Astrocyte reactivity in the glia limitans superficialis of the rat medial prefrontal cortex following sciatic nerve injury

6 Sep

The moderating effect of perceived hope in the relationship between anxiety and posttraumatic growth during the Russian-Ukrainian war

Introduction: This study examines the relationships between perceived hope, posttraumatic growth, well-being, anxiety, and perceived threat of the Russian-Ukrainian War (RUW) in the Czech adult population. Drawing on the evidence of posttraumatic growth (PTG) amidst crisis, we hypothesized that perceived hope moderates the effects of perceived threat of war and anxiety on PTG.

Methods: Data were obtained from 1,000 Czech respondents via an online questionnaire ten months post-invasion. The form included measures of posttraumatic growth, perceived hope, well-being, anxiety and depression, and perceived threat of war.

Results: Our findings reveal that perceived hope acted as a moderator enhancing the positive effects of perceived threat and anxiety on PTG. However, perceived hope did not significantly moderate the direct effects of perceived threats and anxiety on well-being.

Discussion: This study highlights the significant role of hope amidst adversity and underscores its potential as a target for interventions aiming to foster PTG in populations who navigate traumatic experiences.

5 Sep

Estimating the energy of dissipative neural systems

There is, at present, a lack of consensus regarding precisely what is meant by the term 'energy' across the sub-disciplines of neuroscience. Definitions range from deficits in the rate of glucose metabolism in consciousness research to regional changes in neuronal activity in cognitive neuroscience. In computational neuroscience virtually all models define the energy of neuronal regions as a quantity that is in a continual process of dissipation to its surroundings.

This, however, is at odds with the definition of energy used across all sub-disciplines of physics: a quantity that does not change as a dynamical system evolves in time. Here, we bridge this gap between the dissipative models used in computational neuroscience and the energy-conserving models of physics using a mathematical technique first proposed in the context of fluid dynamics.

We go on to derive an expression for the energy of the linear time-invariant (LTI) state space equation. We then use resting-state fMRI data obtained from the human connectome project to show that LTI energy is associated with glucose uptake metabolism. Our hope is that this work paves the way for an increased understanding of energy in the brain, from both a theoretical as well as an experimental perspective.