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Coordination with replay has previously been observed in neurons of the primary visual cortex (Ji and Wilson, 2007) and the striatum (Pennartz et al., 2004; Lansink et al., 2009), a major target of the VTA that represents rewards (Schultz et al., 1992; Cardinal et al., 2002).
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Thus, Rolls and Xiang found evidence that the activity of some hippocampal neurons represents reward associations of places viewed by the animal, and suggested that the concept that the primate hippocampus is involved in object-place event memory might be extended to remembering goals available at different spatial locations.
First, we describe the idea that negative symptoms could arise from a failure to represent reward expectations to enable flexible behavioural adaptation.
241 neurons represented reward location on only one platform (Figure 4A) and 161 represented reward location on both platforms (Figure 4B).
A well-known example includes the reinforcement learning theory based on the temporal difference (TD) error algorithm[1], which is powerful enough to solve difficult problems in machine control and accounts for the basal-ganglia activity representing reward expectancy in monkeys and humans[2] [4].
If the dopamine neurons integrated input from the directly stimulated BSR substrate and translated the afferent impulse flow into a signal representing reward intensity, then cocaine-induced increases in the amplitude and duration of stimulation-induced dopamine transients [54], [85]would increase gain in the BSR substrate and shift the mountain along the price axis.
They interpreted these findings to suggest that the reward-dependent activity of some place cells may represent reward expectation.
Just because we used numerals to represent reward amount does not mean that the monkeys treated the numerals, like the dots, as numerosity cues.
Dopamine neurons of the VTA represent reward prediction error Schultz, 1998 and appear to be an important brain substrate for reinforcement learning (Montague et al., 1996).
The monkeys in this study learned to use both arbitrary symbols and the number of dots in a display to represent reward amount.
In this case, the response of brain regions thought to represent reward-related information might be expected to reflect the amount of information provided by the feedback, rather than the valence of the feedback.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com