Neurochemical Oscillations in the Basal Ganglia

Quantum modeling of common sense

Quantum theory is a powerful framework for probabilistic modeling of cognition. Strong empirical evidence suggests the context- and order-dependent representation of human judgment and decision-making processes, which falls beyond the scope of classical Bayesian probability theories. However, considering behavior as the output of underlying neurobiological processes, a fundamental question remains unanswered: Is cognition a probabilistic process at all?

200-300Hz movement modulated oscillations in the internal globus pallidus of patients with Parkinson's Disease

Symptoms in Parkinson's Disease (PD) have been linked to oscillatory activity within the basal ganglia. In humans, such activity has been detected mainly in the local field potentials (LFPs) recorded from electrode contacts used for deep brain stimulation. Although most studies have focused on activity within the subthalamic nucleus (STN), the internal part of the globus pallidus (GPi) is considered an equally efficacious site for therapeutic neuromodulation. Moreover, while most investigations have evaluated changes in oscillatory activity in the beta (12-35Hz) and gamma (35-100Hz) bands, our preliminary spectral analysis of LFP signals in the GPi suggested distinct activity at higher frequencies as well. We hypothesized there is a unique LFP signature in the GPi that consists of movement modulated spectral power increases above 100Hz. Using invasive recordings from the GPi of patients undergoing DBS, in addition to confirming increased beta band activity within the GPi of patients with PD, we have identified and characterized a previously undescribed peak between 200 and 300Hz centered at approximately 235Hz, whose height and width but not center frequency are movement modulated. An increase in peak height is not transient, but rather persists for the duration of movement. The 200-300Hz rhythms in the GPi could have a functional role in the basal ganglia reentrant circuits by encoding output information entering the thalamo-cortical network or by organizing downstream activity for the successful execution of tasks.

Neurocircuitry for modeling drug effects

The identification and functional understanding of the neurocircuitry that mediates alcohol and drug effects that are relevant for the development of addictive behavior is a fundamental challenge in addiction research. Here we introduce an assumption-free construction of a neurocircuitry that mediates acute and chronic drug effects on neurotransmitter dynamics that is solely based on rodent neuroanatomy. Two types of data were considered for constructing the neurocircuitry: (1) information on the cytoarchitecture and neurochemical connectivity of each brain region of interest obtained from different neuroanatomical techniques; (2) information on the functional relevance of each region of interest with respect to alcohol and drug effects. We used mathematical data mining and hierarchical clustering methods to achieve the highest standards in the preprocessing of these data. Using this approach, a dynamical network of high molecular and spatial resolution containing 19 brain regions and seven neurotransmitter systems was obtained. Further graph theoretical analysis suggests that the neurocircuitry is connected and cannot be separated into further components. Our analysis also reveals the existence of a principal core subcircuit comprised of nine brain regions: the prefrontal cortex, insular cortex, nucleus accumbens, hypothalamus, amygdala, thalamus, substantia nigra, ventral tegmental area and raphe nuclei. Finally, by means of algebraic criteria for synchronizability of the neurocircuitry, the suitability for in silico modeling of acute and chronic drug effects is indicated. Indeed, we introduced as an example a dynamical system for modeling the effects of acute ethanol administration in rats and obtained an increase in dopamine release in the nucleus accumbens-a hallmark of drug reinforcement-to an extent similar to that seen in numerous microdialysis studies. We conclude that the present neurocircuitry provides a structural and dynamical framework for large-scale mathematical models and will help to predict chronic drug effects on brain function.