Multisensory stimuli shift perceptual priors to facilitate rapid behavior

Multisensory stimuli speed behavioral responses, but the mechanisms subserving these effects remain disputed. Historically, the observation that multisensory reaction times (RTs) outpace models assuming independent sensory channels has been taken as evidence for multisensory integration (the “redundant target effect”; RTE). However, this interpretation has been challenged by alternative explanations based on stimulus sequence effects, RT variability, and/or negative correlations in unisensory processing. To clarify the mechanisms subserving the RTE, we collected RTs from 78 undergraduates in a multisensory simple RT task. Based on previous neurophysiological findings, we hypothesized that the RTE was unlikely to reflect these alternative mechanisms, and more likely reflected pre-potentiation of sensory responses through crossmodal phase-resetting. Contrary to accounts based on stimulus sequence effects, we found that preceding stimuli explained only 3–9% of the variance in apparent RTEs. Comparing three plausible evidence accumulator models, we found that multisensory RT distributions were best explained by increased sensory evidence at stimulus onset. Because crossmodal phase-resetting increases cortical excitability before sensory input arrives, these results are consistent with a mechanism based on pre-potentiation through phase-resetting. Mathematically, this model entails increasing the prior log-odds of stimulus presence, providing a potential link between neurophysiological, behavioral, and computational accounts of multisensory interactions.

Multisensory Stimuli Shift Perceptual Priors to Favor Rapid Detection

Multisensory stimuli speed behavioral responses, but the mechanisms subserving these effects remain disputed. Historically, the observation that multisensory reaction times (RTs) outpace models assuming independent sensory channels has been taken as evidence for multisensory integration (the “redundant target effect”; RTE). However, this interpretation has been challenged by alternative explanations based on stimulus sequence effects, RT variability, and/or negative correlations in unisensory processing. To clarify the mechanisms subserving the RTE, we collected RTs from 78 undergraduates in a multisensory simple RT task. Based on previous neurophysiological findings, we hypothesized that the RTE was unlikely to reflect these alternative mechanisms, and more likely reflected pre-potentiation of sensory responses through crossmodal phase-resetting. Contrary to accounts based on stimulus sequence effects, we found that preceding stimuli explained only 3-9% of the variance in apparent RTEs. Comparing three plausible evidence accumulator models, we found that multisensory RT distributions were best explained by increased sensory evidence at stimulus onset. Because crossmodal phase-resetting increases cortical excitability before sensory input arrives, these results are consistent with a mechanism based on pre-potentiation through phase-resetting. Mathematically, this model entails increasing the prior log-odds of stimulus presence, providing a potential link between neurophysiological, behavioral, and computational accounts of multisensory interactions.

Infants tailor their attention to maximize learning

Infants’ remarkable learning abilities allow them to rapidly acquire many complex skills. It has been suggested that infants achieve this learning by optimally allocating their attention to relevant stimuli in the environment, but the underlying mechanisms remain poorly understood. Here, we modeled infants’ looking behavior during a learning task through an ideal learner that quantified the informational structure of environmental stimuli. We show that saccadic latencies, looking time, and time spent engaged with a stimulus sequence are explained by the properties of the learning environments, including the level of surprise of the stimulus, overall predictability of the environment, and progress in learning the environmental structure. These findings reveal the factors that shape infants’ advanced learning, emphasizing their predisposition to seek out stimuli that maximize learning.

Response outcomes gate the impact of expectations on perceptual decisions

ABSTRACTPerceptual decisions are not only determined by current sensory information but are also influenced by expectations based on recent experiences. Can the impact of these expectations be flexibly modulated based on the outcome of previous decisions? We trained rats in several two-alternative forced choice auditory tasks, where the probability to repeat the previous stimulus category was varied in blocks of trials. All rats capitalized on the serial correlations of the stimulus sequence by consistently exploiting atransition bias:a tendency to repeat or alternate their previous response using an internal trial-by-trial estimate of the sequence repeating probability. Surprisingly, this bias was null in trials immediately following an error. The internal estimate however was not reset and it became effective again causing a bias after the next correct response. This ability to rapidly activate and inactivate the bias was captured by a non-linear generative model of rat behavior, whereby a reward-driven modulatory signal gated the use of the latent estimate of the environment statistics on the current decision. These results demonstrate that, based on the outcome of previous choices, rats flexibly modulate how expectations influence their current decisions.

Predictive Coding of Novel versus Familiar Stimuli in the Primary Visual Cortex

To explore theories of predictive coding, we presented mice with repeated sequences of images with novel images sparsely substituted. Under these conditions, mice could be rapidly trained to lick in response to a novel image, demonstrating a high level of performance on the first day of testing. Using 2-photon calcium imaging to record from layer 2/3 neurons in the primary visual cortex, we found that novel images evoked excess activity in the majority of neurons. When a new stimulus sequence was repeatedly presented, a majority of neurons had similarly elevated activity for the first few presentations, which then decayed to almost zero activity. The decay time of these transient responses was not fixed, but instead scaled with the length of the stimulus sequence. However, at the same time, we also found a small fraction of the neurons within the population (∼2%) that continued to respond strongly and periodically to the repeated stimulus. Decoding analysis demonstrated that both the transient and sustained responses encoded information about stimulus identity. We conclude that the layer 2/3 population uses a two-channel predictive code: a dense transient code for novel stimuli and a sparse sustained code for familiar stimuli. These results extend and unify existing theories about the nature of predictive neural codes.