@article {67263, title = {Hunger or thirst state uncertainty is resolved by outcome evaluation in medial prefrontal cortex to guide decision-making.}, journal = {Nature Neuroscience}, volume = {24}, year = {2021}, month = {2021 Jul 01}, pages = {907-912}, abstract = {

Physiological need states direct decision-making toward re-establishing homeostasis. Using a two-alternative forced choice task for mice that models elements of human decisions, we found that varying hunger and thirst states caused need-inappropriate choices, such as food seeking when thirsty. These results show limits on interoceptive knowledge of hunger and thirst states to guide decision-making. Instead, need states were identified after food and water consumption by outcome evaluation, which depended on the medial prefrontal cortex.

}, issn = {1546-1726}, doi = {10.1038/s41593-021-00850-4}, author = {Eiselt, Anne-Kathrin and Chen, Susu and Chen, Jim and Arnold, Jon and Kim, Tahnbee and Pachitariu, Marius and Sternson, Scott M} } @article {47990, title = {Single-cell coding of sensory, spatial and numerical magnitudes in primate prefrontal, premotor and cingulate motor cortices.}, journal = {Experimental Brain Research}, volume = {234}, year = {2016}, month = {2016 Jan}, pages = {241-54}, abstract = {

The representation of magnitude information enables humans and animal species alike to successfully interact with the external environment. However, how various types of magnitudes are processed by single neurons to guide goal-directed behavior remains elusive. Here, we recorded single-cell activity from the dorsolateral prefrontal (PFC), dorsal premotor (PMd) and cingulate motor (CMA) cortices in monkeys discriminating discrete numerical (numerosity), continuous spatial (line length) and basic sensory (spatial frequency) stimuli. We found that almost exclusively PFC neurons represented the different magnitude types during sample presentation and working memory periods. The frequency of magnitude-selective cells in PMd and CMA did not exceed chance level. The proportion of PFC neurons selectively tuned to each of the three magnitude types were comparable. Magnitude coding was mainly dissociated at the single-neuron level, with individual neurons representing only one of the three tested magnitude types. Neuronal magnitude discriminability, coding strength and temporal evolution were comparable between magnitude types encoded by PFC neuron populations. Our data highlight the importance of PFC neurons in representing various magnitude categories. Such magnitude representations are based on largely distributed coding by single neurons that are anatomically intermingled within the same cortical area.

}, keywords = {Animals, Gyrus Cinguli, Judgment, Macaca mulatta, Male, Mathematical Concepts, Motor Cortex, Neurons, Patch-Clamp Techniques, Pattern Recognition, Visual, Prefrontal Cortex, Space Perception}, issn = {1432-1106}, doi = {10.1007/s00221-015-4449-8}, author = {Eiselt, Anne-Kathrin and Nieder, Andreas} } @article {48106, title = {Three pillars for the neural control of appetite.}, journal = {Annual Review of Physiology}, volume = {79}, year = {2016}, month = {2016 Nov 28}, pages = {401-23}, abstract = {

The neural control of appetite is important for understanding motivated behavior along with the present rising prevalence of obesity. Over the past several years, new tools for cell type-specific neuron activity monitoring and perturbation have enabled increasingly detailed analyses of the mechanisms underlying appetite-control systems. Three major neural circuits strongly and acutely influence appetite but with notably different characteristics. Although these circuits interact, they have distinct properties and thus appear to contribute to separate but interlinked processes influencing appetite, thereby forming three pillars of appetite control. Here, we summarize some of the key characteristics of appetite circuits that are emerging from recent work and synthesize the findings into a provisional framework that can guide future studies. Expected final online publication date for the Annual Review of Physiology Volume 79 is February 10, 2017. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

}, issn = {1545-1585}, doi = {10.1146/annurev-physiol-021115-104948}, author = {Sternson, Scott M and Eiselt, Anne-Kathrin} }