Dorsal Posterior Cingulate Cortex Research Articles

Posterior cingulate epilepsy: Seizure semiology and intracranial electrical stimulation using SEEG

PurposeThis study aimed to explore seizure semiology and the effects of intracerebral electrical stimulation on the human posterior cingulate cortex (PCC) using Stereoelectroencephalography (SEEG) to deepen our comprehension of posterior cingulate epilepsy (PCE). MethodsThis study examined the characteristics of seizures through video documentation, by assessing the outcomes of intracranial electrical stimulation (iES) during SEEG. We further identified the connection between the observed semiology and precise anatomical locations within the PCC subregions where seizure onset zones (SOZ) were identified. ResultsAnalysis was conducted on 59 seizures from 15 patients recorded via SEEG. Behavioural arrest emerged as the predominant manifestation across the PCC subregions. Where ictal activity extended to both the mesial and lateral temporal cortex, automatism was predominantly observed in seizures originating from the ventral PCC (vPCC). The retrosplenial cortex (RSC) is associated with complex motor behaviour, with seizure discharges spreading to the temporal lobe. Seizures originating from the PCC include axial tonic and autonomic seizures. Only one case of positive clinical seizures was documented. High frequencies of iES within the PCC induced various clinical responses, categorised as vestibular, visual, psychological, and autonomic, with vestibular reactions primarily occurring in the dorsal PCC (dPCC) and RSC, visual responses in the left RSC, and autonomic reactions in the vPCC and RSC. ConclusionThe manifestations of seizures in PCE vary according to the SOZ and the patterns of seizure propagation. The occurrence of seizures induced by iES is exceedingly rare, indicating that mapping of the PCC could pinpoint the primary sector of PCC.

Directed functional connectivity of the default-mode-network of young and older healthy subjects

Alterations in the default mode network (DMN) are associated with aging. We assessed age-dependent changes of DMN interactions and correlations with a battery of neuropsychological tests, to understand the differences of DMN directed connectivity between young and older subjects. Using a novel multivariate analysis method on resting-state functional MRI data from fifty young and thirty-one healthy older subjects, we calculated intra- and inter-DMN 4-nodes directed pathways. For the old subject group, we calculated the partial correlations of inter-DMN pathways with: psychomotor speed and working memory, executive function, language, long-term memory and visuospatial function. Pathways connecting the DMN with visual and limbic regions in older subjects engaged at BOLD low frequency and involved the dorsal posterior cingulate cortex (PCC), whereas in young subjects, they were at high frequency and involved the ventral PCC. Pathways combining the sensorimotor (SM) cortex and the DMN, were SM efferent in the young subjects and SM afferent in the older subjects. Most DMN efferent pathways correlated with reduced speed and working memory. We suggest that the reduced sensorimotor efferent and the increased need to control such activities, cause a higher dependency on external versus internal cues thus suggesting how physical activity might slow aging.

Increased functional connectivity in the right dorsal auditory stream after a full year of piano training in healthy older adults

Learning to play an instrument at an advanced age may help to counteract or slow down age-related cognitive decline. However, studies investigating the neural underpinnings of these effects are still scarce. One way to investigate the effects of brain plasticity is using resting-state functional connectivity (FC). The current study compared the effects of learning to play the piano (PP) against participating in music listening/musical culture (MC) lessons on FC in 109 healthy older adults. Participants underwent resting-state functional magnetic resonance imaging at three time points: at baseline, and after 6 and 12 months of interventions. Analyses revealed piano training-specific FC changes after 12 months of training. These include FC increase between right Heschl’s gyrus (HG), and other right dorsal auditory stream regions. In addition, PP showed an increased anticorrelation between right HG and dorsal posterior cingulate cortex and FC increase between the right motor hand area and a bilateral network of predominantly motor-related brain regions, which positively correlated with fine motor dexterity improvements. We suggest to interpret those results as increased network efficiency for auditory-motor integration. The fact that functional neuroplasticity can be induced by piano training in healthy older adults opens new pathways to countervail age related decline.

The impact of mindfulness on working memory-related brain activation in breast cancer survivors with cognitive complaints.

Cancer-related cognitive impairment (CRCI) has been associated with altered brain activation after chemotherapy in areas related to working memory. Hence, improving working memory capacity and associated brain activation might aid in the recovery of CRCI. In this study, we investigated the potential of a mindfulness-based intervention (MBI) to impact working memory-related brain activation. Female breast cancer survivors reporting cognitive complaints (N=117) were randomized into a mindfulness (n=43; MBI), physical training (n=36; PT), or waitlist control condition (n=38; WL). Participants completed MRI scans before the intervention, immediately after, and three months post-intervention. Task-based functional MRI was used to measure differences between groups over time in working memory-related brain activation while performing a visual-verbal n-back task. Data of 83 participants (32/26/25 MBI/PT/WL) was included. Compared to the waitlist group, MBI participants showed reduced task-related activation in the right middle frontal and angular gyrus and increased activation in the right dorsal posterior cingulate cortex over time. Compared to the physical training group, MBI participants showed reduced brain activation in the bilateral superior parietal lobule and right dorsal anterior cingulate cortex over time. No differences between physical training and no intervention were identified. This study showed that an 8-week mindfulness-based intervention can significantly alter brain activation across brain regions involved in working memory, attentional control, and emotion processing during performance of a working memory task. This might aid in the recovery of CRCI. Mindfulness might alter brain activation patterns while performing a working memory task, which might ultimately aidin restoring higher order cognitive functions.

65 The Impact of PTSD and Mild Cognitive Impairment on Resting State Brain Functional Connectivity in World Trade Center Responders

Objective:Functional connectivity of the default mode network (DMN) during rest has been shown to be different among adults with Mild Cognitive Impairment (MCI) relative to aged-matched individuals without MCI and is predictive of transition to dementia. Post-traumatic stress disorder (PTSD) is also associated with aberrant connectivity of the DMN. Prior work from this group has demonstrated a higher rate of MCI and PTSD among World Trade Center (WTC) responders relative to the general population. The current study sought to investigate the main and interactive effects of MCI and PTSD on DMN functioning. Based on prior work, we hypothesized that MCI, but not PTSD, would predict aberrant connectivity in the DMN.Participants and Methods:99 WTC responders aged 44–65 stratified by MCI status (yes/no) and PTSD status (yes/no) and matched for age in years, sex (male vs. female), race (white, black, and other), and educational attainment (high school or less, some college / technical school, and university degree), and occupation on September 11, 2001 (law enforcement vs. other) underwent fMRI using a 3T Siemens Biograph MR scanner. A single 10-minute continuous functional MR sequence was acquired while participants were at rest with their eyes open. Group-level analyses were conducted using SPM-12, with correction for multiple comparisons using AFNI's 3dClustSim. Based on this threshold, the number of comparisons in our imaging volume, and the smoothness of our imaging data as measured by 3dFWHMx-acf, a minimum cluster size of 1134 voxels was required to have a corrected p . .05 with 2-sided thresholding. Spherical 3 mm seeds were placed in the dorsal (4, -50, 26) and ventral (4, -60, 46) posterior cingulate cortex (PCC).Results:Individuals with PTSD demonstrated significantly less connectivity of the dorsal posterior cingulate cortex (PCC) with medial insula (T = 5.21), subthalamic nucleus (T = 4.66), and postcentral gyrus (T = 3.81). There was no difference found in this study for connectivity between groups stratified by MCI status. There were no significant results for the ventral PCC seed.Conclusions:Contrary to hypotheses that were driven by a study of cortical thickness in WTC responders, the impact of PTSD appears to outweigh the impact of MCI on dorsal DMN connectivity among WTC responders stratified by PTSD and MCI status. This study is limited by several issues, including low number of female and minority participants, relatively small group cell sizes (n = 23–27 per cell), a brief resting state sequence (10 minutes), and lack of a non-WTC control group. Importantly, responders are a unique population so generalizability to other populations may be limited. Individuals in the current study are now being followed longitudinally to relate baseline resting state functional connectivity with cognitive changes and changes in connectivity over a four-year period.

Analysis of functional connectivity using machine learning and deep learning in different data modalities from individuals with schizophrenia

Objective. Schizophrenia (SCZ) is a severe mental disorder associated with persistent or recurrent psychosis, hallucinations, delusions, and thought disorders that affect approximately 26 million people worldwide, according to the World Health Organization. Several studies encompass machine learning (ML) and deep learning algorithms to automate the diagnosis of this mental disorder. Others study SCZ brain networks to get new insights into the dynamics of information processing in individuals suffering from the condition. In this paper, we offer a rigorous approach with ML and deep learning techniques for evaluating connectivity matrices and measures of complex networks to establish an automated diagnosis and comprehend the topology and dynamics of brain networks in SCZ individuals. Approach. For this purpose, we employed an functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG) dataset. In addition, we combined EEG measures, i.e. Hjorth mobility and complexity, with complex network measurements to be analyzed in our model for the first time in the literature. Main results. When comparing the SCZ group to the control group, we found a high positive correlation between the left superior parietal lobe and the left motor cortex and a positive correlation between the left dorsal posterior cingulate cortex and the left primary motor. Regarding complex network measures, the diameter, which corresponds to the longest shortest path length in a network, may be regarded as a biomarker because it is the most crucial measure in different data modalities. Furthermore, the SCZ brain networks exhibit less segregation and a lower distribution of information. As a result, EEG measures outperformed complex networks in capturing the brain alterations associated with SCZ. Significance. Our model achieved an area under receiver operating characteristic curve (AUC) of 100% and an accuracy of 98.5% for the fMRI, an AUC of 95%, and an accuracy of 95.4% for the EEG data set. These are excellent classification results. Furthermore, we investigated the impact of specific brain connections and network measures on these results, which helped us better describe changes in the diseased brain.

Polygenic risk for neuroticism is associated with less efficient control in more difficult situations

Neuroticism is a heritable trait and a risk factor for mental health due to its relevance to poor control of negative events. To examine the relationship between genetic propensity for neuroticism and control processing, we used the polygenic risk score (PRS) approach and a stop signal task during fMRI. We hypothesized that genetic propensity for neuroticism may moderate control processing as a function of control difficulty. PRSs for neuroticism were computed from a transdiagnostic group of individuals (n=406) who completed the stop signal task. The level of control difficulty was a function of the stop signal asynchrony: shorter asynchrony allows easier stopping whereas longer asynchrony makes stopping difficult. The relationship between PRS for neuroticism and neural activity for controlling responses was examined by the stop signal asynchrony. Although PRS for neuroticism did not relate to the overall inhibitory control, individuals with high PRS for neuroticism showed greater activity in left dorsal prefrontal cortex, middle temporal gyrus, and dorsal posterior cingulate cortex for difficult control. Thus, the genetic propensity for neuroticism affects neural processing in a difficult control context, which may help to explain why individuals with high levels of neuroticism exert poor control of negative events in difficult situations.

Posterior cingulate cortex spontaneous activity associated with motor response inhibition in patients with obsessive-compulsive disorder: A resting-state fMRI study

Recent evidence suggests that broad brain regions, not limited to the fronto-striato-thalamo-cortical circuit, play an important role in motor response inhibition. However, it is still unclear which specific key brain region is responsible for impaired motor response inhibition observed in obsessive-compulsive disorder (OCD).We calculated the fractional amplitude of low-frequency fluctuations (fALFF) and measured response inhibition ability using the stop-signal task in 41 medication-free patients with OCD and 49 healthy control (HC) participants. We explored the brain region that shows different association between the fALFF and the ability of motor response inhibition.Significant differences in fALFF associated with the ability of motor response inhibition were identified in dorsal posterior cingulate cortex (PCC). There was a positive correlation between increased fALFF in the dorsal PCC and impaired motor response inhibition in OCD. In the HC group, there was a negative correlation between the two variables.Our results suggest that the magnitude of resting-state blood oxygen level-dependent oscillation of the dorsal PCC is a key brain region for the underlying mechanisms of impaired motor response inhibition in OCD. Future studies should examine whether this characteristic of dorsal PCC affects other large-scale networks responsible for motor response inhibition of OCD.

Differential engagement of the posterior cingulate cortex during cognitive restructuring of negative self- and social beliefs.

Negative self-beliefs are a core feature of psychopathology, encompassing both negative appraisals about oneself directly (i.e. self-judgment) and negative inferences of how the self is appraised by others (i.e.social judgment). Challenging maladaptive self-beliefs via cognitive restructuring is a core treatment mechanism of gold-standard psychotherapies. However, the neural mechanisms underlying the restructuring of these two kinds of negative self-beliefs are poorly understood. Eighty-six healthy participants cognitively restructured self-judgment and social-judgment negative self-belief statements during 7 Tesla functional magnetic resonance imaging scanning. Cognitive restructuring broadly elicited activation in the core default mode network (DMN), salience and frontoparietal control regions. Restructuring self-judgment relative to social-judgment beliefs was associated with comparatively higher activation in the ventral posterior cingulate cortex (PCC)/retrosplenial cortex, while challenging social-judgment statements was associated with higher activation in the dorsal PCC/precuneus. While both regions showed increased functional connectivity with the supplementary and pre-supplementary motor areas during restructuring, the dorsal PCC displayed greater task-dependent connectivity with distributed regions involved in salience, attention and social cognition. Our findings indicate distinct patterns of PCC engagement contingent upon self- and social domains, highlighting a specialized role of the dorsal PCC in supporting neural interactions between the DMN and frontoparietal/salience networks during cognitive restructuring.

Optimized Cingulate Island Sign in Discriminating Dementia With Lewy Bodies From Alzheimer Disease.

This study aimed to optimize the analysis of cingulate island sign (CIS) to improve its diagnostic accuracy in discriminating dementia with Lewy bodies (DLB) from Alzheimer disease (AD). Patients with DLB (n = 80), AD (n = 75), and normal controls (n = 22) with 18 F-FDG PET imaging were enrolled in this study. Sixty-two DLB patients also underwent dopaminergic PET scans. The optimized/conventional CIS ratios and metabolism in associated brain regions were evaluated by diagnostic accuracy among groups and correlation with cognitive/dopaminergic dysfunction. In discriminating DLB from AD, the optimized CIS ratio calculated by dorsal posterior cingulate cortex (PCC)/lateral occipital lobe metabolism achieved the highest specificity, sensitivity, and accuracy at 0.907, 0.750, and 0.825, respectively. The metabolism of dorsal-PCC positively correlated with cognitive impairment in DLB patients cross-sectionally and longitudinally ( P < 0.001, r = 0.601; P = 0.044, r = 0.645), and also correlated with dopaminergic impairment in the caudate ( P = 0.048, r = 0.315). Optimized CIS ratios of incorporated metabolic activity of dorsal-PCC and occipital subregions are clinically useful for differentiating DLB from AD, in which dorsal-PCC metabolism may provide an objective biomarker to reflect the severity of cognitive impairment in DLB.

Body fat and components of sarcopenia relate to inflammation, brain volume, and neurometabolism in older adults

Obesity and sarcopenia are associated with cognitive impairments at older age. Current research suggests that blood biomarkers may mediate this body-brain crosstalk, altering neurometabolism and brain structure eventually resulting in cognitive performance changes. Seventy-four older adults (60–85 years old) underwent bio-impedance body composition analysis, handgrip strength measurements, 8-Foot Up-and-Go (8UG) test, Montreal Cognitive Assessment (MoCA), blood analysis of interleukin-6 (IL-6), kynurenine, and insulin-like growth factor-1 (IGF-1), as well as brain magnetic resonance imaging (MRI) and proton magnetic resonance spectroscopy (1H-MRS), estimating neurodegeneration and neuroinflammation. Normal fat% or overweight was associated with larger total gray matter volume compared to underweight or obesity in older adults and obesity was associated with higher N-acetylaspartate/Creatine levels in the sensorimotor and dorsolateral prefrontal cortex. Muscle strength, not muscle mass/physical performance, corresponded to lower kynurenine and higher N-acetylaspartate/Creatine levels in the dorsal posterior cingulate and dorsolateral prefrontal cortex. The inflammatory and neurotrophic blood biomarkers did not significantly mediate these body-brain associations. This study used a multimodal approach to comprehensively assess the proposed mechanism of body-brain crosstalk.

N-acetyl-aspartate and Myo-inositol as Markers of White Matter Microstructural Organization in Mild Cognitive Impairment: Evidence from a DTI-1H-MRS Pilot Study

We implemented a multimodal approach to examine associations between structural and neurochemical changes that could signify neurodegenerative processes related to mild cognitive impairment (MCI). Fifty-nine older adults (60-85 years; 22 MCI) underwent whole-brain structural 3T MRI (T1W, T2W, DTI) and proton magnetic resonance spectroscopy (1H-MRS). The regions of interest (ROIs) for 1H-MRS measurements were the dorsal posterior cingulate cortex, left hippocampal cortex, left medial temporal cortex, left primary sensorimotor cortex, and right dorsolateral prefrontal cortex. The findings revealed that subjects in the MCI group showed moderate to strong positive associations between the total N-acetylaspartate to total creatine and the total N-acetylaspartate to myo-inositol ratios in the hippocampus and dorsal posterior cingulate cortex and fractional anisotropy (FA) of WM tracts crossing these regions-specifically, the left temporal tapetum, right corona radiata, and right posterior cingulate gyri. In addition, negative associations between the myo-inositol to total creatine ratio and FA of the left temporal tapetum and right posterior cingulate gyri were observed. These observations suggest that the biochemical integrity of the hippocampus and cingulate cortex is associated with a microstructural organization of ipsilateral WM tracts originating in the hippocampus. Specifically, elevated myo-inositol might be an underlying mechanism for decreased connectivity between the hippocampus and the prefrontal/cingulate cortex in MCI.

Connectome-based predictive modeling of trait forgiveness.

Forgiveness is a positive, prosocial manner of reacting to transgressions and is strongly associated with mental health and well-being. Despite recent studies exploring the neural mechanisms underlying forgiveness, a model capable of predicting trait forgiveness at the individual level has not been developed. Herein, we applied a machine-learning approach, connectome-based predictive modeling (CPM), with whole-brain resting-state functional connectivity (rsFC) to predict individual differences in trait forgiveness in a training set (dataset 1, N = 100, 35 men, 17-24 years). As a result, CPM successfully predicted individual trait forgiveness based on whole-brain rsFC, especially via the functional connectivity of the limbic, prefrontal and temporal areas, which are key contributors to the prediction model comprising regions previously implicated in forgiveness. These regions include the retrosplenial cortex, temporal pole, dorsolateral prefrontal cortex (PFC), dorsal anterior cingulate cortex, precuneus and dorsal posterior cingulate cortex. Importantly, this predictive model could be successfully generalized to an independent sample (dataset 2, N = 71, 17 men, 16-25 years). These findings highlight the important roles of the limbic system, PFC and temporal region in trait forgiveness prediction and represent the initial steps toward establishing an individualized prediction model of forgiveness.

Neurometabolic correlates of posturography in normal aging and older adults with mild cognitive impairment: Evidence from a 1H-MRS study

Proton magnetic resonance spectroscopy (1H-MRS) holds promise for revealing and understanding neurodegenerative processes associated with cognitive and functional impairments in aging. In the present study, we examined the neurometabolic correlates of balance performance in 42 cognitively intact older adults (healthy controls - HC) and 26 older individuals that were diagnosed with mild cognitive impairment (MCI). Neurometabolite ratios of total N-acetyl aspartate (tNAA), glutamate-glutamine complex (Glx), total choline (tCho) and myo-inositol (mIns) relative to total creatine (tCr) were assessed using single voxel 1H-MRS in four different brain regions. Regions of interest were the left hippocampus (HPC), dorsal posterior cingulate cortex (dPCC), left sensorimotor cortex (SM1), and right dorsolateral prefrontal cortex (dlPFC). Center-of-pressure velocity (Vcop) and dual task effect (DTE) were used as measures of balance performance. Results indicated no significant group differences in neurometabolite ratios and balance performance measures. However, our observations revealed that higher tCho/tCr and mIns/tCr in hippocampus and dPCC were generic predictors of worse balance performance, suggesting that neuroinflammatory processes in these regions might be a driving factor for impaired balance performance in aging. Further, we found that higher tNAA/tCr and mIns/tCr and lower Glx/tCr in left SM1 were predictors of better balance performance in MCI but not in HC. The latter observation hints at the possibility that individuals with MCI may upregulate balance control through recruitment of sensorimotor pathways.

Dorsal posterior cingulate cortex responds to negative feedback information supporting learning and relearning of response policies.

Many challenges in life come without explicit instructions. Instead, humans need to test, select, and adapt their behavioral responses based on feedback from the environment. While reward-centric accounts of feedback processing primarily stress the reinforcing aspect of positive feedback, feedback's central function from an information-processing perspective is to offer an opportunity to correct errors, thus putting a greater emphasis on the informational content of negative feedback. Independent of its potential rewarding value, the informational value of performance feedback has recently been suggested to be neurophysiologically encoded in the dorsal portion of the posterior cingulate cortex (dPCC). To further test this association, we investigated multidimensional categorization and reversal learning by comparing negative and positive feedback in an event-related functional magnetic resonance imaging experiment. Negative feedback, compared with positive feedback, increased activation in the dPCC as well as in brain regions typically involved in error processing. Only in the dPCC, subarea d23, this effect was significantly enhanced in relearning, where negative feedback signaled the need to shift away from a previously established response policy. Together with previous findings, this result contributes to a more fine-grained functional parcellation of PCC subregions and supports the dPCC's involvement in the adaptation to behaviorally relevant information from the environment.

A tripartite view of the posterior cingulate cortex.

The posterior cingulate cortex (PCC) is one of the least understood regions of the cerebral cortex. By contrast, the anterior cingulate cortex has been the subject of intensive investigation in humans and model animal systems, leading to detailed behavioural and computational theoretical accounts of its function. The time is right for similar progress to be made in the PCC given its unique anatomical and physiological properties and demonstrably important contributions to higher cognitive functions and brain diseases. Here, we describe recent progress in understanding the PCC, with a focus on convergent findings across species and techniques that lay a foundation for establishing a formal theoretical account of its functions. Based on this converging evidence, we propose that the broader PCC region contains three major subregions - the dorsal PCC, ventral PCC and retrosplenial cortex - that respectively support the integration of executive, mnemonic and spatial processing systems. This tripartite subregional view reconciles inconsistencies in prior unitary theories of PCC function and offers promising new avenues for progress.

Distinct population and single-neuron selectivity for executive and episodic processing in human dorsal posterior cingulate.

Posterior cingulate cortex (PCC) is an enigmatic region implicated in psychiatric and neurological disease, yet its role in cognition remains unclear. Human studies link PCC to episodic memory and default mode network (DMN), while findings from the non-human primate emphasize executive processes more associated with the cognitive control network (CCN) in humans. We hypothesized this difference reflects an important functional division between dorsal (executive) and ventral (episodic) PCC. To test this, we utilized human intracranial recordings of population and single unit activity targeting dorsal PCC during an alternated executive/episodic processing task. Dorsal PCC population responses were significantly enhanced for executive, compared to episodic, task conditions, consistent with the CCN. Single unit recordings, however, revealed four distinct functional types with unique executive (CCN) or episodic (DMN) response profiles. Our findings provide critical electrophysiological data from human PCC, bridging incongruent views within and across species, furthering our understanding of PCC function.

Load-dependent inverted U-shaped connectivity of the default mode network in schizophrenia during a working-memory task: evidence from a replication functional MRI study.

Background:Working-memory deficit is associated with aberrant degree distribution of the brain connectome in schizophrenia. However, the brain neural mechanism underlying the degree redistribution pattern in schizophrenia is still uncertain.Methods:We examined the functional degree distribution of the connectome in 81 patients with schizophrenia and 77 healthy controls across different working-memory loads during an n-back task. We tested the associations between altered degree distribution and clinical symptoms, and we conducted functional connectivity analyses to investigate the neural mechanism underlying altered degree distribution. We repeated these analyses in a second independent data set of 96 participants. In the second data set, we employed machine-learning analysis to study whether the degree distribution pattern of one data set could be used to discriminate between patients with schizophrenia and controls in the other data set.Results:Patients with schizophrenia showed decreased centrality in the dorsal posterior cingulate cortex (dPCC) for the “2-back versus 0-back” contrast compared to healthy controls. The dPCC centrality pattern across all working-memory loads was an inverted U shape, with a left shift of this pattern in patients with schizophrenia. This reduced centrality was correlated with the severity of delusions and related to reduced functional connectivity between the dPCC and the dorsal precuneus. We replicated these results with the second data set, and the machine-learning analyses achieved an accuracy level of 71%.Limitations:We used a limited n-back paradigm that precluded the examination of higher working-memory loads.Conclusion:Schizophrenia is characterized by a load-dependent reduction of centrality in the dPCC, related to the severity of delusions. We suggest that restoring dPCC centrality in the presence of cognitive demands might have a therapeutic effect on persistent delusions in people with schizophrenia.

Distinct connectivity patterns in human medial parietal cortices: Evidence from standardized connectivity map using cortico-cortical evoked potential

The medial parietal cortices are components of the default mode network (DMN), which are active in the resting state. The medial parietal cortices include the precuneus and the dorsal posterior cingulate cortex (dPCC). Few studies have mentioned differences in the connectivity in the medial parietal cortices, and these differences have not yet been precisely elucidated. Electrophysiological connectivity is essential for understanding cortical function or functional differences. Since little is known about electrophysiological connections from the medial parietal cortices in humans, we evaluated distinct connectivity patterns in the medial parietal cortices by constructing a standardized connectivity map using cortico-cortical evoked potential (CCEP). This study included nine patients with partial epilepsy or a brain tumor who underwent chronic intracranial electrode placement covering the medial parietal cortices. Single-pulse electrical stimuli were delivered to the medial parietal cortices (38 pairs of electrodes). Responses were standardized using the z-score of the baseline activity, and a response density map was constructed in the Montreal Neurological Institutes (MNI) space. The precuneus tended to connect with the inferior parietal lobule (IPL), the occipital cortex, superior parietal lobule (SPL), and the dorsal premotor area (PMd) (the four most active regions, in descending order), while the dPCC tended to connect to the middle cingulate cortex, SPL, precuneus, and IPL. The connectivity pattern differs significantly between the precuneus and dPCC stimulation (p<0.05). Regarding each part of the medial parietal cortices, the distributions of parts of CCEP responses resembled those of the functional connectivity database. Based on how the dPCC was connected to the medial frontal area, SPL, and IPL, its connectivity pattern could not be explained by DMN alone, but suggested a mixture of DMN and the frontoparietal cognitive network. These findings improve our understanding of the connectivity profile within the medial parietal cortices. The electrophysiological connectivity is the basis of propagation of electrical activities in patients with epilepsy. In addition, it helps us to better understand the epileptic network arising from the medial parietal cortices.

Aberrant Dynamic Functional Connectivity of Posterior Cingulate Cortex Subregions in Major Depressive Disorder With Suicidal Ideation.

Accumulating evidence indicates the presence of structural and functional abnormalities of the posterior cingulate cortex (PCC) in patients with major depressive disorder (MDD) with suicidal ideation (SI). Nevertheless, the subregional-level dynamic functional connectivity (dFC) of the PCC has not been investigated in MDD with SI. We therefore sought to investigate the presence of aberrant dFC variability in PCC subregions in MDD patients with SI. We analyzed resting-state functional magnetic resonance imaging (fMRI) data from 31 unmedicated MDD patients with SI (SI group), 56 unmedicated MDD patients without SI (NSI group), and 48 matched healthy control (HC) subjects. The sliding-window method was applied to characterize the whole-brain dFC of each PCC subregion [the ventral PCC (vPCC) and dorsal PCC (dPCC)]. In addition, we evaluated associations between clinical variables and the aberrant dFC variability of those brain regions showing significant between-group differences. Compared with HCS, the SI and the NSI groups exhibited higher dFC variability between the left dPCC and left fusiform gyrus and between the right vPCC and left inferior frontal gyrus (IFG). The SI group showed higher dFC variability between the left vPCC and left IFG than the NSI group. Furthermore, the dFC variability between the left vPCC and left IFG was positively correlated with Scale for Suicidal Ideation (SSI) score in patients with MDD (i.e., the SI and NSI groups). Our results indicate that aberrant dFC variability between the vPCC and IFG might provide a neural-network explanation for SI and may provide a potential target for future therapeutic interventions in MDD patients with SI.