Modulation of Oscillatory Power and Connectivity in the Human Posterior Cingulate Cortex Supports the Encoding and Retrieval of Episodic Memories

Existing data from noninvasive studies have led researchers to posit that the posterior cingulate cortex (PCC) supports mnemonic processes: It exhibits degeneration in memory disorders, and fMRI investigations have demonstrated memory-related activation principally during the retrieval of memory items. Despite these data, the role of the PCC in episodic memory has received only limited treatment using the spatial and temporal precision of intracranial EEG, with previous analyses focused on item retrieval. Using data gathered from 21 human participants who underwent stereo-EEG for seizure localization, we characterized oscillatory patterns in the PCC during the encoding and retrieval of episodic memories. We identified a subsequent memory effect during item encoding characterized by increased gamma band oscillatory power and a low-frequency power desynchronization. Fourteen participants had stereotactic electrodes located simultaneously in the hippocampus and PCC, and with these unique data, we describe connectivity changes between these structures that predict successful item encoding and that precede item retrieval. Oscillatory power during retrieval matched the pattern we observed during encoding, with low-frequency (below 15 Hz) desynchronization and a gamma band (especially high gamma, 70–180 Hz) power increase. Encoding is characterized by synchrony between the hippocampus and PCC, centered at 3 Hz, consistent with other observations of properties of this oscillation akin to those for rodent theta activity. We discuss our findings in light of existing theories of episodic memory processing, including the information via desynchronization hypothesis and retrieved context theory, and examine how our data fit with existing theories for the functional role of the PCC. These include a postulated role for the PCC in modulating internally directed attention and for representing or integrating contextual information for memory items.

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Correlation between Traits of Emotion-Based Impulsivity and Intrinsic Default-Mode Network Activity

Neural Plasticity ◽

10.1155/2017/9297621 ◽

2017 ◽

Vol 2017 ◽

pp. 1-9 ◽

Cited By ~ 11

Author(s):

Jizheng Zhao ◽

Dardo Tomasi ◽

Corinde E. Wiers ◽

Ehsan Shokri-Kojori ◽

Şükrü B. Demiral ◽

...

Keyword(s):

Brain Activity ◽

Low Frequency ◽

Cingulate Cortex ◽

Posterior Cingulate Cortex ◽

Anterior Cingulate ◽

Network Activity ◽

High Risk Behaviors ◽

Posterior Cingulate ◽

Healthy Humans ◽

Dorsolateral Prefrontal

Negative urgency (NU) and positive urgency (PU) are implicated in several high-risk behaviors, such as eating disorders, substance use disorders, and nonsuicidal self-injury behavior. The current study aimed to explore the possible link between trait of urgency and brain activity at rest. We assessed the amplitude of low-frequency fluctuations (ALFF) of the resting-state functional magnetic resonance imaging (fMRI) signal in 85 healthy volunteers. Trait urgency measures were related to ALFF in the lateral orbitofrontal cortex, dorsolateral prefrontal cortex, ventral and dorsal medial frontal cortex, anterior cingulate, and posterior cingulate cortex/precuneus. In addition, trait urgency measures showed significant correlations with the functional connectivity of the posterior cingulate cortex/precuneus seed with the thalamus and midbrain region. These findings suggest an association between intrinsic brain activity and impulsive behaviors in healthy humans.

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Neural basis underlying the trait of attachment anxiety and avoidance revealed by the amplitude of low-frequency fluctuations and resting-state functional connectivity

BMC Neuroscience ◽

10.1186/s12868-021-00617-4 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Min Deng ◽

Xing Zhang ◽

Xiaoyan Bi ◽

Chunhai Gao

Keyword(s):

Functional Connectivity ◽

Resting State ◽

Low Frequency ◽

Cingulate Cortex ◽

Posterior Cingulate Cortex ◽

Attachment Anxiety ◽

Frequency Fluctuation ◽

Resting State Functional Connectivity ◽

Attachment Avoidance ◽

Posterior Cingulate

Abstract Background Attachment theory demonstrates that early attachment experience shapes internal working models with mental representations of self and close relationships, which affects personality traits and interpersonal relationships in adulthood. Although research has focused on brain structural and functional underpinnings to disentangle attachment styles in healthy individuals, little is known about the spontaneous brain activity associated with self-reported attachment anxiety and avoidance during the resting state. Methods One hundred and nineteen individuals participated in the study, completing the Experience in Close Relationship scale immediately after an 8-min fMRI scanning. We used the resting-state functional magnetic resonance imaging (rs-fMRI) signal of the amplitude of low-frequency fluctuation and resting-state functional connectivity to identify attachment-related regions and networks. Results Consequently, attachment anxiety is closely associated with the amplitude of low-frequency fluctuations in the right posterior cingulate cortex, over-estimating emotional intensity and exaggerating outcomes. Moreover, the functional connectivity between the posterior cingulate cortex and fusiform gyrus increases detection ability for potential threat or separation information, facilitating behavior motivation. The attachment avoidance is positively correlated with the amplitude of low-frequency fluctuation in the bilateral lingual gyrus and right postcentral and negatively correlated with the bilateral orbital frontal cortex and inferior temporal gyrus. Functional connection with attachment avoidance contains critical nodes in the medial temporal lobe memory system, frontal-parietal network, social cognition, and default mode network necessary to deactivate the attachment system and inhibit attachment-related behavior. Conclusion and implications These findings clarify the amplitude of low-frequency fluctuation and resting-state functional connectivity neural signature of attachment style, associated with attachment strategies in attachment anxiety and attachment avoidance individuals. These findings may improve our understanding of the pathophysiology of the attachment-related disorder.

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Stimulation of the Posterior Cingulate Cortex Impairs Episodic Memory Encoding

Journal of Neuroscience ◽

10.1523/jneurosci.0698-19.2019 ◽

2019 ◽

Vol 39 (36) ◽

pp. 7173-7182 ◽

Cited By ~ 10

Author(s):

Vaidehi S. Natu ◽

Jui-Jui Lin ◽

Alexis Burks ◽

Akshay Arora ◽

Michael D. Rugg ◽

...

Keyword(s):

Episodic Memory ◽

Cingulate Cortex ◽

Posterior Cingulate Cortex ◽

Memory Encoding ◽

Posterior Cingulate ◽

Stimulation Of

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Commentary: Stimulation of the Posterior Cingulate Cortex Impairs Episodic Memory Encoding

Frontiers in Human Neuroscience ◽

10.3389/fnhum.2020.00334 ◽

2020 ◽

Vol 14 ◽

Author(s):

Marie-Lucie Read ◽

Rikki Lissaman

Keyword(s):

Episodic Memory ◽

Cingulate Cortex ◽

Posterior Cingulate Cortex ◽

Memory Encoding ◽

Posterior Cingulate ◽

Stimulation Of

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Characteristics of temporal dynamics of intrinsic brain activity in unmedicated bipolar disorder with suicidality

Australian & New Zealand Journal of Psychiatry ◽

10.1177/0004867420948960 ◽

2020 ◽

Vol 54 (11) ◽

pp. 1115-1124

Author(s):

Jiaying Gong ◽

Guanmao Chen ◽

Mengyao Zhou ◽

Yanbin Jia ◽

Shuming Zhong ◽

...

Keyword(s):

Bipolar Disorder ◽

Suicidal Ideation ◽

Low Frequency ◽

Cingulate Cortex ◽

Posterior Cingulate Cortex ◽

Suicidal Attempt ◽

Healthy Controls ◽

Posterior Cingulate ◽

Frequency Fluctuations ◽

The Right

Background: Bipolar disorder is associated with a high risk of suicide. Routine neuroimaging examination exhibited that bipolar disorder with suicidality was associated with brain structural and functional changes. However, the alterations of brain dynamics have still remained elusive. Purpose: To investigate the alterations of brain dynamics in unmedicated bipolar disorder II depression with suicidality and predict the severity of suicidality. Materials and Methods: This prospective study included 106 bipolar disorder II participants (20 with suicidal attempt, 35 with suicidal ideation, 51 without suicidal ideation) and 50 healthy controls who underwent resting-state functional magnetic resonance imaging between February 2016 and December 2017. We first used sliding window analysis to evaluate the dynamic amplitude of low-frequency fluctuations. Then, we predicted the severity of suicidality using a multivariate regression model. Results: One-way analysis of covariance revealed that the dynamic amplitude of low-frequency fluctuations in the right temporal pole, inferior temporal gyrus, superior temporal gyrus and the bilateral precuneus/posterior cingulate cortex was significantly different among the four groups. Post hoc pairwise comparisons revealed that dynamic amplitude of low-frequency fluctuations was remarkably decreased in the bilateral precuneus/posterior cingulate cortex in the three bipolar disorder II groups compared with that in healthy controls group. Increased dynamic amplitude of low-frequency fluctuations was found in the right superior temporal gyrus and inferior temporal gyrus in the suicidal attempt group compared with that in the other groups, and in the right temporal pole in the suicidal attempt group compared with that in the suicidal ideation and healthy controls groups. Importantly, these temporal variabilities could be used to predict the severity of suicidality ( r = 0.330, p = 0.036), whereas static amplitude of low-frequency fluctuations couldn’t ( r = –0.050, p = 0.532). Conclusion: Our findings indicated that alterations of temporal variability in the precuneus/posterior cingulate cortex are such a common feature of bipolar disorder patients. Besides, the severity of suicidality could be predicted by the dynamic amplitude of low-frequency fluctuations abnormalities rather than static amplitude of low-frequency fluctuations abnormalities, which is the first evidence of dynamic brain alterations in bipolar disorder patients with suicidality. The proposed predictive model may be advantageous for clinical applications.

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