene for reading. The review suggests that reading co-opts a brain circuit centered in the left hemisphere ventral occipital cortex that evolved as a domain-general visual processor. Its adoption by reading depends on the CAN's coordination of the learning and emotional requirements of learning to read at the metabolic, cellular, synaptic, and network levels. By stabilizing a child's self-control and modulating the attention network's inhibitory controls over the reading circuit, the CAN plays a key role in school readiness and learning to read. In addition, the review revealed two beneficial CAN evolutionary adjustments to early-life stress "overloads" that come with incidental costs of school under-performance and dyslexia. A short-term adaptation involving methylation of the FKBP5 and NR3C1 genes is a liability for academic achievement in primary school. The adaptation leading to dyslexia induces alterations in BDNF trafficking, promoting long-term adaptive fitness by protecting against excessive glucocorticoid toxicity but risks reading difficulties by disruptive signaling from the CAN to the attention networks and the reading circuit.

The prefrontal cortex: from monkey to man

The prefrontal cortex is so important to human beings that, if deprived of it, our behaviour is reduced to action-reactions and automatisms, with no ability to make deliberate decisions. Why does the prefrontal cortex hold such importance in humans? In answer, this review draws on the proximity between humans and other primates, which enables us, through comparative anatomical-functional analysis, to understand the cognitive functions we have in common and specify those that distinguish humans from their closest cousins. First, a focus on the lateral region of the prefrontal cortex illustrates the existence of a continuum between rhesus monkeys (the most studied primates in neuroscience) and humans for most of the major cognitive functions in which this region of the brain plays a central role. This continuum involves the presence of elementary mental operations in the rhesus monkey (e.g. working memory or response inhibition) that are constitutive of 'macro-functions' such as planning, problem-solving and even language production. Second, the human prefrontal cortex has developed dramatically compared to that of other primates. This increase seems to concern the most anterior part (the frontopolar cortex). In humans, the development of the most anterior prefrontal cortex is associated with three major and interrelated cognitive changes: (i) a greater working memory capacity, allowing for greater integration of past experiences and prospective futures; (ii) a greater capacity to link discontinuous or distant data, whether temporal or semantic; and (iii) a greater capacity for abstraction, allowing humans to classify knowledge in different ways, to engage in analogical reasoning or to acquire abstract values that give rise to our beliefs and morals. Together, these new skills enable us, among other things, to develop highly sophisticated social interactions based on language, enabling us to conceive beliefs and moral judgements and to conceptualize, create and extend our vision of our environment beyond what we can physically grasp. Finally, a model of the transition of prefrontal functions between humans and non-human primates concludes this review.

Human brain representations of internally generated outcomes of approximate calculation revealed by ultra-high-field brain imaging

Much of human culture's advanced technology owes its existence to the ability to mentally manipulate quantities. Neuroscience has described the brain regions overall recruited by numerical tasks and the neuronal codes representing individual quantities during perceptual tasks. Nevertheless, it remains unknown how quantity representations are combined or transformed during mental computations and how specific quantities are coded in the brain when generated as the result of internal computations rather than evoked by a stimulus. Here, we imaged the brains of adult human subjects at 7 Tesla during an approximate calculation task designed to disentangle in- and outputs of the computation from the operation itself. While physically presented sample numerosities were distinguished in activity patterns along the dorsal visual pathway and within frontal and occipito-temporal regions, a representation of the internally generated result was most prominently detected in higher order regions such as angular gyrus and lateral prefrontal cortex. Behavioral precision in the task was related to cross-decoding performance between sample and result representations in medial IPS regions. This suggests the transformation of sample into result may be carried out within dorsal stream sensory-motor integration regions, and resulting outputs maintained for task purposes in higher-level regions in a format possibly detached from sensory-evoked inputs.

Mapping and comparing fMRI connectivity networks across species

Technical advances in neuroimaging, notably in fMRI, have allowed distributed patterns of functional connectivity to be mapped in the human brain with increasing spatiotemporal resolution. Recent years have seen a growing interest in extending this approach to rodents and non-human primates to understand the mechanism of fMRI connectivity and complement human investigations of the functional connectome. Here, we discuss current challenges and opportunities of fMRI connectivity mapping across species. We underscore the critical importance of physiologically decoding neuroimaging measures of brain (dys)connectivity via multiscale mechanistic investigations in animals. We next highlight a set of general principles governing the organization of mammalian connectivity networks across species. These include the presence of evolutionarily conserved network systems, a dominant cortical axis of functional connectivity, and a common repertoire of topographically conserved fMRI spatiotemporal modes. We finally describe emerging approaches allowing comparisons and extrapolations of fMRI connectivity findings across species. As neuroscientists gain access to increasingly sophisticated perturbational, computational and recording tools, cross-species fMRI offers novel opportunities to investigate the large-scale organization of the mammalian brain in health and disease.

Structural connectivity of the multiple demand network in humans and comparison to the macaque brain

Fluid intelligence encompasses a wide range of abilities such as working memory, problem-solving, and relational reasoning. In the human brain, these abilities are associated with the Multiple Demand Network, traditionally thought to involve combined activity of specific regions predominantly in the prefrontal and parietal cortices. However, the structural basis of the interactions between areas in the Multiple Demand Network, as well as their evolutionary basis among primates, remains largely unexplored. Here, we exploit diffusion MRI to elucidate the major white matter pathways connecting areas of the human core and extended Multiple Demand Network. We then investigate whether similar pathways can be identified in the putative homologous areas of the Multiple Demand Network in the macaque monkey. Finally, we contrast human and monkey networks using a recently proposed approach to compare different species' brains within a common organizational space. Our results indicate that the core Multiple Demand Network relies mostly on dorsal longitudinal connections and, although present in the macaque, these connections are more pronounced in the human brain. The extended Multiple Demand Network relies on distinct pathways and communicates with the core Multiple Demand Network through connections that also appear enhanced in the human compared with the macaque.

fMRI fluctuations within the language network are correlated with severity of hallucinatory symptoms in schizophrenia

Although schizophrenia (SZ) represents a complex multiform psychiatric disorder, one of its most striking symptoms are auditory verbal hallucinations (AVH). While the neurophysiological origin of this pervasive symptom has been extensively studied, there is so far no consensus conclusion on the neural correlates of the vulnerability to hallucinate. With a network-based fMRI approach, following the hypothesis of altered hemispheric dominance (Crow, 1997), we expected that LN alterations might result in self-other distinction impairments in SZ patients, and lead to the distressing subjective experiences of hearing voices. We used the independent component analysis of resting-state fMRI data, to first analyze LN connectivity in three groups of participants: SZ patients with and without hallucinations (AVH/D+ and AVH/D-, respectively), and a matched healthy control (HC) group. Then, we assessed the fMRI fluctuations using additional analyses based on fractional Amplitude of Low Frequency-Fluctuations (fALFF), both at the network- and region of interest (ROI)-level. Specific LN nodes were recruited in the right hemisphere (insula and Broca homologous area) for AVH/D+ , but not for HC and AVH/D-, consistent with a left hemisphere deficit in AVH patients. The fALFF analysis at the ROI level showed a negative correlation between fALFF Slow-4 and P1 Delusions PANSS subscale and a positive correlation between the fALFF Slow-5 and P3 Hallucination PANSS subscale for AVH/D+ only. These effects were not a consequence of structural differences between groups, as morphometric analysis did not evidence any group differences. Given the role of language as an emerging property resulting from the integration of many high-level cognitive processes and the underlying cortical areas, our results suggest that LN features from fMRI connectivity and fluctuations can be a marker of neurophysiological features characterizing SZ patients depending on their vulnerability to hallucinate.

Neuroimaging evidence supporting a dual-network architecture for the control of visuospatial attention in the human brain: a mini review

Neuroimaging studies conducted in the last three decades have distinguished two frontoparietal networks responsible for the control of visuospatial attention. The present review summarizes recent findings on the neurophysiological mechanisms implemented in both networks and describes the evolution from a model centered on the distinction between top-down and bottom-up attention to a model that emphasizes the dynamic interplay between the two networks based on attentional demands. The role of the dorsal attention network (DAN) in attentional orienting, by boosting behavioral performance, has been investigated with multiple experimental approaches. This research effort allowed us to trace a distinction between DAN regions involved in shifting vs. maintenance of attention, gather evidence for the modulatory influence exerted by the DAN over sensory cortices, and identify the electrophysiological correlates of the orienting function. Simultaneously, other studies have contributed to reframing our understanding of the functions of the ventral attention network (VAN) and its relevance for behavior. The VAN is not simply involved in bottom-up attentional capture but interacts with the DAN during reorienting to behaviorally relevant targets, exhibiting a general resetting function. Further studies have confirmed the selective rightward asymmetry of the VAN, proposed a functional dissociation along the anteroposterior axis, and suggested hypotheses about its emergence during the evolution of the primate brain. Finally, novel models of network interactions explain the expression of complex attentional functions and the emergence and restorations of symptoms characterizing unilateral spatial neglect. These latter studies emphasize the importance of considering patterns of network interactions for understanding the consequences of brain lesions.

Design and application of a multimodality-compatible 1Tx/6Rx RF coil for monkey brain MRI at 7T

OBJECTIVE

Blood-oxygen-level-dependent functional MRI allows to investigte neural activities and connectivity. While the non-human primate plays an essential role in neuroscience research, multimodal methods combining functional MRI with other neuroimaging and neuromodulation enable us to understand the brain network at multiple scales.

APPROACH

In this study, a tight-fitting helmet-shape receive array with a single transmit loop for anesthetized macaque brain MRI at 7T was fabricated with four openings constructed in the coil housing to accommodate multimodal devices, and the coil performance was quantitatively evaluated and compared to a commercial knee coil. In addition, experiments over three macaques with infrared neural stimulation (INS), focused ultrasound stimulation (FUS), and transcranial direct current stimulation (tDCS) were conducted.

MAIN RESULTS

The RF coil showed higher transmit efficiency, comparable homogeneity, improved SNR and enlarged signal coverage over the macaque brain. Infrared neural stimulation was applied to the amygdala in deep brain region, and activations in stimulation sites and connected sites were detected, with the connectivity consistent with anatomical information. Focused ultrasound stimulation was applied to the left visual cortex, and activations were acquired along the ultrasound traveling path, with all time course curves consistent with pre-designed paradigms. The existence of transcranial direct current stimulation electrodes brought no interference to the RF system, as evidenced through high-resolution MPRAGE structure images.

SIGNIFICANCE

This pilot study reveals the feasibility for brain investigation at multiple spatiotemporal scales, which may advance our understanding in dynamic brain networks.

Left anterior supramarginal gyrus activity during tool use action observation after extensive tool use training

The advanced use of complex tools is considered a primary characteristic of human evolution and technological advancement. However, questions remain regarding whether humans possess unique underlying brain networks that support advanced tool-using abilities. Specifically, previous studies have demonstrated the presence of a structurally and functionally unique region in the left anterior supramarginal gyrus (aSMG), that is consistently active during tool use action observation. This region has been proposed as a primary hub for integrating semantic and technical information to form action plans with tools. However, it is still largely unknown how tool use motor learning affects left aSMG activation or connectivity with other brain regions. To address this, participants with little experience using chopsticks observed an experimenter using chopsticks to perform a novel task while undergoing two functional magnetic resonance imaging (fMRI) scans. Between the scans, participants underwent four weeks of behavioral training where they learned to use chopsticks and achieve proficiency in the observed task. Results demonstrated a significant change in effective connectivity between the left aSMG and the left anterior intraparietal sulcus (aIPS), a region involved in object affordances and planning grasping actions. These findings suggest that during unfamiliar tool use, the left aSMG integrates semantic and technical information to communicate with regions involved with grasp selection, such as the aIPS. This communication then allows appropriate grasps to be planned based on the physical properties of the objects involved and their potential interactions.

Language Network Connectivity of Euthymic Bipolar Patients Is Altered at Rest and during a Verbal Fluency Task

Abnormalities of the Language Network (LN) have been found in different psychiatric conditions (e.g., schizophrenia and bipolar disorder), supporting the hypothesis that language plays a central role in a high-level integration/connectivity of second-level cognitive processes and the underlying cortical regions. This view implies a continuum of shared neural alterations along the psychotic disorder spectrum. In particular, bipolar disorder (BD) patients were recently documented to have an altered LN asymmetry during resting state. The extent to which the LN architecture is altered and stable also during a language task has yet to be investigated. To address this question, we analyzed fMRI data recorded during an open-eyes resting state session and a silent verbal fluency task in 16 euthymic BD patients and 16 matched healthy controls (HC). Functional connectivity in the LN of both groups was computed using spatial independent component analysis, and group comparisons were carried out to assess the network organization during both rest and active linguistic task conditions. The LN of BD patients involved left and right brain areas during both resting state and linguistic task. Compared to the left-lateralized network found in HC, the BD group was characterized by two anterior clusters (in left frontal and right temporo-insular regions) and the disengagement of the posterior language areas, especially during the verbal fluency task. Our findings support the hypothesis that reduced language lateralization may represent a biological marker across different psychotic disorders and that the altered language network connectivity found at rest in bipolar patients is stable and pervasive as it is also impaired during a verbal fluency task.

Temporal continuity shapes visual responses of macaque face patch neurons

Macaque inferior temporal cortex neurons respond selectively to complex visual images, with recent work showing that they are also entrained reliably by the evolving content of natural movies. To what extent does temporal continuity itself shape the responses of high-level visual neurons? We addressed this question by measuring how cells in face-selective regions of the macaque visual cortex were affected by the manipulation of a movie's temporal structure. Sampling a 5-min movie at 1 s intervals, we measured neural responses to randomized, brief stimuli of different lengths, ranging from 800 ms dynamic movie snippets to 100 ms static frames. We found that the disruption of temporal continuity strongly altered neural response profiles, particularly in the early response period after stimulus onset. The results suggest that models of visual system function based on discrete and randomized visual presentations may not translate well to the brain's natural modes of operation.

Disembodiment and Language in Schizophrenia: An Integrated Psychopathological and Evolutionary Perspective

Different hypotheses have flourished to explain the evolutionary paradox of schizophrenia. In this contribution, we sought to illustrate how, in the schizophrenia spectrum, the concept of embodiment may underpin the phylogenetic and developmental pathways linking sensorimotor processes, the origin of human language, and the construction of a basic sense of the self. In particular, according to an embodied model of language, we suggest that the reuse of basic sensorimotor loops for language, while enabling the development of fully symbolic thought, has pushed the human brain close to the threshold of a severe disruption of self-embodiment processes, which are at the core of schizophrenia psychopathology. We adopted an inter-disciplinary approach (psychopathology, neuroscience, developmental biology) within an evolutionary framework, to gain an integrated, multi-perspectival model on the origin of schizophrenia vulnerability. A maladaptive over-expression of evolutionary-developmental trajectories toward language at the expense of embodiment processes would have led to the evolutionary "trade-off" of a hyper-symbolic activity to the detriment of a disembodied self. Therefore, schizophrenia psychopathology might be the cost of long-term co-evolutive interactions between brain and language.

Default mode network alterations underlie auditory verbal hallucinations in schizophrenia

Although alterations of the default mode network (DMN) in schizophrenia (SZ) have been largely investigated, less research has been carried out on DMN alterations in different sub-phenotypes of this disorder. The aim of this pilot study was to compare DMN features among SZ patients with and without auditory verbal hallucinations (AVH). Three groups of 17 participants each were considered: patients with hallucinations (AVH-SZ), patients without hallucinations (nAVH-SZ) and age-matched healthy controls (HC). The DMN spatial pattern was similar between the nAVH-SZ and HC, but the comparison between these two groups and the AVH-SZ group revealed alterations in the left Angular Gyrus (lAG) node of the DMN. Using a novel approach based on normalized fractional Amplitude of Low-Frequency Fluctuations (fALFF), the AVH-SZ subgroup showed altered spectral activity in the DMN compared with the other two groups, especially in the lower-frequency bands (0.017-0.04 Hz). Significant positive correlations were found for both SZ groups collapsed, and for the nAVH-SZ group alone between delusional scores (PANSS-P1) and slow fALFF bands of the DMN. Narrowing the analysis to the ROI centered on the lAG, significant correlations were found in the AVH-SZ group for hallucination scores (PANSS-P3) and Slow-5 and Slow-4 (both positive), and Slow-3 (negative) fALFF bands. Our results reveal the central role of the lAG in relation to hallucinations, an important cortical area connecting auditory cortex with several hubs (including frontal linguistic centers) and involved in auditory process monitoring.

Altered language network lateralization in euthymic bipolar patients: a pilot study

Bipolar patients (BD) in the euthymic phase show almost no symptoms, nevertheless possibility of relapse is still present. We expected to find a psychobiological trace of their vulnerability by analyzing a specific network-the Language Network (LN)-connecting many high-level processes and brain regions measured at rest. According to Crow's hypothesis on the key role of language in the origin of psychoses, we expected an altered asymmetry of the LN in euthymic BDs. Eighteen euthymic BD patients (10 females; age = 54.50 ± 11.38 years) and 16 healthy controls (HC) (8 females; age = 51.16 ± 11.44 years) underwent a functional magnetic resonance imaging scan at rest. The LN was extracted through independent component analysis. Then, LN time series was used to compute the fractional amplitude of the low-frequency fluctuation (fALFF) index, which was then correlated with clinical scales. Compared with HC, euthymic patients showed an altered LN with greater activation of Broca's area right homologous and anterior insula together with reduced activation of left middle temporal gyrus. The normalized fALFF analysis on BD patients' LN time series revealed that the Slow-5 fALFF band was positively correlated with residual mania symptoms but negatively associated with depression scores. In line with Crow's hypothesis postulating an altered language hemispheric asymmetry in psychoses, we revealed, in euthymic BD patients, a right shift involving both the temporal and frontal linguistic hubs. The fALFF applied to LN allowed us to highlight a number of significant correlations of this measure with residual mania and depression psychiatric symptoms.

Increased connectivity of insula sub-regions correlates with emotional dysregulation in patients with first-episode schizophrenia

Dysfunctional insula is crucial in the development of social cognition deficits, especially emotional dysregulation in patients with schizophrenia. However, function networks of insula sub-regions in schizophrenia are rarely investigated. In this study, functional connectivity between insula sub-regions and whole-brain voxels and its relationship with social cognition ability were investigated in patients with first-episode schizophrenia (FES). This study included 47 patients with FES and 47 healthy controls (HCs). Resting-state functional connectivity (rsFC) was assessed using a seed-based approach, and social cognition was measured by the "managing emotions" branch of the Mayer-Salovey-Caruso Emotional Intelligence Test. Differences in rsFC of insula sub-regions between the two groups were examined. Patients with FES showed increased rsFC between the left anterior insula (AI) and the right inferior frontal gyrus or the right anterior middle cingulate cortex (aMCC) and between the right middle insula and the right aMCC. Moreover, the increased AI-aMCC connectivity correlated negatively with the "managing emotion" scores in patients. This study highlights the altered functional connectivity of insula sub-regions and its correlation with emotional dysregulation in patients with FES. Our findings provide some insights into underlying neuropathological mechanisms associated with emotional regulation deficiency in patients with schizophrenia.

Molecular archaeology of human cognitive traits

The brains and minds of our human ancestors remain inaccessible for experimental exploration. Therefore, we reconstructed human cognitive evolution by projecting nonsynonymous/synonymous rate ratios (ω values) in mammalian phylogeny onto the anatomically modern human (AMH) brain. This atlas retraces human neurogenetic selection and allows imputation of ancestral evolution in task-related functional networks (FNs). Adaptive evolution (high ω values) is associated with excitatory neurons and synaptic function. It shifted from FNs for motor control in anthropoid ancestry (60-41 mya) to attention in ancient hominoids (26-19 mya) and hominids (19-7.4 mya). Selection in FNs for language emerged with an early hominin ancestor (7.4-1.7 mya) and was later accompanied by adaptive evolution in FNs for strategic thinking during recent (0.8 mya-present) speciation of AMHs. This pattern mirrors increasingly complex cognitive demands and suggests that co-selection for language alongside strategic thinking may have separated AMHs from their archaic Denisovan and Neanderthal relatives.

Psychophysiological Indicators of Postural Control. Contribution of the Russian Scientific School. Part I

This article aimed to systematically review the published results of studies of psychophysiological mechanisms of posture maintenance and identify the key factors that influence the effectiveness of postural control. The recommendations of "Preferred Reporting Elements for Systematic Reviews and Meta-Analyzes" (PRISMA) were followed for the review. The results were classified, taking into account the target psychophysiological mechanisms and factors affecting postural control. The article presents the theoretical and empirical results of the Russian scientific school of research on the role of support afferentation in the sensorimotor mechanisms of cognitive and postural functions. Due to the limited number of randomized studies found, it was impossible to make meta-analytic comparisons, so the literature analysis was carried out only qualitatively. Meanwhile, our systematic review provides promising information about possible relationships between stabilometric and psychological indicators of postural control, which have theoretical significance and application in the correction and training of posture control. However, more thorough research is needed to overcome the methodological shortcomings that we have encountered in our qualitative analysis.

The trait and state negative affect can be separately predicted by stable and variable resting-state functional connectivity

BACKGROUND

Many emotional experiences such as anxiety and depression are influenced by negative affect (NA). NA has both trait and state features, which play different roles in physiological and mental health. Attending to NA common to various emotional experiences and their trait-state features might help deepen the understanding of the shared foundation of related emotional disorders.

METHODS

The principal component of five measures was calculated to indicate individuals' NA level. Applying the connectivity-based correlation analysis, we first identified resting-state functional connectives (FCs) relating to NA in sample 1 (n = 367), which were validated through an independent sample (n = 232; sample 2). Next, based on the variability of FCs across large timescale, we further divided the NA-related FCs into high- and low-variability groups. Finally, FCs in different variability groups were separately applied to predict individuals' neuroticism level (which is assumed to be the core trait-related factor underlying NA), and the change of NA level (which represents the state-related fluctuation of NA).

RESULTS

The low-variability FCs were primarily within the default mode network (DMN) and between the DMN and dorsal attention network/sensory system and significantly predicted trait rather than state NA. The high-variability FCs were primarily between the DMN and ventral attention network, the fronto-parietal network and DMN/sensory system, and significantly predicted the change of NA level.

CONCLUSIONS

The trait and state NA can be separately predicted by stable and variable spontaneous FCs with different attentional processes and emotion regulatory mechanisms, which could deepen our understanding of NA.

Network-specific differences in transient brain activity at rest are associated with age-related reductions in motor performance

Multiple functional changes occur in the brain with increasing age. Among those, older adults typically display more restricted fluctuations of brain activity, both during resting-state and task execution. These altered dynamic patterns have been linked to reduced task performance across multiple behavioral domains. Windowed functional connectivity, which is typically employed in the study of connectivity dynamics, however, might not be able to properly characterize moment-to-moment variations of individual networks. In the present study, we used innovation-driven co-activation patterns (ICAP) to overcome this limitation and investigate the length (duration) and frequency (innovation) in which various brain networks emerged across the adult lifespan (N= 92) during a resting-state period. We identified a link between increasing age and a tendency to engage brain areas with distinct functional associations simultaneously as a single network. The emergence of isolated and spatially well-defined visual, motor, frontoparietal, and posterior networks decreased with increased age. This reduction in dynamics of specialized networks mediated age-related performance decreases (i.e., increases in interlimb interference) in a bimanual motor task. Altogether, our findings demonstrated that older compared to younger adults tend to activate fewer network configurations, which include multiple functionally distinct brain areas. The reduction in independent emergence of functionally well-defined and task-relevant networks may reflect an expression of brain dedifferentiation and is likely associated with functional modulatory deficits, negatively impacting motor behavior.

Resting-state dynamic functional connectivity predicts the psychosocial stress response

Acute stress triggers a complex cascade of psychological, physiological, and neural responses, which show large and enduring individual differences. Although previous studies have examined the relationship between the stress response and dynamic features of the brain's resting state, no study has used the brain's dynamic activity in the resting state to predict individual differences in the psychosocial stress response. In the current study, resting-state scans of forty-eight healthy participants were collected, and then their individual acute stress responses during the Montreal Imaging Stress Test (MIST) paradigm were recorded. Results defined a connectivity state (CS) characterized by positive correlations across the whole brain during resting-state that could negatively predict participants' feelings of social evaluative threat during stress tasks. Another CS characterized by negative correlations between the frontal-parietal network (FPN) and almost all other networks, except the dorsal attentional network (DAN), could predict participants' subjective stress, feelings of uncontrollability, and feelings of social evaluative threat. However, no CS could predict participants' salivary cortisol stress response. Overall, these results suggested that the brain state characterized as attentional regulation, linking self-control, and top-down regulation ability, could predict the psychosocial stress response. This study also developed an objective indicator for predicting human stress responses.

Default mode network shows alterations for low-frequency fMRI fluctuations in euthymic bipolar disorder

Bipolar disorder (BD) is a psychiatric condition causing acute dysfunctional mood states and emotion regulation. Specific neuropsychological features are often present also among patients in euthymic phase, who do not show clear psychotic symptoms, and for whom the characterization from functional magnetic resonance imaging (fMRI) is very limited. This study aims at identifying the neural and behavioral correlates of the default mode network (DMN) using the fractional amplitude of low frequency fluctuations (fALFF). Eighteen euthymic BD patients (10 females; age = 54.50 ± 11.38 years) and sixteen healthy controls (HC) (8 females; age = 51.16 ± 11.44 years) underwent a 1.5T fMRI scan at rest. The DMN was extracted through independent component analysis. Then, DMN time series was used to compute the fALFF, which was correlated with clinical scales. From the between-group comparison, no significant differences emerged in correspondence to regions belonging to the DMN. For fALFF analysis, we reported significant increase of low-frequency fluctuations for lower frequencies, and decreases for higher frequencies compared to HC. Correlations with clinical scales showed that an increase in higher frequency spectral content was associated with lower levels of mania and higher levels of anxious symptoms, while an increase in lower frequencies was linked to lower depressive symptoms. Starting from our findings on the DMN in euthymic BD patients, we suggest that the fALFF derived from network time series represents a viable approach to investigate the behavioral correlates of resting state networks, and the pathophysiological mechanisms of different psychiatric conditions.

Stimulating parietal regions of the multiple-demand cortex impairs novel vocabulary learning

Neuroimaging research demonstrated that the early stages of learning engage domain-general networks, non-specialist brain regions that process a wide variety of cognitive tasks. Those networks gradually disengage as learning progresses and learned information becomes processed in brain networks specialised for the specific function (e.g., language). In the current study, we used repetitive transcranial magnetic stimulation (rTMS) in the form of continuous theta burst stimulation (cTBS) to test whether stimulation of the bilateral parietal region of the domain-general network impairs learning new vocabulary, indicating its causal engagement in this process. Twenty participants, with no prior knowledge of Polish, learned Polish words for well-known objects across three training stages. The first training stage started with cTBS applied to either the experimental domain-general bilateral parietal site or the control bilateral precentral site. Immediately after cTBS, the vocabulary training commenced. A different set of words was learned for each site. Immediately after the training stage, participants performed a novel vocabulary test, designed to measure their knowledge of the new words and the effect of stimulation on learning. To measure stimulation effect when the words were more established in the mental lexicon, participants received additional training on the same words but without cTBS (second training stage) and then the full procedures from the first training stage were repeated (third training stage). Results demonstrated that stimulation impaired novel word learning when applied to the bilateral parietal site at the first stage of learning only. This effect was not present when newly learned words were used more proficiently in the third training stage, or at any learning stage during control site stimulation. Our results show that the bilateral parietal region of the domain-general network causally contributes to the successful learning of novel words.

Multisensory deficits in dyslexia may result from a locus coeruleus attentional network dysfunction

A fundamental educational requirement of beginning reading is to learn, access, and rapidly process associations between novel visuospatial symbols and their phonological representations in speech. Children with difficulties in such cross-modal integration are often divided into dyslexia subtypes, based on whether their primary problem is with the written or spoken component of decoding. The present review suggests that starting in infancy, perceptions of audiovisual speech are integrated by mutual oscillatory phase-resetting between sensory cortices, and throughout development visual and auditory experiences are coupled into unified perceptions. Entirely separate subtypes are incompatible with this view. Visual or auditory deficits will invariably affect processing to some degree in both domains. It is suggested that poor auditory/visual integration may be diagnostic for both forms of dyslexia, stemming from an encoding weakness in the early cross-sensory binding of audiovisual speech. The review presents a model of dyslexia as a dysfunction of the large-scale ventral and dorsal attention networks controlling such binding. Excessive glutamatergic neuronal excitability of the attention networks by the Locus coeruleus-norepinephrine system may interfere with multisensory integration, with deleterious effects on the acquisition of reading by degrading graphene/phoneme conversion.

Parietal maps of visual signals for bodily action planning

The posterior parietal cortex (PPC) has long been understood as a high-level integrative station for computing motor commands for the body based on sensory (i.e., mostly tactile and visual) input from the outside world. In the last decade, accumulating evidence has shown that the parietal areas not only extract the pragmatic features of manipulable objects, but also subserve sensorimotor processing of others’ actions. A paradigmatic case is that of the anterior intraparietal area (AIP), which encodes the identity of observed manipulative actions that afford potential motor actions the observer could perform in response to them. On these bases, we propose an AIP manipulative action-based template of the general planning functions of the PPC and review existing evidence supporting the extension of this model to other PPC regions and to a wider set of actions: defensive and locomotor actions. In our model, a hallmark of PPC functioning is the processing of information about the physical and social world to encode potential bodily actions appropriate for the current context. We further extend the model to actions performed with man-made objects (e.g., tools) and artifacts, because they become integral parts of the subject’s body schema and motor repertoire. Finally, we conclude that existing evidence supports a generally conserved neural circuitry that transforms integrated sensory signals into the variety of bodily actions that primates are capable of preparing and performing to interact with their physical and social world.

Neuroplasticity and Crossmodal Connectivity in the Normal, Healthy Brain

Objective

Neuroplasticity enables the brain to establish new crossmodal connections or reorganize old connections which are essential to perceiving a multisensorial world. The intent of this review is to identify and summarize the current developments in neuroplasticity and crossmodal connectivity, and deepen understanding of how crossmodal connectivity develops in the normal, healthy brain, highlighting novel perspectives about the principles that guide this connectivity.

Methods

To the above end, a narrative review is carried out. The data documented in prior relevant studies in neuroscience, psychology and other related fields available in a wide range of prominent electronic databases are critically assessed, synthesized, interpreted with qualitative rather than quantitative elements, and linked together to form new propositions and hypotheses about neuroplasticity and crossmodal connectivity.

Results

Three major themes are identified. First, it appears that neuroplasticity operates by following eight fundamental principles and crossmodal integration operates by following three principles. Second, two different forms of crossmodal connectivity, namely direct crossmodal connectivity and indirect crossmodal connectivity, are suggested to operate in both unisensory and multisensory perception. Third, three principles possibly guide the development of crossmodal connectivity into adulthood. These are labeled as the principle of innate crossmodality, the principle of evolution-driven 'neuromodular' reorganization and the principle of multimodal experience. These principles are combined to develop a three-factor interaction model of crossmodal connectivity.

Conclusions

The hypothesized principles and the proposed model together advance understanding of neuroplasticity, the nature of crossmodal connectivity, and how such connectivity develops in the normal, healthy brain.

Common functional localizers to enhance NHP & cross-species neuroscience imaging research

Functional localizers are invaluable as they can help define regions of interest, provide cross-study comparisons, and most importantly, allow for the aggregation and meta-analyses of data across studies and laboratories. To achieve these goals within the non-human primate (NHP) imaging community, there is a pressing need for the use of standardized and validated localizers that can be readily implemented across different groups. The goal of this paper is to provide an overview of the value of localizer protocols to imaging research and we describe a number of commonly used or novel localizers within NHPs, and keys to implement them across studies. As has been shown with the aggregation of resting-state imaging data in the original PRIME-DE submissions, we believe that the field is ready to apply the same initiative for task-based functional localizers in NHP imaging. By coming together to collect large datasets across research group, implementing the same functional localizers, and sharing the localizers and data via PRIME-DE, it is now possible to fully test their robustness, selectivity and specificity. To do this, we reviewed a number of common localizers and we created a repository of well-established localizer that are easily accessible and implemented through the PRIME-RE platform.

Development of functional connectivity within and among the resting-state networks in anesthetized rhesus monkeys

OBJECTIVE

The age-related changes in the resting-state networks (RSNs) exhibited temporally specific patterns in humans, and humans and rhesus monkeys have similar RSNs. We hypothesized that the RSNs in rhesus monkeys experienced similar developmental patterns as humans.

METHODS

We acquired resting-state fMRI data from 62 rhesus monkeys, which were divided into childhood, adolescence, and early adulthood groups. Group independent component analysis (ICA) was used to identify monkey RSNs. We detected the between-group differences in the RSNs and static, dynamic, and effective functional network connections (FNCs) using one-way variance analysis (ANOVA) and post-hoc analysis.

RESULTS

Eight rhesus RSNs were identified, including cerebellum (CN), left and right lateral visual (LVN and RVN), posterior default mode (pDMN), visuospatial (VSN), frontal (FN), salience (SN), and sensorimotor networks (SMN). In internal connections, the CN, SN, FN, and SMN mainly matured in early adulthood. The static FNCs associated with FN, SN, pDMN primarily experienced fast descending slow ascending type (U-shaped) developmental patterns for maturation, and the dynamic FNCs related to pDMN (RVN, CN, and SMN) and SMN (CN) were mature in early adulthood. The effective FNC results showed that the pDMN and VSN (stimulated), SN (inhibited), and FN (first inhibited then stimulated) chiefly matured in early adulthood.

CONCLUSION

We identified eight monkey RSNs, which exhibited similar development patterns as humans. All the RSNs and FNCs in monkeys were not widely changed but fine-tuned. Our study clarified that the progressive synchronization, exploration, and regulation of cognitive RSNs within the pDMN, FN, SN, and VSN denoted potential maturation of the RSNs throughout development. We confirmed the development patterns of RSNs and FNCs would support the use of monkeys as a best animal model for human brain function.

Combining brain perturbation and neuroimaging in non-human primates

Brain perturbation studies allow detailed causal inferences of behavioral and neural processes. Because the combination of brain perturbation methods and neural measurement techniques is inherently challenging, research in humans has predominantly focused on non-invasive, indirect brain perturbations, or neurological lesion studies. Non-human primates have been indispensable as a neurobiological system that is highly similar to humans while simultaneously being more experimentally tractable, allowing visualization of the functional and structural impact of systematic brain perturbation. This review considers the state of the art in non-human primate brain perturbation with a focus on approaches that can be combined with neuroimaging. We consider both non-reversible (lesions) and reversible or temporary perturbations such as electrical, pharmacological, optical, optogenetic, chemogenetic, pathway-selective, and ultrasound based interference methods. Method-specific considerations from the research and development community are offered to facilitate research in this field and support further innovations. We conclude by identifying novel avenues for further research and innovation and by highlighting the clinical translational potential of the methods.

A causal role for the pulvinar in coordinating task-independent cortico-cortical interactions

The pulvinar is the largest nucleus in the primate thalamus and has topographically organized connections with multiple cortical areas, thereby forming extensive cortico-pulvino-cortical input-output loops. Neurophysiological studies have suggested a role for these transthalamic pathways in regulating information transmission between cortical areas. However, evidence for a causal role of the pulvinar in regulating cortico-cortical interactions is sparse and it is not known whether pulvinar's influences on cortical networks are task-dependent or, alternatively, reflect more basic large-scale network properties that maintain functional connectivity across networks regardless of active task demands. In the current study, under passive viewing conditions, we conducted simultaneous electrophysiological recordings from ventral (area V4) and dorsal (lateral intraparietal area [LIP]) nodes of macaque visual system, while reversibly inactivating the dorsal part of the lateral pulvinar (dPL), which shares common anatomical connectivity with V4 and LIP, to probe a causal role of the pulvinar. Our results show a significant reduction in local field potential phase coherence between LIP and V4 in low frequencies (4-15 Hz) following muscimol injection into dPL. At the local level, no significant changes in firing rates or LFP power were observed in LIP or in V4 following dPL inactivation. Synchronization between pulvinar spikes and cortical LFP phase decreased in low frequencies (4-15 Hz) both in LIP and V4, while the low frequency synchronization between LIP spikes and pulvinar phase increased. These results indicate a causal role for pulvinar in synchronizing neural activity between interconnected cortical nodes of a large-scale network, even in the absence of an active task state.

How does the brain navigate knowledge of social relations? Testing for shared neural mechanisms for shifting attention in space and social knowledge

How does the human brain support reasoning about social relations (e.g., social status, friendships)? Converging theories suggest that navigating knowledge of social relations may co-opt neural circuitry with evolutionarily older functions (e.g., shifting attention in space). Here, we analyzed multivoxel response patterns of fMRI data to examine the neural mechanisms for shifting attention in knowledge of a social hierarchy. The "directions" in which participants mentally navigated social knowledge were encoded in multivoxel patterns in superior parietal cortex, which also encoded directions of attentional shifts in space. Exploratory analyses implicated additional regions of posterior parietal and occipital cortex in encoding analogous mental operations in space and social knowledge. However, cross-domain analyses suggested that attentional shifts in space and social knowledge are likely encoded in functionally independent response patterns. Additionally, cross-participant multivoxel pattern similarity analyses indicated that "directions'' of mental navigation in social knowledge are signaled consistently across participants and across different social hierarchies in a set of brain regions, including the right superior parietal lobule. Taken together, these results elucidate the neural basis of navigating abstract knowledge of social relations, and its connection to more basic mental operations.

Brain Entropy During Aging Through a Free Energy Principle Approach

Neural complexity and brain entropy (BEN) have gained greater interest in recent years. The dynamics of neural signals and their relations with information processing continue to be investigated through different measures in a variety of noteworthy studies. The BEN of spontaneous neural activity decreases during states of reduced consciousness. This evidence has been showed in primary consciousness states, such as psychedelic states, under the name of "the entropic brain hypothesis." In this manuscript we propose an extension of this hypothesis to physiological and pathological aging. We review this particular facet of the complexity of the brain, mentioning studies that have investigated BEN in primary consciousness states, and extending this view to the field of neuroaging with a focus on resting-state functional Magnetic Resonance Imaging. We first introduce historic and conceptual ideas about entropy and neural complexity, treating the mindbrain as a complex nonlinear dynamic adaptive system, in light of the free energy principle. Then, we review the studies in this field, analyzing the idea that the aim of the neurocognitive system is to maintain a dynamic state of balance between order and chaos, both in terms of dynamics of neural signals and functional connectivity. In our exploration we will review studies both on acute psychedelic states and more chronic psychotic states and traits, such as those in schizophrenia, in order to show the increase of entropy in those states. Then we extend our exploration to physiological and pathological aging, where BEN is reduced. Finally, we propose an interpretation of these results, defining a general trend of BEN in primary states and cognitive aging.

Imaging evolution of the primate brain: the next frontier?

Evolution, as we currently understand it, strikes a delicate balance between animals' ancestral history and adaptations to their current niche. Similarities between species are generally considered inherited from a common ancestor whereas observed differences are considered as more recent evolution. Hence comparing species can provide insights into the evolutionary history. Comparative neuroimaging has recently emerged as a novel subdiscipline, which uses magnetic resonance imaging (MRI) to identify similarities and differences in brain structure and function across species. Whereas invasive histological and molecular techniques are superior in spatial resolution, they are laborious, post-mortem, and oftentimes limited to specific species. Neuroimaging, by comparison, has the advantages of being applicable across species and allows for fast, whole-brain, repeatable, and multi-modal measurements of the structure and function in living brains and post-mortem tissue. In this review, we summarise the current state of the art in comparative anatomy and function of the brain and gather together the main scientific questions to be explored in the future of the fascinating new field of brain evolution derived from comparative neuroimaging.

Electrophysiological signatures of resting state networks predict cognitive deficits in stroke

Localized damage to different brain regions can cause specific cognitive deficits. However, stroke lesions can also induce modifications in the functional connectivity of intrinsic brain networks, which could be responsible for the behavioral impairment. Though resting state networks (RSNs) are typically mapped using fMRI, it has been recently shown that they can also be detected from high-density EEG. We build on a state-of-the-art approach to extract RSNs from 64-channels EEG activity in a group of right stroke patients and to identify neural predictors of their cognitive performance. Fourteen RSNs previously found in fMRI and high-density EEG studies on healthy participants were successfully reconstructed from our patients' EEG recordings. We then correlated EEG-RSNs functional connectivity with neuropsychological scores, first considering a wide frequency band (1-80 Hz) and then specific frequency ranges in order to examine the association between each EEG rhythm and the behavioral impairment. We found that visuo-spatial and motor impairments were primarily associated with the dorsal attention network, with contribution dependent on the specific EEG band. These findings are in line with the hypothesis that there is a core system of brain networks involved in specific cognitive domains. Moreover, our results pave the way for low-cost EEG-based monitoring of intrinsic brain networks' functioning in neurological patients to complement clinical-behavioral measures.

The role of transcranial magnetic stimulation in understanding attention-related networks in single subjects

Attention is a cognitive mechanism that has been studied through several methodological viewpoints, including animal models, MRI in stroke patients, and fMRI in healthy subjects. Activation-based fMRI research has also pointed to specific networks that activate during attention tasks. Most recently, network neuroscience has been used to study the functional connectivity of large-scale networks for attention to reveal how strongly correlated networks are to each other when engaged in specific behaviors. While neuroimaging has revealed important information about the neural correlates of attention, it is crucial to better understand how these processes are organized and executed in the brain in single subjects to guide theories and treatments for attention. Noninvasive brain stimulation is an effective tool to causally manipulate neural activity to detect the causal roles of circuits in behavior. We describe how combining transcranial magnetic stimulation (TMS) with modern precision network analysis in single-subject neuroimaging could test the roles of regions, circuits, and networks in regulating attention as a pathway to improve treatment effect magnitudes and specificity.

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Though studied for over 100 years, the brain basis of attention is still queried.

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Complexity in frameworks for attention makes brain mapping difficult.

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Relevant brain networks vary significantly across subjects, challenging progress.

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Single-subject neuroimaging with TMS can improve our understanding of attention.

Resting-State functional networks of different topographic representations in the somatosensory cortex of macaque monkeys and humans

Information processing in the brain is mediated through a complex functional network architecture whose comprising nodes integrate and segregate themselves on different timescales. To gain an understanding of the network function it is imperative to identify and understand the network structure with respect to the underlying anatomical connectivity and the topographic organization. Here we show that the previously described resting-state network for the somatosensory area 3b comprises of distinct networks that are characteristic for different topographic representations. Seed-based resting-state functional connectivity analysis in macaque monkeys and humans using BOLD-fMRI signals from the face, the hand and rest of the medial somatosensory representations of area 3b revealed different correlation patterns. Both monkeys and humans have many similarities in the connectivity networks, although the networks are more complex in humans with many more nodes. In both the species face area network has the highest ipsilateral and contralateral connectivity, which included areas 3b and 4, and ventral premotor area. The area 3b hand network included ipsilateral hand representation in area 4. The emergent functional network structures largely reflect the known anatomical connectivity. Our results show that different body part representations in area 3b have independent functional networks perhaps reflecting differences in the behavioral use of different body parts. The results also show that large cortical areas if considered together, do not give a complete and accurate picture of the network architecture.

From iPS Cells to Rodents and Nonhuman Primates: Filling Gaps in Modeling Parkinson's Disease

Parkinson's disease (PD) is primarily known as a movement disorder because of typical clinical manifestations associated with the loss of dopaminergic neurons in the substantia nigra. However, it is now widely recognized that PD is a much more complex condition, with multiple and severe nonmotor features implicating additional brain areas and organs in the disease process. Pathologically, typical forms of PD are characterized by the accumulation of α-synuclein-rich protein inclusions known as Lewy bodies and Lewy neurites, although other types of protein inclusions are also often present in the brain. Familial forms of PD have provided a wealth of information about molecular pathways leading to neurodegeneration, but only to add to the complexity of the problem and uncover new knowledge gaps. Therefore, modeling PD in the laboratory has become increasingly challenging. Here, we discuss knowledge gaps and challenges in the use of laboratory models for the study of a disease that is clinically heterogeneous and multifactorial. We propose that the combined use of patient-derived cells and animal models, along with current technological tools, will not only expand our molecular and pathophysiological understanding of PD, but also assist in the identification of therapeutic strategies targeting relevant pathogenic pathways. © 2020 International Parkinson and Movement Disorder Society.

Aberrant Advanced Cognitive and Attention-Related Brain Networks in Parkinson's Disease with Freezing of Gait

Background

Freezing of gait (FOG) is a disabling gait disorder influencing patients with Parkinson's disease (PD). Accumulating evidence suggests that FOG is related to the functional alterations within brain networks. We investigated the changes in brain resting-state functional connectivity (FC) in patients with PD with FOG (FOG+) and without FOG (FOG-).

Methods

Resting-state functional magnetic resonance imaging (RS-fMRI) data were collected from 55 PD patients (25 FOG+ and 30 FOG-) and 26 matched healthy controls (HC). Differences in intranetwork connectivity between FOG+, FOG-, and HC individuals were explored using independent component analysis (ICA).

Results

Seven resting-state networks (RSNs) with abnormalities, including motor, executive, and cognitive-related networks, were found in PD patients compared to HC. Compared to FOG- patients, FOG+ patients had increased FC in advanced cognitive and attention-related networks. In addition, the FC values of the auditory network and default mode network were positively correlated with the Gait and Falls Questionnaire (GFQ) and Freezing of Gait Questionnaire (FOGQ) scores in FOG+ patients.

Conclusions

Our findings suggest that the neural basis of PD is associated with impairments of multiple functional networks. Notably, alterations of advanced cognitive and attention-related networks rather than motor networks may be related to the mechanism of FOG.

Cross-species functional alignment reveals evolutionary hierarchy within the connectome

Evolution provides an important window into how cortical organization shapes function and vice versa. The complex mosaic of changes in brain morphology and functional organization that have shaped the mammalian cortex during evolution, complicates attempts to chart cortical differences across species. It limits our ability to fully appreciate how evolution has shaped our brain, especially in systems associated with unique human cognitive capabilities that lack anatomical homologues in other species. Here, we develop a function-based method for cross-species alignment that enables the quantification of homologous regions between humans and rhesus macaques, even when their location is decoupled from anatomical landmarks. Critically, we find cross-species similarity in functional organization reflects a gradient of evolutionary change that decreases from unimodal systems and culminates with the most pronounced changes in posterior regions of the default mode network (angular gyrus, posterior cingulate and middle temporal cortices). Our findings suggest that the establishment of the default mode network, as the apex of a cognitive hierarchy, has changed in a complex manner during human evolution – even within subnetworks.

Evolutional and developmental anatomical architecture of the left inferior frontal gyrus

The left inferior frontal gyrus (IFG) including Broca's area is involved in the processing of many language subdomains, and thus, research on the evolutional and human developmental characteristics of the left IFG will shed light on how language emerges and maturates. In this study, we used diffusion magnetic resonance imaging (dMRI) and resting-state functional MRI (fMRI) to investigate the evolutional and developmental patterns of the left IFG in humans (age 6-8, age 11-13, and age 16-18 years) and macaques. Tractography-based parcellation was used to define the subcomponents of left IFG and consistently identified four subregions in both humans and macaques. This parcellation scheme for left IFG in human was supported by specific coactivation patterns and functional characterization for each subregion. During evolution and development, we found increased functional balance, amplitude of low frequency fluctuations, functional integration, and functional couplings. We also observed higher fractional anisotropy values, i.e. better myelination of dorsal and ventral white matter language pathways during evolution and development. We assume that the resting-state functional connectivity and task-related coactivation mapping are associated with hierarchical language processing. Our findings have shown the evolutional and human developmental patterns of left IFG, and will contribute to the understanding of how the human language evolves and how atypical language developmental disorders may occur.

Studying the visual brain in its natural rhythm

How the brain fluidly orchestrates visual behavior is a central question in cognitive neuroscience. Researchers studying neural responses in humans and nonhuman primates have mapped out visual response profiles and cognitive modulation in a large number of brain areas, most often using pared down stimuli and highly controlled behavioral paradigms. The historical emphasis on reductionism has placed most studies at one pole of an inherent trade-off between strictly controlled experimental variables and open designs that monitor the brain during its natural modes of operation. This bias toward simplified experiments has strongly shaped the field of visual neuroscience, with little guarantee that the principles and concepts established within that framework will apply more generally. In recent years, a growing number of studies have begun to relax strict experimental control with the aim of understanding how the brain responds under more naturalistic conditions. In this article, we survey research that has explicitly embraced the complexity and rhythm of natural vision. We focus on those studies most pertinent to understanding high-level visual specializations in brains of humans and nonhuman primates. We conclude that representationalist concepts borne from conventional visual experiments fall short in their ability to capture the real-life visual operations undertaken by the brain. More naturalistic approaches, though fraught with experimental and analytic challenges, provide fertile ground for neuroscientists seeking new inroads to investigate how the brain supports core aspects of our daily visual experience.

Broca's Area Is Not a Natural Kind

Theories of human cognition prominently feature 'Broca's area', which causally contributes to a myriad of mental functions. However, Broca's area is not a monolithic, multipurpose unit - it is structurally and functionally heterogeneous. Some functions engaging (subsets of) this area share neurocognitive resources, whereas others rely on separable circuits. A decade of converging evidence has now illuminated a fundamental distinction between two subregions of Broca's area that likely play computationally distinct roles in cognition: one belongs to the domain-specific 'language network', the other to the domain-general 'multiple-demand (MD) network'. Claims about Broca's area should be (re)cast in terms of these (and other, as yet undetermined) functional components, to establish a cumulative research enterprise where empirical findings can be replicated and theoretical proposals can be meaningfully compared and falsified.

Biological Characteristics of Connection-Wise Resting-State Functional Connectivity Strength

Functional connectivity is defined as the statistical dependency of neurophysiological activity between 2 separate brain areas. To investigate the biological characteristics of resting-state functional connectivity (rsFC)-and in particular the significance of connection-wise variation in time-series correlations-rsFC was compared with strychnine-based connectivity measured in the macaque. Strychnine neuronography is a historical technique that induces activity in cortical areas through means of local administration of the substance strychnine. Strychnine causes local disinhibition through GABA suppression and leads to subsequent activation of functional pathways. Multiple resting-state fMRI recordings were acquired in 4 macaques (examining in total 299 imaging runs) from which a group-averaged rsFC matrix was constructed. rsFC was observed to be higher (P < 0.0001) between region-pairs with a strychnine-based connection as compared with region-pairs with no strychnine-based connection present. In particular, higher resting-state connectivity was observed in connections that were relatively stronger (weak < moderate < strong; P < 0.01) and in connections that were bidirectional (P < 0.0001) instead of unidirectional in strychnine-based connectivity. Our results imply that the level of correlation between brain areas as extracted from resting-state fMRI relates to the strength of underlying interregional functional pathways.

From State-to-Trait Meditation: Reconfiguration of Central Executive and Default Mode Networks

While brain default mode network (DMN) activation in human subjects has been associated with mind wandering, meditation practice has been found to suppress it and to increase psychological well-being. In addition to DMN activity reduction, experienced meditators (EMs) during meditation practice show an increased connectivity between the DMN and the central executive network (CEN).

While brain default mode network (DMN) activation in human subjects has been associated with mind wandering, meditation practice has been found to suppress it and to increase psychological well-being. In addition to DMN activity reduction, experienced meditators (EMs) during meditation practice show an increased connectivity between the DMN and the central executive network (CEN). However, the gradual change between DMN and CEN configuration from pre-meditation, during meditation, and post-meditation is unknown. Here, we investigated the change in DMN and CEN configuration by means of brain activity and functional connectivity (FC) analyses in EMs across three back-to-back functional magnetic resonance imaging (fMRI) scans: pre-meditation baseline (trait), meditation (state), and post-meditation (state-to-trait). Pre-meditation baseline group comparison was also performed between EMs and healthy controls (HCs). Meditation trait was characterized by a significant reduction in activity and FC within DMN and increased anticorrelations between DMN and CEN. Conversely, meditation state and meditation state-to-trait periods showed increased activity and FC within the DMN and between DMN and CEN. However, the latter anticorrelations were only present in EMs with limited practice. The interactions between networks during these states by means of positive diametric activity (PDA) of the fractional amplitude of low-frequency fluctuations (fALFFs) defined as CEN fALFF¯ − DMN fALFF¯ revealed no trait differences but significant increases during meditation state that persisted in meditation state-to-trait. The gradual reconfiguration in DMN and CEN suggest a neural mechanism by which the CEN negatively regulates the DMN and is probably responsible for the long-term trait changes seen in meditators and reported psychological well-being.

Age-Related Declines in Motor Performance are Associated With Decreased Segregation of Large-Scale Resting State Brain Networks

Aging is typically associated with substantial declines in motor functioning as well as robust changes in the functional organization of brain networks. Previous research has investigated the link between these 2 age-varying factors but examinations were predominantly limited to the functional organization within motor-related brain networks. Little is known about the relationship between age-related behavioral impairments and changes in functional organization at the whole brain (i.e., multiple network) level. This knowledge gap is surprising given that the decreased segregation of brain networks (i.e., increased internetwork connectivity) can be considered a hallmark of the aging process. Accordingly, we investigated the association between declines in motor performance across the adult lifespan (20-75 years) and age-related modulations of functional connectivity within and between resting state networks. Results indicated that stronger internetwork resting state connectivity observed as a function of age was significantly related to worse motor performance. Moreover, performance had a significantly stronger association with the strength of internetwork as compared with intranetwork connectivity, including connectivity within motor networks. These findings suggest that age-related declines in motor performance may be attributed to a breakdown in the functional organization of large-scale brain networks rather than simply age-related connectivity changes within motor-related networks.

fMRI in Non-human Primate: A Review on Factors That Can Affect Interpretation and Dynamic Causal Modeling Application

Dynamic causal modeling (DCM)-a framework for inferring hidden neuronal states from brain activity measurements (e. g., fMRI) and their context-dependent modulation-was developed for human neuroimaging, and has not been optimized for non-human primate (NHP) studies, which are usually done under anesthesia. Animal neuroimaging studies offer the potential to improve effective connectivity modeling using DCM through combining functional imaging with invasive procedures such as in vivo optogenetic or electrical stimulation. Employing a Bayesian approach, model parameters are estimated based on prior knowledge of conditions that might be related to neural and BOLD dynamics (e.g., requires empirical knowledge about the range of plausible parameter values). As such, we address the following questions in this review: What factors need to be considered when applying DCM to NHP data? What differences in functional networks, cerebrovascular architecture and physiology exist between human and NHPs that are relevant for DCM application? How do anesthetics affect vascular physiology, BOLD contrast, and neural dynamics-particularly, effective communication within, and between networks? Considering the factors that are relevant for DCM application to NHP neuroimaging, we propose a strategy for modeling effective connectivity under anesthesia using an integrated physiologic-stochastic DCM (IPS-DCM).

Hemodynamic Correlates of Electrophysiological Activity in the Default Mode Network

Hemodynamic fluctuations in the default mode network (DMN), observed through functional magnetic resonance imaging (fMRI), have been linked to electrophysiological oscillations detected by electroencephalography (EEG). It has been reported that, among the electrophysiological oscillations, those in the alpha frequency range (8–13 Hz) are the most dominant during resting state. We hypothesized that DMN spatial configuration closely depends on the specific neuronal oscillations considered, and that alpha oscillations would mainly correlate with increased blood oxygen-level dependent (BOLD) signal in the DMN. To test this hypothesis, we used high-density EEG (hdEEG) data simultaneously collected with fMRI scanning in 20 healthy volunteers at rest. We first detected the DMN from source reconstructed hdEEG data for multiple frequency bands, and we then mapped the correlation between temporal profile of hdEEG-derived DMN activity and fMRI–BOLD signals on a voxel-by-voxel basis. In line with our hypothesis, we found that the correlation map associated with alpha oscillations, more than with any other frequency bands, displayed a larger overlap with DMN regions. Overall, our study provided further evidence for a primary role of alpha oscillations in supporting DMN functioning. We suggest that simultaneous EEG–fMRI may represent a powerful tool to investigate the neurophysiological basis of human brain networks.