Classical models of perceptual decision-making assume that animals use a single, consistent strategy to form decisions, or that decision-making strategies evolve slowly over time. Here we present new analyses suggesting that this common view is incorrect. We analyzed data from two mouse decision-making experiments and found that choice behavior relies on an interplay between multiple interleaved strategies. These strategies, characterized by states in a hidden Markov model, persist for tens to hundreds of trials before switching, and may alternate multiple times within a session.The identified strategies were highly consistent across animals, consisting of a single "engaged" state, in which decisions relied heavily on the sensory stimulus, and several biased or disengaged states in which errors frequently occurred. These results provide a powerful alternate explanation for "lapses" often observed in psychophysical experiments, and suggest that standard measures of performance mask the presence of dramatic changes in strategy across trials.

The structural polymorphism in transition metal dichalcogenides (TMDs) provides exciting opportunities for developing advanced electronics. For example, MoTe 2 crystallizes in the 2H semiconducting phase at ambient temperature and pressure, but transitions into the 1T′ semimetallic phase at high temperatures. Alloying MoTe 2 with WTe 2 reduces the energy barrier between these two phases, while also allowing access to the T d Weyl semimetal phase. The −RECEIVED

A classic view of the striatum holds that activity in direct and indirect pathways oppositely modulates motor output. Whether this involves direct control of movement, or reflects a cognitive process underlying movement, has remained unresolved. Here we find that strong, opponent control of behavior by the two pathways of the dorsomedial striatum (DMS) depends on a task's cognitive demands. Furthermore, a latent state model (a hidden markov model with generalized linear model observations) reveals that-even within a single task-the contribution of the two pathways to behavior is state-dependent. Specifically, the two pathways have large contributions in one of two states associated with a strategy of evidence accumulation, compared to a state associated with a strategy of repeating previous choices. Thus, both the cognitive demands imposed by a task, as well as the strategy that mice pursue within a task, determine whether DMS pathways provide strong and opponent control of behavior.

Classical models of perceptual decision-making assume that animals use a single, consistent strategy to integrate sensory evidence and form decisions during an experiment. Here we provide analyses showing that this common view is incorrect. We use a latent variable modeling framework to show that decision-making behavior in mice reflects an interplay between different strategies that alternate on a timescale of tens to hundreds of trials. This model provides a powerful alternate explanation for "lapses" commonly observed during psychophysical experiments. Formally, our approach consists of a Hidden Markov Model (HMM) with states corresponding to different decision-making strategies, each parameterized by a distinct Bernoulli generalized linear model (GLM). We fit the resulting model (GLM-HMM) to choice data from two large cohorts of mice in different perceptual decision-making tasks. For both datasets, we found that mouse decision-making was far better described by a GLM-HMM with 3 or 4 states than by a traditional psychophysical model with lapses. The identified states were highly consistent across animals, consisting of a single "engaged" state, in which the strategy relied heavily on the sensory stimulus, and multiple biased or disengaged states in which accuracy was low. These states persisted for many trials, suggesting that lapses were not independent, but reflected state dynamics in which animals were relatively engaged or disengaged for extended periods of time. We found that for most animals, response times and violation rates were positively correlated with disengagement, providing independent correlates of the identified changes in strategy. The GLM-HMM framework thus provides a powerful lens for the analysis of decision-making, and suggests that standard measures of psychophysical performance mask the presence of slow but dramatic alternations in strategy across trials.

We examine anharmonic contributions to the optical phonon modes in bulk T d -MoTe 2 through temperature-dependent Raman spectroscopy. At temperatures ranging from 100 K to 200 K, we find that all modes redshift linearly with temperature in agreement with the Grüneisen model. However, below 100 K we observe nonlinear temperaturedependent frequency shifts in some modes. We demonstrate that this anharmonic behavior is consistent with the decay of an optical phonon into multiple acoustic phonons. Furthermore, the highest frequency Raman modes show large changes in intensity and linewidth near T ≈ 250 K that correlate well with the T d →1T ′ structural phase transition. These results suggest that phonon-phonon interactions can dominate anharmonic contributions at low temperatures in bulk T d -MoTe 2 , an experimental regime that is currently receiving attention in efforts to understand Weyl semimetals.