Data-driven Independent Component Analysis Research Articles

Torture Exposure Modulates Cognitive Control and Attention Neural Network Connectivity During a Go/NoGo Task

BackgroundTorture trauma is characterized by intentional uncontrollable acts, but the long-term effects of torture exposure on cognitive control brain mechanisms are unknown. MethodsA final sample of 33 torture survivors (TSs) and 44 non-TSs, all with a refugee background, completed a Go/NoGo response inhibition task during functional magnetic resonance imaging scanning. Data-driven independent component analysis identified active networks across the task and on Go, NoGo, and error of commission trials. Groups were compared on within-/between-network connectivity while controlling for demographic and psychological symptom covariates. Secondary analyses investigated whether network connectivity moderated the associations between torture exposure and severity on fear (e.g., re-experiencing) and dysphoria (e.g., anhedonia) posttraumatic stress disorder symptoms. ResultsThe TS group exhibited decreased connectivity (compared with the non-TS control group) within the posterior default mode network (specifically the left precuneus) and auditory-motor network (specifically the right superior temporal gyrus) and reduced connectivity between the dorsomedial frontal network and dorsal attention network across the Go/NoGo task. The TS group also showed more negative ventral attention network connectivity during NoGo (i.e., inhibition) trials. No behavioral effects were observed. Secondary analyses revealed that the association between torture exposure and elevated posttraumatic stress dysphoria (not fear) symptoms was moderated by reduced connectivity in the right superior temporal gyrus and between the dorsomedial frontal network and the dorsal attention network. ConclusionsResponse inhibition, attention, and motor networks appear to be less connected in TSs, which may be specifically linked to a posttraumatic stress dysphoria symptom profile. The findings suggest that targeting cognitive control processes may hold promise for alleviating posttraumatic symptoms among survivors of torture.

Affinity of structural white matter tracts between infant and adult pig

BackgroundThe piglet brain has been increasingly used as an excellent surrogate for investigation of pediatric neurodevelopment, nutrition, and traumatic brain injuries. This study intends to establish a piglet brain’s structural connectivity model and compare it with the adult pig, enhancing its application for structurally guided functional analysis. MethodsIn this study, diffusion-weighted (DW)-MRI data from piglets (n=11, 3-week-old) was used to establish piglet model and compare with adult pigs. We employed a data-driven independent component analysis (ICA) method to derive piglet-specific tracts. Pearson correlations and Kullback-Leibler (KL) divergences was employed to identify common tracts and unique tracts for piglet. Common tracts were then used in a blueprint connectome study to highlight differences in regions of interest (ROI). ResultsThe data-driven approach applied to piglet brains revealed 17 common tracts, showing high similarity with adult pigs' white matter (WM) tracts, and identified 3 tracts unique to piglets and 10 negative marker tracts. Additionally, the study highlighted notable differences in 3 ROIs associated with blueprint connectome. Comparing with existing methodsThis study marks a significant shift from surface-based to voxel-based methodologies in analyzing pig brain structural connectivity and generating connectome blueprints. Additionally, it sheds light on the use of the piglet model for developmental studies, offering new perspectives in this area. ConclusionThis study established a piglet brain tract model and conducts a comparative analysis of adult pig’s and piglet’s structural connectivity. These findings underscore the potential use of the piglet brain model in employing piglet model for developmental studies.

Resting-state functional connectivity in lifelong musicians.

It has been postulated that musicianship can lead to enhanced brain and cognitive reserve, but the neural mechanisms of this effect have been poorly understood. Lifelong professional musicianship in conjunction with novel brain imaging techniques offers a unique opportunity to examine brain network differences between musicians and matched controls. In this study we aim to investigate how resting-state functional networks (FNs) manifest in lifelong active musicians. We will evaluate the FNs of lifelong musicians and matched healthy controls using resting-state functional magnetic resonance imaging. We derive FNs using the data-driven independent component analysis approach and analyze the functional network connectivity (FNC) between the default mode (DMN), sensory-motor (SMN), visual (VSN), and auditory (AUN) networks. We examine whether the linear regressions between FNC and age are different between the musicians and the control group. The age trajectory of average FNC across all six pairs of FNs shows significant differences between musicians and controls. Musicians show an increase in average FNC with age while controls show a decrease (P=0.013). When we evaluated each pair of FN, we note that in musicians FNC values increased with age in DMN-AUN, DMN-VSN, and SMN-VSN and in controls FNC values decreased with age in DMN-AUN, DMN-SMN, AUN-SMN, and SMN-VSN. This result provides early evidence that lifelong musicianship may contribute to enhanced brain and cognitive reserve. Results of this study are preliminary and need to be replicated with a larger number of participants.

Exploring Spatio-spectral Electroencephalogram Modulations of Imbuing Emotional Intent during Active Piano Playing.

Imbuing emotional intent serves as a crucial modulator of music improvisation during active musical instrument playing. However, most improvisation-related neural endeavors have been gained without considering the emotional context. This study attempted to exploit reproducible spatio-spectral electroencephalogram (EEG) oscillations of emotional intent using a data-driven independent component analysis framework in an ecological multiday piano playing experiment. Through the four-day 32-ch EEG dataset of 10 professional players, we showed that EEG patterns were substantially affected by both intra- and inter-individual variability underlying the emotional intent of the dichotomized valence (positive vs. negative) and arousal (high vs. low) categories. Less than half (3-4) of the 10 participants analogously exhibited day-reproducible (≥ three days) spectral modulations at the right frontal beta in response to the valence contrast as well as the frontal central gamma and the superior parietal alpha to the arousal counterpart. In particular, frontal engagement facilitated a better understanding of the frontal cortex (e.g., dorsolateral prefrontal cortex and anterior cingulate cortex) and its role in intervening emotional processes and expressing spectral signatures that are relatively resistant to natural EEG variability. Such ecologically vivid EEG findings may lead to better understanding of the development of a brain-computer music interface infrastructure capable of guiding the training, performance, and appreciation for emotional improvisatory status or actuating music interaction via emotional context.

Resting-state functional connectivity of salience network in schizophrenia and depression

To explore the salience network (SN) functional alterations in schizophrenia and depression, resting-state functional magnetic resonance imaging (rs-fMRI) data from 29 patients with schizophrenia (SCH), 28 patients with depression (DEP) and 30 healthy controls (HC) were obtained. The SN was derived from data-driven group independent component analysis (gICA). ANCOVA and post hoc tests were performed to discover the FC differences of SN between groups. The ANCOVA demonstrated a significant group effect in FC with right inferior and middle temporal gyrus (ITG and MTG), left caudate, and right precentral gyrus. Post-hoc analyses revealed an opposite altered FC pattern between SN and right ITG and MTG for both patient groups. The DEP group showed a reduced FC between SN and right ITG and MTG compared with HC whereas the SCH group showed an increased FC. In addition, the SCH group showed decreased FC between SN and left caudate, and enhanced FC between SN and right precentral gyrus compared to the other two groups. Our findings suggest distinct FC of SN in schizophrenia and depression, supporting that the resting-state FC pattern of SN may be a transdiagnostic difference between depression and schizophrenia and may play a critical role in the pathogenesis of these two disorders.

P.008 Functional network reorganization in temporal lobe epilepsy: looking beyond the hippocampus

Background: Temporal lobe epilepsy (TLE) has been redefined as a disorder associated with network-level dysfunction not limited to the epileptic zone. As such, as resting state (rs) fMRI has been used to evaluate the implicated resting state networks (RSN) and their ensuing functional impairments. However, few studies have analyzed patients with (TLE-HS) and without (TLE-nonHS) hippocampal sclerosis independently. Whereas TLE-HS often warrants surgical intervention, drug-resistant TLE-nonHS might pose challenges for diagnosis and treatment decisions. Methods: This study aimed to investigate functional connectivity changes (FC) of RSNs beyond the hippocampus using rs-fMRI. Rs-fMRI data was acquired from 16 TLE-HS and nine TLE-nonHS, along with 25 healthy controls (HC). RSNs were established using a data-driven independent component analysis approach, in order to determine significant connections between HC and patient groups ipsilateral and contralateral to the seizure focus. Results: When comparing TLE-HS to HC, FC changes were found for the dorsal-attentional (DAN), visual, fronto-parietal (FPN), sensorimotor and default-mode networks (DMN). Alterations in the DAN, DMN and FPN were found when comparing TLE-nonHS to HC. Conclusions: This study demonstrated widespread network reorganization across TLE subtypes. These FC patterns hold promise as a prognostic biomarker, and may be used to define subsequent function and dysfunction in this patient population.

Reorganization of large-scale brain networks in deaf signing adults: The role of auditory cortex in functional reorganization following deafness

If the brain is deprived of input from one or more senses during development, functional and structural reorganization of the deprived regions takes place. However, little is known about how sensory deprivation affects large-scale brain networks. In the present study, we use data-driven independent component analysis (ICA) to characterize large-scale brain networks in 15 deaf early signers and 24 hearing non-signers based on resting-state functional MRI data. We found differences between the groups in independent components representing the left lateralized control network, the default network, the ventral somatomotor network, and the attention network. In addition, we showed stronger functional connectivity for deaf compared to hearing individuals from the middle and superior temporal cortices to the cingulate cortex, insular cortex, cuneus and precuneus, supramarginal gyrus, supplementary motor area, and cerebellum crus 1, and stronger connectivity for hearing non-signers to hippocampus, middle and superior frontal gyri, pre- and postcentral gyri, and cerebellum crus 8. These results show that deafness induces large-scale network reorganization, with the middle/superior temporal cortex as a central node of plasticity. Cross-modal reorganization may be associated with behavioral adaptations to the environment, including superior ability in some visual functions such as visual working memory and visual attention, in deaf signers.

Disorganized resting-state functional connectivity between the dorsal attention network and intrinsic networks in Parkinson's disease with freezing of gait.

Freezing of gait (FOG) is a common and complex manifestation of Parkinson's disease (PD) and is associated with impairment of attention. The purpose of this study was to evaluate the functional network connectivity (FNc) changes between the dorsal attention network (DAN) and the other seven intrinsic networks relevant to attention, visual-spatial, executive and motor functions in PD with or without FOG. Forty-three idiopathic PD patients (21 with FOG [FOG+] versus 22 without FOG [FOG-]) and 18 healthy controls (HC) were recruited in this study. The data-driven independent component analysis (ICA) method was used to extract and analyze the above-mentioned resting-state networks (RSNs). Compared with FOG-, FOG+ displayed decreased positive connectivity between the DAN and medial visual network (mVN) and sensory-motor network (SMN) and increased negative connectivity between the DAN and default mode network (DMN). The within-network connectivity in the SMN and visual networks were decreased, whereas the connectivity within DMN was increased significantly in FOG+. Correlation analysis showed that the clock drawing test (CDT) scores were positively correlated with the functional connectivity of mVN (r=0.573, p=0.008) and lateral visual network (lVN) (r=0.510, p=0.022), the Timed Up and Go Test (TUG) duration were negatively correlated with the connectivity of SMN (r= -0.629, p=0.003), and the Frontal Assessment Battery (FAB) scores were negatively correlated with the connectivity of DMN in FOG+. Functional connectivity was changed in multiple intra-networks in patients with FOG. Inordinate inter-network connectivity between the DAN and other intrinsic networks may partly contribute to the mechanism of freezing.

Functional networks in non-human primate spinal cord and the effects of injury

Spontaneous fluctuations of Blood Oxygenation-Level Dependent (BOLD) MRI signal in a resting state have previously been detected and analyzed to describe intrinsic functional networks in the spinal cord of rodents, non-human primates and human subjects. In this study we combined high resolution imaging at high field with data-driven Independent Component Analysis (ICA) to i) delineate fine-scale functional networks within and between segments of the cervical spinal cord of monkeys, and also to ii) characterize the longitudinal effects of a unilateral dorsal column injury on these networks. Seven distinct functional hubs were revealed within each spinal segment, with new hubs detected at bilateral intermediate and gray commissure regions in addition to the bilateral dorsal and ventral horns previously reported. Pair-wise correlations revealed significantly stronger connections between hubs on the dominant hand side. Unilateral dorsal-column injuries disrupted predominantly inter-segmental rather than intra-segmental functional connectivities as revealed by correlation strengths and graph-theory based community structures. The effects of injury on inter-segmental connectivity were evident along the length of the cord both below and above the lesion region. Connectivity strengths recovered over time and there was revival of inter-segmental communities as animals recovered function. BOLD signals of frequency 0.01–0.033 Hz were found to be most affected by injury. The results in this study provide new insights into the intrinsic functional architecture of spinal cord and underscore the potential of functional connectivity measures to characterize changes in networks after an injury and during recovery.

Structural and functional brain abnormalities in misophonia

Misophonia is a newly described condition in which specific ordinary sounds provoke disproportionately strong negative affect. Since evidence for neurobiological abnormalities underlying misophonia is scarce, we tested whether misophonia patients differed from healthy controls in grey matter volumes and resting-state functional connectivity. We collected structural magnetic resonance imaging and resting-state functional magnetic resonance imaging data from 24 misophonia patients and 25 matched controls. Compared to controls, voxel-based morphometry showed larger right amygdala volume in misophonia patients. Follow-up seed-based functional connectivity analysis of the amygdala showed a different pattern of connectivity with the cerebellum, driven by greater connectivity with the left amygdala. Additional data-driven independent component analysis showed greater connectivity within lateral occipital cortices and fusiform gyri in the ventral attention network. We propose that the amygdala enlargement may be associated with heightened emotional reactivity in misophonia. The higher connectivity between left amygdala and cerebellum might be linked to a tendency to exhibit reflex-like physical reactions to triggers. Higher attention network connectivity may reflect sensory enhancement of visual triggers or visual imagery related to trigger sounds. In sum, we found structural and functional abnormalities which implicate dysfunction of emotional and attentional systems in misophonia.

Chronic generalized pain disrupts whole brain functional connectivity in mice

Fibromyalgia (FM) is a generalized chronic pain condition whose pathophysiology is poorly understood, and both basic and translational research are needed to advance the field. Here we used the Sluka model to test whether FM-like pain in mice would produce detectable brain modifications using resting-state (rs) functional Magnetic Resonance Imaging (fMRI). Mice received intramuscular acid saline treatment, images were acquired at 7T 5days post-treatment, and pain thresholds tested 3weeks post-scanning. Data-driven Independent Component Analysis revealed significant reduction of functional connectivity (FC) across several component pairs, with major changes for the Retrosplenial cortex (RSP) central to the default mode network, and to a lesser extent the Periaqueductal gray (PAG), a key pain processing area. Seed-to-seed analysis focused on 14 pain-related areas showed strongest FC reduction for RSP with several cortical areas (somatosensory, prefrontal and insular), and for PAG with both cortical (somatosensory) and subcortical (habenula, thalamus, parabrachial nucleus) areas. RSP-PAG FC was also reduced, and this decreased FC tended to be positively correlated with pain levels at individual subject level. Finally, seed-voxelwise analysis focused on PAG confirmed seed-to-seed findings and, also detected reduced PAG FC with the anterior cingulate cortex, increasingly studied in aversive pain effects. In conclusion, FM-like pain triggers FC alterations in the mouse, which are detected by rs-fMRI and are reminiscent of some human findings. The study reveals the causal fingerprint of FM-like pain in rodents, and indicates that both RSP and PAG connectional patterns could be suitable biomarkers, with mechanistic and translational value, for further investigations.

Altered resting-state network connectivity in panic disorder: an independent ComponentAnalysis.

Panic disorder (PD) is a prevalent anxiety disorder but its neurobiology remains poorly understood. It has been proposed that the pathophysiology of PD is related to an abnormality in a particular neural network. However, most studies investigating resting-state functional connectivity (FC) have relied on a priori restrictions of seed regions, which may bias observations. This study investigated changes in intra and internetwork FC in the whole brain of patients with PD using resting-state functional magnetic resonance imaging. A voxel-wise data-driven independent component analysis was performed on 26 PD patients and 27 healthy controls (HCs).We compared the differences in the intra and internetwork FC between the two groups of subjects using statistical parametric mapping with two-sample t-tests. PD patients exhibited decreased intra-network FC in the right anterior cingulate cortex (ACC) of the anterior default mode network, the left precentral and postcentral gyrus of the sensorimotor network, the right lobule V/VI, the cerebellum vermis, and the left lobule VI of the cerebellum network compared with the HCs. The intra-network FC in the right ACC was negatively correlated with symptom severity. None of the pairs of resting state networks showed significant differences in functional network connectivity between the two groups. These results suggest that the brain networks associated with emotion regulation, interoceptive awareness, and fear and somatosensory processing may play an important role in the pathophysiology of PD.

Processing communicative facial and vocal cues in the superior temporal sulcus

Facial and vocal cues provide critical social information about other humans, including their emotional and attentional states and the content of their speech. Recent work has shown that the face-responsive region of posterior superior temporal sulcus (“fSTS”) also responds strongly to vocal sounds. Here, we investigate the functional role of this region and the broader STS by measuring responses to a range of face movements, vocal sounds, and hand movements using fMRI. We find that the fSTS responds broadly to different types of audio and visual face action, including both richly social communicative actions, as well as minimally social noncommunicative actions, ruling out hypotheses of specialization for processing speech signals, or communicative signals more generally. Strikingly, however, responses to hand movements were very low, whether communicative or not, indicating a specific role in the analysis of face actions (facial and vocal), not a general role in the perception of any human action. Furthermore, spatial patterns of response in this region were able to decode communicative from noncommunicative face actions, both within and across modality (facial/vocal cues), indicating sensitivity to an abstract social dimension. These functional properties of the fSTS contrast with a region of middle STS that has a selective, largely unimodal auditory response to speech sounds over both communicative and noncommunicative vocal nonspeech sounds, and nonvocal sounds. Region of interest analyses were corroborated by a data-driven independent component analysis, identifying face-voice and auditory speech responses as dominant sources of voxelwise variance across the STS. These results suggest that the STS contains separate processing streams for the audiovisual analysis of face actions and auditory speech processing.

Structural and Functional Brain Abnormalities in Misophonia

Misophonia is a newly described condition in which specific ordinary sounds provoke disproportionately strong negative affect. Since evidence for neurobiological abnormalities underlying misophonia is scarce, we tested whether misophonia patients differed from healthy controls in grey matter volumes and resting-state functional connectivity. We collected structural magnetic resonance imaging and resting-state functional magnetic resonance imaging data from 24 misophonia patients and 25 matched controls. Compared to controls, voxel-based morphometry showed larger right amygdala volume in misophonia patients. Follow-up seed-based functional connectivity analysis of the amygdala showed a different pattern of connectivity with the cerebellum, driven by greater connectivity with the left amygdala. Additional data-driven independent component analysis showed greater connectivity within lateral occipital cortices and fusiform gyri in the ventral attention network. We propose that the amygdala enlargement may be associated with heightened emotional reactivity in misophonia. The higher connectivity between left amygdala and cerebellum might be linked to a tendency to exhibit reflex-like physical reactions to triggers. Higher attention network connectivity may reflect sensory enhancement of visual triggers or visual imagery related to trigger sounds. In sum, we found structural and functional abnormalities which implicate dysfunction of emotional and attentional systems in misophonia.

Separating dopamine D2 and D3 receptor sources of [11C]-(+)-PHNO binding potential: Independent component analysis of competitive binding

Development of medications selective for dopamine D2 or D3 receptors is an active area of research in numerous neuropsychiatric disorders including addiction and Parkinson’s disease. The positron emission tomography (PET) radiotracer [11C]-(+)-PHNO, an agonist that binds with high affinity to both D2 and D3 receptors, has been used to estimate relative receptor subtype occupancy by drugs based on a priori knowledge of regional variation in the expression of D2 and D3 receptors. The objective of this work was to use a data-driven independent component analysis (ICA) of receptor blocking scans to separate D2-and D3-related signal in [11C]-(+)-PHNO binding data in order to improve the precision of subtype specific measurements of binding and occupancy. Eight healthy volunteers underwent [11C]-(+)-PHNO PET scans at baseline and at two time points following administration of the D3-preferring antagonist ABT-728 (150–1000 ​mg). Parametric binding potential (BPND) images were analyzed as four-dimensional image series using ICA to extract two independent sources of variation in [11C]-(+)-PHNO BPND. Spatial source maps for each component were consistent with respective regional patterns of D2-and D3-related binding. ICA-derived occupancy estimates from each component were similar to D2-and D3-specific occupancy estimated from a region-based approach (intraclass correlation coefficients ​> ​0.95). ICA-derived estimates of D3 receptor occupancy improved quality of fit to a single site binding model. Furthermore, ICA-derived estimates of the regional fraction of [11C]-(+)-PHNO binding related to D3 receptors was generated for each subject and values showed good agreement with region-based model estimates and prior literature values. In summary, ICA successfully separated D2-and D3-related components of the [11C]-(+)-PHNO binding signal, establishing this approach as a powerful data-driven method to quantify distinct biological features from PET data composed of mixed data sources.

Physical exercise increases involvement of motor networks as a compensatory mechanism during a cognitively challenging task.

Neuroimaging studies suggest that older adults may compensate for declines in cognitive function through neural compensation and reorganization of neural resources. While neural compensation as a key component of cognitive reserve is an important factor that mediates cognitive decline, the field lacks a quantitative measure of neural compensatory ability, and little is known about factors that may modify compensation, such as physical exercise. Twenty-five healthy older adults participated in a 6-week dance training exercise program. Gait speed, cognitive function, and functional magnetic resonance imaging during a challenging memory task were measured before and after the exercise program. In this study, we used a newly proposed data-driven independent component analysis approach to measure neural compensatory ability and tested the effect of physical exercise on neural compensation through a longitudinal study. After the exercise program, participants showed significantly improved memory performance in Logical Memory Test (WMS(LM)) (P<.001) and Rey Auditory Verbal Learning Test (P=.001) and increased gait speed measured by the 6-minute walking test (P=.01). Among all identified neural networks, only the motor cortices and cerebellum showed greater involvement during the memory task after exercise. Importantly, subjects who activated the motor network only after exercise (but not before exercise) showed WMS(LM) increases. We conclude that physical exercise improved gait speed, cognitive function, and compensatory ability through increased involvement of motor-related networks.

Trade-off of cerebello-cortical and cortico-cortical functional networks for planning in 6-year-old children

Childhood is a critical period for the development of cognitive planning. There is a lack of knowledge on its neural mechanisms in children. This study aimed to examine cerebello-cortical and cortico-cortical functional connectivity in association with planning skills in 6-year-olds (n = 76). We identified the cerebello-cortical and cortico-cortical functional networks related to cognitive planning using activation likelihood estimation (ALE) meta-analysis on existing functional imaging studies on spatial planning, and data-driven independent component analysis (ICA) of children's resting-state functional MRI (rs-fMRI). We investigated associations of cerebello-cortical and cortico-cortical functional connectivity with planning ability in 6-year-olds, as assessed using the Stockings of Cambridge task. Long-range functional connectivity of two cerebellar networks (lobules VI and lateral VIIa) with the prefrontal and premotor cortex were greater in children with poorer planning ability. In contrast, cortico-cortical association networks were not associated with the performance of planning in children. These results highlighted the key contribution of the lateral cerebello-frontal functional connectivity, but not cortico-cortical association functional connectivity, for planning ability in 6-year-olds. Our results suggested that brain adaptation to the acquisition of planning ability during childhood is partially achieved through the engagement of the cerebello-cortical functional connectivity.

Increased intrinsic brain connectivity between pons and somatosensory cortex during attacks of migraine with aura.

The neurological disturbances of migraine aura are caused by transient cortical dysfunction due to waves of spreading depolarization that disrupt neuronal signaling. The effects of these cortical events on intrinsic brain connectivity during attacks of migraine aura have not previously been investigated. Studies of spontaneous migraine attacks are notoriously challenging due to their unpredictable nature and patient discomfort. We investigated 16 migraine patients with visual aura during attacks and in the attack-free state using resting state fMRI. We applied a hypothesis-driven seed-based approach focusing on cortical visual areas and areas involved in migraine pain, and a data-driven independent component analysis approach to detect changes in intrinsic brain signaling during attacks. In addition, we performed the analyses after mirroring the MRI data according to the side of perceived aura symptoms. We found a marked increase in connectivity during attacks between the left pons and the left primary somatosensory cortex including the head and face somatotopic areas (peak voxel: P = 0.0096, (x, y, z) = (-54, -32, 32), corresponding well with the majority of patients reporting right-sided pain. For aura-side normalized data, we found increased connectivity during attacks between visual area V5 and the lower middle frontal gyrus in the symptomatic hemisphere (peak voxel: P = 0.0194, (x, y, z) = (40, 40, 12). The present study provides evidence of altered intrinsic brain connectivity during attacks of migraine with aura, which may reflect consequences of cortical spreading depression, suggesting a link between aura and headache mechanisms. Hum Brain Mapp 38:2635-2642, 2017. © 2017 Wiley Periodicals, Inc.

Independent component analysis model utilizing de-mixing information for improved non-Gaussian process monitoring

The de-mixing matrix generated from independent component analysis (ICA) can reveal information about the relations between variables and independent components, but the traditional ICA model does not preserve the whole de-mixing information for the purpose of feature extraction and dimensionality reduction, so that some important information may be abandoned. Multi-block strategy has been improved to be an efficient method to deal with numerous data. However, the manner of dividing original data is still subject for discussion and the priori knowledge is necessary for process division. This paper proposes a totally data-driven ICA model that divides de-mixing matrix based on the Generalized Dice’s coefficient and combines the results from sub-blocks using Bayesian inference. All information in de-mixing matrix is fully utilized and the ability of monitoring non-Gaussian process is improved. Meanwhile, a corresponding contribution plot is developed for fault diagnosis to find the root causes. The performance of the proposed method is illustrated through a numerical example and the Tennessee Eastman benchmark case study.

Task-evoked brain functional magnetic susceptibility mapping by independent component analysis (ϿICA)

BackgroundConventionally, independent component analysis (ICA) is performed on an fMRI magnitude dataset to analyze brain functional mapping (AICA). By solving the inverse problem of fMRI, we can reconstruct the brain magnetic susceptibility (Ͽ) functional states. Upon the reconstructed Ͽ dataspace, we propose an ICA-based brain functional Ͽ mapping method (ϿICA) to extract task-evoked brain functional map. New methodsA complex division algorithm is applied to a timeseries of fMRI phase images to extract temporal phase changes (relative to an OFF-state snapshot). A computed inverse MRI (CIMRI) model is used to reconstruct a 4D brain Ͽ response dataset. ϿICA is implemented by applying a spatial InfoMax ICA algorithm to the reconstructed 4D Ͽ dataspace. ResultsWith finger-tapping experiments on a 7T system, the ϿICA-extracted Ͽ-depicted functional map is similar to the SPM-inferred functional Ͽ map by a spatial correlation of 0.67±0.05. In comparison, the AICA-extracted magnitude-depicted map is correlated with the SPM magnitude map by 0.81±0.05. The understanding of the inferiority of ϿICA to AICA for task-evoked functional map is an ongoing research topic. Comparison with existing methodsFor task-evoked brain functional mapping, we compare the data-driven ICA method with the task-correlated SPM method. In particular, we compare ϿICA with AICA for extracting task-correlated timecourses and functional maps. ConclusionϿICA can extract a Ͽ-depicted task-evoked brain functional map from a reconstructed Ͽ dataspace without the knowledge about brain hemodynamic responses. The ϿICA-extracted brain functional Ͽ map reveals a bidirectional BOLD response pattern that is unavailable (or different) from AICA.