Episodic memory in aspects of brain information transfer by resting-state network topology

Activity flow under the manipulation of cognitive load and training

Flexible cognitive functions, such as working memory (WM), usually require a balance between localized and distributed information processing. However, it is challenging to uncover how local and distributed processing specifically contributes to task-induced activity in a region. Although the recently proposed activity flow mapping approach revealed the relative contribution of distributed processing, few studies have explored the adaptive and plastic changes that underlie cognitive manipulation. In this study, we recruited 51 healthy volunteers (31 females) and investigated how the activity flow and brain activation of the frontoparietal systems was modulated by WM load and training. While the activation of both executive control network (ECN) and dorsal attention network (DAN) increased linearly with memory load at baseline, the relative contribution of distributed processing showed a linear response only in the DAN, which was prominently attributed to within-network activity flow. Importantly, adaptive training selectively induced an increase in the relative contribution of distributed processing in the ECN and also a linear response to memory load, which were predominantly due to between-network activity flow. Furthermore, we demonstrated a causal effect of activity flow prediction through training manipulation on connectivity and activity. In contrast with classic brain activation estimation, our findings suggest that the relative contribution of distributed processing revealed by activity flow prediction provides unique insights into neural processing of frontoparietal systems under the manipulation of cognitive load and training. This study offers a new methodological framework for exploring information integration versus segregation underlying cognitive processing.

Neuroinflammation mechanisms of neuromodulation therapies for anxiety and depression

Mood disorders are associated with elevated inflammation, and the reduction of symptoms after multiple treatments is often accompanied by pro-inflammation restoration. A variety of neuromodulation techniques that regulate regional brain activities have been used to treat refractory mood disorders. However, their efficacy varies from person to person and lack reliable indicator. This review summarizes clinical and animal studies on inflammation in neural circuits related to anxiety and depression and the evidence that neuromodulation therapies regulate neuroinflammation in the treatment of neurological diseases. Neuromodulation therapies, including transcranial magnetic stimulation (TMS), transcranial electrical stimulation (TES), electroconvulsive therapy (ECT), photobiomodulation (PBM), transcranial ultrasound stimulation (TUS), deep brain stimulation (DBS), and vagus nerve stimulation (VNS), all have been reported to attenuate neuroinflammation and reduce the release of pro-inflammatory factors, which may be one of the reasons for mood improvement. This review provides a better understanding of the effective mechanism of neuromodulation therapies and indicates that inflammatory biomarkers may serve as a reference for the assessment of pathological conditions and treatment options in anxiety and depression.

Efficacy and safety of simultaneous rTMS-tDCS over bilateral angular gyrus on neuropsychiatric symptoms in patients with moderate Alzheimer's disease: A prospective, randomized, sham-controlled pilot study

BACKGROUND

Treating neuropsychiatric symptoms (NPS) in Alzheimer's disease (AD) remains highly challenging. Noninvasive brain stimulation using repetitive transcranial magnetic stimulation (rTMS) or transcranial direct current stimulation (tDCS) is of considerable interest in this context.

OBJECTIVE

To investigate the efficacy and safety of a novel technique involving simultaneous application of rTMS and tDCS (rTMS-tDCS) over bilateral angular gyrus (AG, P5/P6 electrode site) for AD-related NPS.

METHODS

Eighty-four AD patients were randomized to receive rTMS-tDCS, single-rTMS, single-tDCS, or sham stimulation for 4 weeks, with evaluation at week-4 (W4, immediately after treatment) and week-12 (W12, follow-up period) after initial examination. Primary outcome comprising Neuropsychiatric Inventory (NPI) score and secondary outcomes comprising mini-mental state examination (MMSE), AD assessment scale-cognitive subscale (ADAS-cog), and Pittsburgh sleep quality index (PSQI) scores were collected and analyzed by a two-factor (time and treatment), mixed-design ANOVA.

RESULTS

rTMS-tDCS produced greater improvement in NPI scores than single-tDCS and sham at W4 and W12 (both P < 0.017) and trended better than single-rTMS (W4: P = 0.058, W12: P = 0.034). rTMS-tDCS improved MMSE scores compared with single-tDCS at W4 (P = 0.011) and sham at W4 and W12 (both P < 0.017). rTMS-tDCS also significantly improved PSQI compared with single-rTMS and sham (both P < 0.017). Interestingly, rTMS-tDCS-induced NPI/PSQI improvement was significantly associated with MMSE/ADAS-cog improvement. tDCS- and/or rTMS-related adverse events appeared slightly and briefly.

CONCLUSIONS

rTMS-tDCS application to bilateral AG can effectively improve AD-related NPS, cognitive function, and sleep quality with considerable safety.

Individual functional parcellation revealed compensation of dynamic limbic network organization in healthy ageing

Using group-level functional parcellations and constant-length sliding window analysis, dynamic functional connectivity studies have revealed network-specific impairment and compensation in healthy ageing. However, functional parcellation and dynamic time windows vary across individuals; individual-level ageing-related brain dynamics are uncertain. Here, we performed individual parcellation and individual-length sliding window clustering to characterize ageing-related dynamic network changes. Healthy participants (n = 637, 18-88 years) from the Cambridge Centre for Ageing and Neuroscience dataset were included. An individual seven-network parcellation, varied from group-level parcellation, was mapped for each participant. For each network, strong and weak cognitive brain states were revealed by individual-length sliding window clustering and canonical correlation analysis. The results showed negative linear correlations between age and change ratios of sizes in the default mode, frontoparietal, and salience networks and a positive linear correlation between age and change ratios of size in the limbic network (LN). With increasing age, the occurrence and dwell time of strong states showed inverted U-shaped patterns or a linear decreasing pattern in most networks but showed a linear increasing pattern in the LN. Overall, this study reveals a compensative increase in emotional networks (i.e., the LN) and a decline in cognitive and primary sensory networks in healthy ageing. These findings may provide insights into network-specific and individual-level targeting during neuromodulation in ageing and ageing-related diseases.

Abnormal dynamic reconfiguration of the large-scale functional network in schizophrenia during the episodic memory task

Episodic memory deficits are the core feature in schizophrenia (SCZ). Numerous studies have revealed abnormal brain activity associated with this disorder during episodic memory, however previous work has only relied on static analysis methods that treat the brain as a static monolithic structure, ignoring the dynamic features at different time scales. Here, we applied dynamic functional connectivity analysis to functional magnetic resonance imaging data during episodic memory and quantify integration and recruitment metrics to reveal abnormal dynamic reconfiguration of brain networks in SCZ. In the specific frequency band of 0.06-0.125 Hz, SCZ showed significantly higher integration during encoding and retrieval, and the abnormalities were mainly in the default mode, frontoparietal, and cingulo-opercular modules. Recruitment of SCZ was significantly higher during retrieval, mainly in the visual module. Interestingly, interactions between groups and task status in recruitment were found in the dorsal attention, visual modules. Finally, we observed that integration was significantly associated with memory performance in frontoparietal regions. Our findings revealed the time-varying evolution of brain networks in SCZ, while improving our understanding of cognitive decline and other pathophysiologies in brain diseases.