Behavioral state-dependent oscillatory activity in prefrontal cortex induced by chronic social defeat stress

Astrocyte regulation of behavioral outputs: the versatile roles of calcium

Behavior arises from coordinated brain-wide neural and glial networks, enabling organisms to perceive, interpret, and respond to stimuli. Astrocytes play an important role in shaping behavioral output, yet the underlying molecular mechanisms are not fully understood. Astrocytes respond to intrinsic and extrinsic cues with calcium (Ca2+) fluctuations, which are highly heterogeneous across spatio-temporal scales, contexts, and brain regions. This heterogeneity allows astrocytes to exert dynamic regulatory effects on neuronal function but has made it challenging to understand the precise mechanisms and pathways linking astrocytic Ca2+ to specific behavioral outcomes, and the functional relevance of these signals remains unclear. Here, we review recent literature uncovering roles for astrocytic Ca2+ signaling in a wide array of behaviors, including cognitive, homeostatic, and affective focusing on its physiological roles, and potential pathological implications. We specifically highlight how different types of astrocytic Ca2+ signals are linked to distinct behavioral outcomes and discuss limitations and unanswered questions that remain to be addressed.

Mesoscale brain-wide fluctuation analysis: revealing ketamine's rapid antidepressant across multiple brain regions

Depression has been linked to cortico-limbic brain regions, and ketamine is known for its rapid antidepressant effects. However, how these brain regions encode depression collaboratively and how ketamine regulates these regions to exert its prompt antidepressant effects through mesoscale brain-wide fluctuations remain elusive. In this study, we used a multidisciplinary approach, including multi-region in vivo recordings in mice, chronic social defeat stress (CSDS), and machine learning, to construct a Mesoscale Brain-Wide Fluctuation Analysis platform (MBFA-platform). This platform analyzes the mesoscale brain-wide fluctuations of multiple brain regions from the perspective of local field potential oscillations and network dynamics. The decoder results demonstrate that our MBFA platform can accurately classify the Control/CSDS and ketamine/saline-treated groups based on neural oscillation and network activities among the eight brain regions. We found that multiple-region LFPs patterns are disrupted in CSDS-induced social avoidance, with the basolateral amygdala playing a key role. Ketamine primarily exerts the compensatory effects through network dynamics, contributing to its rapid antidepressant effect. These findings highlight the MBFA platform as an interdisciplinary tool for revealing mesoscale brain-wide fluctuations underlying complex emotional pathologies, providing insights into the etiology of psychiatry. Furthermore, the platform's evaluation capabilities present a novel approach for psychiatric therapeutic interventions.

The functional heterogeneity of non-suicidal self-injury: insights from latent profile analysis

BACKGROUND

The functional aspects of non-suicidal self-injury (NSSI) among adolescents represent a complex phenomenon requiring deeper understanding. While research has identified various NSSI functions, including emotional regulation, attention-seeking, and social avoidance, the field lacks comprehensive analysis of how these functions cluster into distinct profiles. Understanding these functional profiles is crucial for developing targeted interventions.

METHOD

A cross-sectional study of 1,783 adolescents (1,464 girls, 318 boys) aged 12-18 years was conducted across 14 psychiatric or general hospitals in nine Chinese provinces. Participants completed the Functional Assessment of Self-Mutilation (FASM), which assesses 22 distinct NSSI functions across three primary dimensions: emotional regulation, attention-seeking, and social avoidance. Additional measures included the Patient Health Questionnaire (PHQ-9) for depression and Generalized Anxiety Disorder Scale (GAD-7) for anxiety symptoms. Latent profile analysis was employed to identify distinct patterns in NSSI functions, with model selection based on fit indices including AIC, BIC, entropy, and LMRT.

RESULTS

Latent profile analysis revealed four distinct functional profiles: low attention-seeking-high social avoidance (LA-HS, 19.7%), high attention-seeking-high social avoidance (HA-HS, 9.5%), low attention-seeking and social avoidance (LA-LS, 57.8%), and high attention-seeking-low social avoidance (HA-LS, 13.0%). The HA-HS profile demonstrated the most severe clinical presentation, showing significantly elevated scores in NSSI frequency (M = 26.160, SD = 9.771), anxiety (GAD-7: M = 16.265, SD = 4.951), and depression (PHQ-9: M = 20.612, SD = 6.003). The LA-HS profile showed the second-highest severity (NSSI: M = 25.800, SD = 10.058; GAD-7: M = 14.775, SD = 5.376; PHQ-9: M = 19.966, SD = 5.938). Both profiles also demonstrated significantly higher rates of suicidal ideation (HA-HS: 77.6%; LA-HS: 79.2%) compared to other profiles.

CONCLUSIONS

Our findings reveal distinct patterns in how adolescents utilize NSSI functionally, particularly regarding attention-seeking and social avoidance dimensions. These functional profiles show meaningful associations with psychological outcomes, suggesting that understanding NSSI functions, rather than just behaviors, may be crucial for assessment and intervention. The identification of these distinct functional profiles among Chinese adolescents highlights the importance of function-specific approaches in clinical assessment and treatment planning.

Large-scale coupling of prefrontal activity patterns as a mechanism for cognitive control in health and disease: evidence from rodent models

Cognitive control of behavior is crucial for well-being, as allows subject to adapt to changing environments in a goal-directed way. Changes in cognitive control of behavior is observed during cognitive decline in elderly and in pathological mental conditions. Therefore, the recovery of cognitive control may provide a reliable preventive and therapeutic strategy. However, its neural basis is not completely understood. Cognitive control is supported by the prefrontal cortex, structure that integrates relevant information for the appropriate organization of behavior. At neurophysiological level, it is suggested that cognitive control is supported by local and large-scale synchronization of oscillatory activity patterns and neural spiking activity between the prefrontal cortex and distributed neural networks. In this review, we focus mainly on rodent models approaching the neuronal origin of these prefrontal patterns, and the cognitive and behavioral relevance of its coordination with distributed brain systems. We also examine the relationship between cognitive control and neural activity patterns in the prefrontal cortex, and its role in normal cognitive decline and pathological mental conditions. Finally, based on these body of evidence, we propose a common mechanism that may underlie the impaired cognitive control of behavior.