Biology subjects

Mayr, U.

Publications and source records attributed to Mayr, U..

8 recordsLinked to original sources

bioRxiv2025

Hippocampal transformations occur along dimensions of memory interference

The role of the hippocampus in resolving memory interference has been greatly elucidated by considering the relationship between the similarity of visual stimuli (input) and corresponding similarity of hippocampal activity patterns (output). However, these input-output functions can take surprisingly different forms. Here, we reconcile seemingly conflicting findings by considering the possibility that the hippocampus prioritizes different dimensions of visual similarity across different stages of learning. First, we generated a set of natural scene images from two visual categories and rigorously characterized visual similarity using a wide array of methods: neural networks, artificial intelligence models, and human perceptual and memory decisions. We then identified two orthogonal dimensions of visual similarity that each predicted memory interference, but that did so at distinct stages of learning. Using high-resolution fMRI, we then tested for dimension-specific input-output functions within the hippocampus. Within CA3 and dentate gyrus (CA3/DG), we show that dimensions of visual similarity were inverted (repulsion) at stages of learning when they contributed to memory interference. In contrast, CA3/DG preserved similarity when dimensions did not contribute to interference. These findings reveal that hippocampal representations of visually-similar stimuli are highly dynamic and critically depend on the dimensions of similarity that currently contribute to memory interference.

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bioRxiv2023

Broadscale dampening of uncertainty adjustment in the aging brain

0.The ability to prioritize among input features according to relevance enables adaptive behaviors across the human lifespan. However, relevance often remains ambiguous, and such uncertainty increases demands for dynamic control. While both cognitive stability and flexibility decline during healthy ageing, it is unknown whether aging alters how uncertainty impacts perception and decision-making, and if so, via which neural mechanisms. Here, we assess uncertainty adjustment across the adult lifespan (N = 100; cross-sectional) via behavioral modelling and a theoretically informed set of EEG-, fMRI-, and pupil-based signatures. On the group level, older adults show a broad dampening of uncertainty adjustment relative to younger adults. At the individual level, older individuals with more young-like neural responses also showed better maintained cognitive control. Our results highlight neural mechanisms whose maintenance plausibly enables flexible task-set, perception, and decision computations across the adult lifespan.

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bioRxiv2022

The Role of Conjunctive Representations in Prioritizing and Selecting Planned Actions

For flexible goal-directed behavior, prioritizing and selecting a specific action among multiple candidates is often important. Working memory has long been assumed to play a role in prioritization and planning, while bridging cross-temporal contingencies during action selection. However, studies of working memory have mostly focused on memory for single components of an action plan, such as a rule or a stimulus, rather than management of all of these elements during planning. Therefore, it is not known how post-encoding prioritization and selection operate on the entire profile of representations for prospective actions. Here, we assessed how such control processes unfold over action representations, highlighting the role of conjunctive representations that nonlinearly integrate task-relevant features during maintenance and prioritization of action plans. For each trial, participants prepared two independent rule-based actions simultaneously, then they were retro-cued to select one as their response. Prior to the start of the trial, one rule-based action was randomly assigned to be high priority by cueing that it was more likely to be tested. We found that both full action plans were maintained as conjunctive representations during action preparation, regardless of priority. However, during output selection, the conjunctive representation of the high priority action plan was more enhanced and readily selected as an output. Further, the strength of conjunctive representation was related to behavioral interference when the low priority action was tested. Thus, multiple integrated representations were maintained for upcoming actions and served as the target of post-encoding attentional selection mechanisms to prioritize and select an action from those in working memory.

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bioRxiv2020

The Role of Conjunctive Representations in Controlling Actions

Action selection appears to rely on conjunctive representations that nonlinearly integrate task-relevant features (Kikumoto & Mayr, 2020). We test here the corollary hypothesis that such representations are also intricately involved during attempts to stop an action--a key aspect of action regulation. We tracked both conjunctive representations and those of constituent rule, stimulus, or response features through trial-by-trial representational similarity analysis of the EEG signal in a combined, rule-selection and stop-signal paradigm. Across two experiments with student participants (N = 57), we found (a) that the strength of decoded conjunctive representations prior to the stop signal uniquely predicted trial-by-trial stopping success (Exp. 1) and (b) that these representations were selectively suppressed following the onset of the stop signal (Exp. 1 and 2). We conclude that conjunctive representations are key to successful action execution and therefore need to be suppressed when an intended action is no longer appropriate. Statement of RelevanceSome theorists have posited that as a necessary step during action selection, action-relevant features need to be combined within a conjunctive representation that is more than the sum if its basic features. Consequently, such representations should also play a critical role when trying to stop an intended action--a key aspect of self-regulation. However direct evidence of conjunctive representations has been elusive. Using a method for tracking both conjunctive and basic-feature representations on a trial-by-trial basis in the EEG signal, we show that the stronger the conjunctive representations, the harder it was to stop the intended action. Furthermore, the stopping process also selectively reduced the strength of conjunctive representations. These results further our knowledge about action regulation by showing that conjunctive representations are a necessary precursor for carrying out actions successfully and for that reason also need to be the target of self-regulatory stopping attempts.

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bioRxiv2019

Conjunctive Representations that Integrate Stimuli, Responses, and Rules are Critical for Action Selection

People can use abstract rules to flexibly configure and select actions for specific situations. Yet how exactly rules shape actions towards specific sensory and/or motor requirements remains unclear. One possibility is that rules become integrated with sensory/response features in a non-linear, conjunctive manner (e.g., event files; Hommel, 1998) to drive rule-guided action selection. To dynamically track such conjunctive representations during action selection, we applied a time-resolved representational similarity analysis to the spectral-temporal profiles of the EEG signal, while participants selected actions based on varying rules. Across two experiments, we found that action selection engages conjunctive representations binding action rules to specific sensory/motor settings throughout the entire selection period. The strength of conjunctions was the most important predictor of trial-by-trial variability in response times (RTs) and was closely, and selectively, related to an important behavioral indicator of event files--the partial-overlap priming pattern. Thus, conjunctive representations were functionally dissociated from their constituent action features and play a critical role during flexible selection of action.

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bioRxiv2019

Balancing Model-Based and Memory-Free Action Selection under Competitive Pressure

In competitive situations, winning depends on selecting actions that surprise the opponent. Such unpredictable action can be generated based on representations of the opponents strategy and choice history (model-based counter-prediction) or by choosing actions in a memory-free, stochastic manner. Across five different experiments using a variant of a matching-pennies game with simulated and human opponents we found that people toggle between these two strategies, using model-based selection used when recent wins signal the appropriateness of the current model, but reverting to stochastic selection following losses. Also, after wins, feedback-related, mid-frontal EEG activity reflected information about the opponents global and local strategy, and predicted upcoming choices. After losses, this activity was nearly absent--indicating that the internal model is suppressed after negative feedback. We suggest that the mixed-strategy approach allows negotiating two conflicting goals: (1) exploiting the opponents deviations from randomness while (2) remaining unpredictable for the opponent.

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bioRxiv2018

Decoding Hierarchical Control of Sequential Behavior in Oscillatory EEG Activity

Despite strong theoretical reasons for assuming that abstract representations organize complex action sequences in terms of subplans (chunks) and sequential positions, we lack methods to directly track such content-independent, hierarchical representations in humans. We applied time-resolved, multivariate decoding analysis to the pattern of rhythmic EEG activity that was registered while participants planned and executed individual elements from pre-learned, structured sequences. Across three experiments, the theta and alpha-band activity independently coded basic elements and abstract control representations, in particular the ordinal position of basic elements, but also the identity and position of chunks. Further, a robust representation of higher-level, chunk identity information was only found in individuals with above-median working memory capacity, potentially providing a neural-level explanation for working-memory differences in sequential performance. Our results suggest that by decoding oscillations we can track how the cognitive system traverses through the states of a hierarchical control structure.

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bioRxiv2017

EEG Decoding Reveals the Temporal Dynamics and Functional Relevance of Goal-Relevant Representations

Models of action control assume that abstract task-set settings regulate lower-level stimulus/response representations. Yet, we know little about the functional and dynamic properties of task-set representations in humans. Using a cued task-switching paradigm, we show that information about task sets and lower-level stimulus/response aspects can be extracted through decoding analyses from the scalp electrophysiological signal (EEG) on the single-trial level and with high temporal resolution. Task-sets are active throughout the entire processing cascade and trial-to-trial variations in task-set strength emerges as a remarkably strong predictor of variability in performance, both within and between individuals. Also, taskset strength is related to stimulus representation strength at an early period and to the strength of response representations at a later period, consistent with the notion that task-sets coordinate successive, lower-level representations in a concurrent manner. These results demonstrate a powerful approach towards uncovering stages of information processing and their relative importance for performance.

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