Decoding Neural Representations of Affective Scenes in Retinotopic Visual Cortex.

The perception of opportunities and threats in complex visual scenes represents one of the main functions of the human visual system. The underlying neurophysiology is often studied by having observers view pictures varying in affective content. It has been shown that viewing emotionally engaging, compared with neutral, pictures (1) heightens blood flow in limbic, frontoparietal, and anterior visual structures and (2) enhances the late positive event-related potential (LPP). The role of retinotopic visual cortex in this process has, however, been contentious, with competing theories predicting the presence versus absence of emotion-specific signals in retinotopic visual areas. Recording simultaneous electroencephalography-functional magnetic resonance imaging while observers viewed pleasant, unpleasant, and neutral affective pictures, and applying multivariate pattern analysis, we found that (1) unpleasant versus neutral and pleasant versus neutral decoding accuracy were well above chance level in retinotopic visual areas, (2) decoding accuracy in ventral visual cortex (VVC), but not in early or dorsal visual cortex, was correlated with LPP, and (3) effective connectivity from amygdala to VVC predicted unpleasant versus neutral decoding accuracy, whereas effective connectivity from ventral frontal cortex to VVC predicted pleasant versus neutral decoding accuracy. These results suggest that affective scenes evoke valence-specific neural representations in retinotopic visual cortex and that these representations are influenced by reentry signals from anterior brain regions.

The Microstructure of Attentional Control in the Dorsal Attention Network.

The top-down control of attention involves command signals arising chiefly in the dorsal attention network (DAN) in frontal and parietal cortex and propagating to sensory cortex to enable the selective processing of incoming stimuli based on their behavioral relevance. Consistent with this view, the DAN is active during preparatory (anticipatory) attention for relevant events and objects, which, in vision, may be defined by different stimulus attributes including their spatial location, color, motion, or form. How this network is organized to support different forms of preparatory attention to different stimulus attributes remains unclear. We propose that, within the DAN, there exist functional microstructures (patterns of activity) specific for controlling attention based on the specific information to be attended. To test this, we contrasted preparatory attention to stimulus location (spatial attention) and to stimulus color (feature attention), and used multivoxel pattern analysis to characterize the corresponding patterns of activity within the DAN. We observed different multivoxel patterns of BOLD activation within the DAN for the control of spatial attention (attending left vs. right) and feature attention (attending red vs. green). These patterns of activity for spatial and feature attentional control showed limited overlap with each other within the DAN. Our findings thus support a model in which the DAN has different functional microstructures for distinctive forms of top-down control of visual attention.

Theta Oscillations Index Frontal Decision-Making and Mediate Reciprocal Frontal-Parietal Interactions in Willed Attention.

Attention can be attracted reflexively by sensory signals, biased by learning or reward, or focused voluntarily based on momentary goals. When voluntary attention is focused by purely internal decision processes (will), rather than instructions via external cues, we call this "willed attention." In prior work, we reported ERP and fMRI correlates of willed spatial attention in trial-by-trial cuing tasks. Here we further investigated the oscillatory mechanisms of willed attention by contrasting the event-related EEG spectrogram between instructional and choice cues. Two experiments were conducted at 2 different sites using the same visuospatial attention paradigm. Consistent between the 2 experiments, we found increases in frontal theta power (starting at ~500 ms post cue) for willed attention relative to instructed attention. This frontal theta increase was accompanied by increased frontal-parietal theta-band coherence and bidirectional Granger causality. Additionally, the onset of attention-related posterior alpha power lateralization was delayed in willed attention relative to instructed attention, and the amount of delay was related to the timing of frontal theta increase. These results, replicated across 2 experiments, suggest that theta oscillations are the neuronal signals indexing decision-making in the frontal cortex, and mediating reciprocal communications between the frontal executive and parietal attentional control regions during willed attention.

Deciding where to attend: Large-scale network mechanisms underlying attention and intention revealed by graph-theoretic analysis.

The neural mechanisms by which intentions are transformed into actions remain poorly understood. We investigated the network mechanisms underlying spontaneous voluntary decisions about where to focus visual-spatial attention (willed attention). Graph-theoretic analysis of two independent datasets revealed that regions activated during willed attention form a set of functionally-distinct networks corresponding to the frontoparietal network, the cingulo-opercular network, and the dorsal attention network. Contrasting willed attention with instructed attention (where attention is directed by external cues), we observed that the dorsal anterior cingulate cortex was allied with the dorsal attention network in instructed attention, but shifted connectivity during willed attention to interact with the cingulo-opercular network, which then mediated communications between the frontoparietal network and the dorsal attention network. Behaviorally, greater connectivity in network hubs, including the dorsolateral prefrontal cortex, the dorsal anterior cingulate cortex, and the inferior parietal lobule, was associated with faster reaction times. These results, shown to be consistent across the two independent datasets, uncover the dynamic organization of functionally-distinct networks engaged to support intentional acts.

Top-down Modulation of Neural Activity in Anticipatory Visual Attention: Control Mechanisms Revealed by Simultaneous EEG-fMRI.

In covert visual attention, frontoparietal attention control areas are thought to issue signals to selectively bias sensory neurons to facilitate behaviorally relevant information and suppress distraction. We investigated the relationship between activity in attention control areas and attention-related modulation of posterior alpha activity using simultaneous electroencephalography (EEG) and functional magnetic resonance imaging in humans during cued visual-spatial attention. Correlating single-trial EEG alpha power with blood-oxygen-level dependent (BOLD) activity, we found that BOLD in the intraparietal sulcus (IPS) and left middle frontal gyrus was inversely correlated with occipital alpha power. Importantly, in IPS, inverse correlations were stronger for alpha within the hemisphere contralateral to the attended hemifield, implicating the IPS in the enhancement of task-relevant sensory areas. Positive BOLD-alpha correlations were observed in sensorimotor cortices and the default mode network, suggesting a mechanism of active suppression over task-irrelevant areas. The magnitude of cue-induced alpha lateralization was positively correlated with BOLD in dorsal anterior cingulate cortex and dorsolateral prefrontal cortex, implicating a role of executive control in attention. These results show that IPS and frontal executive areas are the main sources of biasing influences on task-relevant visual cortex, whereas task-irrelevant default mode network and sensorimotor cortex are inhibited during visual attention.

Proteomic Analysis Reveals the Leaf Color Regulation Mechanism in Chimera Hosta "Gold Standard" Leaves.

Leaf color change of variegated leaves from chimera species is regulated by fine-tuned molecular mechanisms. Hosta "Gold Standard" is a typical chimera Hosta species with golden-green variegated leaves, which is an ideal material to investigate the molecular mechanisms of leaf variegation. In this study, the margin and center regions of young and mature leaves from Hosta "Gold Standard", as well as the leaves from plants after excess nitrogen fertilization were studied using physiological and comparative proteomic approaches. We identified 31 differentially expressed proteins in various regions and development stages of variegated leaves. Some of them may be related to the leaf color regulation in Hosta "Gold Standard". For example, cytosolic glutamine synthetase (GS1), heat shock protein 70 (Hsp70), and chloroplastic elongation factor G (cpEF-G) were involved in pigment-related nitrogen synthesis as well as protein synthesis and processing. By integrating the proteomics data with physiological results, we revealed the metabolic patterns of nitrogen metabolism, photosynthesis, energy supply, as well as chloroplast protein synthesis, import and processing in various leaf regions at different development stages. Additionally, chloroplast-localized proteoforms involved in nitrogen metabolism, photosynthesis and protein processing implied that post-translational modifications were crucial for leaf color regulation. These results provide new clues toward understanding the mechanisms of leaf color regulation in variegated leaves.

Neural substrate of the late positive potential in emotional processing.

The late positive potential (LPP) is a reliable electrophysiological index of emotional perception in humans. Despite years of research, the brain structures that contribute to the generation and modulation of LPP are not well understood. Recording EEG and fMRI simultaneously, and applying a recently proposed single-trial ERP analysis method, we addressed the problem by correlating the single-trial LPP amplitude evoked by affective pictures with the blood oxygen level-dependent (BOLD) activity. Three results were found. First, relative to neutral pictures, pleasant and unpleasant pictures elicited enhanced LPP, as well as heightened BOLD activity in both visual cortices and emotion-processing structures such as amygdala and prefrontal cortex, consistent with previous findings. Second, the LPP amplitude across three picture categories was significantly correlated with BOLD activity in visual cortices, temporal cortices, amygdala, orbitofrontal cortex, and insula. Third, within each picture category, LPP-BOLD coupling revealed category-specific differences. For pleasant pictures, the LPP amplitude was coupled with BOLD in occipitotemporal junction, medial prefrontal cortex, amygdala, and precuneus, whereas for unpleasant pictures significant LPP-BOLD correlation was observed in ventrolateral prefrontal cortex, insula, and posterior cingulate cortex. These results suggest that LPP is generated and modulated by an extensive brain network composed of both cortical and subcortical structures associated with visual and emotional processing and the degree of contribution by each of these structures to the LPP modulation is valence specific.

Coupling between visual alpha oscillations and default mode activity.

Although, on average, the magnitude of alpha oscillations (8 to 12 Hz) is decreased in task-relevant cortices during externally oriented attention, its fluctuations have significant consequences, with increased level of alpha associated with decreased level of visual processing and poorer behavioral performance. Functional MRI signals exhibit similar fluctuations. The default mode network (DMN) is on average deactivated in cognitive tasks requiring externally oriented attention. Momentarily insufficient deactivation of DMN, however, is often accompanied by decreased efficiency in stimulus processing, leading to attentional lapses. These observations appear to suggest that visual alpha power and DMN activity may be positively correlated. To what extent such correlation is preserved in the resting state is unclear. We addressed this problem by recording simultaneous EEG-fMRI from healthy human participants under two resting-state conditions: eyes-closed and eyes-open. Short-time visual alpha power was extracted as time series, which was then convolved with a canonical hemodynamic response function (HRF), and correlated with blood-oxygen-level-dependent (BOLD) signals. It was found that visual alpha power was positively correlated with DMN BOLD activity only when the eyes were open; no such correlation existed when the eyes were closed. Functionally, this could be interpreted as indicating that (1) under the eyes-open condition, strong DMN activity is associated with reduced visual cortical excitability, which serves to block external visual input from interfering with introspective mental processing mediated by DMN, while weak DMN activity is associated with increased visual cortical excitability, which helps to facilitate stimulus processing, and (2) under the eyes-closed condition, the lack of external visual input renders such a gating mechanism unnecessary.

Effects of emotional conditioning on early visual processing: temporal dynamics revealed by ERP single-trial analysis.

Studies using event-related potentials (ERPs) have shown that affectively arousing stimuli enhance attention and perception. In addition, simple neutral stimuli, when paired with emotionally engaging unconditioned stimuli (i.e., the CS+) in classical conditioning paradigms, were found to evoke increased sensory responses as learning progresses, compared to responses elicited by the same stimuli not paired with a noxious stimulus (CS-). To date the detailed trial-to-trial temporal dynamics of this sensory facilitation process is not known. Signal averaging required for the ERP analysis eliminates trial-to-trial information of temporal cortical dynamics. In the current study, a novel single-trial analysis method called Analysis of Single-trial ERP and Ongoing activity (ASEO) was adopted to study the detailed electrocortical dynamics of sensory processing during classical aversive conditioning. Focusing on the P1 component of the ERP evoked by simple grating patterns serving as CS+ and CS-, we found that over a session of conditioning trials, there were three phases of P1 amplitude changes for both CS+ and CS-: (1) an initial decrease phase, (2) a subsequent increase phase, and (3) a final habituating phase. Tests on the rates of P1 amplitude changes in each of the three phases between CS+ and CS- conditions revealed differential effects of CS+ and CS- for all three phases. No such effects were found for a session of control trials where the same grating patterns were paired with checkerboards. We interpret these results as providing evidence supporting the view that emotional experience can modulate early visual processing and dynamics of perceptual learning.

Gating by inhibition during top-down control of willed attention.

In natural settings, the control of attention may be influenced both by external information as well as internal decision-making processes driven by intent (e.g. free will). In past studies of spatial attention, we and others have developed experimental paradigms that permit individuals to choose where to direct their attention on a trial-by-trial basis in the absence of instructive external cues - we term this willed attention. Here we investigate the electrophysiological correlates of willed attention by recording EEG activity when subjects decided to focus covert attention on one of two lateralized target locations versus when they decided to maintain attention at fixation. Independent of the direction of attention, decisions to attend, relative to decisions not to attend, resulted in significant increases in both frontal theta (4-7 Hz) power and central alpha (8-13 Hz) power. We found that focusing spatial attention, as indexed by occipital alpha lateralization was predicted across subjects by the decision-related alpha increases over central scalp regions, but not changes in frontal theta power. This finding is interpreted in terms of the Gating by Inhibition model, where the central alpha EEG signals reflect cortical inhibition of decision processes that lead to the expression of willed attention.

Machine Learning Models Identify Multimodal Measurements Highly Predictive of Transdiagnostic Symptom Severity for Mood, Anhedonia, and Anxiety.

BACKGROUND: Insights from neuroimaging-based biomarker research have not yet translated into clinical practice. This translational gap may stem from a focus on diagnostic classification, rather than on prediction of transdiagnostic psychiatric symptom severity. Currently, no transdiagnostic, multimodal predictive models of symptom severity that include neurobiological characteristics have emerged. METHODS: We built predictive models of 3 common symptoms in psychiatric disorders (dysregulated mood, anhedonia, and anxiety) from the Consortium for Neuropsychiatric Phenomics dataset (N = 272), which includes clinical scale assessments, resting-state functional magnetic resonance imaging (MRI), and structural MRI measures from patients with schizophrenia, bipolar disorder, and attention-deficit/hyperactivity disorder and healthy control subjects. We used an efficient, data-driven feature selection approach to identify the most predictive features from these high-dimensional data. RESULTS: This approach optimized modeling and explained 65% to 90% of variance across the 3 symptom domains, compared to 22% without using the feature selection approach. The top performing multimodal models retained a high level of interpretability that enabled several clinical and scientific insights. First, to our surprise, structural features did not substantially contribute to the predictive strength of these models. Second, the Temperament and Character Inventory scale emerged as a highly important predictor of symptom variation across diagnoses. Third, predictive resting-state functional MRI connectivity features were widely distributed across many intrinsic resting-state networks. CONCLUSIONS: Combining resting-state functional MRI with select questions from clinical scales enabled high prediction of symptom severity across diagnostically distinct patient groups and revealed that connectivity measures beyond a few intrinsic resting-state networks may carry relevant information for symptom severity.

Fear conditioning prompts sparser representations of conditioned threat in primary visual cortex.

Repeated exposure to threatening stimuli alters sensory responses. We investigated the underlying neural mechanism by re-analyzing previously published simultaneous electroencephalogram-functional magnetic resonance imaging (EEG-fMRI) data from humans viewing oriented gratings during Pavlovian fear conditioning. In acquisition, one grating (CS+) was paired with a noxious noise, the unconditioned stimulus (US). The other grating (CS-) was never paired with the US. In habituation, which preceded acquisition, and in extinction, the same two gratings were presented without US. Using fMRI multivoxel patterns in primary visual cortex during habituation as reference, we found that during acquisition, aversive learning selectively prompted systematic changes in multivoxel patterns evoked by CS+. Specifically, CS+ evoked voxel patterns in V1 became sparser as aversive learning progressed, and the sparsified pattern appeared to be preserved in extinction. Concomitant with the voxel pattern changes, occipital alpha oscillations were increasingly more desynchronized during CS+ (but not CS-) trials. Across acquisition trials, the rate of change in CS+-related alpha desynchronization was correlated with the rate of change in multivoxel pattern representations of CS+. Furthermore, alpha oscillations co-varied with blood-oxygen-level-dependent (BOLD) data in the ventral attention network, but not with BOLD in the amygdala. Thus, fear conditioning prompts persistent sparsification of voxel patterns evoked by threat, likely mediated by attention-related mechanisms.

Machine Learning Identifies Large-Scale Reward-Related Activity Modulated by Dopaminergic Enhancement in Major Depression.

BACKGROUND: Theoretical models have emphasized systems-level abnormalities in major depressive disorder (MDD). For unbiased yet rigorous evaluations of pathophysiological mechanisms underlying MDD, it is critically important to develop data-driven approaches that harness whole-brain data to classify MDD and evaluate possible normalizing effects of targeted interventions. Here, using an experimental therapeutics approach coupled with machine learning, we investigated the effect of a pharmacological challenge aiming to enhance dopaminergic signaling on whole-brain response to reward-related stimuli in MDD. METHODS: Using a double-blind, placebo-controlled design, we analyzed functional magnetic resonance imaging data from 31 unmedicated MDD participants receiving a single dose of 50 mg amisulpride (MDDAmisulpride), 26 MDD participants receiving placebo (MDDPlacebo), and 28 healthy control subjects receiving placebo (HCPlacebo) recruited through two independent studies. An importance-guided machine learning technique for model selection was used on whole-brain functional magnetic resonance imaging data probing reward anticipation and consumption to identify features linked to MDD (MDDPlacebo vs. HCPlacebo) and dopaminergic enhancement (MDDAmisulpride vs. MDDPlacebo). RESULTS: Highly predictive classification models emerged that distinguished MDDPlacebo from HCPlacebo (area under the curve = 0.87) and MDDPlacebo from MDDAmisulpride (area under the curve = 0.89). Although reward-related striatal activation and connectivity were among the most predictive features, the best truncated models based on whole-brain features were significantly better relative to models trained using striatal features only. CONCLUSIONS: Results indicate that in MDD, enhanced dopaminergic signaling restores abnormal activation and connectivity in a widespread network of regions. These findings provide new insights into the pathophysiology of MDD and pharmacological mechanism of antidepressants at the system level in addressing reward processing deficits among depressed individuals.

Amygdala Adaptation and Temporal Dynamics of the Salience Network in Conditioned Fear: A Single-Trial fMRI Study.

Research in rodents has established the role of the amygdaloid complex in defensive responses to conditioned threat. In human imaging studies, however, activation of the amygdala by conditioned threat cues is often not observed. One hypothesis states that this finding reflects adaptation of amygdaloid responses over time. We tested this hypothesis by estimating single-trial neural responses over a large number of conditioning trials. Functional MRI (fMRI) was recorded from 18 participants during classical differential fear conditioning: Participants viewed oriented grayscale grating stimuli (45° or 135°) presented centrally in random order. In the acquisition block, one grating (the CS+) was paired with a noxious noise, the unconditioned stimulus (US), on 25% of trials. The other grating, denoted CS-, was never paired with the US. Consistent with previous reports, BOLD in dorsal anterior cingulate cortex (dACC) and insula, but not the amygdala, was heightened when viewing CS+ stimuli that were not paired with US compared to CS- stimuli. Trial-by-trial analysis showed that over the course of acquisition, activity in the amygdala attenuated. Interestingly, activity in the dACC and insula also declined. Representational similarity analysis (RSA) corroborated these results, indicating that the voxel patterns evoked by CS+ and CS- in these brain regions became less distinguishable over time. Together, the present findings support the hypothesis that the lack of BOLD differences in the amygdaloid complex in many studies of classical conditioning is due to adaptation, and the adaptation effects may reflect changes in large-scale networks mediating aversive conditioning, particularly the salience network.

Amplitude of Sensorimotor Mu Rhythm Is Correlated with BOLD from Multiple Brain Regions: A Simultaneous EEG-fMRI Study.

The mu rhythm is a field oscillation in the ∼10Hz range over the sensorimotor cortex. For decades, the suppression of mu (event-related desynchronization) has been used to index movement planning, execution, and imagery. Recent work reports that non-motor processes, such as spatial attention and movement observation, also desynchronize mu, raising the possibility that the mu rhythm is associated with the activity of multiple brain regions and systems. In this study, we tested this hypothesis by recording simultaneous resting-state EEG-fMRI from healthy subjects. Independent component analysis (ICA) was applied to extract the mu components. The amplitude (power) fluctuations of mu were estimated as a time series using a moving-window approach, which, after convolving with a canonical hemodynamic response function (HRF), was correlated with blood-oxygen-level-dependent (BOLD) signals from the entire brain. Two main results were found. First, mu power was negatively correlated with BOLD from areas of the sensorimotor network, the attention control network, the putative mirror neuron system, and the network thought to support theory of mind. Second, mu power was positively correlated with BOLD from areas of the salience network, including anterior cingulate cortex and anterior insula. These results are consistent with the hypothesis that sensorimotor mu rhythm is associated with multiple brain regions and systems. They also suggest that caution should be exercised when attempting to interpret mu modulation in terms of a single brain network.

Age-Related Differences in the Modulation of Small-World Brain Networks during a Go/NoGo Task.

Although inter-regional phase synchrony of neural oscillations has been proposed as a plausible mechanism for response control, little is known about the possible effects due to normal aging. We recorded multi-channel electroencephalography (EEG) from healthy younger and older adults in a Go/NoGo task, and examined the aging effects on synchronous brain networks with graph theoretical analysis. We found that in both age groups, brain networks in theta, alpha or beta band for either response execution (Go) or response inhibition (NoGo) condition showed prominent small-world property. Furthermore, small-world property of brain networks showed significant differences between different task conditions. Further analyses of node degree suggested that frontal-central theta band phase synchrony was enhanced during response inhibition, whereas during response execution, increased phase synchrony was observed in beta band over central-parietal regions. More interestingly, these task-related modulations on brain networks were well preserved and even more robust in older adults compared with younger adults. Taken together, our findings not only suggest that response control involves synchronous brain networks in functionally-distinct frequency bands, but also indicate an increase in the recruitment of brain network resources due to normal aging.

Large-scale functional brain connectivity during emotional engagement as revealed by beta-series correlation analysis.

It has been hypothesized that the medial prefrontal cortex (mPFC) is a hub in the network that mediates appetitive responses whereas the amygdala is thought to mediate both aversive and appetitive processing. Both structures may facilitate adaptive responses to emotional challenge by linking perception, attention, memory, and motor circuits. We provide an initial exploration of these hypotheses by recording simultaneous EEG-fMRI in eleven participants viewing affective pictures. MPFC- and amygdala-seeded functional connectivity maps were generated by applying the beta-series correlation method. The mPFC-seeded correlation map encompassed visual regions, sensorimotor areas, prefrontal cortex, and medial temporal lobe structures, exclusively for pleasant content. For the amygdala-seeded correlation map, a similar set of distributed brain areas appeared in the unpleasant-neutral contrast, with the addition of structures such as the insula and thalamus. A substantially sparser network was recruited for the pleasant-neutral contrast. Using the late positive potential (LPP) to index the intensity of emotional engagement, functional connectivity was found to be stronger in trials with larger LPP. These results demonstrate that mPFC-mediated functional interactions are engaged specifically during appetitive processing, whereas the amygdala is coupled to distinct sets of brain regions during both aversive and appetitive processing. The strength of these interactions varies as a function of the intensity of emotional engagement.