The trade-off between pulse duration and power in optical excitation of midbrain dopamine neurons approximates Bloch’s law

Pallikaras, Vasilios; Carter, Francis; Velázquez-Martínez, David N.; Arvanitogiannis, Andreas; Shizgal, Peter

doi:10.1016/j.bbr.2021.113702

Cited by 7 publications

(7 citation statements)

References 33 publications

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“…Prior to and following testing in the triadic-trial paradigm, data were obtained from four Experiment-2 subjects showing how time allocation varies as a function of the duration of the optical pulses delivered to the ChR2-expressing midbrain dopamine neurons (Figure S11). The location of the time-allocation versus pulse-duration curves along the pulse-duration axis reflects the behavioral effectiveness of the stimulation 22 : the shorter the pulse duration required to achieve a given level of time allocation, the more “bang” for the optical “buck.” In all four cases, the curves shifted leftwards (towards shorter durations) between the pre- and post-triadic-trial testing, indicating that the optical stimulation had become more effective.…”

Section: Resultsmentioning

confidence: 99%

Does phasic dopamine release cause policy updates?

Carter

Cossette

Trujillo-Pisanty

et al. 2022

Preprint

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Phasic dopamine activity is believed to both encode reward-prediction errors (RPEs) and to cause the adaptations that these errors engender. If so, a rat working for optogenetic stimulation of dopamine neurons will repeatedly update its policy and/or action values, thus iteratively increasing its work rate. Here, we challenge this view by demonstrating stable, non-maximal work rates in the face of repeated optogenetic stimulation of midbrain dopamine neurons. Furthermore, we show that rats learn to discriminate between world states distinguished only by their history of dopamine activation. Comparison of these results to reinforcement learning simulations suggests that the induced dopamine transients acted more as rewards than RPEs. However, pursuit of dopaminergic stimulation drifted upwards over a time scale of days and weeks, despite its stability within trials. To reconcile the results with prior findings, we consider multiple roles for dopamine signaling.

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Section: Resultsmentioning

confidence: 99%

Does phasic dopamine release cause policy updates?

Carter

Cossette

Trujillo-Pisanty

et al. 2022

Preprint

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“…A four-parameter equation was fitted to the data: (TA − TAmin)/(TAmax − TAmin) = 1/[1 + exp{−Slp × (log10 (d) − Loc)}]. Where: d = Pulse intensity or frequency, Loc = Value of the location parameter (it refers to the placement of the curve within the stimulation range, and together with TA 50 informs about rightward or leftward shifts), TA = Time allocation, TAmin = Minimal time allocation, TAmax = Maximal time allocation, and Slp = Slope parameter determining the steepness of the rise ( Trujillo-Pisanty et al, 2020 ; Pallikaras et al, 2021 ). PRISM (v9, GraphPad Software, San Diego, CA, United States) was used to fit functions, statistical analysis, and produce data graphs.…”

Section: Methodsmentioning

confidence: 99%

On the Similarity Between the Reinforcing and the Discriminative Properties of Intracranial Self-Stimulation

Velázquez-Martínez

Pacheco-Gomez

Toscano-Zapien

et al. 2022

Front. Behav. Neurosci.

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Rats work very hard for intracranial self-stimulation (ICSS) and tradeoff effort or time allocation for intensity and frequency parameters producing a sigmoidal function of the subjective reward magnitude of ICSS. Previous studies using electrical intracranial stimuli (ICS) as a discriminative cue focused on estimating detection thresholds or on the discrimination between intensities. To our knowledge, there is no direct comparison of the reinforcer tradeoff functions with the discriminative functions. Rats were trained to press and hold the lever for ICSS using the maximum reinforcing intensity below motor alterations or avoidance behavior. First, rats were trained to hold the lever for 1 s; after stability, they undergo trials where intensity or frequency was decreased on 0.1 log step. Thereafter, they undergo further training with a hold of 2 and later of 4 s to determine tradeoff with intensity or frequency. The same rats were trained on a discrimination task where the previously used ICSS signaled a lever where a 1 s hold response was followed by a reinforcing ICSS; on randomly alternating trials, a −0.6 log ICS signaled an alternate lever where a similar hold response led to a reinforcer. After mastering discrimination, generalization tests were carried out with varying intensity or frequency. Rats completed training with 2 and later 4 s hold response. After the completion of each task, the rats had different doses of a pimozide challenge while their intensity and hold-down requirement were varied. With regards to the rats’ tradeoff response time allocation as a function of intensity or frequency, sigmoid functions were displaced to the right when long responses were required. Rats that learned the discrimination task attained a discrimination index of 90–98%. Discrimination accuracy decreased slightly with the increase of hold requirement, but generalization gradients were not displaced to the right as a function of the response requirement. Pimozide induced a dose-dependent displacement of the time-allocation gradients, but it did not affect the generalization gradients. It is concluded that rats integrate response requirements as part of the reinforcement tradeoff function, but the response cost is not integrated into the discriminative function of ICSS.

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“…pulse-duration curves along the pulse-duration axis reflects the behavioural effectiveness of the stimulation (Pallikaras et al, 2022): the shorter the pulse duration required to achieve a given level of time allocation, the more 'bang' for the optical 'buck'. In all four cases, the curves shifted leftwards (towards shorter durations) between the pre-and post-triadic-trial testing, indicating that the optical stimulation had become more effective.…”

Section: Valuation Of Dopamine Stimulation Grew Slowly Over Extended ...mentioning

confidence: 99%

Does phasic dopamine release cause policy updates?

Carter,

Cossette,

Trujillo‐Pisanty

et al. 2023

Eur J of Neuroscience

Self Cite

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Phasic dopamine activity is believed to both encode reward‐prediction errors (RPEs) and to cause the adaptations that these errors engender. If so, a rat working for optogenetic stimulation of dopamine neurons will repeatedly update its policy and/or action values, thus iteratively increasing its work rate. Here, we challenge this view by demonstrating stable, non‐maximal work rates in the face of repeated optogenetic stimulation of midbrain dopamine neurons. Furthermore, we show that rats learn to discriminate between world states distinguished only by their history of dopamine activation. Comparison of these results to reinforcement learning simulations suggests that the induced dopamine transients acted more as rewards than RPEs. However, pursuit of dopaminergic stimulation drifted upwards over a time scale of days and weeks, despite its stability within trials. To reconcile the results with prior findings, we consider multiple roles for dopamine signalling.

show abstract

The trade-off between pulse duration and power in optical excitation of midbrain dopamine neurons approximates Bloch’s law

Cited by 7 publications

References 33 publications

Does phasic dopamine release cause policy updates?

Does phasic dopamine release cause policy updates?

On the Similarity Between the Reinforcing and the Discriminative Properties of Intracranial Self-Stimulation

Does phasic dopamine release cause policy updates?

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