Robust dynamic brain coactivation states estimated in individuals

Brain fingerprinting and cognitive behavior predicting using functional connectome of high inter-subject variability

The functional connectivity (FC) graph of the brain has been widely recognized as a ``fingerprint'' that can be used to identify individuals from a group of subjects. Research has indicated that individual identification accuracy can be improved by eliminating the impact of shared information among individuals. However, current research extracts not only shared information of inter-subject but also individual-specific information from FC graphs, resulting in incomplete separation of shared information and fingerprint information among individuals, leading to lower individual identification accuracy across all functional magnetic resonance imaging (fMRI) states session pairs and poor cognitive behavior prediction performance. In this paper, we propose a method to enhance inter-subject variability combining conditional variational autoencoder (CVAE) network and sparse dictionary learning (SDL) module. By embedding fMRI state information in the encoding and decoding processes, the CVAE network can better capture and represent the common features among individuals and enhance inter-subject variability by residual. Our experimental results on Human Connectome Project (HCP) data show that the refined connectomes obtained by using CVAE with SDL can accurately distinguish an individual from the remaining participants. The success accuracies reached 99.7 % and 99.6 % in the session pair rest1-rest2 and reverse rest2-rest1, respectively. In the identification experiment involving task-task combinations carried out on the same day, the identification accuracies ranged from 94.2 % to 98.8 %. Furthermore, we showed the Frontoparietal and Default networks make the most significant contributions to individual identification and the edges that significantly contribute to individual identification are found within and between the Frontoparietal and Default networks. Additionally, high-level cognitive behaviors can also be better predicted with the obtained refined connectomes, suggesting that higher fingerprinting can be useful for resulting in higher behavioral associations. In summary, our proposed framework provides a promising approach to use functional connectivity networks for studying cognition and behavior, promoting a deeper understanding of brain functions.

Non-invasive suppression of the human nucleus accumbens (NAc) with transcranial focused ultrasound (tFUS) modulates the reward network: a pilot study

Background

The nucleus accumbens (NAc) is a key node of the brain reward circuit driving reward-related behavior. Dysregulation of NAc has been demonstrated to contribute to pathological markers of addiction in substance use disorder (SUD) making it a potential therapeutic target for brain stimulation. Transcranial focused ultrasound (tFUS) is an emerging non-invasive brain stimulation approach that can modulate deep brain regions with a high spatial resolution. However, there is currently no evidence showing how the brain activity of NAc and brain functional connectivity within the reward network neuromodulated by tFUS on the NAc.

Methods

In this pilot study, we carried out a single-blind, sham-controlled clinical trial using functional magnetic resonance imaging (fMRI) to investigate the underlying mechanism of tFUS neuromodulating the reward network through NAc in ten healthy adults. Specifically, the experiment consists of a 20-min concurrent tFUS/fMRI scan and two 24-min resting-state fMRI before and after the tFUS session.

Results

Firstly, our results demonstrated the feasibility and safety of 20-min tFUS on NAc. Additionally, our findings demonstrated that bilateral NAc was inhibited during tFUS on the left NAc compared to sham. Lastly, increased functional connectivity between the NAc and medial prefrontal cortex (mPFC) was observed after tFUS on the left NAc, but no changes for the sham group.

Conclusion

Delivering tFUS to the NAc can modulate brain activations and functional connectivity within the reward network. These preliminary findings suggest that tFUS could be potentially a promising neuromodulation tool for the direct and non-invasive management of the NAc and shed new light on the treatment for SUD and other brain diseases that involve reward processing.

Multi-modal neuroimaging reveals differences in alcohol-cue reactivity but not neurometabolite concentrations in adolescents who drink alcohol

BACKGROUND

The objective of this multi-modal neuroimaging study was to identify neuroscience-informed treatment targets for adolescent alcohol use disorder (AUD) by examining potential neural alterations associated with adolescent alcohol use.

METHODS

Adolescents (ages 17-19) who heavily used (n=49) or did not use alcohol (n=22) were recruited for a multi-modal neuroimaging protocol, including proton magnetic resonance spectroscopy within the dorsal anterior cingulate cortex (dACC) and an fMRI alcohol cue-reactivity task. The alcohol cue-reactivity task was analyzed across 11 a priori regions-of-interest (ROI), including the dACC, and in an exploratory whole-brain approach. Correlations were run between neurometabolite levels and alcohol cue-reactivity in the dACC.

RESULTS

There were no significant group differences in absolute neurometabolite concentrations. Compared to the control group, the alcohol-using group exhibited heightened alcohol cue reactivity in the left amygdala ROI (p=0.04). The whole-brain approach identified higher alcohol cue reactivity in the alcohol-using group compared to controls in the amygdala and occipital regions, and lower reactivity in the parietal lobe. Whole-brain sex effects were noted, with females displaying higher reactivity regardless of group. No significant correlations were found between neurometabolite levels and alcohol cue-reactivity in the dACC.

CONCLUSIONS

The null neurometabolic findings may be due to age, relatively low severity of alcohol use, and non-treatment-seeking status of the participants. Females showed overall higher reactivity to alcohol cues, indicating a sex effect regardless of alcohol use history. Higher amygdala reactivity in alcohol-using adolescents suggests that emotional processing related to alcohol cues may be a useful target for future adolescent AUD interventions.

Spatiotemporal dynamics of hippocampal-cortical networks underlying the unique phenomenological properties of trauma-related intrusive memories

Trauma-related intrusive memories (TR-IMs) possess unique phenomenological properties that contribute to adverse post-traumatic outcomes, positioning them as critical intervention targets. However, transdiagnostic treatments for TR-IMs are scarce, as their underlying mechanisms have been investigated separate from their unique phenomenological properties. Extant models of more general episodic memory highlight dynamic hippocampal-cortical interactions that vary along the anterior-posterior axis of the hippocampus (HPC) to support different cognitive-affective and sensory-perceptual features of memory. Extending this work into the unique properties of TR-IMs, we conducted a study of eighty-four trauma-exposed adults who completed daily ecological momentary assessments of TR-IM properties followed by resting-state functional magnetic resonance imaging (rs-fMRI). Spatiotemporal dynamics of anterior and posterior hippocampal (a/pHPC)-cortical networks were assessed using co-activation pattern analysis to investigate their associations with different properties of TR-IMs. Emotional intensity of TR-IMs was inversely associated with the frequency and persistence of an aHPC-default mode network co-activation pattern. Conversely, sensory features of TR-IMs were associated with more frequent co-activation of the HPC with sensory cortices and the ventral attention network, and the reliving of TR-IMs in the "here-and-now" was associated with more persistent co-activation of the pHPC and the visual cortex. Notably, no associations were found between HPC-cortical network dynamics and conventional symptom measures, including TR-IM frequency or retrospective recall, underscoring the utility of ecological assessments of memory properties in identifying their neural substrates. These findings provide novel insights into the neural correlates of the unique features of TR-IMs that are critical for the development of individualized, transdiagnostic treatments for this pervasive, difficult-to-treat symptom.

Dynamic nonreversibility view of intrinsic brain organization and brain dynamic analysis of repetitive transcranial magnitude stimulation

Intrinsic neural activities are characterized as endless spontaneous fluctuation over multiple time scales. However, how the intrinsic brain organization changes over time under local perturbation remains an open question. By means of statistical physics, we proposed an approach to capture whole-brain dynamics based on estimating time-varying nonreversibility and k-means clustering of dynamic varying nonreversibility patterns. We first used synthetic fMRI to investigate the effects of window parameters on the temporal variability of varying nonreversibility. Second, using real test-retest fMRI data, we examined the reproducibility, reliability, biological, and physiological correlation of the varying nonreversibility substates. Finally, using repetitive transcranial magnetic stimulation-fMRI data, we investigated the modulation effects of repetitive transcranial magnetic stimulation on varying nonreversibility substate dynamics. The results show that: (i) as window length increased, the varying nonreversibility variance decreased, while the sliding step almost did not alter it; (ii) the global high varying nonreversibility states and low varying nonreversibility states were reproducible across multiple datasets and different window lengths; and (iii) there were increased low varying nonreversibility states and decreased high varying nonreversibility states when the left frontal lobe was stimulated, but not the occipital lobe. Taken together, these results provide a thermodynamic equilibrium perspective of intrinsic brain organization and reorganization under local perturbation.

Compensatory increase in ipsilesional supplementary motor area and premotor connectivity is associated with greater gait impairments: a personalized fMRI analysis in chronic stroke

Background

Balance and mobility impairments are prevalent post-stroke and a large number of survivors require walking assistance at 6 months post-stroke which diminishes their overall quality of life. Personalized interventions for gait and balance rehabilitation are crucial. Recent evidence indicates that stroke lesions in primary motor pathways, such as corticoreticular pathways (CRP) and corticospinal tract (CST), may lead to reliance on alternate motor pathways as compensation, but the current evidence lacks comprehensive knowledge about the underlying neural mechanisms.

Methods

In this study, we investigate the functional connectivity (FC) changes within the motor network derived from an individualized cortical parcellation approach in 33 participants with chronic stroke compared to 17 healthy controls. The correlations between altered motor FC and gait deficits (i.e., walking speed and walking balance) were then estimated in the stroke population to understand the compensation mechanism of the motor network in motor function rehabilitation post-stroke.

Results

Our results demonstrated significant FC increases between ipsilesional medial supplementary motor area (SMA) and premotor in stroke compared to healthy controls. Furthermore, we also revealed a negative correlation between ipsilesional SMA-premotor FC and self-selected walking speed, as well as the Functional Gait Assessment (FGA) scores.

Conclusion

The increased FC between the ipsilesional SMA and premotor regions could be a compensatory mechanism within the motor network following a stroke when the individual can presumably no longer rely on the more precise CST modulation of movements to produce a healthy walking pattern. These findings enhance our understanding of individualized motor network FC changes and their connection to gait and walking balance impairments post-stroke, improving stroke rehabilitation interventions.

Bilateral effect of acupuncture on cerebrum and cerebellum in ischaemic stroke patients with hemiparesis: a randomised clinical and neuroimaging trial

BACKGROUND

Acupuncture involving the limb region may be effective for stroke rehabilitation clinically, but the visualised and explanatory evidence is limited. Our objectives were to assess the specific effects of acupuncture for ischaemic stroke (IS) patients with hemiparesis and investigate its therapy-driven modification in functional connectivity.

METHODS

IS patients were randomly assigned (2:1) to receive 10 sessions of hand-foot 12 needles acupuncture (HA, n=30) or non-acupoint (NA) acupuncture (n=16), enrolling gender-matched and age-matched healthy controls (HCs, n=34). The clinical outcomes were the improved Fugl-Meyer Assessment scores including upper and lower extremity (ΔFM, ΔFM-UE, ΔFM-LE). The neuroimaging outcome was voxel-mirrored homotopic connectivity (VMHC). Static and dynamic functional connectivity (sFC, DFC) analyses were used to study the neuroplasticity reorganisation.

RESULTS

46 ISs (mean(SD) age, 59.37 (11.36) years) and 34 HCs (mean(SD) age, 52.88 (9.69) years) were included in the per-protocol analysis of clinical and neuroimaging. In clinical, ΔFM scores were 5.00 in HA group and 2.50 in NA group, with a dual correlation between ΔFM and ΔVMHC (angular: r=0.696, p=0.000; cerebellum: r=-0.716, p=0.000) fitting the linear regression model (R2=0.828). In neuroimaging, ISs demonstrated decreased VMHC in bilateral postcentral gyrus and cerebellum (Gaussian random field, GRF corrected, voxel p<0.001, cluster p<0.05), which fitted the logistic regression model (AUC=0.8413, accuracy=0.7500). Following acupuncture, VMHC in bilateral superior frontal gyrus orbital part was increased with cerebro-cerebellar changes, involving higher sFC between ipsilesional superior frontal gyrus orbital part and the contralesional orbitofrontal cortex as well as cerebellum (GRF corrected, voxel p<0.001, cluster p<0.05). The coefficient of variation of VMHC was decreased in bilateral posterior cingulate gyrus (PPC) locally (GRF corrected, voxel p<0.001, cluster p<0.05), with integration states transforming into segregation states overall (p<0.05). There was no acupuncture-related adverse event.

CONCLUSIONS

The randomised clinical and neuroimaging trial demonstrated acupuncture could promote the motor recovery and modified cerebro-cerebellar VMHC via bilateral static and dynamic reorganisations for IS patients with hemiparesis.

Resting-state EEG dynamic functional connectivity distinguishes non-psychotic major depression, psychotic major depression and schizophrenia

This study aims to identify dynamic patterns within the spatiotemporal feature space that are specific to nonpsychotic major depression (NPMD), psychotic major depression (PMD), and schizophrenia (SCZ). The study also evaluates the effectiveness of machine learning algorithms based on these network manifestations in differentiating individuals with NPMD, PMD, and SCZ. A total of 579 participants were recruited, including 152 patients with NPMD, 45 patients with PMD, 185 patients with SCZ, and 197 healthy controls (HCs). A dynamic functional connectivity (DFC) approach was employed to estimate the principal FC states within each diagnostic group. Incremental proportions of data (ranging from 10% to 100%) within each diagnostic group were used for variability testing. DFC metrics, such as proportion, mean duration, and transition number, were examined among the four diagnostic groups to identify disease-related neural activity patterns. These patterns were then used to train a two-layer classifier for the four groups (HC, NPMD, PMD, and SCZ). The four principal brain states (i.e., states 1,2,3, and 4) identified by the DFC approach were highly representative within and across diagnostic groups. Between-group comparisons revealed significant differences in network metrics of state 2 and state 3, within delta, theta, and gamma frequency bands, between healthy individuals and patients in each diagnostic group (p < 0.01, FDR corrected). Moreover, the identified key dynamic network metrics achieved an accuracy of 73.1 ± 2.8% in the four-way classification of HC, NPMD, PMD, and SCZ, outperforming the static functional connectivity (SFC) approach (p < 0.001). These findings suggest that the proposed DFC approach can identify dynamic network biomarkers at the single-subject level. These biomarkers have the potential to accurately differentiate individual subjects among various diagnostic groups of psychiatric disorders or healthy controls. This work may contribute to the development of a valuable EEG-based diagnostic tool with enhanced accuracy and assistive capabilities.

CAMBA framework: Unveiling the brain asymmetry alterations and longitudinal changes after stroke using resting-state EEG

Hemispheric asymmetry or lateralization is a fundamental principle of brain organization. However, it is poorly understood to what extent the brain asymmetries across different levels of functional organizations are evident in health or altered in brain diseases. Here, we propose a framework that integrates three degrees of brain interactions (isolated nodes, node-node, and edge-edge) into a unified analysis pipeline to capture the sliding window-based asymmetry dynamics at both the node and hemisphere levels. We apply this framework to resting-state EEG in healthy and stroke populations and investigate the stroke-induced abnormal alterations in brain asymmetries and longitudinal asymmetry changes during poststroke rehabilitation. We observe that the mean asymmetry in patients was abnormally enhanced across different frequency bands and levels of brain interactions, with these abnormal patterns strongly associated with the side of the stroke lesion. Compared to healthy controls, patients displayed significant alterations in asymmetry fluctuations, disrupting and reconfiguring the balance of inter-hemispheric integration and segregation. Additionally, analyses reveal that specific abnormal asymmetry metrics in patients tend to move towards those observed in healthy controls after short-term brain-computer interface rehabilitation. Furthermore, preliminary evidence suggests that baseline clinical and asymmetry features can predict poststroke improvements in the Fugl-Meyer assessment of the lower extremity (mean absolute error of about 2). Overall, these findings advance our understanding of hemispheric asymmetry. Our framework offers new insights into the mechanisms underlying brain alterations and recovery after a brain lesion, may help identify prognostic biomarkers, and can be easily extended to different functional modalities.

Trait- and state-like co-activation pattern dynamics in current and remitted major depressive disorder

BACKGROUND

Distinguishing between trait- and state-like neural alternations in major depressive disorder (MDD) may advance our understanding of this recurring disorder. We aimed to investigate dynamic functional connectivity alternations in unmedicated individuals with current or past MDD using co-activation pattern analyses.

METHODS

Resting-state functional magnetic resonance imaging data were acquired from individuals with first-episode current MDD (cMDD, n = 50), remitted MDD (rMDD, n = 44), and healthy controls (HCs, n = 64). Using a data-driven consensus clustering technique, four whole-brain states of spatial co-activation were identified and associated metrics (dominance, entries, transition frequency) were analyzed with respect to clinical characteristics.

RESULTS

Relative to rMDD and HC, cMDD showed increased dominance and entries of state 1 (primarily involving default mode network (DMN)), and decreased dominance of state 4 (mostly involving frontal-parietal network (FPN)). Among cMDD, state 1 entries correlated positively with trait rumination. Conversely, relative to cMDD and HC, individuals with rMDD were characterized by increased state 4 entries. Relative to HC, both MDD groups showed increased state 4-to-1 (FPN to DMN) transition frequency but reduction in state 3 (spanning visual attention, somatosensory, limbic networks), with the former metric specifically related to trait rumination.

LIMITATIONS

Further confirmation with longitudinal studies are required.

CONCLUSIONS

Regardless of symptoms, MDD was characterized by increased FPN-to-DMN transitions and reduced dominance of a hybrid network. State-related effect emerged in regions critically implicated in repetitive introspection and cognitive control. Asymptomatic individuals with past MDD were uniquely linked to increased FPN entries. Our findings identify trait-like brain network dynamics that might increase vulnerability to future MDD.

Estimating dynamic individual coactivation patterns based on densely sampled resting-state fMRI data and utilizing it for better subject identification

As a complex dynamic system, the brain exhibits spatially organized recurring patterns of activity over time. Coactivation patterns (CAPs), which analyzes data from each single frame, have been utilized to detect transient brain activity states recently. However, previous CAP analyses have been conducted at the group level, which might neglect meaningful individual differences. Here, we estimated individual CAP states at both subject- and scan-level based on a densely sampled dataset: Midnight Scan Club. We used differential identifiability, which measures the gap between intra- and inter-subject similarity, to evaluate individual differences. We found individual CAPs at the subject-level achieved the best fingerprinting ability by maintaining high intra-subject similarity and enlarging inter-subject differences, and brain regions of association networks mainly contributed to the identifiability. On the other hand, scan-level CAP states were unstable across scans for the same participant. Expectedly, we found subject-specific CAPs became more reliable and discriminative with more data (i.e., longer duration). As the acquisition time of each participant is limited in practice, our results recommend a data collection strategy that collects more scans with appropriate duration (e.g., 12 ~ 15 min/scan) to obtain more reliable subject-specific CAPs, when total acquisition time is fixed (e.g., 150 min). In summary, this work has constructed reliable subject-specific CAP states with meaningful individual differences, and recommended an appropriate data collection strategy, which can guide subsequent investigations into individualized brain dynamics.

Leading basic modes of spontaneous activity drive individual functional connectivity organization in the resting human brain

Spontaneous activity of the human brain provides a window to explore intrinsic principles of functional organization. However, most studies have focused on interregional functional connectivity. The principles underlying rich repertoires of instantaneous activity remain largely unknown. We apply a recently proposed eigen-microstate analysis to three resting-state functional MRI datasets to identify basic modes that represent fundamental activity patterns that coexist over time. We identify five leading basic modes that dominate activity fluctuations. Each mode exhibits a distinct functional system-dependent coactivation pattern and corresponds to specific cognitive profiles. In particular, the spatial pattern of the first leading basis mode shows the separation of activity between the default-mode and primary and attention regions. Based on theoretical modelling, we further reconstruct individual functional connectivity as the weighted superposition of coactivation patterns corresponding to these leading basic modes. Moreover, these leading basic modes capture sleep deprivation-induced changes in brain activity and interregional connectivity, primarily involving the default-mode and task-positive regions. Our findings reveal a dominant set of basic modes of spontaneous activity that reflect multiplexed interregional coordination and drive conventional functional connectivity, furthering the understanding of the functional significance of spontaneous brain activity.

Left or right ear? A neuroimaging study using combined taVNS/fMRI to understand the interaction between ear stimulation target and lesion location in chronic stroke

BACKGROUND

Implanted vagus nerve stimulation (VNS) and transcutaneous auricular VNS (taVNS) have been primarily administered clinically to the unilateral-left vagus nerve. This left-only convention has proved clinically beneficial in brain disorders. However, in stroke survivors, the presence of a lesion in the brain may complicate VNS-mediated signaling, and it is important to understand the laterality effects of VNS in stroke survivors to optimize the intervention.

OBJECTIVE

To understand whether taVNS delivered to different ear targets relative to the lesion (ipsilesional vs contralesional vs bilateral vs sham) impacts blood oxygenation level dependent (BOLD) signal propagation in stroke survivors.

METHODS

We enrolled 20 adults with a prior history of stroke. Each participant underwent a single visit, during which taVNS was delivered concurrently during functional magnetic resonance imaging (fMRI) acquisition. Each participant received three discrete active stimulation conditions (ipsilesional, contralesional, bilateral) and one sham condition in a randomized order. Stimulation-related BOLD signal changes in the active conditions were compared to sham conditions to understand the interaction taVNS and laterality effects.

RESULTS

All active taVNS conditions deactivated the contralesional default mode network related regions compared to sham, however only ipsilesional taVNS enhanced the activations in the ipsilesional visuomotor and secondary visual cortex. Furthermore, we reveal an interaction in task activations between taVNS and cortical visuomotor areas, where ipsilesional taVNS significantly increased ipsilesional visuomotor activity and decreased contralesional visuomotor activity compared to sham.

CONCLUSION

Laterality of taVNS relative to the lesion is a critical factor in optimizing taVNS in a stroke population, with ipsilesional stimulation providing largest direct brain activation and should be explored further when designing taVNS studies in neurorehabilitation.