About

Kirsten Adam is an Assistant Professor of Psychological Sciences at Rice University. Her research focuses on cognitive neuroscience methods, including EEG and fMRI, to investigate how the brain manages limited attentional resources. Her work addresses central questions about successful and failed attention deployment, such as how irrelevant information is ignored and how failures of attention can cascade into memory failures. She is a member of the Ken Kennedy Institute and the Institute of Health Resilience and Innovation. Dr. Adam earned her Ph.D. in Cognitive Psychology from the University of Chicago in 2018, her M.S. in Cognitive Neuroscience from the University of Oregon in 2014, and her B.A. in Biological Sciences from the University of Notre Dame in 2012.

Research topics

• Computer Science
• Psychology
• Neuroscience
• Cognitive psychology
• Machine Learning
• Artificial Intelligence
• Statistics
• Mathematics

Selected publications

• Dissociable contributions of working memory capacity and lapses of attention to cognitive deficits in schizophrenia

  2026-05-05

  articleOpen access

  Working Memory (WM) impairment is a central feature of schizophrenia, yet it remains unclear whether WM deficits primarily reflect reduced storage capacity or inconsistent attentional engagement of available capacity. Traditional trial-averaged measures obscure this distinction. In this study, we combined a multi-item visual WM task with computational modeling to distinguish maximum storage capacity from trial-to-trial consistency of attentional engagement in people with schizophrenia (PSZ, N=52) and healthy control subjects (HCS, N=41). Participants completed two task variants that differed in response demands: a Free Response Order condition that permitted self-selected report order and a Random Response Order condition that imposed an externally determined order. PSZ showed robust impairments in average WM performance across tasks. Model-based analyses revealed that these impairments reflected both a reduction in maximum WM capacity and reduced consistency of attentional engagement. Capacity estimates were stable across task contexts, whereas consistency was selectively reduced in PSZ when response order was externally imposed. Time-resolved analyses demonstrated that group differences were stable across the experimental session and were not attributable to learning or fatigue effects. These findings indicate that WM deficits in schizophrenia arise from distinct impairments in both storage capacity and attentional consistency, and that task context influences the expression of these deficits. Parsing these components advances mechanistic models of cognitive dysfunction in schizophrenia and may help guide the design of cognitive assessments that are more sensitive to underlying process-level impairments.

  PublisherDOI

• Dissociating Contributions of Theta and Alpha Oscillations from Aperiodic Neural Activity in Human Visual Working Memory

  Research Explorer (The University of Manchester) · 2026-02-18

  preprintOpen access

  While visual working memory (WM) is strongly associated with reductions in occipitoparietal alpha (8–12 Hz) power, the role of frontal midline theta (4–7 Hz) power is less clear, with both increases and decreases widely reported. Here, we test the hypothesis that this theta paradox can be explained by nonoscillatory, aperiodic neural activity dynamics. Because traditional time–frequency analyses of electroencephalography (EEG) data conflate oscillations and aperiodic activity, event-related changes in aperiodic activity can manifest as task-related changes in apparent oscillations, even when none are present. Reanalyzing EEG data from two visual WM experiments (n = 74, of either sex), and leveraging spectral parameterization, we found systematic changes in aperiodic activity with WM load, and we replicated classic alpha, but not theta, oscillatory effects after controlling for aperiodic changes. Aperiodic activity decreased during WM retention and further flattened over the occipitoparietal cortex with an increase in WM load. After controlling for these dynamics, aperiodic-adjusted alpha power decreased with increasing WM load. In contrast, aperiodic-adjusted theta power appeared to increase during WM retention, but because aperiodic activity reduces more, it falsely appears as though theta “oscillatory” power (e.g., total band power) is reduced. Furthermore, only a minority of participants (31/74) had a detectable degree of theta oscillations. These results offer a potential resolution to the theta paradox where studies show contrasting power changes. Additionally, we have identified novel aperiodic dynamics during human visual WM.

  PublisherDOI

• No evidence for an object working memory capacity benefit in a whole-report task

  2026-05-08

  articleOpen accessSenior author
  PublisherOA PDFDOI

• Exploring neural mechanisms underlying error-related impairments in active working memory suggests an adaptive shielding of contents during cognitive control

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-07-23

  preprintOpen access

  Goal-directed behavior relies on cognitive flexibility - the ability to rapidly adapt ongoing thoughts and behaviors while preserving task-relevant information. The performance monitoring system optimizes such behavior by detecting and evaluating errors, while the working memory (WM) system maintains relevant information and protects it from interference. We investigated how these two systems interact. In prior work (Wessel et al., 2022), we found that motor errors impaired active WM maintenance (Error-Related Impairment of Active working Memory; ERIAM). Here, we aimed to identify the source of ERIAM by tracking a neurophysiological marker of visual WM maintenance - the contralateral delay activity (CDA) - throughout the error-making process. Forty-two human participants maintained visual information in WM while performing a motoric task during the delay period. Consistent with prior results, a significant ERIAM effect occurred: motor errors impaired WM performance. Critically, CDA amplitudes did not differ between motor correct and error trials before the flanker task, ruling out a general performance deficit. The CDA was also unaffected immediately after flankers, ruling out a perceptual interference explanation. Significant CDA differences only emerged after motor errors, supporting a genuinely error-related origin of the ERIAM effect. Contrary to prediction, however, CDA was more disrupted after correct responses than errors, and greater disruptions predicted a smaller ERIAM effect. These findings suggest that participants might store WM in multiple states to reduce interference from errors and that the CDA dynamics reflect these adaptive shielding strategies. These findings provide new insights into the source of error-related interference in active WM.

  PublisherOA PDFDOI

• Distributed and drifting signals for working memory load in human cortex

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-09-16

  preprintOpen access1st authorCorresponding

  Increasing working memory (WM) load incurs behavioral costs, and whether the neural constraints on behavioral costs are localized (i.e., emanating from the intraparietal sulcus) or distributed across cortex remains an active area of debate. In a pre-registered fMRI experiment, 12 humans (12 scanner-hours each) performed a visual WM task with varying memory load (0-4 items). We replicated a localized, load-dependent increase in univariate BOLD activity in parietal cortex. However, we also observed both systematic increases and decreases in univariate activity with load across the visual hierarchy. Importantly, multivariate activation patterns encoded WM load regardless of the direction of the univariate effect, arguing against a restricted locus of load signals in parietal cortex. Finally, we observed representational drift in activity patterns encoding memory load across scanning sessions. Our results suggest a distributed code for memory load that may be continually refined over time to support more efficient information storage.

  PublisherOA PDFDOI

• Distracted but not defeated: Voxel population codes flexibly transform to support high-fidelity working memory representations

  Journal of Vision · 2025-07-15

  articleOpen access

  Working memory (WM) is surprisingly robust to sensory distraction, but there is debate about how neural codes protect WM against sensory interference (Kamitani & Tong, 2005; LaRocque et al., 2012; Rademaker et al., 2019). Some studies propose that memory representations transform within early visual areas to minimize interference (Libby & Buschman, 2021), while others suggest that these memory representations are offloaded to frontoparietal regions, reducing early visual regions’ role in WM storage (Xu, 2021). We used fMRI to test whether early visual regions “multi-task” to concurrently support WM and the processing of incoming sensory information. Eight participants performed a spatial WM task, remembering the angular spatial position of a flickering checkerboard circle. On half of the trials, the screen was blank during the delay; on the other half, identical checkerboard circles flickered in other locations. We used circular ridge regression to decode spatial position, testing within-condition and cross-condition classification accuracy. The frontoparietal account predicts that sensory distractors degrade WM representations, leading to poor classification accuracy in early visual regions when training and testing on distractor-present trials. The flexible multi-tasking account predicts a cross-over interaction because mnemonic information is transformed but not lost. Decoding accuracy was similar in the distractor-present and distractor-absent conditions, consistent with the lack of a behavioral effect on recall error. However, we observed a crossover interaction as early as V1: Training on distractor-absent trials yielded better decoding for distractor-absent trials than distractor-present trials, and vice-versa. Cross-time generalization analyses showed a particularly robust cross-over interaction when training on late-delay period data. Notably, this interaction was absent in areas such as IPS. While our findings accommodate a prominent role for frontoparietal regions in storage and maintenance, they also suggest that voxel population codes in early visual regions flexibly transform to support storage of mnemonic information.

  PublisherDOI

• Capacity-aligned feedback enhances visual working memory performance

  2025-09-22

  articleOpen accessSenior author

  Because Visual Working Memory (VWM) capacity is limited, previous research has aimed to improve VWM with feedback and monetary incentives. However, the effects of feedback and incentives on VWM have been mixed. Here, we propose an “optimal strategy” account to explain when feedback will be effective versus ineffective at improving VWM performance. We hypothesized that incentivizing individuals with performance goals that are aligned to their capacity would yield higher average performance and fewer performance failures (“lapses”). Participants completed a whole-report VWM task and we varied the performance goal needed to earn bonus money on each trial (e.g., “Remember 3!”). In Experiments 1a and 1b, performance goals varied from 1 to 5 items, and we manipulated whether goals were blocked (Experiment 1a) or intermixed (Experiment 1b). In Experiment 2 (pre-registered), we replicated Experiment 1a with a larger sample size to examine individual differences in optimal VWM performance. Across all three experiments, group-averaged optimal VWM performance corresponded to goals that aligned to typical group-level capacity (~3 items). In contrast, supra-capacity goals (e.g., “remember 5 items”) tended to harm VWM performance by increasing lapses, consistent with an overload effect. In Experiment 2, we found that participants performed best when goals corresponded to their individual capacity estimate, and replicated overload effects at supra-capacity goals. However, we found a trade-off between metacognitive accuracy and optimal VWM performance. Altogether, our results suggest that VWM performance improvements rely on feedback that encourages the allocation of typical capacity limits, rather than encouraging maximizing performance.

  PublisherOA PDFDOI

• Prospective and retrospective awareness of moment-to-moment fluctuations in visual working memory performance.

  Journal of Experimental Psychology General · 2025-10-06 · 1 citations

  article

  = 85), we demonstrate that retrospective awareness is more sensitive to VWM performance fluctuations than prospective awareness in young adults, though both metacognitive abilities are imperfect. Poor metacognitive abilities reflected a general tendency-particularly among low VWM capacity individuals-to overestimate upcoming VWM performance. When individuals overestimated their upcoming VWM performance (i.e., prospective failures), VWM performance significantly reduced compared to the preceding trials of a prospective failure. Moreover, this reduction in performance significantly lingered into subsequent trials. However, individuals' prospective and retrospective awareness better aligned to VWM performance after a prospective failure. This postfailure calibration occurred even without feedback signaling a prospective failure (Experiment 2), suggesting a metacognitive efficiency in recognizing the initial overestimation. Taken together, our results suggest that individuals, particularly low-capacity individuals, have a limited awareness toward upcoming VWM performance but exhibit metacognitive adjustments immediately following a prospective failure. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

  PublisherDOI

• How Long-Term Learning Alters Visual Working Memory Representations: Evidence from EEG

  Journal of Vision · 2025-07-15

  articleOpen access

  Visual Working memory (VWM), our central system for temporarily holding visual information in mind for further thought and action, is limited in capacity. To overcome such limitations, we frequently leverage prior knowledge from visual long-term memory (VLTM), allowing us to integrate and represent information more efficiently. Yet, it is not well understood how prior knowledge affects the representation of information in VWM. Here, we assessed how prior learning affects the load of VWM representations by using multivariate load classification from EEG. Participants (N=30) learned a 6-color visual array to criterion, and then completed a VWM task including both new and pre-learned arrays. Crucially, new arrays differed in set size (0, 1, 2 or 6), which we used to train a classifier to identify the load in VWM from the multivariate EEG signal. After establishing strong classification accuracy (~55%; chance = 25%), we asked the classifier to predict the load elicited by pre-learned arrays. We find evidence that the availability of VLTM for pre-learned arrays reduced load in VWM, as the classifier predicts a load of 1 or 2, instead of 6 – the actual set size of pre-learned arrays. However, further exploration revealed that representations of pre-learned arrays were still dissociable from pure VWM representations of lower set sizes. This was further supported by representational similarity analyses, which suggested that the obtained representational pattern for pre-learned arrays was best explained by a model assuming 1) a reduction in load in VWM together with 2) a distinct contribution from VLTM to the representation. We conclude that the availability of prior knowledge reduces the load in VWM but leads to qualitative changes in multivariate neural signals, potentially rendering memory representations more distinctive.

  PublisherDOI

• Beyond Routine Maintenance: Current Trends in Working Memory Research

  Journal of Cognitive Neuroscience · 2025-01-01 · 5 citations

  reviewOpen access1st authorCorresponding

  Working memory (WM) is an evolving concept. Our understanding of the neural functions that support WM develops iteratively alongside the approaches used to study it, and both can be profoundly shaped by available tools and prevailing theoretical paradigms. Here, the organizers of the 2024 Working Memory Symposium-inspired by this year's meeting-highlight current trends and looming questions in WM research. This review is organized into sections describing (1) ongoing efforts to characterize WM function across sensory modalities, (2) the growing appreciation that WM representations are malleable to context and future actions, (3) the enduring problem of how multiple WM items and features are structured and integrated, and (4) new insights about whether WM shares function with other cognitive processes that have conventionally been considered distinct. This review aims to chronicle where the field is headed and calls attention to issues that are paramount for future research.

  PublisherOA PDFDOI

Recent grants

• Probing interactions of working- and long-term memory

  NSF · $132k · 2021–2023

Frequent coauthors

• Edward K. Vogel

  53 shared

• Edward Awh

  University of Chicago

  36 shared

• John T. Serences

  University of California, San Diego

  19 shared

• Edward K. Vogel

  University of Chicago

  14 shared

• Keisuke Fukuda

  University of Toronto

  13 shared

• Irida Mance

  Apple (United States)

  8 shared

• Joshua J. Foster

  Netherlands Institute for Neuroscience

  7 shared

• Nash Unsworth

  7 shared

Labs

• Adam LabPI

Education

• PhD, Department of Psychology

  University of Chicago

  2018

• M.S., Department of Psychology

  University of Oregon

  2015

• B.S., Biological Sciences

  University of Notre Dame

  2012