Zimmermannkondrup4339

One of the most influential accounts of central orbitofrontal cortex-that it mediates behavioral flexibility-has been challenged by the finding that discrimination reversal in macaques, the classic test of behavioral flexibility, is unaffected when lesions are made by excitotoxin injection rather than aspiration. This suggests that the critical brain circuit mediating behavioral flexibility in reversal tasks lies beyond the central orbitofrontal cortex. To determine its identity, a group of nine macaques were taught discrimination reversal learning tasks, and its impact on gray matter was measured. Magnetic resonance imaging scans were taken before and after learning and compared with scans from two control groups, each comprising 10 animals. One control group learned discrimination tasks that were similar but lacked any reversal component, and the other control group engaged in no learning. Gray matter changes were prominent in posterior orbitofrontal cortex/anterior insula but were also found in three other frontal cortical regions lateral orbitofrontal cortex (orbital part of area 12 [12o]), cingulate cortex, and lateral prefrontal cortex. In a second analysis, neural activity in posterior orbitofrontal cortex/anterior insula was measured at rest, and its pattern of coupling with the other frontal cortical regions was assessed. Activity coupling increased significantly in the reversal learning group in comparison with controls. In a final set of experiments, we used similar structural imaging procedures and analyses to demonstrate that aspiration lesion of central orbitofrontal cortex, of the type known to affect discrimination learning, affected structure and activity in the same frontal cortical circuit. The results identify a distributed frontal cortical circuit associated with behavioral flexibility.Neurons form complex networks that evolve over multiple time scales. In order to thoroughly characterize these networks, time dependencies must be explicitly modeled. Here, we present a statistical model that captures both the underlying structural and temporal dynamics of neuronal networks. Our model combines the class of Stochastic Block Models for community formation with Gaussian processes to model changes in the community structure as a smooth function of time. We validate our model on synthetic data and demonstrate its utility on three different studies using in vitro cultures of dissociated neurons.DNA sequences are often recognized by multi-domain proteins that may have higher affinity and specificity than single-domain proteins. However, the higher affinity to DNA might be coupled with slower recognition kinetics. In this study, we address this balance between stability and kinetics for multi-domain Cys2His2- (C2H2-) type zinc-finger (ZF) proteins. These proteins are the most prevalent DNA-binding domain in eukaryotes and C2H2 type zinc-finger proteins (C2H2-ZFPs) constitute nearly one-half of all known and predicted transcription factors in human. Extensive contact with DNA via tandem ZF domains confers high stability on the sequence-specific complexes. However, this can limit target search efficiency, especially for low abundance ZFPs. Earlier, we found that asymmetrical distribution of electrostatic charge among the three ZF domains of the low abundance transcription factor Egr-1 facilitates its DNA search process. Here, on a diverse set of 273 human C2H2-ZFP comprised of 3-15 tandem ZF domains, we find that, in many cases, electrostatic charge and binding specificity are asymmetrically distributed among the ZF domains so that neighbouring domains have different DNA-binding properties. find more For proteins containing 3-6 ZF domains, we show that the low abundance proteins possess a higher degree of non-specific asymmetry and vice versa. Our findings suggest that where the electrostatics of tandem ZF domains are similar (i.e., symmetrical), the ZFPs are more abundant to optimize their DNA search efficiency. This study reveals new insights into the fundamental determinants of recognition by C2H2-ZFPs of their DNA binding sites in the cellular landscape. The importance of electrostatic asymmetry with respect to binding site recognition by C2H2-ZFPs suggests the possibility that it may also be important in other ZFP systems and reveals a new design feature for zinc finger engineering.Decision making relies on adequately evaluating the consequences of actions on the basis of past experience and the current physiological state. A key role in this process is played by the basal ganglia, where neural activity and plasticity are modulated by dopaminergic input from the midbrain. Internal physiological factors, such as hunger, scale signals encoded by dopaminergic neurons and thus they alter the motivation for taking actions and learning. However, to our knowledge, no formal mathematical formulation exists for how a physiological state affects learning and action selection in the basal ganglia. We developed a framework for modelling the effect of motivation on choice and learning. The framework defines the motivation to obtain a particular resource as the difference between the desired and the current level of this resource, and proposes how the utility of reinforcements depends on the motivation. To account for dopaminergic activity previously recorded in different physiological states, the paper argues that the prediction error encoded in the dopaminergic activity needs to be redefined as the difference between utility and expected utility, which depends on both the objective reinforcement and the motivation. We also demonstrate a possible mechanism by which the evaluation and learning of utility of actions can be implemented in the basal ganglia network. The presented theory brings together models of learning in the basal ganglia with the incentive salience theory in a single simple framework, and it provides a mechanistic insight into how decision processes and learning in the basal ganglia are modulated by the motivation. Moreover, this theory is also consistent with data on neural underpinnings of overeating and obesity, and makes further experimental predictions.