Neural substrates of human fear generalization: A 7T-fMRI investigation.

Fear generalization - the tendency to interpret ambiguous stimuli as threatening due to perceptual similarity to a learned threat - is an adaptive process. Overgeneralization, however, is maladaptive and has been implicated in a number of anxiety disorders. Neuroimaging research has indicated several regions sensitive to effects of generalization, including regions involved in fear excitation (e.g., amygdala, insula) and inhibition (e.g., ventromedial prefrontal cortex). Research has suggested several other small brain regions may play an important role in this process (e.g., hippocampal subfields, bed nucleus of the stria terminalis [BNST], habenula), but, to date, these regions have not been examined during fear generalization due to limited spatial resolution of standard human neuroimaging. To this end, we utilized the high spatial resolution of 7T fMRI to characterize the neural circuits involved in threat discrimination and generalization. Additionally, we examined potential modulating effects of trait anxiety and intolerance of uncertainty on neural activation during threat generalization. In a sample of 31 healthy undergraduate students, significant positive generalization effects (i.e., greater activation for stimuli with increasing perceptual similarity to a learned threat cue) were observed in the visual cortex, thalamus, habenula and BNST, while negative generalization effects were observed in the dentate gyrus, CA1, and CA3. Associations with individual differences were underpowered, though preliminary findings suggested greater generalization in the insula and primary somatosensory cortex may be correlated with self-reported anxiety. Overall, findings largely support previous neuroimaging work on fear generalization and provide additional insight into the contributions of several previously unexplored brain regions.

Emotional Objectivity: Neural Representations of Emotions and Their Interaction with Cognition.

Recent advances in our understanding of information states in the human brain have opened a new window into the brain's representation of emotion. While emotion was once thought to constitute a separate domain from cognition, current evidence suggests that all events are filtered through the lens of whether they are good or bad for us. Focusing on new methods of decoding information states from brain activation, we review growing evidence that emotion is represented at multiple levels of our sensory systems and infuses perception, attention, learning, and memory. We provide evidence that the primary function of emotional representations is to produce unified emotion, perception, and thought (e.g., "That is a good thing") rather than discrete and isolated psychological events (e.g., "That is a thing. I feel good"). The emergent view suggests ways in which emotion operates as a fundamental feature of cognition, by design ensuring that emotional outcomes are the central object of perception, thought, and action.

Towards a state-space geometry of neural responses to natural scenes: A steady-state approach.

Our understanding of information processing by the mammalian visual system has come through a variety of techniques ranging from psychophysics and fMRI to single unit recording and EEG. Each technique provides unique insights into the processing framework of the early visual system. Here, we focus on the nature of the information that is carried by steady state visual evoked potentials (SSVEPs). To study the information provided by SSVEPs, we presented human participants with a population of natural scenes and measured the relative SSVEP response. Rather than focus on particular features of this signal, we focused on the full state-space of possible responses and investigated how the evoked responses are mapped onto this space. Our results show that it is possible to map the relatively high-dimensional signal carried by SSVEPs onto a 2-dimensional space with little loss. We also show that a simple biologically plausible model can account for a high proportion of the explainable variance (~73%) in that space. Finally, we describe a technique for measuring the mutual information that is available about images from SSVEPs. The techniques introduced here represent a new approach to understanding the nature of the information carried by SSVEPs. Crucially, this approach is general and can provide a means of comparing results across different neural recording methods. Altogether, our study sheds light on the encoding principles of early vision and provides a much needed reference point for understanding subsequent transformations of the early visual response space to deeper knowledge structures that link different visual environments.

Changes in EEG multiscale entropy and power-law frequency scaling during the human sleep cycle.

We explored changes in multiscale brain signal complexity and power-law scaling exponents of electroencephalogram (EEG) frequency spectra across several distinct global states of consciousness induced in the natural physiological context of the human sleep cycle. We specifically aimed to link EEG complexity to a statistically unified representation of the neural power spectrum. Further, by utilizing surrogate-based tests of nonlinearity we also examined whether any of the sleep stage-dependent changes in entropy were separable from the linear stochastic effects contained in the power spectrum. Our results indicate that changes of brain signal entropy throughout the sleep cycle are strongly time-scale dependent. Slow wave sleep was characterized by reduced entropy at short time scales and increased entropy at long time scales. Temporal signal complexity (at short time scales) and the slope of EEG power spectra appear, to a large extent, to capture a common phenomenon of neuronal noise, putatively reflecting cortical balance between excitation and inhibition. Nonlinear dynamical properties of brain signals accounted for a smaller portion of entropy changes, especially in stage 2 sleep.

Electrophysiological and phenomenological effects of short-term immersion in an altered sensory environment.

We examined the spontaneous cerebral electrophysiology and phenomenology during short-term perceptual deprivation consisting of an edgeless visual field combined with monotonous auditory input that eliminated potential grounding cues (multimodal Ganzfeld). Subjects (N = 22) were instructed to self-report perceptual fading using a button press. Relaxed wakefulness with closed eyes and viewing of a time-varying stimulus array served as control conditions. The power of parieto-occipital alpha rhythms during perceptual deprivation was midway between the eyes-closed and eyes-open conditions, with a state-specific frequency acceleration. Oscillatory alpha power remained enhanced in the multimodal Ganzfeld relative to viewing time-varying signals, despite no indication of diminished brain arousal. Subjects experienced a range of perceptual phenomena while in the altered sensory environment and individuals with faster alpha oscillations self-reported a greater number of fading episodes. We suggest that alpha-band electroencephalogram (EEG) dynamics signal internally oriented mentation in response to brief perceptual deprivation.

A practical comparison of algorithms for the measurement of multiscale entropy in neural time series data.

There is a broad family of statistical methods for capturing time series regularity, with increasingly widespread adoption by the neuroscientific community. A common feature of these methods is that they permit investigators to quantify the entropy of brain signals - an index of unpredictability/complexity. Despite the proliferation of algorithms for computing entropy from neural time series data there is scant evidence concerning their relative stability and efficiency. Here we evaluated several different algorithmic implementations (sample, fuzzy, dispersion and permutation) of multiscale entropy in terms of their stability across sessions, internal consistency and computational speed, accuracy and precision using a combination of electroencephalogram (EEG) and synthetic 1/ƒ noise signals. Overall, we report fair to excellent internal consistency and longitudinal stability over a one-week period for the majority of entropy estimates, with several caveats. Computational timing estimates suggest distinct advantages for dispersion and permutation entropy over other entropy estimates. Considered alongside the psychometric evidence, we suggest several ways in which researchers can maximize computational resources (without sacrificing reliability), especially when working with high-density M/EEG data or multivoxel BOLD time series signals.

Trajectories of resting frontal brain activity and psychopathology in female adolescents exposed to child maltreatment.

Resting frontal electroencephalogram (EEG) alpha asymmetry patterns reflecting different affective and motivational tendencies have been proposed as a putative mechanism underlying resilience among maltreated youth. This 2-year prospective study examined whether developmental stability of resting frontal alpha asymmetry moderated the relation between child maltreatment severity and psychopathology in female adolescents (n = 43; ages 12-16) recruited from child protection agencies. Results identified two trajectories of resting frontal asymmetry: 60.5% displayed stable right and 39.5% displayed stable left frontal alpha asymmetry. Although individuals with these alpha asymmetry profiles experienced comparable childhood trauma severity, adolescents with stable left alpha asymmetry and lower levels of trauma were less likely to present symptoms or an episode of posttraumatic stress disorder (PTSD) and depression over 2 years than those with stable right alpha asymmetry and lower levels of trauma. These findings suggest that developmental patterns of resting left frontal brain activity may buffer against psychopathology in maltreated female youth.

Differential aversive learning enhances orientation discrimination.

A number of recent studies have documented rapid changes in behavioural sensory acuity induced by aversive learning in the olfactory and auditory modalities. The effect of aversive learning on the discrimination of low-level features in the visual system of humans remains unclear. Here, we used a psychophysical staircase procedure to estimate discrimination thresholds for oriented grating stimuli, before and after differential aversive learning. We discovered that when a target grating orientation was conditioned with an aversive loud noise, it subsequently led to an improvement of discrimination acuity in nearly all subjects. However, no such change was observed in a control group conditioned to an orientation shifted by ±90° from the target. Our findings cannot be explained by contextual learning or sensitisation factors. The results converge with those reported in the olfactory modality and provide further evidence that early sensory systems can be rapidly modified by recently experienced reinforcement histories.

Multimodal Imaging Evidence for a Frontoparietal Modulation of Visual Cortex during the Selective Processing of Conditioned Threat.

Emotionally salient cues are detected more readily, remembered better, and evoke greater visual cortical responses compared with neutral stimuli. The current study used concurrent EEG-fMRI recordings to identify large-scale network interactions involved in the amplification of visual cortical activity when viewing aversively conditioned cues. To generate a continuous neural signal from pericalcarine visual cortex, we presented rhythmic (10/sec) phase-reversing gratings, the orientation of which predicted the presence (CS+) or absence (CS-) of a cutaneous electric shock (i.e., the unconditioned stimulus). The resulting single trial steady-state visual evoked potential (ssVEP) amplitude was regressed against the whole-brain BOLD signal, resulting in a measure of ssVEP-BOLD coupling. Across all trial types, ssVEP-BOLD coupling was observed in both primary and extended visual cortical regions, the rolandic operculum, as well as the thalamus and bilateral hippocampus. For CS+ relative to CS- trials during the conditioning phase, BOLD-alone analyses showed CS+ enhancement at the occipital pole, superior temporal sulci, and the anterior insula bilaterally, whereas ssVEP-BOLD coupling was greater in the pericalcarine cortex, inferior parietal cortex, and middle frontal gyrus. Dynamic causal modeling analyses supported connectivity models in which heightened activity in pericalcarine cortex for threat (CS+) arises from cortico-cortical top-down modulation, specifically from the middle frontal gyrus. No evidence was observed for selective pericalcarine modulation by deep cortical structures such as the amygdala or anterior insula, suggesting that the heightened engagement of pericalcarine cortex for threat stimuli is mediated by cortical structures that constitute key nodes of canonical attention networks.

Entrainment of visual steady-state responses is modulated by global spatial statistics.

The rhythmic delivery of visual stimuli evokes large-scale neuronal entrainment in the form of steady-state oscillatory field potentials. The spatiotemporal properties of stimulus drive appear to constrain the relative degrees of neuronal entrainment. Specific frequency ranges, for example, are uniquely suited for enhancing the strength of stimulus-driven brain oscillations. When it comes to the nature of the visual stimulus itself, studies have used a plethora of inputs ranging from spatially unstructured empty fields to simple contrast patterns (checkerboards, gratings, stripes) and complex arrays (human faces, houses, natural scenes). At present, little is known about how the global spatial statistics of the input stimulus influence entrainment of scalp-recorded electrophysiological signals. In this study, we used rhythmic entrainment source separation of scalp EEG to compare stimulus-driven phase alignment for distinct classes of visual inputs, including broadband spatial noise ensembles with varying second-order statistics, natural scenes, and narrowband sine-wave gratings delivered at a constant flicker frequency. The relative magnitude of visual entrainment was modulated by the global properties of the driving stimulus. Entrainment was strongest for pseudo-naturalistic broadband visual noise patterns in which luminance contrast is greatest at low spatial frequencies (a power spectrum slope characterized by 1/ƒ-2).NEW & NOTEWORTHY Rhythmically modulated visual stimuli entrain the activity of neuronal populations, but the effect of global stimulus statistics on this entrainment is unknown. We assessed entrainment evoked by 1) visual noise ensembles with different spectral slopes, 2) complex natural scenes, and 3) narrowband sinusoidal gratings. Entrainment was most effective for broadband noise with naturalistic luminance contrast. This reveals some global properties shaping stimulus-driven brain oscillations in the human visual system.

Representation of affect in sensory cortex.

Contemporary neuroscience suggests that perception is perhaps best understood as a dynamically iterative process that does not honor cleanly segregated "bottom-up" or "top-down" streams. We argue that there is substantial empirical support for the idea that affective influences infiltrate the earliest reaches of sensory processing and even that primitive internal affective dimensions (e.g., goodness-to-badness) are represented alongside physical dimensions of the external world.

Developmental changes in spontaneous electrocortical activity and network organization from early to late childhood.

We investigated the development of spontaneous (resting state) cerebral electric fields and their network organization from early to late childhood in a large community sample of children. Critically, we examined electrocortical maturation across one-year windows rather than creating aggregate averages that can miss subtle maturational trends. We implemented several novel methodological approaches including a more fine grained examination of spectral features across multiple electrodes, the use of phase-lagged functional connectivity to control for the confounding effects of volume conduction and applying topological network analyses to weighted cortical adjacency matrices. Overall, there were major decreases in absolute EEG spectral density (particularly in the slow wave range) across cortical lobes as a function of age. Moreover, the peak of the alpha frequency increased with chronological age and there was a redistribution of relative spectral density toward the higher frequency ranges, consistent with much of the previous literature. There were age differences in long range functional brain connectivity, particularly in the alpha frequency band, culminating in the most dense and spatially variable networks in the oldest children. We discovered age-related reductions in characteristic path lengths, modularity and homogeneity of alpha-band cortical networks from early to late childhood. In summary, there is evidence of large scale reorganization in endogenous brain electric fields from early to late childhood, suggesting reduced signal amplitudes in the presence of more functionally integrated and band limited coordination of neuronal activity across the cerebral cortex.

Perceiving threat in the face of safety: excitation and inhibition of conditioned fear in human visual cortex.

Previous findings have established that cortical sensory systems exhibit experience-dependent biases toward stimuli consistently associated with threat. It remains unclear whether safety cues also facilitate perceptual engagement or how competition between learned threat and safety cues is resolved within visual cortex. Here, we used classical discrimination conditioning with simple luminance modulated visual stimuli that predicted the presence or absence of an aversive sound to examine visuocortical competition between features signaling threat versus safety. We tracked steady-state visual evoked potentials to label distinct visual cortical responses in humans to conditioned and control stimuli. Trial-by-trial expectancy ratings collected online confirmed that participants discriminated between threat and safety cues. Conditioning was associated with heightened activation of the extended visual cortex in response to the threat, but not the safety, stimulus. Cortical facilitation for the threatening stimulus was selective and not decreased by simultaneously presenting safe and associatively novel cues. Our findings shed light on the sensory brain dynamics associated with experience-dependent acquisition of perceptual biases for danger and safety signals.

Transcranial focused ultrasound to the posterior cingulate cortex modulates default mode network and subjective experience: an fMRI pilot study.

Background: Transcranial focused ultrasound (TFUS) is an emerging neuromodulation tool for temporarily altering brain activity and probing network functioning. The effects of TFUS on the default mode network (DMN) are unknown. Objective: The study examined the effects of transcranial focused ultrasound (TFUS) on the functional connectivity of the default mode network (DMN), specifically by targeting the posterior cingulate cortex (PCC). Additionally, we investigated the subjective effects of TFUS on mood, mindfulness, and self-related processing. Methods: The study employed a randomized, single-blind design involving 30 healthy subjects. Participants were randomly assigned to either the active TFUS group or the sham TFUS group. Resting-state functional magnetic resonance imaging (rs-fMRI) scans were conducted before and after the TFUS application. To measure subjective effects, the Toronto Mindfulness Scale, the Visual Analog Mood Scale, and the Amsterdam Resting State Questionnaire were administered at baseline and 30 min after sonication. The Self Scale and an unstructured interview were also administered 30 min after sonication. Results: The active TFUS group exhibited significant reductions in functional connectivity along the midline of the DMN, while the sham TFUS group showed no changes. The active TFUS group demonstrated increased state mindfulness, reduced Global Vigor, and temporary alterations in the sense of ego, sense of time, and recollection of memories. The sham TFUS group showed an increase in state mindfulness, too, with no other subjective effects. Conclusions: TFUS targeted at the PCC can alter DMN connectivity and cause changes in subjective experience. These findings support the potential of TFUS to serve both as a research tool and as a potential therapeutic intervention.

Luminance, but not chromatic visual pathways, mediate amplification of conditioned danger signals in human visual cortex.

Complex organisms rely on experience to optimize the function of perceptual and motor systems in situations relevant to survival. It is well established that visual cues reliably paired with danger are processed more efficiently than neutral cues, and that such facilitated sensory processing extends to low levels of the visual system. The neurophysiological mechanisms mediating biased sensory processing, however, are not well understood. Here we used grating stimuli specifically designed to engage luminance or chromatic pathways of the human visual system in a differential classical conditioning paradigm. Behavioral ratings and visual electroencephalographic steady-state potentials were recorded in healthy human participants. Our findings indicate that the visuocortical response to high-spatial-frequency isoluminant (red-green) grating stimuli was not modulated by fear conditioning, but low-contrast, low-spatial-frequency reversal of grayscale gratings resulted in pronounced conditioning effects. We conclude that sensory input conducted via the chromatic pathways into retinotopic visual cortex has limited access to the bi-directional connectivity with brain networks mediating the acquisition and expression of fear, such as the amygdaloid complex. Conversely, luminance information is necessary to establish amplification of learned danger signals in hierarchically early regions of the visual system.

A Scalable Framework for Closed-Loop Neuromodulation with Deep Learning.

Closed-loop neuromodulation measures dynamic neural or physiological activity to optimize interventions for clinical and nonclinical behavioral, cognitive, wellness, attentional, or general task performance enhancement. Conventional closed-loop stimulation approaches can contain biased biomarker detection (decoders and error-based triggering) and stimulation-type application. We present and verify a novel deep learning framework for designing and deploying flexible, data-driven, automated closed-loop neuromodulation that is scalable using diverse datasets, agnostic to stimulation technology (supporting multi-modal stimulation: tACS, tDCS, tFUS, TMS), and without the need for personalized ground-truth performance data. Our approach is based on identified periods of responsiveness - detected states that result in a change in performance when stimulation is applied compared to no stimulation. To demonstrate our framework, we acquire, analyze, and apply a data-driven approach to our open sourced GX dataset, which includes concurrent physiological (ECG, EOG) and neuronal (EEG) measures, paired with continuous vigilance/attention-fatigue tracking, and High-Definition transcranial electrical stimulation (HD-tES). Our framework's decision process for intervention application identified 88.26% of trials as correct applications, showed potential improvement with varying stimulation types, or missed opportunities to stimulate, whereas 11.25% of trials were predicted to stimulate at inopportune times. With emerging datasets and stimulation technologies, our unifying and integrative framework; leveraging deep learning (Convolutional Neural Networks - CNNs); demonstrates the adaptability and feasibility of automated multimodal neuromodulation for both clinical and nonclinical applications.

Early information processing biases in social anxiety.

Considerable controversy persists regarding the nature of threat-related attention biases in social anxiety. Previous studies have not considered how variations in the temporal and energetic dimensions of affective stimulus delivery interact with anxiety-related individual differences to predict biased attention. We administered a visual dot-probe task, using faces that varied in affective intensity (mild, moderate, strong) and presentation rate (100, 500, 1,250 ms) to a selected sample. The high, compared to the low, socially anxious group showed vigilance towards angry faces and emotionally ambiguous faces more generally during rapid (100 ms) presentations. By 1,250 ms, there was only a non-specific motor slowing associated with angry faces in the high socially anxious group. Findings suggest the importance of considering both chronometric and energetic dimensions of affective stimuli when examining anxiety-related attention biases. Future studies should consider using designs that more closely replicate aspects of real-world interaction to study processing biases in socially anxious populations.

Attentional capture by angry faces in girls who self-injure: Evidence from steady state visual evoked potentials.

BACKGROUND: Non-suicidal self-injury (NSSI) is a significant public health concern, not only because of the personal and social cost of the behavior itself, but also because it increases risk for future self-injurious behaviors, including suicide attempts. NSSI is increasingly prevalent during adolescence, which highlights the need for research aimed at identifying modifiable risk factors that can be targeted to reduce future risk. Building from theoretical models that highlight interpersonal processes, this study examined whether adolescents with an NSSI history exhibit greater difficulty inhibiting attention to emotionally salient interpersonal stimuli (face), indexed via steady state visual evoked potentials (SSVEPs), which provide a direct neural index of the ability to inhibit attention to task-irrelevant stimuli. METHODS: Adolescent girls aged 13-17 with (n = 26) and without (n = 28) an NSSI history completed a change-detection computer task during which frequency-tagged SSVEPs were used to assess adolescents' ability to inhibit attention to affectively salient stimuli from spatially superimposed targets. RESULTS: Compared with adolescents with no NSSI history, adolescents with NSSI demonstrated difficulty inhibiting attention to angry adult faces. CONCLUSIONS: These findings underscore specific deficits in attentional filtering among girls with an NSSI history, which, if replicated and extended, could be a promising intervention target for reducing risk for future NSSI.

Changes in EEG cross-frequency coupling during cognitive behavioral therapy for social anxiety disorder.

Coupling between EEG delta and beta oscillations is enhanced among anxious and healthy individuals during anticipatory anxiety. EEG coupling patterns associated with psychotherapy have not yet been quantified in socially anxious individuals. In this study, we used a double baseline, repeated measures design, in which 25 adults with a principal diagnosis of social anxiety disorder completed 12 weekly sessions of standardized group cognitive behavioral therapy and four EEG assessments: two at pretreatment, one at midtreatment, and one at posttreatment. Treatment was associated with reductions in symptom severity across multiple measures and informants, as well as reductions in delta-beta coupling at rest and during speech anticipation. Moreover, the clinical group exhibited greater coupling at pretreatment than did post hoc control participants with low social anxiety. The EEG cross-frequency profiles in the clinical group normalized by the posttreatment assessment. These findings provide evidence of concomitant improvement in neural and behavioral functioning among socially anxious adults undergoing psychotherapy.

Frontal brain oscillatory coupling in children of parents with social phobia: a pilot study.

Spectral coupling between delta and beta oscillations has been related to anxiety. The authors provide preliminary evidence that frontal brain oscillatory coupling discriminates children born to socially phobic versus healthy parents, despite there being no difference in parental perceptions of their children's shyness.