Accumulating evidence in service of sensory decision making is a core cognitive function. However, previous work has focused either on the dynamics of neural activity during decision-making or on models of evidence accumulation governing behavior. We unify these two perspectives by introducing an evidence-accumulation framework that simultaneously describes multi-neuron population spiking activity and dynamic stimulus-driven behavior during sensory decision-making. We apply our method to

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... ral choices and neural activity recorded from three brain regions - the posterior parietal cortex (PPC), the frontal orienting fields (FOF), and the anterior-dorsal striatum (ADS) - while rats performed a pulse-based accumulation task. The model accurately captures the relationship between stimuli and neural activity, the coordinated activity of neural populations, and the distribution of animal choices in response to the stimulus. Model fits show strikingly distinct accumulation models expressed within each brain region, and that all differ strongly from the accumulation strategy expressed at the level of choices. In particular, the FOF exhibited a suboptimal 'primacy' strategy, where early sensory evidence was favored. Including neural data in the model led to improved prediction of the moment-by-moment value of accumulated evidence and the intended-and ultimately made-choice of the animal. Our approach offers a window into the neural representation of accumulated evidence and provides a principled framework for incorporating neural responses into accumulation models.