A cognitive model of response omissions in distraction paradigms.

The effects of distraction on responses manifest in three ways: prolonged reaction times, and increased error and response omission rates. However, the latter effect is often ignored or assumed to be due to a separate cognitive process. We investigated omissions occurring in two paradigms that manipulated distraction. One required simple stimulus detection of younger participants, the second required choice responses and was completed by both younger and older participants. We fit data from these paradigms with a model that identifies three causes of omissions: two are related to the process of accumulating the evidence on which a response is based: intrinsic omissions (due to between-trial variation in accumulation rates making it impossible to ever reach the evidence threshold) and design omissions (due to response windows that cause slow responses not to be recorded; a third, contaminant omissions, allows for a cause unrelated to the response process. In both data sets systematic differences in omission rates across conditions were accounted for by task-related omissions. Intrinsic omissions played a lesser role than design omissions, even though the presence of design omissions was not evident in descriptive analyses of the data. The model provided an accurate account of all aspects of the detection data and the choice-response data, but slightly underestimated overall omissions in the choice paradigm, particularly in older participants, suggesting that further investigation of contaminant omission effects is needed.

Hierarchical Learning of Statistical Regularities over Multiple Timescales of Sound Sequence Processing: A Dynamic Causal Modeling Study.

Our understanding of the sensory environment is contextualized on the basis of prior experience. Measurement of auditory ERPs provides insight into automatic processes that contextualize the relevance of sound as a function of how sequences change over time. However, task-independent exposure to sound has revealed that strong first impressions exert a lasting impact on how the relevance of sound is contextualized. Dynamic causal modeling was applied to auditory ERPs collected during presentation of alternating pattern sequences. A local regularity (a rare p = .125 vs. common p = .875 sound) alternated to create a longer timescale regularity (sound probabilities alternated regularly creating a predictable block length), and the longer timescale regularity changed halfway through the sequence (the regular block length became shorter or longer). Predictions should be revised for local patterns when blocks alternated and for longer patterning when the block length changed. Dynamic causal modeling revealed an overall higher precision for the error signal to the rare sound in the first block type, consistent with the first impression. The connectivity changes in response to errors within the underlying neural network were also different for the two blocks with significantly more revision of predictions in the arrangement that violated the first impression. Furthermore, the effects of block length change suggested errors within the first block type exerted more influence on the updating of longer timescale predictions. These observations support the hypothesis that automatic sequential learning creates a high-precision context (first impression) that impacts learning rates and updates to those learning rates when predictions arising from that context are violated. The results further evidence automatic pattern learning over multiple timescales simultaneously, even during task-independent passive exposure to sound.

Initial Uncertainty Impacts Statistical Learning in Sound Sequence Processing.

This paper features two studies confirming a lasting impact of first learning on how subsequent experience is weighted in early relevance-filtering processes. In both studies participants were exposed to sequences of sound that contained a regular pattern on two different timescales. Regular patterning in sound is readily detected by the auditory system and used to form "prediction models" that define the most likely properties of sound to be encountered in a given context. The presence and strength of these prediction models is inferred from changes in automatically elicited components of auditory evoked potentials. Both studies employed sound sequences that contained both a local and longer-term pattern. The local pattern was defined by a regular repeating pure tone occasionally interrupted by a rare deviating tone (p=0.125) that was physically different (a 30msvs. 60ms duration difference in one condition and a 1000Hz vs. 1500Hz frequency difference in the other). The longer-term pattern was defined by the rate at which the two tones alternated probabilities (i.e., the tone that was first rare became common and the tone that was first common became rare). There was no task related to the tones and participants were asked to ignore them while focussing attention on a movie with subtitles. Auditory-evoked potentials revealed long lasting modulatory influences based on whether the tone was initially encountered as rare and unpredictable or common and predictable. The results are interpreted as evidence that probability (or indeed predictability) assigns a differential information-value to the two tones that in turn affects the extent to which prediction models are updated and imposed. These effects are exposed for both common and rare occurrences of the tones. The studies contribute to a body of work that reveals that probabilistic information is not faithfully represented in these early evoked potentials and instead exposes that predictability (or conversely uncertainty) may trigger value-based learning modulations even in task-irrelevant incidental learning.

Time as context: The influence of hierarchical patterning on sensory inference.

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.

Intertrial RT variability affects level of target-related interference in cued task switching.

In cued task switching, performance relies on proactive and reactive control processes. Proactive control is evident in the reduction in switch cost under conditions that promote advance preparation. However, the residual switch cost that remains under conditions of optimal proactive control indicates that, on switch trials, the target continues to elicit interference that is resolved using reactive control. We examined whether posttarget interference varies as a function of trial-by-trial variability in preparation. We investigated target congruence effects on behavior and target-locked ERPs extracted across the response time (RT) distribution, using orthogonal polynomial trend analysis (OPTA). Early N2, late N2, and P3b amplitudes were differentially modulated across the RT distribution. There was a large congruence effect on late N2 and P3b, which increased with RT for P3b amplitude, but did not vary with trial type. This suggests that target properties impact switch and repeat trials equally and do not contribute to residual switch cost. P3b amplitude was larger, and latency later, for switch than repeat trials, and this difference became larger with increasing RT, consistent with sustained carryover effects on highly prepared switch trials. These results suggest that slower, less prepared responses are associated with greater target-related interference during target identification and processing, as well as slower, more difficult decision processes. They also suggest that neither general nor switch-specific preparation can ameliorate the effects of target-driven interference. These findings highlight the theoretical advances achieved by integrating RT distribution analyses with ERP and OPTA to examine trial-by-trial variability in performance and brain function.

First-impression bias effects on mismatch negativity to auditory spatial deviants.

Internal models of regularities in the world serve to facilitate perception as redundant input can be predicted and neural resources conserved for that which is new or unexpected. In the auditory system, this is reflected in an evoked potential component known as mismatch negativity (MMN). MMN is elicited by the violation of an established regularity to signal the inaccuracy of the current model and direct resources to the unexpected event. Prevailing accounts suggest that MMN amplitude will increase with stability in regularity; however, observations of first-impression bias contradict stability effects. If tones rotate probabilities as a rare deviant (p = .125) and common standard (p = .875), MMN elicited to the initial deviant tone reaches maximal amplitude faster than MMN to the first standard when later encountered as deviant-a differential pattern that persists throughout rotations. Sensory inference is therefore biased by longer-term contextual information beyond local probability statistics. Using the same multicontext sequence structure, we examined whether this bias generalizes to MMN elicited by spatial sound cues using monaural sounds (n = 19, right first deviant and n = 22, left first deviant) and binaural sounds (n = 19, right first deviant). The characteristic differential modulation of MMN to the two tones was observed in two of three groups, providing partial support for the generalization of first-impression bias to spatially deviant sounds. We discuss possible explanations for its absence when the initial deviant was delivered monaurally to the right ear.

Surprising sequential effects on MMN.

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.

Initial uncertainty impacts statistical learning in sound sequence processing.

This paper features two studies confirming a lasting impact of first learning on how subsequent experience is weighted in early relevance-filtering processes. In both studies participants were exposed to sequences of sound that contained a regular pattern on two different timescales. Regular patterning in sound is readily detected by the auditory system and used to form "prediction models" that define the most likely properties of sound to be encountered in a given context. The presence and strength of these prediction models is inferred from changes in automatically elicited components of auditory evoked potentials. Both studies employed sound sequences that contained both a local and longer-term pattern. The local pattern was defined by a regular repeating pure tone occasionally interrupted by a rare deviating tone (p=0.125) that was physically different (a 30msvs. 60ms duration difference in one condition and a 1000Hz vs. 1500Hz frequency difference in the other). The longer-term pattern was defined by the rate at which the two tones alternated probabilities (i.e., the tone that was first rare became common and the tone that was first common became rare). There was no task related to the tones and participants were asked to ignore them while focussing attention on a movie with subtitles. Auditory-evoked potentials revealed long lasting modulatory influences based on whether the tone was initially encountered as rare and unpredictable or common and predictable. The results are interpreted as evidence that probability (or indeed predictability) assigns a differential information-value to the two tones that in turn affects the extent to which prediction models are updated and imposed. These effects are exposed for both common and rare occurrences of the tones. The studies contribute to a body of work that reveals that probabilistic information is not faithfully represented in these early evoked potentials and instead exposes that predictability (or conversely uncertainty) may trigger value-based learning modulations even in task-irrelevant incidental learning.

Titrating decision processes in the mental rotation task.

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

Mismatch negativity (MMN) to pitch change is susceptible to order-dependent bias.

Pattern learning facilitates prediction about upcoming events. Within the auditory system such predictions can be studied by examining effects on a component of the auditory-evoked potential known as mismatch negativity (MMN). MMN is elicited when sound does not conform to the characteristics inferred from statistical probabilities derived from the recent past. Stable patterning in sequences elevates confidence in automatically generated perceptual inferences about what sound should come next and when. MMN amplitude should be larger when sequence is highly stable compared to when it is more volatile. This expectation has been tested using a multi-timescale paradigm. In this study, two sounds of different duration alternate roles as a predictable repetitive "standard" and rare MMN-eliciting "deviation." The paradigm consists of sound sequences that differ in the rate at which the roles of two tones alternate, varying from slowly changing (high stability) to rapidly alternating (low stability). Previous studies using this paradigm discovered a "primacy bias" affecting how stability in patterning impacts MMN amplitude. The primacy bias refers to the observation that the effect of longer-term stability within sequences only appears to impact MMN to the sound first encountered as deviant (the sound that is rare when the sequence commences). This study determines whether this order-driven bias generalizes to sequences that contain two tones differing in pitch. By manipulating (within-subjects) the order in which sounds are encountered as deviants the data demonstrate the two defining characteristics of primacy bias: (1) sequence stability only ever impacts MMN amplitude to the first-deviant sound; and (2) within higher stability sequences, MMN is significantly larger when a sound is the first compared to when it is the second deviant. The results are consistent with a general order-driven bias exerting modulating effects on MMN amplitude over a longer timescale.