Excitation-inhibition balance

Nicolas Brunel discusses excitation-inhibition balance and mathematical explanations of irregular activity in cortical networks.

Visual representations become progressively more abstract along the cortical hierarchy. These abstract representations define notions like objects and shapes but at the cost of spatial specificity. By contrast, low-level regions represent spatially local but simple input features. How do spatially non-specific representations of abstract concepts in high-level areas flexibly modulate the low-level sensory representations in appropriate ways to guide context-driven and goal-directed behaviors across various tasks? We present a biologically motivated and trainable neural network model of dyna

Background: The balance of excitation and inhibition (E-I) is a key functional property of cortical microcircuits [1] which changes through lifespan. Adolescence is considered a crucial period for the maturation of E-I balance [2,3]. This has been primarily observed in animal studies, and human in vivo evidence on adolescent maturation of the E-I balance at an individual level is limited. Here, we investigated an in vivo marker of regional E-I balance in human adolescents based on individualized biophysical network models. Methods: Regional E-I balance was estimated using large-scale simulati

…features of brain activity such as excitation-inhibition balance. This approach allows personalized models of the brain to be fitted to individual subjects’ imaging data through parameter optimization [1, 2]. However, the process typically requires several thousand simulations per subject, making it computationally expensive and limiting its scalability to larger subject pools and more complex models. To address this,

…GABAergic function and improving the excitation-inhibition balance. However, very few neuro-behavioral studies have explored the beneficial effects of DR outside models of age-related neuropathologies. Therefore, here, we set out to explore DR's-therapeutic potential for stress-induced psychopathologies, by utilizing the "Individual behavioral profiling" approach. Towards that end, after exposing the animals to stress, an “individual Behavioral Profiling” analysis was used to identify, prior to t

…Maintaining an optimal excitation-inhibition balance is vital for PVT function, yet the sources of glutamatergic and GABAergic inputs are presently unclear. We identified subcortical glutamatergic and GABAergic inputs to the PVT by retrograde viral tracing in vGLUT2-Cre and vGAT-Cre mice, respectively. We found distinct retrogradely labelled cell groups containing purely vGLUT2+positive, purely vGAT+ or mixed neurons thro

The first-line pharmacological treatments for PTSD patients are serotonin reuptake inhibitors (SSRIs) and tricyclic antidepressants (TCAs). However, both treatments achieve full recovery in fewer than 30% of patients, underscoring the variability in responsiveness among individuals. To this day, there is a profound lack of knowledge regarding the neural mechanisms underlying responsiveness to these treatments. In our study, employing a male rat model of PTSD, we utilized individual behavioral profiling (IBP) following comprehensive behavioral assessments to distinguish between trauma-affected

…inputs during STP in a CA1 neuron with balanced excitation and inhibition. We performed invitro experiments on the CA3-CA1 network in acute hippocampal slices from mice expressing channelrhodopsin specifically i

The electrophysiological signal recorded from the brain shows rhythmic activity (oscillations) at different frequencies. One such rhythm, called gamma (~30-80 Hz), is modulated by high-level cognitive processes such as attention, memory, and meditation and, therefore, could provide clues about mechanisms underlying high-level cognition. Interestingly, gamma oscillations can be “induced” in the brain by presenting certain stimuli such as bars, gratings, and color patches (especially red hues). Moreover, these stimulus-induced gamma oscillations weaken with age and the onset of Alzheimer’s Disea

Fluctuations in arousal, controlled by subcortical neuromodulatory systems, continuously shape cortical state, with profound consequences for information processing. Yet, how arousal signals influence cortical population activity in detail has so far only been characterized for a few selected brain regions. Traditional accounts conceptualize arousal as a homogeneous modulator of neural population activity across the cerebral cortex. Recent insights, however, point to a higher specificity of arousal effects on different components of neural activity and across cortical regions. Here, we provide