Brain regions typically contain intermixed subpopulations of neurons with different connectivity and neurotransmitters. This complicates identification of neuronal phenotypes in electrophysiological experiments without using direct detection of unique molecular markers. A prime example of this difficulty is the identification of dopamine (DA) neurons in the midbrain ventral tegmental area (VTA). Although immunocytochemistry (ICC) against tyrosine hydroxylase (TH) is widely used to identify DA neurons, a high false negative rate for TH ICC following ex vivo electrophysiology experiments was recently reported, calling into question the validity of comparing DA and non-DA VTA neurons based on post-hoc ICC. However, in whole cell recordings from randomly selected rat VTA neurons we have found that TH labeling is consistently detected in ∼55% of neurons even after long recording durations (range: 2.5-150 min). This is consistent with our prior anatomical finding that 55% of VTA neurons are TH(+). To directly estimate a false negative rate for our ICC method we recorded VTA neurons from mice in which EGFP production is driven by the TH promoter. All 12 EGFP(+) neurons recorded with a K-gluconate internal solution (as used in our rat recordings) were strongly labeled by TH ICC (recording duration 16.6±1.8 min). However, using recording electrodes with an internal solution with high Cl(-) concentration reduced the intensity of TH co-labeling, in some cases to background (recording duration 16.7±0.9 min; n = 10). Thus TH is a highly reliable molecular marker for DA neurons in VTA patch clamp recordings provided compatible microelectrode solutions are used.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0015222 | PLOS |
Adaptive behavior depends on the ability to predict specific events, particularly those related to rewards. Armed with such associative information, we can infer the current value of predicted rewards based on changing circumstances and desires. To support this ability, neural systems must represent both the value and identity of predicted rewards, and these representations must be updated when they change.
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December 2024
Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, Friedman Brain Institute, New York, NY, United States.
Introduction: Diabetes is a metabolic disorder of glucose homeostasis that is a significant risk factor for neurodegenerative diseases, such as Alzheimer's disease, as well as mood disorders, which often precede neurodegenerative conditions. We examined the medial habenulainterpeduncular nucleus (MHb-IPN), as this circuit plays crucial roles in mood regulation, has been linked to the development of diabetes after smoking, and is rich in cholinergic neurons, which are affected in other brain areas in Alzheimer's disease.
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Front Nutr
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Department of Pathophysiology, School of Basic Medicine, Qingdao University, Qingdao, Shandong, China.
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View Article and Find Full Text PDFTrends Neurosci
January 2025
Department of Anesthesiology of the Children's Hospital and School of Brain Science and Brain Medicine, Zhejiang University School of Medicine and National Clinical Research Center for Child Health, Zhejiang University, Hangzhou, Zhejiang Province 310058, China; NHC and CAMS Key Laboratory of Medical Neurobiology, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, Zhejiang Province 310058, China. Electronic address:
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View Article and Find Full Text PDFNat Commun
January 2025
Department of Neuroscience, Technion Medical School, Bat-Galim, Haifa, Israel.
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