Most recent paper

Jumping over baselines with new methods to predict activation maps from resting-state fMRI.

Fri, 02/12/2021 - 19:13
Related Articles

Jumping over baselines with new methods to predict activation maps from resting-state fMRI.

Sci Rep. 2021 Feb 10;11(1):3480

Authors: Lacosse E, Scheffler K, Lohmann G, Martius G

Abstract
Cognitive fMRI research primarily relies on task-averaged responses over many subjects to describe general principles of brain function. Nonetheless, there exists a large variability between subjects that is also reflected in spontaneous brain activity as measured by resting state fMRI (rsfMRI). Leveraging this fact, several recent studies have therefore aimed at predicting task activation from rsfMRI using various machine learning methods within a growing literature on 'connectome fingerprinting'. In reviewing these results, we found lack of an evaluation against robust baselines that reliably supports a novelty of predictions for this task. On closer examination to reported methods, we found most underperform against trivial baseline model performances based on massive group averaging when whole-cortex prediction is considered. Here we present a modification to published methods that remedies this problem to large extent. Our proposed modification is based on a single-vertex approach that replaces commonly used brain parcellations. We further provide a summary of this model evaluation by characterizing empirical properties of where prediction for this task appears possible, explaining why some predictions largely fail for certain targets. Finally, with these empirical observations we investigate whether individual prediction scores explain individual behavioral differences in a task.

PMID: 33568695 [PubMed - in process]

How to Interpret Resting-State fMRI: Ask Your Participants.

Fri, 02/12/2021 - 19:13
Related Articles

How to Interpret Resting-State fMRI: Ask Your Participants.

J Neurosci. 2021 Feb 10;41(6):1130-1141

Authors: Gonzalez-Castillo J, Kam JWY, Hoy CW, Bandettini PA

Abstract
Resting-state fMRI (rsfMRI) reveals brain dynamics in a task-unconstrained environment as subjects let their minds wander freely. Consequently, resting subjects navigate a rich space of cognitive and perceptual states (i.e., ongoing experience). How this ongoing experience shapes rsfMRI summary metrics (e.g., functional connectivity) is unknown, yet likely to contribute uniquely to within- and between-subject differences. Here we argue that understanding the role of ongoing experience in rsfMRI requires access to standardized, temporally resolved, scientifically validated first-person descriptions of those experiences. We suggest best practices for obtaining those descriptions via introspective methods appropriately adapted for use in fMRI research. We conclude with a set of guidelines for fusing these two data types to answer pressing questions about the etiology of rsfMRI.

PMID: 33568446 [PubMed - in process]

Brain Structure and Function of Chronic Low Back Pain Patients on Long-Term Opioid Analgesic Treatment: A Preliminary Study.

Fri, 02/12/2021 - 19:13
Related Articles

Brain Structure and Function of Chronic Low Back Pain Patients on Long-Term Opioid Analgesic Treatment: A Preliminary Study.

Mol Pain. 2021 Jan-Dec;17:1744806921990938

Authors: Murray K, Lin Y, Makary MM, Whang PG, Geha P

Abstract
Chronic low back pain (CLBP) is often treated with opioid analgesics (OA), a class of medications associated with a significant risk of misuse. However, little is known about how treatment with OA affect the brain in chronic pain patients. Gaining this knowledge is a necessary first step towards understanding OA associated analgesia and elucidating long-term risk of OA misuse. Here we study CLBP patients chronically medicated with opioids without any evidence of misuse and compare them to CLBP patients not on opioids and to healthy controls using structural and functional brain imaging. CLBP patients medicated with OA showed loss of volume in the nucleus accumbens and thalamus, and an overall significant decrease in signal to noise ratio in their sub-cortical areas. Power spectral density analysis (PSD) of frequency content in the accumbens' resting state activity revealed that both medicated and unmedicated patients showed loss of PSD within the slow-5 frequency band (0.01-0.027 Hz) while only CLBP patients on OA showed additional density loss within the slow-4 frequency band (0.027-0.073 Hz). We conclude that chronic treatment with OA is associated with altered brain structure and function within sensory limbic areas.

PMID: 33567986 [PubMed - in process]

Resting-State Functional Network Models for Posttraumatic Stress Disorder.

Thu, 02/11/2021 - 19:13
Related Articles

Resting-State Functional Network Models for Posttraumatic Stress Disorder.

J Neurophysiol. 2021 Feb 10;:

Authors: Tu JW

Abstract
Four recent articles were examined for their use of resting-state functional magnetic resonance imaging on participants with posttraumatic symptoms. Theory-driven computations were complemented by the novel use of network metrics which revealed reduced global centrality and higher efficiency within the default mode network for participants with posttraumatic symptoms. Data-driven methods from other studies revealed associations between functional networks and PTSD symptoms as well as clusters of functional activation corresponding to different PTSD presentations.

PMID: 33566738 [PubMed - as supplied by publisher]

Functional connectivity of hippocampus in temporal lobe epilepsy depends on hippocampal dominance: a systematic review of the literature.

Thu, 02/11/2021 - 19:13
Related Articles

Functional connectivity of hippocampus in temporal lobe epilepsy depends on hippocampal dominance: a systematic review of the literature.

J Neurol. 2021 Feb 10;:

Authors: Milton CK, O'Neal CM, Conner AK

Abstract
BACKGROUND: Lateralized alterations in hippocampal function in the resting-state have been demonstrated for patients with temporal lobe epilepsy (TLE). However, resting-state fMRI of the hippocampus has yet to be substantiated as an adjunct to standard pre-operative assessments of the seizure focus.
OBJECTIVE: Here we report the results of a systematic review of resting-state fMRI studies investigating laterality of hippocampal network connectivity in TLE patients.
METHODS: A search of the PubMed, SCOPUS, Web of Science, and Embase databases for full-length articles written in English was conducted through June 2020 using the following terms: 'resting state fMRI,' 'hippocampus,' 'epilepsy,' and 'laterality.'
RESULTS: Our literature search yielded a total of 42 papers. After excluding studies that did not include patients with epilepsy, utilize resting-state fMRI, or explore the relationship between functional connectivity and disease lateralization, 20 publications were selected for inclusion. From these studies, a total of 528 patients, 258 with left TLE and 270 with right TLE, and 447 healthy controls were included. Of the 20 studies included, 18 found that patients with TLE demonstrated decreased hippocampal functional connectivity ipsilateral to the epileptogenic focus and 10 additionally reported increased hippocampal functional connectivity contralateral to the epileptogenic focus. Several studies demonstrated that the duration of disease was correlated with these changes in functional connectivity. This implies that a compensatory mechanism may be present in patients with treatment-refractory TLE.
CONCLUSION: The consistency of this hippocampal connectivity pattern across multiple studies suggests resting-state fMRI may be useful as a non-invasive diagnostic tool for preoperative evaluation of TLE patients.

PMID: 33564915 [PubMed - as supplied by publisher]

Neural and social correlates of attitudinal brokerage: using the complete social networks of two entire villages.

Thu, 02/11/2021 - 19:13
Related Articles

Neural and social correlates of attitudinal brokerage: using the complete social networks of two entire villages.

Proc Biol Sci. 2021 Feb 10;288(1944):20202866

Authors: Youm Y, Kim J, Kwak S, Chey J

Abstract
To avoid polarization and maintain small-worldness in society, people who act as attitudinal brokers are critical. These people maintain social ties with people who have dissimilar and even incompatible attitudes. Based on resting-state functional magnetic resonance imaging (n = 139) and the complete social networks from two Korean villages (n = 1508), we investigated the individual-level neural capacity and social-level structural opportunity for attitudinal brokerage regarding gender role attitudes. First, using a connectome-based predictive model, we successfully identified the brain functional connectivity that predicts attitudinal diversity of respondents' social network members. Brain regions that contributed most to the prediction included mentalizing regions known to be recruited in reading and understanding others' belief states. This result was corroborated by leave-one-out cross-validation, fivefold cross-validation and external validation where the brain connectivity identified in one village was used to predict the attitudinal diversity in another independent village. Second, the association between functional connectivity and attitudinal diversity of social network members was contingent on a specific position in a social network, namely, the structural brokerage position where people have ties with two people who are not otherwise connected.

PMID: 33563127 [PubMed - in process]

Sensory Processing Sensitivity Predicts Individual Differences in Resting-State Functional Connectivity Associated with Depth of Processing.

Wed, 02/10/2021 - 19:12
Related Articles

Sensory Processing Sensitivity Predicts Individual Differences in Resting-State Functional Connectivity Associated with Depth of Processing.

Neuropsychobiology. 2021 Feb 09;:1-15

Authors: Acevedo BP, Santander T, Marhenke R, Aron A, Aron E

Abstract
BACKGROUND: Sensory processing sensitivity (SPS) is a biologically based temperament trait associated with enhanced awareness and responsivity to environmental and social stimuli. Individuals with high SPS are more affected by their environments, which may result in overarousal, cognitive depletion, and fatigue.
METHOD: We examined individual differences in resting-state (rs) brain connectivity (using functional MRI) as a function of SPS among a group of adults (M age = 66.13 ± 11.44 years) immediately after they completed a social affective "empathy" task. SPS was measured with the Highly Sensitive Person (HSP) Scale and correlated with rs brain connectivity.
RESULTS: Results showed enhanced rs brain connectivity within the ventral attention, dorsal attention, and limbic networks as a function of greater SPS. Region of interest analyses showed increased rs brain connectivity between the hippocampus and the precuneus (implicated in episodic memory); while weaker connectivity was shown between the amygdala and the periaqueductal gray (important for anxiety), and the hippocampus and insula (implicated in habitual cognitive processing).
CONCLUSIONS: The present study showed that SPS is associated with rs brain connectivity implicated in attentional control, consolidation of memory, physiological homeostasis, and deliberative cognition. These results support theories proposing "depth of processing" as a central feature of SPS and highlight the neural processes underlying this cardinal feature of the trait.

PMID: 33561863 [PubMed - as supplied by publisher]

Cerebral areas affected by unilateral acupuncture on SP3 in healthy volunteers: An explorative resting-state fMRI study.

Wed, 02/10/2021 - 19:12
Related Articles

Cerebral areas affected by unilateral acupuncture on SP3 in healthy volunteers: An explorative resting-state fMRI study.

Brain Behav. 2021 Feb 09;:e02057

Authors: Wang F, Yang T, Li X, Liu X, Cao D, Wang D, Yang Y, Li C, Qu Y, Zhao X, Sun Z, Asakawa T

Abstract
OBJECTIVE: The study aimed to explore the cerebral areas with changes in regional homogeneity (ReHo) and amplitude of low-frequency fluctuation (ALFF) values induced by effective acupuncture on the Taibai (SP3) point.
METHODS: In the study, 15 healthy right-handed volunteers (seven males and eight females, 20-35 years old) were enrolled. The average ages of the subjects were 28.0 ± 4.24 years for males and 27.4 ± 3.65 years for females. A 3.0T magnetic resonance imaging (MRI) system was used to perform resting-state functional MRI scan after sham and effective acupuncture on the SP3 point. The differences in cerebral ReHo and ALFF values between posteffective acupuncture and postsham acupuncture were compared using the SPM 12 software.
RESULTS: ReHo values of bilateral BA18, cuneus, and BA17, along with BA41, BA22, postcentral gyrus, and BA7 on the right side, were decreased by effective SP3 acupuncture. The ALFF values of bilateral BA 30 and left parahippocampal area were increased, whereas the values of bilateral BA18, BA19, cuneus, posterior cingulate gyrus, and BA7, along with the right superior occipital lobule, postcentral gyrus, and left precuneus, were decreased.
CONCLUSIONS: The most dominant cerebral areas affected by SP3 acupuncture were bilateral visual-related cortices (lingual gyrus, cuneus, and calcarine), along with the unilateral postcentral gyrus and superior parietal lobule. These findings may be potential explanations for the available clinical reports concerning the efficacy of SP3 acupuncture. Further clinical and experimental studies on SP3 acupuncture are required.

PMID: 33560579 [PubMed - as supplied by publisher]

Resting fMRI-guided TMS results in subcortical and brain network modulation indexed by interleaved TMS/fMRI.

Wed, 02/10/2021 - 19:12
Related Articles

Resting fMRI-guided TMS results in subcortical and brain network modulation indexed by interleaved TMS/fMRI.

Exp Brain Res. 2021 Feb 09;:

Authors: Oathes DJ, Zimmerman JP, Duprat R, Japp SS, Scully M, Rosenberg BM, Flounders MW, Long H, Deluisi JA, Elliott M, Shandler G, Shinohara RT, Linn KA

Abstract
Traditional non-invasive imaging methods describe statistical associations of functional co-activation over time. They cannot easily establish hierarchies in communication as done in non-human animals using invasive methods. Here, we interleaved functional MRI (fMRI) recordings with non-invasive transcranial magnetic stimulation (TMS) to map causal communication between the frontal cortex and subcortical target structures including the subgenual anterior cingulate cortex (sgACC) and the amygdala. Seed-based correlation maps from each participant's resting fMRI scan determined individual stimulation sites with high temporal correlation to targets for the subsequent TMS/fMRI session(s). The resulting TMS/fMRI images were transformed to quantile responses, so that regions of high-/low-quantile response corresponded to the areas of the brain with the most positive/negative evoked response relative to the global brain response. We then modeled the average quantile response for a given region (e.g., structure or network) to determine whether TMS was effective in the relative engagement of the downstream targets. Both the sgACC and amygdala were differentially influenced by TMS. Furthermore, we found that the sgACC distributed brain network was modulated in response to fMRI-guided TMS. The amygdala, but not its distributed network, also responded to TMS. Our findings suggest that individual targeting and brain response measurements reflect causal circuit mapping to the sgACC and amygdala in humans. These results set the stage to further map circuits in the brain and link circuit pathway integrity to clinical intervention outcomes, especially when the intervention targets specific pathways and networks as is possible with TMS.

PMID: 33560448 [PubMed - as supplied by publisher]

Effects of short-term cognitive-coping therapy on resting-state brain function in obsessive-compulsive disorder.

Wed, 02/10/2021 - 19:12
Related Articles

Effects of short-term cognitive-coping therapy on resting-state brain function in obsessive-compulsive disorder.

Brain Behav. 2021 Feb 09;:e02059

Authors: Ma JD, Wang CH, Huang P, Wang X, Shi LJ, Li HF, Sang DE, Kou SJ, Li ZR, Zhao HZ, Lian HK, Hu XZ

Abstract
BACKGROUND: Obsessive-compulsive disorder (OCD) tends to be treatment refractory. Recently, cognitive-coping therapy (CCT) for OCD is reported to be an efficacious psychotherapy. However, the underlying neurophysiological mechanism remains unknown. Here, the effects of CCT on OCD and the resting-state brain function were investigated.
METHODS: Fifty-nine OCD patients underwent CCT, pharmacotherapy plus CCT (pCCT), or pharmacotherapy. Before and after a 4-week treatment, Yale-Brown obsessive-compulsive scale (Y-BOCS) was evaluated and resting-state functional magnetic resonance imaging (rs-fMRI) was scanned.
RESULTS: Compared with the baseline, significant reduction of Y-BOCS scores was found after four-week treatment (p < .001) in groups of CCT and pCCT, not in pharmacotherapy. Post-treatment Y-BOCS scores of CCT group and pCCT group were not different, but significantly lower than that of pharmacotherapy group (p < .001). Compared with pretreatment, two clusters of brain regions with significant change in amplitude of low-frequency fluctuation (ALFF) were obtained in those who treated with CCT and pCCT, but not in those who received pharmacotherapy. The ALFF in cluster 1 (insula, putamen, and postcentral gyrus in left cerebrum) was decreased, while the ALFF in cluster 2 (occipital medial gyrus, occipital inferior gyrus, and lingual gyrus in right hemisphere) was increased after treatment (corrected p < .05). The changes of ALFF were correlated with the reduction of Y-BOCS score and were greater in remission than in nonremission. The reduction of the fear of negative events was correlated to the changes of ALFF of clusters and the reduction of Y-BOCS score.
CONCLUSIONS: The effectiveness of CCT for OCD was related to the alteration of resting-state brain function-the brain plasticity.
TRIAL REGISTRATION: ChiCTR-IPC-15005969.

PMID: 33559216 [PubMed - as supplied by publisher]

Alcohol Use Disorder and Its Comorbidity With HIV Infection Disrupts Anterior Cingulate Cortex Functional Connectivity.

Wed, 02/10/2021 - 19:12
Related Articles

Alcohol Use Disorder and Its Comorbidity With HIV Infection Disrupts Anterior Cingulate Cortex Functional Connectivity.

Biol Psychiatry Cogn Neurosci Neuroimaging. 2020 Nov 28;:

Authors: Honnorat N, Fama R, Müller-Oehring EM, Zahr NM, Pfefferbaum A, Sullivan EV, Pohl KM

Abstract
BACKGROUND: Individuals with alcohol use disorder (AUD) have a heightened risk of contracting HIV infection. The effects of these two diseases and their comorbidity on brain structure have been well described, but their effects on brain function have never been investigated at the scale of whole-brain connectomes.
METHODS: In contrast with prior studies that restricted analyses to specific brain networks or examined relatively small groups of participants, our analyses are based on whole-brain functional connectomes of 292 participants.
RESULTS: Relative to participants without AUD, the functional connectivity between the anterior cingulate cortex and orbitofrontal cortex was lower for participants with AUD. Compared with participants without AUD+HIV comorbidity, the functional connectivity between the anterior cingulate cortex and hippocampus was lower for the AUD+HIV participants. Compromised connectivity between these pairs was significantly correlated with greater total lifetime alcohol consumption; the effects of total lifetime alcohol consumption on executive functioning were significantly mediated by the functional connectivity between the pairs.
CONCLUSIONS: Taken together, our results suggest that the functional connectivity of the anterior cingulate cortex is disrupted in individuals with AUD alone and AUD with HIV infection comorbidity. Moreover, the affected connections are associated with deficits in executive functioning, including heightened impulsiveness.

PMID: 33558196 [PubMed - as supplied by publisher]

Theoretical properties of distance distributions and novel metrics for nearest-neighbor feature selection.

Wed, 02/10/2021 - 01:12
Related Articles

Theoretical properties of distance distributions and novel metrics for nearest-neighbor feature selection.

PLoS One. 2021;16(2):e0246761

Authors: Dawkins BA, Le TT, McKinney BA

Abstract
The performance of nearest-neighbor feature selection and prediction methods depends on the metric for computing neighborhoods and the distribution properties of the underlying data. Recent work to improve nearest-neighbor feature selection algorithms has focused on new neighborhood estimation methods and distance metrics. However, little attention has been given to the distributional properties of pairwise distances as a function of the metric or data type. Thus, we derive general analytical expressions for the mean and variance of pairwise distances for Lq metrics for normal and uniform random data with p attributes and m instances. The distribution moment formulas and detailed derivations provide a resource for understanding the distance properties for metrics and data types commonly used with nearest-neighbor methods, and the derivations provide the starting point for the following novel results. We use extreme value theory to derive the mean and variance for metrics that are normalized by the range of each attribute (difference of max and min). We derive analytical formulas for a new metric for genetic variants, which are categorical variables that occur in genome-wide association studies (GWAS). The genetic distance distributions account for minor allele frequency and the transition/transversion ratio. We introduce a new metric for resting-state functional MRI data (rs-fMRI) and derive its distance distribution properties. This metric is applicable to correlation-based predictors derived from time-series data. The analytical means and variances are in strong agreement with simulation results. We also use simulations to explore the sensitivity of the expected means and variances in the presence of correlation and interactions in the data. These analytical results and new metrics can be used to inform the optimization of nearest neighbor methods for a broad range of studies, including gene expression, GWAS, and fMRI data.

PMID: 33556091 [PubMed - as supplied by publisher]

Disrupted balance of long and short-range functional connectivity density in Alzheimer's disease (AD) and mild cognitive impairment (MCI) patients: a resting-state fMRI study.

Wed, 02/10/2021 - 01:12
Related Articles

Disrupted balance of long and short-range functional connectivity density in Alzheimer's disease (AD) and mild cognitive impairment (MCI) patients: a resting-state fMRI study.

Ann Transl Med. 2021 Jan;9(1):65

Authors: Mao Y, Liao Z, Liu X, Li T, Hu J, Le D, Pei Y, Sun W, Lin J, Qiu Y, Zhu J, Chen Y, Qi C, Su H, Yu E

Abstract
Background: Alzheimer's disease (AD) is an age-progressive neurodegenerative disorder that affects cognitive function. There have been several functional connectivity (FC) strengths; however, FC density needs more development in AD. Therefore, this study wanted to determine the alternations in resting-state functional connectivity density (FCD) induced by Alzheimer's and mild cognitive impairment (MCI).
Methods: One hundred and eleven AD patients, 29 MCI patients, and 73 healthy controls (age- and sex-matched) were recruited and assessed using resting-state functional magnetic resonance imaging (MRI) scanning. The ultra-fast graph theory called FCD mapping was used to calculate the voxel-wise short- and long-range FCD values of the brain. We performed voxel-based between-group comparisons of FCD values to show the cerebral regions with significant FCD alterations. We performed Pearson's correlation analyses between aberrant functional connectivity densities and several clinical variables with adjustment for age and sex.
Results: Patients with cognition decline showed significantly abnormal long-range FCD in the cerebellum crus I, right insula, left inferior frontal gyrus, left superior frontal gyrus, left inferior frontal gyrus, and right middle frontal gyrus. The short-range FCD changed in the cerebellum crus I, left inferior frontal gyrus, left superior occipital gyrus, and right middle frontal gyrus. The long- and short-range functional connectivity in the left inferior frontal gyrus was positively correlated with Mini-mental State Examination (MMSE) scores.
Conclusions: FCD in the identified regions reflects mechanism and compensation for loss of cognitive function. These findings could improve the pathology of AD and MCI and supply a neuroimaging marker for AD and MCI.

PMID: 33553358 [PubMed]

Temporal dynamic changes of intrinsic brain activity in Alzheimer's disease and mild cognitive impairment patients: a resting-state functional magnetic resonance imaging study.

Wed, 02/10/2021 - 01:12
Related Articles

Temporal dynamic changes of intrinsic brain activity in Alzheimer's disease and mild cognitive impairment patients: a resting-state functional magnetic resonance imaging study.

Ann Transl Med. 2021 Jan;9(1):63

Authors: Li T, Liao Z, Mao Y, Hu J, Le D, Pei Y, Sun W, Lin J, Qiu Y, Zhu J, Chen Y, Qi C, Ye X, Su H, Yu E

Abstract
Background: Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by memory impairment. Previous studies have largely focused on alterations of static brain activity occurring in patients with AD. Few studies to date have explored the characteristics of dynamic brain activity in cognitive impairment, and their predictive ability in AD patients.
Methods: One hundred and eleven AD patients, 29 MCI patients, and 73 healthy controls (HC) were recruited. The dynamic amplitude of low-frequency fluctuation (dALFF) and the dynamic fraction amplitude of low-frequency fluctuation (dfALFF) were used to assess the temporal variability of local brain activity in patients with AD or mild cognitive impairment (MCI). Pearson's correlation coefficients were calculated between the metrics and subjects' behavioral scores.
Results: The results of analysis of variance indicated that the AD, MCI, and HC groups showed significant variability of dALFF in the cerebellar posterior and middle temporal lobes. In AD patients, these brain regions had high dALFF variability. Significant dfALFF variability was found between the three groups in the left calcarine cortex and white matter. The AD group showed lower dfALFF than the MCI group in the left calcarine cortex.
Conclusions: Compared to HC, AD patients were found to have increased dALFF variability in the cerebellar posterior and temporal lobes. This abnormal pattern may diminish the capacity of the cerebellum and temporal lobes to participate in the cerebrocerebellar circuits and default mode network (DMN), which regulate cognition and emotion in AD. The findings above indicate that the analysis of dALFF and dfALFF based on functional magnetic resonance imaging data may give a new insight into the neurophysiological mechanisms of AD.

PMID: 33553356 [PubMed]

The Medial Thalamus Plays an Important Role in the Cognitive and Emotional Modulation of Orofacial Pain: A Functional Magnetic Resonance Imaging-Based Study.

Wed, 02/10/2021 - 01:12
Related Articles

The Medial Thalamus Plays an Important Role in the Cognitive and Emotional Modulation of Orofacial Pain: A Functional Magnetic Resonance Imaging-Based Study.

Front Neurol. 2020;11:589125

Authors: Jin Y, Yang H, Zhang F, Wang J, Liu H, Yang X, Long H, Li F, Gong Q, Lai W

Abstract
The thalamus plays a critical role in the perception of orofacial pain. We investigated the neural mechanisms of orofacial pain by exploring the intrinsic functional alterations of the thalamus and assessing the changes in functional connectivity (FC) between the thalamic subregions with significant functional alterations and other brain regions in orofacial pain using the seed-based FC approach. There were 49 participants in the orofacial pain group and 49 controls. Orofacial pain was caused by orthodontic separators. The resting-state functional magnetic resonance imaging data of the two groups were analyzed to obtain the fractional amplitude of low-frequency fluctuations (fALFF) of the thalamus; the thalamic subregions with significant fALFF abnormalities were used as seeds for FC analysis. Student's t-tests were used for comparisons. Pearson's correlation analysis was performed using SPM software. Forty-four participants with orofacial pain (mean age, 21.0 ± 0.9 years; 24 women) and 49 age- and sex-matched controls (mean age, 21.0 ± 2.6 years; 27 women) were finally included. Compared with the control group, the orofacial pain group demonstrated the following: (1) increased function in the dorsal area of the thalamus and decreased function in the medial thalamus; (2) decreased FC between the medial thalamus and 12 brain regions (p < 0.05, family-wise error corrected, voxel > 100); and (3) potential positive and negative correlations between the medial thalamus-seeded FC and visual analog scale score changes (p < 0.05, AlphaSim corrected). The findings show that the medial and dorsal thalami play important roles in orofacial pain perception, and that the medial thalamus likely plays an important role in the cognitive and emotional modulation of orofacial pain.

PMID: 33551953 [PubMed]

Resting State Functional Connectivity of Brain With Electroconvulsive Therapy in Depression: Meta-Analysis to Understand Its Mechanisms.

Wed, 02/10/2021 - 01:12
Related Articles

Resting State Functional Connectivity of Brain With Electroconvulsive Therapy in Depression: Meta-Analysis to Understand Its Mechanisms.

Front Hum Neurosci. 2020;14:616054

Authors: Sinha P, Joshi H, Ithal D

Abstract
Introduction: Electroconvulsive therapy (ECT) is a commonly used brain stimulation treatment for treatment-resistant or severe depression. This study was planned to find the effects of ECT on brain connectivity by conducting a systematic review and coordinate-based meta-analysis of the studies performing resting state fMRI (rsfMRI) in patients with depression receiving ECT. Methods: We systematically searched the databases published up to July 31, 2020, for studies in patients having depression that compared resting-state functional connectivity (rsFC) before and after a course of pulse wave ECT. Meta-analysis was performed using the activation likelihood estimation method after extracting details about coordinates, voxel size, and method for correction of multiple comparisons corresponding to the significant clusters and the respective rsFC analysis measure with its method of extraction. Results: Among 41 articles selected for full-text review, 31 articles were included in the systematic review. Among them, 13 articles were included in the meta-analysis, and a total of 73 foci of 21 experiments were examined using activation likelihood estimation in 10 sets. Using the cluster-level interference method, one voxel-wise analysis with the measure of amplitude of low frequency fluctuations and one seed-voxel analysis with the right hippocampus showed a significant reduction (p < 0.0001) in the left cingulate gyrus (dorsal anterior cingulate cortex) and a significant increase (p < 0.0001) in the right hippocampus with the right parahippocampal gyrus, respectively. Another analysis with the studies implementing network-wise (posterior default mode network: dorsomedial prefrontal cortex) resting state functional connectivity showed a significant increase (p < 0.001) in bilateral posterior cingulate cortex. There was considerable variability as well as a few key deficits in the preprocessing and analysis of the neuroimages and the reporting of results in the included studies. Due to lesser studies, we could not do further analysis to address the neuroimaging variability and subject-related differences. Conclusion: The brain regions noted in this meta-analysis are reasonably specific and distinguished, and they had significant changes in resting state functional connectivity after a course of ECT for depression. More studies with better neuroimaging standards should be conducted in the future to confirm these results in different subgroups of depression and with varied aspects of ECT.

PMID: 33551779 [PubMed]

Resting-State Co-activation Patterns as Promising Candidates for Prediction of Alzheimer's Disease in Aged Mice.

Wed, 02/10/2021 - 01:12
Related Articles

Resting-State Co-activation Patterns as Promising Candidates for Prediction of Alzheimer's Disease in Aged Mice.

Front Neural Circuits. 2020;14:612529

Authors: Adhikari MH, Belloy ME, Van der Linden A, Keliris GA, Verhoye M

Abstract
Alzheimer's disease (AD), a neurodegenerative disorder marked by accumulation of extracellular amyloid-β (Aβ) plaques leads to progressive loss of memory and cognitive function. Resting-state fMRI (RS-fMRI) studies have provided links between these two observations in terms of disruption of default mode and task-positive resting-state networks (RSNs). Important insights underlying these disruptions were recently obtained by investigating dynamic fluctuations in RS-fMRI signals in old TG2576 mice (a mouse model of amyloidosis) using a set of quasi-periodic patterns (QPP). QPPs represent repeating spatiotemporal patterns of neural activity of predefined temporal length. In this article, we used an alternative methodology of co-activation patterns (CAPs) that represent instantaneous and transient brain configurations that are likely contributors to the emergence of commonly observed RSNs and QPPs. We followed a recently published approach for obtaining CAPs that divided all time frames, instead of those corresponding to supra-threshold activations of a seed region as done traditionally, to extract CAPs from RS-fMRI recordings in 10 TG2576 female mice and eight wild type littermates at 18 months of age. Subsequently, we matched the CAPs from the two groups using the Hungarian method and compared the temporal (duration, occurrence rate) and the spatial (lateralization of significantly co-activated and co-deactivated voxels) properties of matched CAPs. We found robust differences in the spatial components of matched CAPs. Finally, we used supervised learning to train a classifier using either the temporal or the spatial component of CAPs to distinguish the transgenic mice from the WT. We found that while duration and occurrence rates of all CAPs performed the classification with significantly higher accuracy than the chance-level, blood oxygen level-dependent (BOLD) signals of significantly activated voxels from individual CAPs turned out to be a significantly better predictive feature demonstrating a near-perfect classification accuracy. Our results demonstrate resting-state co-activation patterns are a promising candidate in the development of a diagnostic, and potentially, prognostic RS-fMRI biomarker of AD.

PMID: 33551755 [PubMed - in process]

Alzheimer's Disease Projection From Normal to Mild Dementia Reflected in Functional Network Connectivity: A Longitudinal Study.

Wed, 02/10/2021 - 01:12
Related Articles

Alzheimer's Disease Projection From Normal to Mild Dementia Reflected in Functional Network Connectivity: A Longitudinal Study.

Front Neural Circuits. 2020;14:593263

Authors: Sendi MSE, Zendehrouh E, Miller RL, Fu Z, Du Y, Liu J, Mormino EC, Salat DH, Calhoun VD

Abstract
Background: Alzheimer's disease (AD) is the most common age-related problem and progresses in different stages, including mild cognitive impairment (early stage), mild dementia (middle-stage), and severe dementia (late-stage). Recent studies showed changes in functional network connectivity obtained from resting-state functional magnetic resonance imaging (rs-fMRI) during the transition from healthy aging to AD. By assuming that the brain interaction is static during the scanning time, most prior studies are focused on static functional or functional network connectivity (sFNC). Dynamic functional network connectivity (dFNC) explores temporal patterns of functional connectivity and provides additional information to its static counterpart.
Method: We used longitudinal rs-fMRI from 1385 scans (from 910 subjects) at different stages of AD (from normal to very mild AD or vmAD). We used group-independent component analysis (group-ICA) and extracted 53 maximally independent components (ICs) for the whole brain. Next, we used a sliding-window approach to estimate dFNC from the extracted 53 ICs, then group them into 3 different brain states using a clustering method. Then, we estimated a hidden Markov model (HMM) and the occupancy rate (OCR) for each subject. Finally, we investigated the link between the clinical rate of each subject with state-specific FNC, OCR, and HMM.
Results: All states showed significant disruption during progression normal brain to vmAD one. Specifically, we found that subcortical network, auditory network, visual network, sensorimotor network, and cerebellar network connectivity decrease in vmAD compared with those of a healthy brain. We also found reorganized patterns (i.e., both increases and decreases) in the cognitive control network and default mode network connectivity by progression from normal to mild dementia. Similarly, we found a reorganized pattern of between-network connectivity when the brain transits from normal to mild dementia. However, the connectivity between visual and sensorimotor network connectivity decreases in vmAD compared with that of a healthy brain. Finally, we found a normal brain spends more time in a state with higher connectivity between visual and sensorimotor networks.
Conclusion: Our results showed the temporal and spatial pattern of whole-brain FNC differentiates AD form healthy control and suggested substantial disruptions across multiple dynamic states. In more detail, our results suggested that the sensory network is affected more than other brain network, and default mode network is one of the last brain networks get affected by AD In addition, abnormal patterns of whole-brain dFNC were identified in the early stage of AD, and some abnormalities were correlated with the clinical score.

PMID: 33551754 [PubMed - in process]

Propagating patterns of intrinsic activity along macroscale gradients coordinate functional connections across the whole brain.

Tue, 02/09/2021 - 19:11
Related Articles

Propagating patterns of intrinsic activity along macroscale gradients coordinate functional connections across the whole brain.

Neuroimage. 2021 Feb 04;:117827

Authors: Yousefi B, Keilholz S

Abstract
The intrinsic activity of the human brain, observed with resting-state fMRI (rsfMRI) and functional connectivity, exhibits macroscale spatial organization such as functional networks and gradients. Dynamic analysis techniques have shown that functional connectivity is a mere summary of time-varying patterns with distinct spatial and temporal characteristics. A better understanding of these patterns might provide insight into aspects of the brain's intrinsic activity that cannot be inferred by functional connectivity or the spatial maps derived from it, such as functional networks and gradients. Here, we describe three spatiotemporal patterns of coordinated activity across the whole brain obtained by averaging similar ∼20-second-long segments of rsfMRI timeseries. In each of these patterns, activity propagates along a particular macroscale functional gradient, simultaneously across the cerebral cortex and in most other brain regions. In some regions, like the thalamus, the propagation suggests previously-undescribed gradients. The coordinated activity across areas is consistent with known tract-based connections, and nuanced differences in the timing of peak activity between regions point to plausible driving mechanisms. The magnitude of correlation within and particularly between functional networks is remarkably diminished when these patterns are regressed from the rsfMRI timeseries, a quantitative demonstration of their significant role in functional connectivity. Taken together, our results suggest that a few recurring patterns of propagating intrinsic activity along macroscale gradients give rise to and coordinate functional connections across the whole brain.

PMID: 33549755 [PubMed - as supplied by publisher]

Hemodynamic Matrix Factorization for Functional Magnetic Resonance Imaging.

Tue, 02/09/2021 - 19:11
Related Articles

Hemodynamic Matrix Factorization for Functional Magnetic Resonance Imaging.

Neuroimage. 2021 Feb 04;:117814

Authors: Hütel M, Antonelli M, Melbourne A, Ourselin S

Abstract
The General Linear Model (GLM) used in task-fMRI relates activated brain areas to extrinsic task conditions. The translation of resulting neural activation into a hemodynamic response is commonly approximated with a linear convolution model using a hemodynamic response function (HRF). There are two major limitations in GLM analysis. First, the GLM assumes that neural activation is either on or off and matches the exact stimulus duration in the corresponding task timings. Second, brain networks observed in resting-state fMRI experiments present also during task experiments, but the GLM approach models these task-unrelated brain activity as noise. A novel kernel matrix factorization approach, called hemodynamic matrix factorization (HMF), is therefore proposed that addresses both limitations by assuming that task-related and task-unrelated brain activity can be modeled with the same convolution model as in GLM analysis. By contrast to the GLM, the proposed HMF is a blind source separation (BSS) technique, which decomposes fMRI data into modes. Each mode comprises of a neural activation time course and a spatial mapping. Two versions of HMF are proposed in which the neural activation time course of each mode is convolved with either the canonical HRF or predetermined subject-specific HRFs. Firstly, HMF with the canonical HRF is applied to two open-source cohorts. These cohorts comprise of several task experiments including motor, incidental memory, spatial coherence discrimination, verbal discrimination task and a very short localization task, engaging multiple parts of the eloquent cortex. HMF modes were obtained whose neural activation time course followed original task timings and whose corresponding spatial map matched cortical areas known to be involved in the respective task processing. Secondly, the alignment of these neural activation time courses to task timings were further improved by replacing the canonical HRF with subject-specific HRFs during HMF mode computation. In addition to task-related modes, HMF also produced seemingly task-unrelated modes whose spatial maps matched known resting-state networks. The validity of a fMRI task experiment relies on the assumption that the exposure to a stimulus for a given time causes an imminent increase in neural activation of equal duration. The proposed HMF is an attempt to falsify this assumption and allows to identify subject task participation that does not comply with the experiment instructions.

PMID: 33549748 [PubMed - as supplied by publisher]