The most influential account of phasic dopamine holds that it reports reward prediction errors (RPEs). The RPE-based interpretation of dopamine signaling is, in its original form, probably too simple and fails to explain all the properties of phasic dopamine observed in behaving animals. This Perspective helps to resolve some of the conflicting interpretations of dopamine that currently exist in the literature.
View Article and Find Full Text PDFThe goal of this study was to gather information about freshwater fishes in Letchworth State Park (42.615275° N, -77.992825° W), a portion of New York State-owned land located in the Genesee River Watershed that lacks known data about its fish diversity.
View Article and Find Full Text PDFIn a previous study, adaptive responses to a single polycyclic aromatic hydrocarbon (PAH), benzo[a]pyrene (BaP), were identified in brown bullhead (Ameiurus nebulosus) captured from contaminated sites across the Great Lakes. The tumor suppressor p53 and phase I toxin metabolizing CYP1A genes showed a elevated and refractory response, respectively, up to the F1 generation (Williams and Hubberstey, 2014). As an extension to the first study, bullhead were exposed to sediment collected from sites along the Detroit River to see if these adaptive responses are attainable when fish from a contaminated site are exposed to a mixture of contaminants, instead of a single compound.
View Article and Find Full Text PDFThe role of dopamine (DA) as a reward prediction error (RPE) signal in reinforcement learning (RL) tasks has been well-established over the past decades. Recent work has shown that the RPE interpretation can also account for the effects of DA on interval timing by controlling the speed of subjective time. According to this theory, the timing of the dopamine signal relative to reward delivery dictates whether subjective time speeds up or slows down: Early DA signals speed up subjective time and late signals slow it down.
View Article and Find Full Text PDFDeciphering the neural patterns underlying brain functions is essential to understanding how neurons are organized into networks. This deciphering has been greatly facilitated by optogenetics and its combination with optoelectronic devices to control neural activity with millisecond temporal resolution and cell type specificity. However, targeting small brain volumes causes photoelectric artefacts, in particular when light emission and recording sites are close to each other.
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