The insula is a brain structure implicated in disparate cognitive, affective, and regulatory functions, including interoceptive awareness, emotional responses, and empathic processes. While classically considered a limbic region, recent evidence from network analysis suggests a critical role for the insula, particularly the anterior division, in high-level cognitive control and attentional processes. The crucial insight and view we present here is of the anterior insula as an integral hub in mediating dynamic interactions between other large-scale brain networks involved in externally oriented attention and internally oriented or self-related cognition. The model we present postulates that the insula is sensitive to salient events, and that its core function is to mark such events for additional processing and initiate appropriate control signals. The anterior insula and the anterior cingulate cortex form a "salience network" that functions to segregate the most relevant among internal and extrapersonal stimuli in order to guide behavior. Within the framework of our network model, the disparate functions ascribed to the insula can be conceptualized by a few basic mechanisms: (1) bottom-up detection of salient events, (2) switching between other large-scale networks to facilitate access to attention and working memory resources when a salient event is detected, (3) interaction of the anterior and posterior insula to modulate autonomic reactivity to salient stimuli, and (4) strong functional coupling with the anterior cingulate cortex that facilitates rapid access to the motor system. In this manner, with the insula as its integral hub, the salience network assists target brain regions in the generation of appropriate behavioral responses to salient stimuli. We suggest that this framework provides a parsimonious account of insula function in neurotypical adults, and may provide novel insights into the neural basis of disorders of affective and social cognition.
Whether we feel sympathy for another, listen to our heartbeat, experience pain or negotiate, the insular cortex is thought to integrate perceptions, emotions, thoughts, and plans into one subjective image of "our world". The insula has hence been ascribed an integrative role, linking information from diverse functional systems. Nevertheless, various anatomical and functional studies in humans and non-human primates also indicate a functional differentiation of this region. In order to investigate this functional differentiation as well as the mechanisms of the functional integration in the insula, we performed activation-likelihood-estimation (ALE) meta-analyses of 1,768 functional neuroimaging experiments. The analysis revealed four functionally distinct regions on the human insula, which map to the social-emotional, the sensorimotor, the olfacto-gustatory, and the cognitive network of the brain. Sensorimotor tasks activated the mid-posterior and social-emotional tasks the anterior-ventral insula. In the central insula activation by olfacto-gustatory stimuli was found, and cognitive tasks elicited activation in the anterior-dorsal region. A conjunction analysis across these domains revealed that aside from basic somatosensory and motor processes all tested functions overlapped on the anterior-dorsal insula. This overlap might constitute a correlate for a functional integration between different functional systems and thus reflect a link between them necessary to integrate different qualities into a coherent experience of the world and setting the context for thoughts and actions.
The neural networks that putatively modulate aspects of normal emotional behavior have been implicated in the pathophysiology of mood disorders by converging evidence from neuroimaging, neuropathological and lesion analysis studies. These networks involve the medial prefrontal cortex (MPFC) and closely related areas in the medial and caudolateral orbital cortex (medial prefrontal network), amygdala, hippocampus, and ventromedial parts of the basal ganglia, where alterations in grey matter volume and neurophysiological activity are found in cases with recurrent depressive episodes. Such findings hold major implications for models of the neurocircuits that underlie depression. In particular evidence from lesion analysis studies suggests that the MPFC and related limbic and striato-pallido-thalamic structures organize emotional expression. The MPFC is part of a larger “default system” of cortical areas that include the dorsal PFC, mid- and posterior cingulate cortex, anterior temporal cortex, and entorhinal and parahippocampal cortex, which has been implicated in self-referential functions. Dysfunction within and between structures in this circuit may induce disturbances in emotional behavior and other cognitive aspects of depressive syndromes in humans. Further, because the MPFC and related limbic structures provide forebrain modulation over visceral control structures in the hypothalamus and brainstem, their dysfunction can account for the disturbances in autonomic regulation and neuroendocrine responses that are associated with mood disorders. This paper discusses these systems together with the neurochemical systems that impinge on them and form the basis for most pharmacological therapies.
It is commonly assumed that functional brain connectivity reflects structural brain connectivity. The exact relationship between structure and function, however, might not be straightforward. In this review we aim to examine how our understanding of the relationship between structure and function in the 'resting' brain has advanced over the last several years. We discuss eight articles that directly compare resting-state functional connectivity with structural connectivity and three clinical case studies of patients with limited white matter connections between the cerebral hemispheres. All studies examined show largely convergent results: the strength of resting-state functional connectivity is positively correlated with structural connectivity strength. However, functional connectivity is also observed between regions where there is little or no structural connectivity, which most likely indicates functional correlations mediated by indirect structural connections (i.e. via a third region). As the methodologies for measuring structural and functional connectivity continue to improve and their complementary strengths are applied in parallel, we can expect important advances in our diagnostic and prognostic capacities in diseases like Alzheimer's, multiple sclerosis, and stroke.
The descending projections from motor cortex share many features with top-down or backward connections in visual cortex; for example, corticospinal projections originate in infragranular layers, are highly divergent and (along with descending cortico-cortical projections) target cells expressing NMDA receptors. This is somewhat paradoxical because backward modulatory characteristics would not be expected of driving motor command signals. We resolve this apparent paradox using a functional characterisation of the motor system based on Helmholtz’s ideas about perception; namely, that perception is inference on the causes of visual sensations. We explain behaviour in terms of inference on the causes of proprioceptive sensations. This explanation appeals to active inference, in which higher cortical levels send descending proprioceptive predictions, rather than motor commands. This process mirrors perceptual inference in sensory cortex, where descending connections convey predictions, while ascending connections convey prediction errors. The anatomical substrate of this recurrent message passing is a hierarchical system consisting of functionally asymmetric driving (ascending) and modulatory (descending) connections: an arrangement that we show is almost exactly recapitulated in the motor system, in terms of its laminar, topographic and physiological characteristics. This perspective casts classical motor reflexes as minimising prediction errors and may provide a principled explanation for why motor cortex is agranular.
Recent research has shown that social anxiety disorder (SAD) is accompanied by abnormalities in brain functional connections. However, these findings are based on group comparisons, and, therefore, little is known about whether functional connections could be used in the diagnosis of an individual patient with SAD. Here, we explored the potential of the functional connectivity to be used for SAD diagnosis. Twenty patients with SAD and 20 healthy controls were scanned using resting-state functional magnetic resonance imaging. The whole brain was divided into 116 regions based on automated anatomical labeling atlas. The functional connectivity between each pair of regions was computed using Pearson’s correlation coefficient and used as classification feature. Multivariate pattern analysis was then used to classify patients from healthy controls. The pattern classifier was designed using linear support vector machine. Experimental results showed a correct classification rate of 82.5 % (p < 0.001) with sensitivity of 85.0 % and specificity of 80.0 %, using a leave-one-out cross-validation method. It was found that the consensus connections used to distinguish SAD were largely located within or across the default mode network, visual network, sensory-motor network, affective network, and cerebellar regions. Specifically, the right orbitofrontal region exhibited the highest weight in classification. The current study demonstrated that functional connectivity had good diagnostic potential for SAD, thus providing evidence for the possible use of whole brain functional connectivity as a complementary tool in clinical diagnosis. In addition, this study confirmed previous work and described novel pathophysiological mechanisms of SAD.
Morally judicious behavior forms the fabric of human sociality. Here, we sought to investigate neural activity associated with different facets of moral thought. Previous research suggests that the cognitive and emotional sources of moral decisions might be closely related to theory of mind, an abstract-cognitive skill, and empathy, a rapid-emotional skill. That is, moral decisions are thought to crucially refer to other persons’ representation of intentions and behavioral outcomes as well as (vicariously experienced) emotional states. We thus hypothesized that moral decisions might be implemented in brain areas engaged in ‘theory of mind’ and empathy. This assumption was tested by conducting a large-scale activation likelihood estimation (ALE) meta-analysis of neuroimaging studies, which assessed 2,607 peak coordinates from 247 experiments in 1,790 participants. The brain areas that were consistently involved in moral decisions showed more convergence with the ALE analysis targeting theory of mind versus empathy. More specifically, the neurotopographical overlap between morality and empathy disfavors a role of affective sharing during moral decisions. Ultimately, our results provide evidence that the neural network underlying moral decisions is probably domain-global and might be dissociable into cognitive and affective sub-systems.
There is now a wealth of evidence that anterior insular and anterior cingulate cortices have a close functional relationship, such that they may be considered together as input and output regions of a functional system. This system is typically engaged across cognitive, affective, and behavioural contexts, suggesting that it is of fundamental importance for mental life. Here, we review the literature and reinforce the case that these brain regions are crucial, firstly, for the production of subjective feelings and, secondly, for co-ordinating appropriate responses to internal and external events. This model seeks to integrate higher-order cortical functions with sensory representation and autonomic control: it is argued that feeling states emerge from the raw data of sensory (including interoceptive) inputs and are integrated through representations in conscious awareness. Correspondingly, autonomic nervous system reactivity is particularly important amongst the responses that accompany conscious experiences. Potential clinical implications are also discussed.
This article addresses the neuroanatomical evidence for a progression of integrative representations of affective feelings from the body that lead to an ultimate representation of all feelings in the bilateral anterior insulae, or "the sentient self." Evidence for somatotopy in the primary interoceptive sensory cortex is presented, and the organization of the mid-insula and the anterior insula is discussed. Issues that need to be addressed are highlighted. A possible basis for subjectivity in a cinemascopic model of awareness is presented.
Functional neuroimaging investigations in the fields of social neuroscience and neuroeconomics indicate that the anterior insular cortex (AI) is consistently involved in empathy, compassion, and interpersonal phenomena such as fairness and cooperation. These findings suggest that AI plays an important role in social emotions, hereby defined as affective states that arise when we interact with other people and that depend on the social context. After we link the role of AI in social emotions to interoceptive awareness and the representation of current global emotional states, we will present a model suggesting that AI is not only involved in representing current states, but also in predicting emotional states relevant to the self and others. This model also proposes that AI enables us to learn about emotional states as well as about the uncertainty attached to events, and implies that AI plays a dominant role in decision making in complex and uncertain environments. Our review further highlights that dorsal and ventro-central, as well as anterior and posterior subdivisions of AI potentially subserve different functions and guide different aspects of behavioral regulation. We conclude with a section summarizing different routes to understanding other people's actions, feelings and thoughts, emphasizing the notion that the predominant role of AI involves understanding others' feeling and bodily states rather than their action intentions or abstract beliefs.
The medial prefrontal cortex (mPFC) has been associated with diverse functions including attentional processes, visceromotor activity, decision making, goal directed behavior, and working memory. Using retrograde tracing techniques, we examined, compared, and contrasted afferent projections to the four divisions of the mPFC in the rat: the medial (frontal) agranular (AGm), anterior cingulate (AC), prelimbic (PL), and infralimbic (IL) cortices. Each division of the mPFC receives a unique set of afferent projections. There is a shift dorsoventrally along the mPFC from predominantly sensorimotor input to the dorsal mPFC (AGm and dorsal AC) to primarily ‘limbic’ input to the ventral mPFC (PL and IL). The AGm and dorsal AC receive afferent projections from widespread areas of the cortex (and associated thalamic nuclei) representing all sensory modalities. This information is presumably integrated at, and utilized by, the dorsal mPFC in goal directed actions. In contrast with the dorsal mPFC, the ventral mPFC receives significantly less cortical input overall and afferents from limbic as opposed to sensorimotor regions of cortex. The main sources of afferent projections to PL/IL are from the orbitomedial prefrontal, agranular insular, perirhinal and entorhinal cortices, the hippocampus, the claustrum, the medial basal forebrain, the basal nuclei of amygdala, the midline thalamus and monoaminergic nuclei of the brainstem. With a few exceptions, there are few projections from the hypothalamus to the dorsal or ventral mPFC. Accordingly, subcortical limbic information mainly reaches the mPFC via the midline thalamus and basal nuclei of amygdala. As discussed herein, based on patterns of afferent (as well as efferent) projections, PL is positioned to serve a direct role in cognitive functions homologous to dorsolateral PFC of primates, whereas IL appears to represent a visceromotor center homologous to the orbitomedial PFC of primates.
We review the literature on interoception as it relates to depression and anxiety, with a focus on belief, and alliesthesia. The connection between increased but noisy afferent interoceptive input, self-referential and belief-based states, and top-down modulation of poorly predictive signals is integrated into a neuroanatomical and processing model for depression and anxiety. The advantage of this conceptualization is the ability to specifically examine the interface between basic interoception, self-referential belief-based states, and enhanced top-down modulation to attenuate poor predictability. We conclude that depression and anxiety are not simply interoceptive disorders but are altered interoceptive states as a consequence of noisily amplified self-referential interoceptive predictive belief states.
Recently, there have been great interests for computer-aided diagnosis of Alzheimer’s disease (AD) and its prodromal stage, mild cognitive impairment (MCI). Unlike the previous methods that considered simple low-level features such as gray matter tissue volumes from MRI, and mean signal intensities from PET, in this paper, we propose a deep learning-based latent feature representation with a stacked auto-encoder (SAE). We believe that there exist latent non-linear complicated patterns inherent in the low-level features such as relations among features. Combining the latent information with the original features helps build a robust model in AD/MCI classification, with high diagnostic accuracy. Furthermore, thanks to the unsupervised characteristic of the pre-training in deep learning, we can benefit from the target-unrelated samples to initialize parameters of SAE, thus finding optimal parameters in fine-tuning with the target-related samples, and further enhancing the classification performances across four binary classification problems: AD vs. healthy normal control (HC), MCI vs. HC, AD vs. MCI, and MCI converter (MCI-C) vs. MCI non-converter (MCI-NC). In our experiments on ADNI dataset, we validated the effectiveness of the proposed method, showing the accuracies of 98.8, 90.7, 83.7, and 83.3 % for AD/HC, MCI/HC, AD/MCI, and MCI-C/MCI-NC classification, respectively. We believe that deep learning can shed new light on the neuroimaging data analysis, and our work presented the applicability of this method to brain disease diagnosis.
In humans, the anterior insula (aI) has been the topic of considerable research and ascribed a vast number of functional properties by way of neuroimaging and lesion studies. Here, we argue that the aI, at least in part, plays a role in domain-general attentional control and highlight studies (Dosenbach et al. 2006; Dosenbach et al. 2007) supporting this view. Additionally, we discuss a study (Ploran et al. 2007) that implicates aI in processes related to the capture of focal attention. Task-level control and focal attention may or may not reflect information processing supported by a single functional area (within the aI). Therefore, we apply a novel technique (Cohen et al. 2008) that utilizes resting state functional connectivity MRI (rs-fcMRI) to determine whether separable regions exist within the aI. rs-fcMRI mapping suggests that the ventral portion of the aI is distinguishable from more dorsal/anterior regions, which are themselves distinct from more posterior parts of the aI. When these regions are applied to functional MRI (fMRI) data, the ventral and dorsal/anterior regions support processes potentially related to both task-level control and focal attention, whereas the more posterior aI regions did not. These findings suggest that there exists some functional heterogeneity within aI that may subserve related but distinct types of higher-order cognitive processing.
We have recently shown that damage to the insula leads to a profound disruption of addiction to cigarette smoking (Naqvi et al., Science 315:531-534, 2007). Yet, there is little understanding of why the insula should play such an important role in an addictive behavior. A broad literature (much of it reviewed in this issue) has addressed the role of the insula in processes related to conscious interoception, emotional experience, and decision-making. Here, we review evidence for the role of the insula in drug addiction, and propose a novel theoretical framework for addiction in which the insula represents the interoceptive effects of drug taking, making this information available to conscious awareness, memory and executive functions. A central theme of this framework is that a primary goal for the addicted individual is to obtain the effects of the drug use ritual upon the body, and representations of this goal in interoceptive terms by the insula contribute to how addicted individuals feel, remember, and decide about taking drugs. This makes drug addiction like naturally motivated behaviors, such as eating and sex, for which an embodied ritual is the primary goal.
To detect erroneous action outcomes is necessary for flexible adjustments and therefore a prerequisite of adaptive, goal-directed behavior. While performance monitoring has been studied intensively over two decades and a vast amount of knowledge on its functional neuroanatomy has been gathered, much less is known about conscious error perception, often referred to as error awareness. Here, we review and discuss the conditions under which error awareness occurs, its neural correlates and underlying functional neuroanatomy. We focus specifically on the anterior insula, which has been shown to be (a) reliably activated during performance monitoring and (b) modulated by error awareness. Anterior insular activity appears to be closely related to autonomic responses associated with consciously perceived errors, although the causality and directions of these relationships still needs to be unraveled. We discuss the role of the anterior insula in generating versus perceiving autonomic responses and as a key player in balancing effortful task-related and resting-state activity. We suggest that errors elicit reactions highly reminiscent of an orienting response and may thus induce the autonomic arousal needed to recruit the required mental and physical resources. We discuss the role of norepinephrine activity in eliciting sufficiently strong central and autonomic nervous responses enabling the necessary adaptation as well as conscious error perception.
The right temporoparietal junction (rTPJ) is frequently associated with different capacities that to shift attention to unexpected stimuli (reorienting of attention) and to understand others’ (false) mental state [theory of mind (ToM), typically represented by false belief tasks]. Competing hypotheses either suggest the rTPJ representing a unitary region involved in separate cognitive functions or consisting of subregions subserving distinct processes. We conducted activation likelihood estimation (ALE) meta-analyses to test these hypotheses. A conjunction analysis across ALE meta-analyses delineating regions consistently recruited by reorienting of attention and false belief studies revealed the anterior rTPJ, suggesting an overarching role of this specific region. Moreover, the anatomical difference analysis unravelled the posterior rTPJ as higher converging in false belief compared with reorienting of attention tasks. This supports the concept of an exclusive role of the posterior rTPJ in the social domain. These results were complemented by meta-analytic connectivity mapping (MACM) and resting-state functional connectivity (RSFC) analysis to investigate whole-brain connectivity patterns in task-constrained and task-free brain states. This allowed for detailing the functional separation of the anterior and posterior rTPJ. The combination of MACM and RSFC mapping showed that the posterior rTPJ has connectivity patterns with typical ToM regions, whereas the anterior part of rTPJ co-activates with the attentional network. Taken together, our data suggest that rTPJ contains two functionally fractionated subregions: while posterior rTPJ seems exclusively involved in the social domain, anterior rTPJ is involved in both, attention and ToM, conceivably indicating an attentional shifting role of this region.
In neuroscience, there is a growing consensus that higher cognitive functions may be supported by distributed networks involving different cerebral regions, rather than by single brain areas. Communication within these networks is mediated by white matter tracts and is particularly prominent in the frontal lobes for the control and integration of information. However, the detailed mapping of frontal connections remains incomplete, albeit crucial to an increased understanding of these cognitive functions. Based on 47 high-resolution diffusion-weighted imaging datasets (age range 22–71 years), we built a statistical normative atlas of the frontal lobe connections in stereotaxic space, using state-of-the-art spherical deconvolution tractography. We dissected 55 tracts including U-shaped fibers. We further characterized these tracts by measuring their correlation with age and education level. We reported age-related differences in the microstructural organization of several, specific frontal fiber tracts, but found no correlation with education level. Future voxel-based analyses, such as voxel-based morphometry or tract-based spatial statistics studies, may benefit from our atlas by identifying the tracts and networks involved in frontal functions. Our atlas will also build the capacity of clinicians to further understand the mechanisms involved in brain recovery and plasticity, as well as assist clinicians in the diagnosis of disconnection or abnormality within specific tracts of individual patients with various brain diseases.
The anatomy and functional role of the inferior fronto-occipital fascicle (IFOF) remain poorly known. We accurately analyze its course and the anatomical distribution of its frontal terminations. We propose a classification of the IFOF in different subcomponents. Ten hemispheres (5 left, 5 right) were dissected with Klingler’s technique. In addition to the IFOF dissection, we performed a 4-T diffusion tensor imaging study on a single healthy subject. We identified two layers of IFOF. The first one is superficial and antero-superiorly directed, terminating in the inferior frontal gyrus. The second is deeper and consists of three portions: posterior, middle and anterior. The posterior component terminates in the middle frontal gyrus (MFG) and dorso-lateral prefrontal cortex. The middle component terminates in the MFG and lateral orbito-frontal cortex. The anterior one is directed to the orbito-frontal cortex and frontal pole. In vivo tractography study confirmed these anatomical findings. We suggest that the distribution of IFOF fibers within the frontal lobe corresponds to a fine functional segmentation. IFOF can be considered as a “multi-function” bundle, with each anatomical subcomponent subserving different brain processing. The superficial layer and the posterior component of the deep layer, which connects the occipital extrastriate, temporo-basal and inferior frontal cortices, might subserve semantic processing. The middle component of the deep layer could play a role in a multimodal sensory–motor integration. Finally, the anterior component of the deep layer might be involved in emotional and behavioral aspects.
Local functional homogeneity of the human cortex indicates the boundaries between functionally heterogeneous regions and varies remarkably across the cortical mantle. It is unclear whether these variations have the neurobiological and structural basis. We employed structural and resting-state functional magnetic resonance imaging scans from 482 healthy subjects and computed the vertex-wise regional homogeneity of low-frequency fluctuations (2dReHo) and five measures of cortical morphology. We then used these metrics to examine regional variation, morphological association and functional covariance network of 2dReHo. Within the ventral visual stream, increases of 2dReHo reflect reduced complexity of information processing or functional hierarchies. Along the divisions of the prefrontal cortex and posteromedial cortex, the gradients of 2dReHo revealed the hierarchical organization within the two association areas, respectively. Individual differences in 2dReHo are associated with those of cortical morphology, and their whole-brain inter-regional covariation is organized into a functional covariance network, comprising five hierarchically organized modules with hubs of both primary sensory and high-order association areas. These highly reproducible observations suggest that local functional homogeneity has neurobiological relevance that is likely determined by anatomical, developmental and neurocognitive factors and should serve as a neuroimaging marker to investigate the human brain function.