catecholaminergic

Chemistry of the adaptive mind: lessons from dopamine

The human brain faces a variety of computational dilemmas, including the flexibility/stability, the speed/accuracy and the labor/leisure tradeoff. I will argue that striatal dopamine is particularly well suited to dynamically regulate these computational tradeoffs depending on constantly changing task demands. This working hypothesis is grounded in evidence from recent studies on learning, motivation and cognitive control in human volunteers, using chemical PET, psychopharmacology, and/or fMRI. These studies also begin to elucidate the mechanisms underlying the huge variability in catecholaminergic drug effects across different individuals and across different task contexts. For example, I will demonstrate how effects of the most commonly used psychostimulant methylphenidate on learning, Pavlovian and effortful instrumental control depend on fluctuations in current environmental volatility, on individual differences in working memory capacity and on opportunity cost respectively.

An in-silico framework to study the cholinergic modulation of the neocortex

Neuromodulators control information processing in cortical microcircuits by regulating the cellular and synaptic physiology of neurons. Computational models and detailed simulations of neocortical microcircuitry offer a unifying framework to analyze the role of neuromodulators on network activity. In the present study, to get a deeper insight in the organization of the cortical neuropil for modeling purposes, we quantify the fiber length per cortical volume and the density of varicosities for catecholaminergic, serotonergic and cholinergic systems using immunocytochemical staining and stereological techniques. The data obtained are integrated into a biologically detailed digital reconstruction of the rodent neocortex (Markram et al, 2015) in order to model the influence of modulatory systems on the activity of the somatosensory cortex neocortical column. Simulations of ascending modulation of network activity in our model predict the effects of increasing levels of neuromodulators on diverse neuron types and synapses and reveal a spectrum of activity states. Low levels of neuromodulation drive microcircuit activity into slow oscillations and network synchrony, whereas high neuromodulator concentrations govern fast oscillations and network asynchrony. The models and simulations thus provide a unifying in silico framework to study the role of neuromodulators in reconfiguring network activity.

Catecholaminergic modulation of persistent neuronal activity in the mouse auditory cortex

Evolution of the sleep-waking cycle in transgenic mice with an age-dependent accumulation of neuromelanin in catecholaminergic neurons, a new humanized model of Parkinson’s Disease

Fiber density analysis of the catecholaminergic projections in the Japanese quail

FENS Forum 2024