In the face of ambiguity: intrinsic brain organization in development predicts one's bias toward positivity or negativity.

Exacerbated negativity bias, including in responses to ambiguity, represents a common phenotype of internalizing disorders. Individuals differ in their propensity toward positive or negative appraisals of ambiguity. This variability constitutes one's valence bias, a stable construct linked to mental health. Evidence suggests an initial negativity in response to ambiguity that updates via regulatory processes to support a more positive bias. Previous work implicates the amygdala and prefrontal cortex, and regions of the cingulo-opercular system, in this regulatory process. Nonetheless, the neurodevelopmental origins of valence bias remain unclear. The current study tests whether intrinsic brain organization predicts valence bias among 119 children and adolescents (6 to 17 years). Using whole-brain resting-state functional connectivity, a machine-learning model predicted valence bias (r = 0.20, P = 0.03), as did a model restricted to amygdala and cingulo-opercular system features (r = 0.19, P = 0.04). Disrupting connectivity revealed additional intra-system (e.g. fronto-parietal) and inter-system (e.g. amygdala to cingulo-opercular) connectivity important for prediction. The results highlight top-down control systems and bottom-up perceptual processes that influence valence bias in development. Thus, intrinsic brain organization informs the neurodevelopmental origins of valence bias, and directs future work aimed at explicating related internalizing symptomology.

Concussion-Related Disruptions to Hub Connectivity in the Default Mode Network Are Related to Symptoms and Cognition.

Concussions present with a myriad of symptomatic and cognitive concerns; however, the relationship between these functional disruptions and the underlying changes in the brain are not yet well understood. Hubs, or brain regions that are connected to many different functional networks, may be specifically disrupted after concussion. Given the implications in concussion research, we quantified hub disruption within the default mode network (DMN) and between the DMN and other brain networks. We collected resting-state functional magnetic resonance imaging data from collegiate student-athletes (n = 44) at three time points: baseline (before beginning their athletic season), acute post-injury (approximately 48h after a diagnosed concussion), and recovery (after starting return-to-play progression, but before returning to contact). We used self-reported symptoms and computerized cognitive assessments collected across similar time points to link these functional connectivity changes to clinical outcomes. Concussion resulted in increased connectivity between regions within the DMN compared with baseline and recovery, and this post-injury connectivity was more positively related to symptoms and more negatively related to visual memory performance compared with baseline and recovery. Further, concussion led to decreased connectivity between DMN hubs and visual network non-hubs relative to baseline and recovery, and this post-injury connectivity was more negatively related to somatic symptoms and more positively related to visual memory performance compared with baseline and recovery. Relationships between functional connectivity, symptoms, and cognition were not significantly different at baseline versus recovery. These results highlight a unique relationship between self-reported symptoms, visual memory performance, and acute functional connectivity changes involving DMN hubs after concussion in athletes. This may provide evidence for a disrupted balance of within- and between-network communication highlighting possible network inefficiencies after concussion. These results aid in our understanding of the pathophysiological disruptions after concussion and inform our understanding of the associations between disruptions in brain connectivity and specific clinical presentations acutely post-injury.

Brain activity associated with taste stimulation: A mechanism for neuroplastic change?

PURPOSE: Neuroplasticity may be enhanced by increasing brain activation and bloodflow in neural regions relevant to the target behavior. We administered precisely formulated and dosed taste stimuli to determine whether the associated brain activity patterns included areas that underlie swallowing control. METHODS: Five taste stimuli (unflavored, sour, sweet-sour, lemon, and orange suspensions) were administered in timing-regulated and temperature-controlled 3 mL doses via a customized pump/tubing system to 21 healthy adults during functional magnetic resonance imaging (fMRI). Whole-brain analyses of fMRI data assessed main effects of taste stimulation as well as differential effects of taste profile. RESULTS: Differences in brain activity associated with taste stimulation overall as well as specific stimulus type were observed in key taste and swallowing regions including the orbitofrontal cortex, insula, cingulate, and pre- and postcentral gyri. Overall, taste stimulation elicited increased activation in swallowing-related brain regions compared to unflavored trials. Different patterns of blood oxygen level-dependent (BOLD) signal were noted by taste profile. For most areas, sweet-sour and sour trials elicited increases in BOLD compared to unflavored trials within that region, whereas lemon and orange trials yielded reductions in BOLD. This was despite identical concentrations of citric acid and sweetener in the lemon, orange, and sweet-sour solutions. CONCLUSIONS: These results suggest that neural activity in swallowing-relevant regions can be amplified with taste stimuli and may be differentially affected by specific properties within very similar taste profiles. These findings provide critical foundational information for interpreting disparities in previous studies of taste effects on brain activity and swallowing function, defining optimal stimuli to increase brain activity in swallowing-relevant regions, and harnessing taste to enhance neuroplasticity and recovery for persons with swallowing disorders.

Constructing neural network models from brain data reveals representational transformations linked to adaptive behavior.

The human ability to adaptively implement a wide variety of tasks is thought to emerge from the dynamic transformation of cognitive information. We hypothesized that these transformations are implemented via conjunctive activations in "conjunction hubs"-brain regions that selectively integrate sensory, cognitive, and motor activations. We used recent advances in using functional connectivity to map the flow of activity between brain regions to construct a task-performing neural network model from fMRI data during a cognitive control task. We verified the importance of conjunction hubs in cognitive computations by simulating neural activity flow over this empirically-estimated functional connectivity model. These empirically-specified simulations produced above-chance task performance (motor responses) by integrating sensory and task rule activations in conjunction hubs. These findings reveal the role of conjunction hubs in supporting flexible cognitive computations, while demonstrating the feasibility of using empirically-estimated neural network models to gain insight into cognitive computations in the human brain.

Global connectivity fingerprints predict the domain generality of multiple-demand regions.

A set of distributed cognitive control networks are known to contribute to diverse cognitive demands, yet it is unclear how these networks gain this domain-general capacity. We hypothesized that this capacity is largely due to the particular organization of the human brain's intrinsic network architecture. Specifically, we tested the possibility that each brain region's domain generality is reflected in its level of global (hub-like) intrinsic connectivity as well as its particular global connectivity pattern ("connectivity fingerprint"). Consistent with prior work, we found that cognitive control networks exhibited domain generality as they represented diverse task context information covering sensory, motor response, and logic rule domains. Supporting our hypothesis, we found that the level of global intrinsic connectivity (estimated with resting-state functional magnetic resonance imaging [fMRI]) was correlated with domain generality during tasks. Further, using a novel information fingerprint mapping approach, we found that each cognitive control region's unique rule response profile("information fingerprint") could be predicted based on its unique intrinsic connectivity fingerprint and the information content in regions outside cognitive control networks. Together, these results suggest that the human brain's intrinsic network architecture supports its ability to represent diverse cognitive task information largely via the location of multiple-demand regions within the brain's global network organization.

Global connectivity of the fronto-parietal cognitive control network is related to depression symptoms in the general population.

We all vary in our mental health, even among people not meeting diagnostic criteria for mental illness. Understanding this individual variability may reveal factors driving the risk for mental illness, as well as factors driving subclinical problems that still adversely affect quality of life. To better understand the large-scale brain network mechanisms underlying this variability, we examined the relationship between mental health symptoms and resting-state functional connectivity patterns in cognitive control systems. One such system is the fronto-parietal cognitive control network (FPN). Changes in FPN connectivity may impact mental health by disrupting the ability to regulate symptoms in a goal-directed manner. Here we test the hypothesis that FPN dysconnectivity relates to mental health symptoms even among individuals who do not meet formal diagnostic criteria but may exhibit meaningful symptom variation. We found that depression symptoms severity negatively correlated with between-network global connectivity (BGC) of the FPN. This suggests that decreased connectivity between the FPN and the rest of the brain is related to increased depression symptoms in the general population. These findings complement previous clinical studies to support the hypothesis that global FPN connectivity contributes to the regulation of mental health symptoms across both health and disease.

Genetic Taster Status as a Mediator of Neural Activity and Swallowing Mechanics in Healthy Adults.

As part of a larger study examining relationships between taste properties and swallowing, we assessed the influence of genetic taster status (GTS) on measures of brain activity and swallowing physiology during taste stimulation in healthy men and women. Twenty-one participants underwent videofluoroscopic swallowing study (VFSS) and functional magnetic resonance imaging (fMRI) during trials of high-intensity taste stimuli. The precisely formulated mixtures included sour, sweet-sour, lemon, and orange taste profiles and unflavored controls. Swallowing physiology was characterized via computational analysis of swallowing mechanics plus other kinematic and temporal measures, all extracted from VFSS recordings. Whole-brain analysis of fMRI data assessed blood oxygen responses to neural activity associated with taste stimulation. Swallowing morphometry, kinematics, temporal measures, and neuroimaging analysis revealed differential responses by GTS. Supertasters exhibited increased amplitude of most pharyngeal movements, and decreased activity in the primary somatosensory cortex compared to nontasters and midtasters. These preliminary findings suggest baseline differences in swallowing physiology and the associated neural underpinnings associated with GTS. Given the potential implications for dysphagia risk and recovery patterns, GTS should be included as a relevant variable in future research regarding swallowing function and dysfunction.

Cognitive task information is transferred between brain regions via resting-state network topology.

Resting-state network connectivity has been associated with a variety of cognitive abilities, yet it remains unclear how these connectivity properties might contribute to the neurocognitive computations underlying these abilities. We developed a new approach-information transfer mapping-to test the hypothesis that resting-state functional network topology describes the computational mappings between brain regions that carry cognitive task information. Here, we report that the transfer of diverse, task-rule information in distributed brain regions can be predicted based on estimated activity flow through resting-state network connections. Further, we find that these task-rule information transfers are coordinated by global hub regions within cognitive control networks. Activity flow over resting-state connections thus provides a large-scale network mechanism for cognitive task information transfer and global information coordination in the human brain, demonstrating the cognitive relevance of resting-state network topology.

Corrigendum: Psychopaths Show Enhanced Amygdala Activation during Fear Conditioning.

[This corrects the article on p. 348 in vol. 7, PMID: 27014154.].

Activity flow over resting-state networks shapes cognitive task activations.

Resting-state functional connectivity (FC) has helped reveal the intrinsic network organization of the human brain, yet its relevance to cognitive task activations has been unclear. Uncertainty remains despite evidence that resting-state FC patterns are highly similar to cognitive task activation patterns. Identifying the distributed processes that shape localized cognitive task activations may help reveal why resting-state FC is so strongly related to cognitive task activations. We found that estimating task-evoked activity flow (the spread of activation amplitudes) over resting-state FC networks allowed prediction of cognitive task activations in a large-scale neural network model. Applying this insight to empirical functional MRI data, we found that cognitive task activations can be predicted in held-out brain regions (and held-out individuals) via estimated activity flow over resting-state FC networks. This suggests that task-evoked activity flow over intrinsic networks is a large-scale mechanism explaining the relevance of resting-state FC to cognitive task activations.

Integrated Brain Network Architecture Supports Cognitive Task Performance.

Spontaneous fluctuations in neural activity and connectivity are thought to support cognition and behavior. In this issue of Neuron, Shine et al. (2016) describe a possible mechanism responsible for fluctuations in the human brain's network architecture that are related to rapid shifts in cognitive state.

Higher Intelligence Is Associated with Less Task-Related Brain Network Reconfiguration.

UNLABELLED: The human brain is able to exceed modern computers on multiple computational demands (e.g., language, planning) using a small fraction of the energy. The mystery of how the brain can be so efficient is compounded by recent evidence that all brain regions are constantly active as they interact in so-called resting-state networks (RSNs). To investigate the brain's ability to process complex cognitive demands efficiently, we compared functional connectivity (FC) during rest and multiple highly distinct tasks. We found previously that RSNs are present during a wide variety of tasks and that tasks only minimally modify FC patterns throughout the brain. Here, we tested the hypothesis that, although subtle, these task-evoked FC updates from rest nonetheless contribute strongly to behavioral performance. One might expect that larger changes in FC reflect optimization of networks for the task at hand, improving behavioral performance. Alternatively, smaller changes in FC could reflect optimization for efficient (i.e., small) network updates, reducing processing demands to improve behavioral performance. We found across three task domains that high-performing individuals exhibited more efficient brain connectivity updates in the form of smaller changes in functional network architecture between rest and task. These smaller changes suggest that individuals with an optimized intrinsic network configuration for domain-general task performance experience more efficient network updates generally. Confirming this, network update efficiency correlated with general intelligence. The brain's reconfiguration efficiency therefore appears to be a key feature contributing to both its network dynamics and general cognitive ability. SIGNIFICANCE STATEMENT: The brain's network configuration varies based on current task demands. For example, functional brain connections are organized in one way when one is resting quietly but in another way if one is asked to make a decision. We found that the efficiency of these updates in brain network organization is positively related to general intelligence, the ability to perform a wide variety of cognitively challenging tasks well. Specifically, we found that brain network configuration at rest was already closer to a wide variety of task configurations in intelligent individuals. This suggests that the ability to modify network connectivity efficiently when task demands change is a hallmark of high intelligence.

Psychopaths Show Enhanced Amygdala Activation during Fear Conditioning.

Psychopathy is a personality disorder characterized by emotional deficits and a failure to inhibit impulsive behavior and is often subdivided into "primary" and "secondary" psychopathic subtypes. The maladaptive behavior related to primary psychopathy is thought to reflect constitutional "fearlessness," while the problematic behavior related to secondary psychopathy is motivated by other factors. The fearlessness observed in psychopathy has often been interpreted as reflecting a fundamental deficit in amygdala function, and previous studies have provided support for a low-fear model of psychopathy. However, many of these studies fail to use appropriate screening procedures, use liberal inclusion criteria, or have used unconventional approaches to assay amygdala function. We measured brain activity with BOLD imaging in primary and secondary psychopaths and non-psychopathic control subjects during Pavlovian fear conditioning. In contrast to the low-fear model, we observed normal fear expression in primary psychopaths. Psychopaths also displayed greater differential BOLD activity in the amygdala relative to matched controls. Inverse patterns of activity were observed in the anterior cingulate cortex (ACC) for primary versus secondary psychopaths. Primary psychopaths exhibited a pattern of activity in the dorsal and ventral ACC consistent with enhanced fear expression, while secondary psychopaths exhibited a pattern of activity in these regions consistent with fear inhibition. These results contradict the low-fear model of psychopathy and suggest that the low fear observed for psychopaths in previous studies may be specific to secondary psychopaths.

Eye Movements Index Implicit Memory Expression in Fear Conditioning.

The role of contingency awareness in simple associative learning experiments with human participants is currently debated. Since prior work suggests that eye movements can index mnemonic processes that occur without awareness, we used eye tracking to better understand the role of awareness in learning aversive Pavlovian conditioning. A complex real-world scene containing four embedded household items was presented to participants while skin conductance, eye movements, and pupil size were recorded. One item embedded in the scene served as the conditional stimulus (CS). One exemplar of that item (e.g. a white pot) was paired with shock 100 percent of the time (CS+) while a second exemplar (e.g. a gray pot) was never paired with shock (CS-). The remaining items were paired with shock on half of the trials. Participants rated their expectation of receiving a shock during each trial, and these expectancy ratings were used to identify when (i.e. on what trial) each participant became aware of the programmed contingencies. Disproportionate viewing of the CS was found both before and after explicit contingency awareness, and patterns of viewing distinguished the CS+ from the CS-. These observations are consistent with "dual process" models of fear conditioning, as they indicate that learning can be expressed in patterns of viewing prior to explicit contingency awareness.

Functionally distinct amygdala subregions identified using DTI and high-resolution fMRI.

Although the amygdala is often directly linked with fear and emotion, amygdala neurons are activated by a wide variety of emotional and non-emotional stimuli. Different subregions within the amygdala may be engaged preferentially by different aspects of emotional and non-emotional tasks. To test this hypothesis, we measured and compared the effects of novelty and fear on amygdala activity. We used high-resolution blood oxygenation level-dependent (BOLD) imaging and streamline tractography to subdivide the amygdala into three distinct functional subunits. We identified a laterobasal subregion connected with the visual cortex that responds generally to visual stimuli, a non-projecting region that responds to salient visual stimuli, and a centromedial subregion connected with the diencephalon that responds only when a visual stimulus predicts an aversive outcome. We provide anatomical and functional support for a model of amygdala function where information enters through the laterobasal subregion, is processed by intrinsic circuits in the interspersed tissue, and is then passed to the centromedial subregion, where activation leads to behavioral output.

Rapid amygdala responses during trace fear conditioning without awareness.

The role of consciousness in learning has been debated for nearly 50 years. Recent studies suggest that conscious awareness is needed to bridge the gap when learning about two events that are separated in time, as is true for trace fear conditioning. This has been repeatedly shown and seems to apply to other forms of classical conditioning as well. In contrast to these findings, we show that individuals can learn to associate a face with the later occurrence of a shock, even if they are unable to perceive the face. We used a novel application of magnetoencephalography (MEG) to non-invasively record neural activity from the amygdala, which is known to be important for fear learning. We demonstrate rapid (∼ 170-200 ms) amygdala responses during the stimulus free period between the face and the shock. These results suggest that unperceived faces can serve as signals for impending threat, and that rapid, automatic activation of the amygdala contributes to this process. In addition, we describe a methodology that can be applied in the future to study neural activity with MEG in other subcortical structures.

How to detect amygdala activity with magnetoencephalography using source imaging.

In trace fear conditioning a conditional stimulus (CS) predicts the occurrence of the unconditional stimulus (UCS), which is presented after a brief stimulus free period (trace interval)(1). Because the CS and UCS do not co-occur temporally, the subject must maintain a representation of that CS during the trace interval. In humans, this type of learning requires awareness of the stimulus contingencies in order to bridge the trace interval(2-4). However when a face is used as a CS, subjects can implicitly learn to fear the face even in the absence of explicit awareness*. This suggests that there may be additional neural mechanisms capable of maintaining certain types of "biologically-relevant" stimuli during a brief trace interval. Given that the amygdala is involved in trace conditioning, and is sensitive to faces, it is possible that this structure can maintain a representation of a face CS during a brief trace interval. It is challenging to understand how the brain can associate an unperceived face with an aversive outcome, even though the two stimuli are separated in time. Furthermore investigations of this phenomenon are made difficult by two specific challenges. First, it is difficult to manipulate the subject's awareness of the visual stimuli. One common way to manipulate visual awareness is to use backward masking. In backward masking, a target stimulus is briefly presented (< 30 msec) and immediately followed by a presentation of an overlapping masking stimulus(5). The presentation of the mask renders the target invisible(6-8). Second, masking requires very rapid and precise timing making it difficult to investigate neural responses evoked by masked stimuli using many common approaches. Blood-oxygenation level dependent (BOLD) responses resolve at a timescale too slow for this type of methodology, and real time recording techniques like electroencephalography (EEG) and magnetoencephalography (MEG) have difficulties recovering signal from deep sources. However, there have been recent advances in the methods used to localize the neural sources of the MEG signal(9-11). By collecting high-resolution MRI images of the subject's brain, it is possible to create a source model based on individual neural anatomy. Using this model to "image" the sources of the MEG signal, it is possible to recover signal from deep subcortical structures, like the amygdala and the hippocampus*.

Dissociation between implicit and explicit responses in postconditioning UCS revaluation after fear conditioning in humans.

The nature of the relationship between explicit and implicit learning is a topic of considerable debate. To investigate this relationship we conducted two experiments on postconditioning revaluation of the unconditional stimulus (UCS) in human fear conditioning. In Experiment 1, the intensity of the UCS was decreased after acquisition for one group (devaluation) and held constant for another group (control). A subsequent test revealed that even though both groups exhibited similar levels of UCS expectancy, the devaluation group had significantly smaller conditional skin conductance responses. The devaluation effect was not explained by differences in the explicit estimates of UCS probability or explicit knowledge that the UCS intensity had changed. In Experiment 2, the value of the UCS was increased after acquisition for one group (inflation) and held constant for another group (control). Test performance revealed that UCS inflation did not alter expectancy ratings, but the inflation group exhibited larger learned skin conductance responses than the control group. The inflation effect was not explained by differences in the explicit estimates of UCS probability or explicit knowledge that the UCS intensity had changed. The SCR revaluation effect was not dependent on explicit memory processes in either experiment. In both experiments we found differences on an implicit measure of learning in the absence of changes in explicit measures. Together, the differences observed between expectancy measures and skin conductance support the idea that these responses might reflect different types of memory formed during the same training procedure and be supported by separate neural systems.

The interplay of attention and emotion: top-down attention modulates amygdala activation in psychopathy.

Psychopathic behavior has long been attributed to a fundamental deficit in fear that arises from impaired amygdala function. Growing evidence has demonstrated that fear-potentiated startle (FPS) and other psychopathy-related deficits are moderated by focus of attention, but to date, no work on adult psychopathy has examined attentional modulation of the amygdala or concomitant recruitment of relevant attention-related circuitry. Consistent with previous FPS findings, here we report that psychopathy-related differences in amygdala activation appear and disappear as a function of goal-directed attention. Specifically, decreased amygdala activity was observed in psychopathic offenders only when attention was engaged in an alternative goal-relevant task prior to presenting threat-relevant information. Under this condition, psychopaths also exhibited greater activation in selective-attention regions of the lateral prefrontal cortex (LPFC) than did nonpsychopaths, and this increased LPFC activation mediated psychopathy's association with decreased amygdala activation. In contrast, when explicitly attending to threat, amygdala activation did not differ in psychopaths and nonpsychopaths. This pattern of amygdala activation highlights the potential role of LPFC in mediating the failure of psychopathic individuals to process fear and other important information when it is peripheral to the primary focus of goal-directed attention.

Resting-state connectivity of the amygdala is altered following Pavlovian fear conditioning.

Neural plasticity in the amygdala is necessary for the acquisition and storage of memory in Pavlovian fear conditioning, but most neuroimaging studies have focused only on stimulus-evoked responses during the conditioning session. This study examined changes in the resting-state functional connectivity (RSFC) of the amygdala before and after Pavlovian fear conditioning, an emotional learning task. Behavioral results from the conditioning session revealed that participants learned normally and fMRI data recorded during learning identified a number of stimulus-evoked changes that were consistent with previous work. A direct comparison between the pre- and post-conditioning amygdala connectivity revealed a region of dorsal prefrontal cortex (PFC) in the superior frontal gyrus that showed a significant increase in connectivity following the conditioning session. A behavioral measure of explicit memory performance was positively correlated with the change in amygdala connectivity within a neighboring region in the superior frontal gyrus. Additionally, an implicit autonomic measure of conditioning was positively correlated with the change in connectivity between the amygdala and the anterior cingulate cortex (ACC). The resting-state data show that amygdala connectivity is altered following Pavlovian fear conditioning and that these changes are also related to behavioral outcomes. These alterations may reflect the operation of a consolidation process that strengthens neural connections to support memory after the learning event.