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Task-Evoked Dynamic Network Analysis Through Hidden Markov Modeling.
Complex thought and behavior arise through dynamic recruitment of large-scale brain networks. The signatures of this process may be observable in electrophysiological data; yet robust modeling of rapidly changing functional network structure on rapid cognitive timescales remains a considerable challenge. Here, we present one potential solution using Hidden Markov Models (HMMs), which are able to identify brain states characterized by engaging distinct functional networks that reoccur over time. We show how the HMM can be inferred on continuous, parcellated source-space Magnetoencephalography (MEG) task data in an unsupervised manner, without any knowledge of the task timings. We apply this to a freely available MEG dataset in which participants completed a face perception task, and reveal task-dependent HMM states that represent whole-brain dynamic networks transiently bursting at millisecond time scales as cognition unfolds. The analysis pipeline demonstrates a general way in which the HMM can be used to do a statistically valid whole-brain, group-level task analysis on MEG task data, which could be readily adapted to a wide range of task-based studies.
How Sensitive Are Conventional MEG Functional Connectivity Metrics With Sliding Windows to Detect Genuine Fluctuations in Dynamic Functional Connectivity?
Despite advances in the field of dynamic connectivity, fixed sliding window approaches for the detection of fluctuations in functional connectivity are still widely used. The use of conventional connectivity metrics in conjunction with a fixed sliding window comes with the arbitrariness of the chosen window lengths. In this paper we use multivariate autoregressive and neural mass models with a priori defined ground truths to systematically analyze the sensitivity of conventional metrics in combination with different window lengths to detect genuine fluctuations in connectivity for various underlying state durations. Metrics of interest are the coherence, imaginary coherence, phase lag index, phase locking value and the amplitude envelope correlation. We performed analysis for two nodes and at the network level. We demonstrate that these metrics show indeed higher variability for genuine temporal fluctuations in connectivity compared to a static connectivity state superimposed by noise. Overall, the error of the connectivity estimates themselves decreases for longer state durations (order of seconds), while correlations of the connectivity fluctuations with the ground truth was higher for longer state durations. In general, metrics, in combination with a sliding window, perform poorly for very short state durations. Increasing the SNR of the system only leads to a moderate improvement. In addition, at the network level, only longer window widths were sufficient to detect plausible resting state networks that matched the underlying ground truth, especially for the phase locking value, amplitude envelope correlation and coherence. The length of these longer window widths did not necessarily correspond to the underlying state durations. For short window widths resting state network connectivity patterns could not be retrieved. We conclude that fixed sliding window approaches for connectivity can detect modulations of connectivity, but mostly if the underlying dynamics operate on moderate to slow timescales. In practice, this can be a drawback, as state durations can vary significantly in empirical data.
Decoding Movement States in Stepping Cycles Based on Subthalamic LFPs in Parkinsonian Patients.
Gait disturbances are a prominent feature of Parkinson's disease (PD), often refractory to medication or continuous deep brain stimulation (DBS) on basal ganglia targets such as the subthalamic nucleus (STN). Here we sought to identify movement states during stepping cycles, such as left leg stance and right leg stance. To this end we analyzed local field potential (LFP) activity in STN using a combination of the multivariate autoregressive (MAR) model and the Hidden Markov model (HMM). Our results confirm that information is present in the STN related to movement states in stepping cycles, and that it is feasible to decode movement states based on STN LFPs recorded from DBS electrodes. This information can be used to implement temporally flexible stimulation strategies in order to facilitate patterns of neural modulation associated with better gait performance.
Frontal evoked γ activity modulates behavioural performance in Autism Spectrum Disorders in a perceptual simultaneity task.
Autism spectrum disorders (ASDs) are associated with anomalies in time perception. In a perceptual simultaneity task, individuals with ASD demonstrate superior performance compared to typically developing (TD) controls. γ-activity, a robust marker of visual processing, is reportedly altered in ASD in response to a wide variety of tasks and these differences may be related to superior performance in perceptual simultaneity. Using time-frequency analysis, we assessed evoked γ-band phase-locking in magnetoencephalographic recordings of 16 ASD individuals and 17 age-matched TD controls. Individuals judged whether presented visual stimuli were simultaneous or asynchronous. We identified left frontal γ-activity in ASD, which was associated with a reduced perception of simultaneity. Where feature binding was observed at a neurophysiological level in parieto-occipital cortices in ASD in apparent simultaneity (asynchronous stimuli with short delay between them), this did not predict the correct behavioural outcome. These findings suggest distinct γ profiles in ASD associated with the perception of simultaneity.
Associative and semantic memory deficits in amnestic mild cognitive impairment as revealed by functional magnetic resonance imaging.
OBJECTIVE: To identify the neural underpinnings of cognitive deficits associated with memory problems in amnestic mild cognitive impairment (aMCI). BACKGROUND: Functional magnetic resonance imaging (fMRI) is increasingly used to assess patients with aMCI and could potentially help predict conversion to Alzheimer disease, but imaging results so far have been inconsistent in identifying brain activation patterns in aMCI. There is an immediate need to identify the neural substrates of different memory components that are affected by aMCI. METHODS: We used fMRI to study 13 patients with aMCI and 15 healthy age-matched controls during an associative memory encoding and recognition task. The picture-pair memory task encompassed different types of recognition trials to investigate recollection versus familiarity, and manipulated the relationship between paired pictures to investigate semantic processing. RESULTS: Brain activation during both encoding and recognition was lower in patients than controls, with greatest implications in the medial temporal lobe during encoding. Patients also had much greater impairment of associative recollection than recognition based on familiarity, along with a failure to recruit regions that normally respond to violations of learned associations. Finally, patients' impaired semantic encoding was reflected by deficient activation of a left frontotemporal network responsible for elaborate semantic processes. CONCLUSIONS: We show that a simple fMRI task may be sensitive to deficits in different memory components in aMCI and could thus prove useful in the development of an fMRI tool to assess and monitor patients.
The neural basis of age-related changes in motor imagery of gait: an fMRI study.
BACKGROUND: Aging is often associated with modifications of gait. Recent studies have revealed a strong relationship between gait and executive functions in healthy and pathological aging. We hypothesized that modification of gait due to aging may be related to changes in frontal lobe function. METHODS: Fourteen younger (27.0±3.6 years) and 14 older healthy adults (66.0±3.5 years) performed a motor imagery task of gait as well as a matched visual imagery task. Task difficulty was modulated to investigate differential activation for precise control of gait. Task performance was assessed by recording motor imagery latencies, eye movements, and electromyography during functional magnetic resonance imaging scanning. RESULTS: Our results showed that both healthy older and young adults recruited a network of brain regions comprising the bilateral supplementary motor cortex and primary motor cortex, right prefrontal cortex, and cerebellum, during motor imagery of gait. We observed an age-related increase in brain activity in the right supplementary motor area (BA6), the right orbitofrontal cortex (BA11), and the left dorsolateral frontal cortex (BA10). Activity in the left hippocampus was significantly modulated by task difficulty in the elderly participants. Executive functioning correlated with magnitude of increases in right primary motor cortex (BA4) during the motor imagery task. CONCLUSIONS: Besides demonstrating a general overlap in brain regions recruited in young and older participants, this study shows age-related changes in cerebral activation during mental imagery of gait. Our results underscore the importance of executive function (dorsolateral frontal cortex) and spatial navigation or memory function (hippocampus) in gait control in elderly individuals.
Gender differences in the neural network of facial mimicry of smiles--An rTMS study.
Under theories of embodied emotion, exposure to a facial expression triggers facial mimicry. Facial feedback is then used to recognize and judge the perceived expression. However, the neural bases of facial mimicry and of the use of facial feedback remain poorly understood. Furthermore, gender differences in facial mimicry and emotion recognition suggest that different neural substrates might accompany the production of facial mimicry, and the processing of facial feedback, in men and women. Here, repetitive transcranial magnetic stimulation (rTMS) was applied to the right primary motor cortex (M1), the right primary somatosensory cortex (S1), or, in a control condition, the vertex (VTX). Facial mimicry of smiles and emotion judgments were recorded in response to video clips depicting changes from neutral or angry to happy facial expressions. While in females rTMS over M1 and S1 compared to VTX led to reduced mimicry and, in the case of M1, delayed detection of smiles, there was no effect of TMS condition for males. We conclude that in female participants M1 and S1 play a role in the mimicry and in the use of facial feedback for accurate processing of smiles.
Persistent affective biases in human amygdala response following implicit priming with negative emotion concepts.
To what extent do past experiences shape our behaviors, perceptions, and thoughts even without explicit knowledge of these influences? Behavioral research has demonstrated that various cognitive processes can be influenced by conceptual representations implicitly primed during a preceding and unrelated task. Here we investigated whether emotion processing might also be influenced by prior incidental exposure to negative semantic material and which neural substrates would mediate these effects. During a first (priming) task, participants performed a variant of the hangman game with either negative or neutral emotion-laden words. Subsequently, they performed a second, unrelated visual task with fearful and neutral faces presented at attended or unattended locations. Participants were generally not aware of any relationships between the two tasks. We found that priming with emotional words enhanced amygdala sensitivity to faces in the subsequent visual task, while decreasing discriminative responses to threat. Furthermore, the magnitude of the induced bias in behavior and amygdala activation was predicted by the effectiveness of semantic access observed in the priming task. This demonstrates that emotional processing can be modulated by implicit influence of environmental information processed at an earlier time, independently of volitional control.
Brain systems underlying encounter expectancy bias in spider phobia.
Spider-phobic individuals are characterized by exaggerated expectancies to be faced with spiders (so-called encounter expectancy bias). Whereas phobic responses have been linked to brain systems mediating fear, little is known about how the recruitment of these systems relates to exaggerated expectancies of threat. We used fMRI to examine spider-phobic and control participants while they imagined visiting different locations in a forest after having received background information about the likelihood of encountering different animals (spiders, snakes, and birds) at these locations. Critically, imagined encounter expectancies modulated brain responses differently in phobics as compared with controls. Phobics displayed stronger negative modulation of activity in the lateral prefrontal cortex, precuneus, and visual cortex by encounter expectancies for spiders, relative to snakes or birds (within-participants analysis); these effects were not seen in controls. Between-participants correlation analyses within the phobic group further corroborated the hypothesis that these phobia-specific modulations may underlie irrationality in encounter expectancies (deviations of encounter expectancies from objective background information) in spider phobia; the greater the negative modulation a phobic participant displayed in the lateral prefrontal cortex, precuneus, and visual cortex, the stronger was her bias in encounter expectancies for spiders. Interestingly, irrationality in expectancies reflected in frontal areas relied on right rather than left hemispheric deactivations. Our data accord with the idea that expectancy biases in spider phobia may reflect deficiencies in cognitive control and contextual integration that are mediated by right frontal and parietal areas.
The influence of individual motor imagery ability on cerebral recruitment during gait imagery.
Motor imagery (MI) is often used in combination with neuroimaging techniques to study the cognitive control of gait. However, imagery ability (IA) varies widely across individuals, potentially influencing the pattern of cerebral recruitment during MI. The aim of the current study was to investigate this effect of IA on the neural correlates of gait control using functional magnetic resonance imaging (fMRI). Twenty healthy young subjects were subdivided into a good and bad imagers group, on the basis of their performance on two mental chronometry tests. For the whole group, MI activated a bilateral network of areas highly consistent with previous studies, encompassing primary motor cortex (BA 4), supplementary motor area, and other frontal and parietal areas, anterior insula, and cerebellum. Compared to bad imagers, good imagers showed higher activation in the right BA 4, left prefrontal cortex (BA 10), right thalamus, and bilateral cerebellum. Good imagers thus appear better able to recruit motor areas during MI, but also activate a prefrontal executive area (BA 10), which integrates information from the body and the environment and participates in higher-order gait control. These differences were found even though the two groups did not differ in other imagery abilities according to a standard questionnaire for vividness of motor and visual imagery. Future studies on MI should take into account these effects, and control for IA when comparing different populations, using appropriate measures. A better understanding of the neural mechanisms that underlie MI ability is crucial to accurately evaluate locomotor skills in clinical measures and neurorehabilitation techniques.
Self-regulation of inter-hemispheric visual cortex balance through real-time fMRI neurofeedback training.
Recent advances in neurofeedback based on real-time functional magnetic resonance imaging (fMRI) allow for learning to control spatially localized brain activity in the range of millimeters across the entire brain. Real-time fMRI neurofeedback studies have demonstrated the feasibility of self-regulating activation in specific areas that are involved in a variety of functions, such as perception, motor control, language, and emotional processing. In most of these previous studies, participants trained to control activity within one region of interest (ROI). In the present study, we extended the neurofeedback approach by now training healthy participants to control the interhemispheric balance between their left and right visual cortices. This was accomplished by providing feedback based on the difference in activity between a target visual ROI and the corresponding homologue region in the opposite hemisphere. Eight out of 14 participants learned to control the differential feedback signal over the course of 3 neurofeedback training sessions spread over 3 days, i.e., they produced consistent increases in the visual target ROI relative to the opposite visual cortex. Those who learned to control the differential feedback signal were subsequently also able to exert that control in the absence of neurofeedback. Such learning to voluntarily control the balance between cortical areas of the two hemispheres might offer promising rehabilitation approaches for neurological or psychiatric conditions associated with pathological asymmetries in brain activity patterns, such as hemispatial neglect, dyslexia, or mood disorders.
Negative emotions facilitate isometric force through activation of prefrontal cortex and periaqueductal gray.
Emotions are considered to modulate action readiness. Previous studies have demonstrated increased force production following exposure to emotionally arousing visual stimuli; however the neural mechanisms underlying how precise force output is controlled within varying emotional contexts remain poorly understood. To identify the neural correlates of emotion-modulated motor behaviour, twenty-two participants produced a submaximal isometric precision-grip contraction while viewing pleasant, unpleasant, neutral or blank images (without visual feedback of force output). Force magnitude was continuously recorded together with change in brain activity using functional magnetic resonance imaging. Viewing unpleasant images resulted in reduced force decay during force maintenance as compared with pleasant, neutral and blank images. Subjective valence and arousal ratings significantly predicted force production during maintenance. Neuroimaging revealed that negative valence and its interaction with force output correlated with increased activity in right inferior frontal gyrus (rIFG), while arousal was associated with amygdala and periaqueductal gray (PAG) activation. Force maintenance alone was correlated with cerebellar activity. These data demonstrate a valence-driven modulation of force output, mediated by a cortico-subcortical network involving rIFG and PAG. These findings are consistent with engagement of motor pathways associated with aversive motivation, eliciting defensive behaviour and action preparedness in response to negative emotional signals.
Tuned SQUID-MRI system with resonant frequency adjustment
We describe a low field, bench-top MRI system for small samples, based on a permanent magnet. Signals are received at 830 kHz using a tuned SQUID magnetometer, cooled in a modified liquid helium cryostat. The SQUID input circuit has an intrinsic Q -factor of 28,000, so this is damped by flux-locking electronics and an additional feedback loop to give an effective Q of between 40 and 200 for imaging. The resonant frequency is adjusted by a control rod coupled to a trimmer capacitor mounted in the liquid helium volume. Images of a test object acquired using the cooled receiver exhibit up to two-fold SNR gains in regions close to the sensor, compared to an equivalent room temperature coil, with the noise level dominated by losses coupled from the magnet pole faces. © 2007 IEEE.