Dr Alex Provost

Time, or more specifically temporal structure, is a critical variable in understanding how the auditory system uses acoustic patterns to predict input, and to filter events based on their relevance. A key index of this filtering process is the auditory evoked potential component known as mismatch negativity or MMN. In this paper we review findings of smaller MMN in schizophrenia through the lens of time as an influential contextual variable. More specifically, we review studies that show how MMN to a locally rare pattern-deviation is modulated by the longer-term context in which it occurs. Empirical data is presented from a non-clinical sample confirming that the absence of a stable higher-order structure to sound sequences alters the way MMN amplitude changes over time. This result is discussed in relation to how hierarchical pattern learning might enrich our understanding of how and why MMN amplitude modulation is disrupted in schizophrenia.

Recent decades have witnessed amazing advances in both mathematical models of cognition and in the field of cognitive neuroscience. These developments were initially independent of one another, but recently the fields have started to become interested in joining forces. The resulting joint modeling of behavioral and neural data can be difficult, but has proved fruitful. We briefly review different approaches used in decision-making research for linking behavioral and neural data, and also provide an example. Our example provides a tight link between behavioral data and evoked scalp potentials measured during mental rotation. The example model illustrates a powerful hypothesis-driven way of linking such data sets. We demonstrate the use of such a model, provide a model comparison against interesting alternatives, and discuss the conclusions that follow from applying such a joint model.

Although first-impressions are known to impact decision-making and to have prolonged effects on reasoning, it is less well known that the same type of rapidly formed assumptions can explain biases in automatic relevance filtering outside of deliberate behavior. This paper features two studies in which participants have been asked to ignore sequences of sound while focusing attention on a silent movie. The sequences consisted of blocks, each with a high-probability repetition interrupted by rare acoustic deviations (i.e., a sound of different pitch or duration). The probabilities of the two different sounds alternated across the concatenated blocks within the sequence (i.e., short-to-long and long-to-short). The sound probabilities are rapidly and automatically learned for each block and a perceptual inference is formed predicting the most likely characteristics of the upcoming sound. Deviations elicit a prediction-error signal known as mismatch negativity (MMN). Computational models of MMN generally assume that its elicitation is governed by transition statistics that define what sound attributes are most likely to follow the current sound. MMN amplitude reflects prediction confidence, which is derived from the stability of the current transition statistics. However, our prior research showed that MMN amplitude is modulated by a strong first-impression bias that outweighs transition statistics. Here we test the hypothesis that this bias can be attributed to assumptions about predictable vs. unpredictable nature of each tone within the first encountered context, which is weighted by the stability of that context. The results of Study 1 show that this bias is initially prevented if there is no 1:1 mapping between sound attributes and probability, but it returns once the auditory system determines which properties provide the highest predictive value. The results of Study 2 show that confidence in the first-impression bias drops if assumptions about the temporal stability of the transition-statistics are violated. Both studies provide compelling evidence that the auditory system extrapolates patterns on multiple timescales to adjust its response to prediction-errors, while profoundly distorting the effects of transition-statistics by the assumptions formed on the basis of first-impressions.

The mismatch negativity (MMN) is conceptualized as a confidence-weighted error signal elicited when a deviation violates the predicted next-state based on regularity. The mechanisms underpinning its generation remain contentious. Smaller MMN response is a robust finding in schizophrenia and reduced amplitude may implicate impairment in prediction-error signalling. An enriched understanding of factors that influence MMN size in healthy people is a prerequisite for translating the relevance of reduced MMN in schizophrenia. This paper features two studies designed to explore factors that impact MMN in healthy individuals. Study 1 confirms that MMN amplitude does not faithfully reflect transition statistics and is susceptible to order-driven bias. In study 2, we demonstrate that an order-driven bias remains despite repeated encounters with sound sequences. These data demonstrate that factors that impact on MMN size in non-clinical groups are not fully understood and that some mechanisms driving relevance filtering are likely influenced by 'top-down' expectations.

© 2015 APA, all rights reserved). Shepard and Metzler's (1971) seminal mental-rotation task-which requires participants to decide if 1 object is a rotated version of another or its mirror image-has played a central role in the study of spatial cognition. We provide the first quantitative model of behavior in this task that is comprehensive in the sense of simultaneously providing an account of both error rates and the full distribution of response times. We used Brown and Heathcote's (2008) model of choice processing to separate out the contributions of mental rotation and decision stages. This model-based titration process was applied to data from a paradigm where converging evidence supported performance being based on rotation rather than other strategies. Stimuli were similar to Shepard and Metzler's block figures except a long major axis made rotation angle well defined for mirror stimuli, enabling comprehensive modeling of both mirror and normal responses. Results supported a mental rotation stage based on Larsen's (2014) model, where rotation takes a variable amount of time with a mean and variance that increase linearly with rotation angle. Differences in response threshold differences were largely responsible for mirror responses being slowed, and for errors increasing with rotation angle for some participants. (PsycINFO Database Record

Repetitious patterns enable the auditory system to form prediction models specifying the most likely characteristics of subsequent sounds. Pattern deviations elicit mismatch negativity (MMN), the amplitude of which is modulated by the size of the deviation and confidence in the model. Todd et al. (Neuropsychologia 49:3399-3405, 2011; J Neurophysiol 109:99-105, 2013) demonstrated that a multi-timescale sequence reveals a bias that profoundly distorts the impact of local sound statistics on the MMN amplitude. Two sounds alternate roles as repetitious "standard" and rare "deviant" rapidly (every 0.8 min) or slowly (every 2.4 min). The bias manifests as larger MMN to the sound first encountered as deviant in slow compared to fast changing sequences, but no difference for the sound first encountered as a standard. We propose that the bias is due to how Bayesian priors shape filters of sound relevance. By examining the time-course of change in MMN amplitude we show that the bias manifests immediately after roles change but rapidly disappears thereafter. The bias was reflected in the response to deviant sounds only (not in response to standards), consistent with precision estimates extracted from second order patterns modulating gain differentially for the two sounds. Evoked responses to deviants suggest that pattern extraction and reactivation of priors can operate over tens of minutes or longer. Both MMN and deviant responses establish that: (1) priors are defined by the most proximally encountered probability distribution when one exists but; (2) when no prior exists, one is instantiated by sequence onset characteristics; and (3) priors require context interruption to be updated. © 2013 Springer Science+Business Media.