Biology subjects

Lewis-Peacock, J. A.

Publications and source records attributed to Lewis-Peacock, J. A..

13 recordsLinked to original sources

bioRxiv2026

Working memory adaptively recomputes plans amid distraction

Navigating daily tasks requires working memory to retain information, formulate plans, and execute goal-directed actions. While frequent distractions may momentarily disrupt planned actions, individuals typically exhibit the cognitive resilience necessary to regroup and resume goal-directed behavior. How people adapt to these perturbations in dynamic environments remains unclear. To address this, we developed a working memory paradigm inspired by the arcade game Snake, in which participants navigated an agent to collect memorized targets while EEG and eye-tracking data were recorded. On each trial, participants encoded the location of one or two targets (apples), maintained them during a delay, and then guided a virtual agent (snake) to collect them. Critically, on 50% of trials, a secondary task introduced high-value novel targets that required immediate pursuit; these interruptions altered the agents spatial position, necessitating a re-evaluation of the original plan upon returning to the primary goal. Behaviorally, participants prioritized the target proximal to the agent and flexibly revised their collection order after distraction according to the agents updated position. Eye-movement analyses showed structured gaze sweeps during encoding that were consistent with efficient route planning. Representational similarity analyses of EEG data revealed that agent-centered object vectors were represented more strongly than absolute object locations during the delay. Following distraction, object vectors were recomputed relative to the agents new position, and representational strength was redistributed when the action plan was updated. Whereas neural representations were biased toward the distal, future-relevant target, gaze was preferentially directed toward the proximal, immediately relevant target, suggesting complementary roles for internal attention and external attention in multistep planning. During distraction, backward gaze sweeps revisited memorized target locations, indicating that replanning unfolded dynamically while the intervening task was still ongoing. These data demonstrate that prospective neural coding and attentional sampling coordinate to adapt behaviors to the shifting demands of goal pursuit in dynamic environments.

neuroscience↗

bioRxiv2026

Temporal expectation triggers competition in working memory that leads to forgetting

Working memory (WM) provides a flexible but capacity-limited workspace for maintaining information over short intervals, whereas long-term memory (LTM) serves as a vast and enduring repository for preserving information over extended periods. Decades of research suggest that they are two distinct yet connected systems that together enable adaptive behavior. The link between WM and LTM may not be straightforward, however, as recent evidence has shown that activation-dependent competition among items in WM can weaken their representations in LTM. In the current study, we examined how dynamic competition among items for limited WM resources affects their retention in LTM. We induced competition between items by manipulating temporal expectations in a WM task with either a short (1 s) or a long (4 s) memory delay. Human participants (N = 20) initially prioritized items expected to be tested early, but shifted their priority to items expected to be tested later when the early test did not occur. Using electroencephalography (EEG) and multivariate pattern analysis (MVPA), we tracked the dynamic fluctuations in WM contents based on expected task relevance across the delay window. We linked these temporal profiles during WM with the long-term recognition performance of each item and found that forgetting was associated with a marked decrease in neural evidence for items deemed no longer relevant during the later delay period. These results demonstrate that WM representations fluctuate with temporal expectations and that the de-prioritization of items during WM maintenance is what drives their long-term forgetting.

neuroscience↗

bioRxiv2025

Rapid inversion of singleton distractor representations underlies learned attentional suppression

In visually complex and dynamically changing environments, humans must often filter out salient but task-irrelevant stimuli. Prior work shows that with repeated exposure to color singleton distractors, individuals can learn to divert attention away from these salient items. However, the neural mechanisms supporting such attentional suppression remain unclear. The present study examined the temporal trajectories of singleton distractor representations during visual search to address this gap. Using multivariate pattern analyses of EEG data in human subjects (N = 40, 30 females, 10 males), we identified two clusters of decodable singleton distractor representations: an early cluster from 100-200 ms and a later cluster from 200-400 ms. Temporal generalization analyses showed that the later representations were inverted versions of the early ones. Importantly, stronger late, but not early representations, predicted faster search responses, suggesting that the later signals support distractor suppression. This representational inversion facilitates suppressing singleton distractors in the spatial priority map. Comparing decoding evidence across locations revealed that singleton distractor locations were suppressed relative to non-singleton distractors. Moreover, comparing the neural coding of locations revealed that the spatial organization in the singleton distractor neural space was inverted relative to that in the target neural space. Together, these findings reveal a rapid representational inversion underlying salient distractor suppression at the onset of visual search. This inversion of singleton distractor signals was likely driven by top-down control mechanisms that transform bottom-up saliency signals, producing an inverted arrangement of target and distractor information within a shared neural space. Significance StatementA primary goal of attention is to select relevant information while ignoring irrelevant input from the external environment. Although the mechanisms of attentional enhancement have been extensively studied, the mechanisms underlying attentional suppression remain less well understood. While prior work has made important progress in identifying when attentional suppression is engaged, the neural mechanisms that implement suppression are still unclear. Here, we show that neural representations of salient singleton distractors undergo a rapid inversion approximately 200 ms after search onset. These inverted representations can subsequently be read out as suppression signals during the computation of spatial priorities. Together, our findings suggest that transforming initial pop-out distractor signals into an inverted representational format might drive rapid attentional suppression and support goal-directed visual search.

neuroscience↗

bioRxiv2025

Population-level constraints on single neuron tuning changes during behavioral adaptation

In neurofeedback training, select neurons - of the billions that comprise the brain - are able to adapt their activity to produce a desired behavior, even though the feedback signal is low-dimensional. However, the extent that individual neurons are able to alter their activity within the context of the neurofeedback population is unclear. Using a brain-computer interface in monkeys (n=2; Macaca mulatta), we tested how the tuning of individual neurons changed in response to various feedback perturbations. Overall, we found that neurons that co-varied their activity the most with the population and those that contributed most to the behavior prior to the perturbation were most resistant to change- regardless of perturbation type. The degree to which individual neurons counteracted the applied perturbation explained daily differences in how well neurons collectively produced adapted behavior. Our work provides important insight into how population-level constraints impact the ability of individual neurons to adapt and support behavioral flexibility.

bioengineering↗

bioRxiv2024

Neural correlates of kinematic features of passive finger movement revealed by univariate and multivariate fMRI analyses

Finger movements are associated with a relatively large neural representation. Passive finger movement - which involves refraining from actively performing or resisting movement - is a robust approach to investigate the neural representation of kinesthesia and proprioception in the brain. While some studies have characterized the neural correlates of passive finger movement, they have relied solely on mass univariate analysis, potentially affecting result sensitivity. Additionally, limited consideration has been given to stimulus duration, a factor closely tied to some kinematic features (amplitude and velocity), which recently proposed modeling approaches now take into account. Here, we reanalyzed previously published data using univariate and multivariate analysis to understand how kinesthesia is neurally encoded in neurotypical subjects in two separate experiments. Systematic passive stimulation of the fingers was provided using an MR-compatible robot while functional magnetic resonance imaging data was recorded. Our analyses consisted of univariate and multivariate approaches, conducted separately for each kinematic feature and adjusted for stimulus duration, regardless of whether brain activation scales with it. We provide a detailed mapping of brain areas related to amplitude, velocity, and direction of passive finger movement, including sensorimotor, subcortical, and cerebellar areas. In general, multivariate pattern analysis was more sensitive than the univariate approach in identifying brain regions associated with passive finger movement. Our univariate analysis demonstrated that activity in sensorimotor and subcortical areas was higher for larger amplitudes and slower velocities, which opposes to the original studys results, likely due to our treatment of stimulus duration as a confounder specified as a parametric modulator. A novel result, we also demonstrated that brain activity in sensorimotor areas was higher for extension compared to flexion of passive finger movement. In terms of kinematic features, a larger neural representation was found for amplitude and direction compared to velocity of passive finger movement. This indicates that kinesthesia and proprioception may be more reliant on displacement than kinematic aspects of passive finger movement. While univariate analyses are limited in addressing spatial heterogeneity and subject-level variability, our multivariate analyses showed increased sensitivity in identifying brain regions encoding passive movement. Our findings may extend the knowledge of how the brain encodes physical movements and may help design neurorehabilitation strategies.

neuroscience↗

bioRxiv2024

Neural population variance explains adaptation differences during learning

Variability, a ubiquitous feature of neural activity, plays an integral role in behavior. However, establishing a causal relationship between neural signals and behavior is difficult. By defining a mathematical mapping between neural spiking activity and behavior, we investigate the role of spiking variability in adaptation during a brain-computer interface (BCI) behavior in male rhesus macaques (Macaca mulatta, n=2). Recent BCI evidence demonstrates that creating novel neural patterns is harder than repurposing existing patterns to respond to changes in external input. However, what limits the ability to repurpose, or adapt, patterns under different magnitudes of change is less well-characterized. Here, we present evidence that variance in neural spiking activity reveals differences in learnability between easy and hard adaptation conditions and across sessions. Furthermore, our study illuminates the limitations in neural changes underlying behavior within a neurofeedback paradigm. Significance StatementVariability in neural activity is a major driver of behavioral variability, though it is unclear how variability is balanced with stable neural activity as new behaviors become more practiced. By using a brain-computer interface methodology, we define a mathematical mapping between neural spiking activity and a behavioral control signal. Through thoughtful manipulation of this mapping, we incite the subjects (rhesus macaques) to learn and adapt neural activity to regain behavioral proficiency. We find that metrics of neural population variability are differentially modulated depending on difficulty of the imposed manipulation. Our exciting results provide important implications for brain-computer interface applications as well as our understanding of learning and adaptation more broadly. Our work represents an important step forwards towards understanding population neural dynamics in this critical component of behavior.

bioengineering↗

bioRxiv2021

Rewarded extinction increases amygdalar connectivity and stabilizes long-term memory traces in the vmPFC

Neurobiological evidence in rodents indicates that threat extinction incorporates reward neurocircuitry. Consequently, incorporating reward associations with an extinction memory may be an effective strategy to persistently attenuate threat responses. Moreover, while there is considerable research on the short-term effects of extinction strategies in humans, the long-term effects of extinction are rarely considered. In a within-subjects fMRI study, we compared counterconditioning (a form of rewarded-extinction) to standard extinction, at recent (24 hours) and remote ([~]1 month) retrieval tests. Relative to standard extinction, counterconditioning diminished 24-hour relapse of arousal and threat expectancy, and reduced activity in brain regions associated with the appraisal and expression of threat (e.g., thalamus, insula, periaqueductal gray). The retrieval of reward-associated extinction memory was accompanied by functional connectivity between the amygdala and the ventral striatum, whereas the retrieval of standard-extinction memories was associated with connectivity between the amygdala and ventromedial prefrontal cortex (vmPFC). One-month later, the retrieval of both standard- and rewarded-extinction was associated with amygdala-vmPFC connectivity. However, only rewarded extinction created a stable memory trace in the vmPFC, identified through overlapping multivariate patterns of fMRI activity from extinction to 24-hour and 1-month retrieval. These findings provide new evidence that reward may generate a more stable and enduring memory trace of attenuated threat in humans. Significance StatementPrevalent treatments for pathological fear and anxiety are based on the principles of Pavlovian extinction. Unfortunately, extinction forms weak memories that only temporarily inhibit the retrieval of threat associations. Thus, to increase the translational relevance of extinction research, it is critical to investigate whether extinction can be augmented to form a more enduring memory, especially after long intervals. Here, we used a multi-day fMRI paradigm in humans to compare the short- and long-term neurobehavioral effects of aversive-to-appetitive counterconditioning, a form of augmented extinction. Our results provide novel evidence that including an appetitive stimulus during extinction can reduce short-term threat relapse and stabilize the memory trace of extinction in the vmPFC, for at least one month after learning.

neuroscience↗

bioRxiv2020

Differential neural plasticity of individual fingers revealed by fMRI neurofeedback

Previous work has shown that fMRI activity patterns associated with individual fingers can be shifted by temporary impairment of the hand. Here, we investigated whether these neural activity patterns could be modulated endogenously and whether any behavioral changes result from this modulation. We used decoded neurofeedback in healthy individuals to encourage participants to shift the neural activity pattern in sensorimotor cortex of the middle finger towards the index finger, and the ring finger towards the little finger. We first mapped the neural activity patterns for all fingers of the right hand in an fMRI pattern localizer session. Then, in three subsequent neurofeedback sessions, participants were rewarded after middle/ring finger presses according to their activity pattern overlap during each trial. A force-sensitive keyboard was used to ensure that participants were not altering their physical finger coordination patterns. We found evidence that participants could learn to shift the activity pattern of the ring finger but not of the middle finger. Increased variability of these activity patterns during the localizer session was associated with the ability of participants to modulate them using neurofeedback. Participants also showed an increased preference for the ring finger but not for the middle finger in a post-neurofeedback motor task. Our results show that neural activity and behaviors associated with the ring finger are more readily modulated than those associated with the middle finger. These results have broader implications for rehabilitation of individual finger movements, which may be limited or enhanced by individual finger plasticity after neurological injury.

neuroscience↗

bioRxiv2019

Neural reinstatement guides context-dependent emotional memory retrieval

Reactivating the memory of a context improves retrieval of information learned in that context. But does context reactivation resolve memory competition between related but conflicting emotional experiences? Here, we asked whether spontaneously retrieved episodic context disambiguates competing memories of fear and safety in the healthy brain and in posttraumatic stress disorder. During fMRI, subjects learned that items from an object category were a threat, and then learned that different items from the same category were safe in a unique context. The next day, subjects viewed new threat ambiguous stimuli from the same category and reported their expectation of threat. Multivoxel pattern analysis (MVPA) was used to identify and decode neural patterns unique to the context of safety learning. We show that in healthy adults the degree of neural reinstatement of the safe context predicted activity to threat ambiguous stimuli in the ventromedial prefrontal cortex (vmPFC) and hippocampus, regions important for contextual modulation of emotional memory retrieval. The degree of context reinstatement also disambiguated subjects feelings of threat versus safety. In contrast, context reinstatement did not resolve emotional memory retrieval in subjects with PTSD, indicating a contextual processing deficit in this group. Finally, multivoxel pattern similarity between safe and threat ambiguous stimuli overlapped in the vmPFC in healthy adults but not in PTSD. These findings reveal how neural reinstatement helps resolve context-dependent memory retrieval between opposing sources of emotional information. Understanding how the human brain separately encodes and retrieves competing memories of related events has broad implications for the study of emotional memory, associative learning, and the neuropathophysiology of affective disorders.

neuroscience↗

bioRxiv2018

Predictability changes what we remember in familiar temporal contexts

The human brain constantly anticipates the future based on memories of the past. Encountering a familiar situation reactivates memory of previous encounters which can trigger a prediction of what comes next to facilitate responsiveness. However, a prediction error can lead to pruning of the offending memory, a process that weakens its representation in the brain and leads to forgetting. Our goal in this study was to evaluate whether memories are spared from pruning in situations that allow for more abstract yet reliable predictions. We hypothesized that when the category, but not the identity, of a new stimulus can be anticipated, this will reduce pruning of existing memories and also reduce encoding of the specifics of new memories. Participants viewed a sequence of objects, some of which reappeared multiple times ("cues"), followed always by novel items. Half of the cues were followed by new items from different (unpredictable) categories, while others were followed by new items from a single (predictable) category. Pattern classification of fMRI data was used to identify category-specific predictions after each cue. Pruning was observed only in unpredictable contexts, while encoding of new items suffered more in predictable contexts. These findings demonstrate that how episodic memories are updated is influenced by the reliability of abstract-level predictions in familiar contexts.

neuroscience↗

bioRxiv2018

Focus on the breath: Brain decoding reveals internal states of attention during meditation

Meditation practices are used to cultivate internally-oriented attention to bodily sensations, which may improve health via cognitive and emotion regulation of bodily signals. However, it remains unclear how meditation impacts internal attention states due to lack of measurement tools that can objectively assess mental states during meditation practice itself, and produce time estimates of internal focus at individual or group levels. To address these measurement gaps, we tested the feasibility of applying multi-voxel pattern analysis (MVPA) to single-subject fMRI data to (1) learn and recognize internal attentional (IA) states relevant for meditation during a directed IA task, and (2) decode or estimate the presence of those IA states during an independent meditation session. Within a mixed sample of experienced meditators and novice controls (N=16), we first used MVPA to develop single-subject brain classifiers for 5 modes of attention during an IA task in which subjects were specifically instructed to engage in one of five states (i.e., meditation-related states: breath attention, mind wandering, and self-referential processing, and control states: attention to feet and sounds). Using standard cross-validation procedures, MVPA classifiers were trained in five of six IA blocks for each subject, and predictive accuracy was tested on the independent sixth block (iterated until all block volumes were tested, N=2160). Across participants, all five IA states were significantly recognized well above chance (>41% vs. 20% chance). At the individual level, IA states were recognized in most participants (87.5%), suggesting that recognition of IA neural patterns may be generalizable for most participants, particularly experienced meditators. Next, for those who showed accurate IA neural patterns, the originally trained classifiers were then applied to a separate meditation run (10-min) to make an inference about the percentage time engaged in each IA state (breath attention, mind wandering, or self-referential processing). Preliminary group-level analyses demonstrated that during meditation practice, participants spent more time attending to breath compared to mind wandering or self-referential processing. This paradigm established the feasibility of using MVPA classifiers to objectively assess mental states during meditation at the participant level, which holds promise for improved measurement of internal attention states cultivated by meditation.

neuroscience↗

bioRxiv2018

A simulation-based approach to improve decoded neurofeedback performance

The neural correlates of specific brain functions such as visual orientation tuning and individual finger movements can be revealed using multivoxel pattern analysis (MVPA) of fMRI data. Neurofeedback based on these distributed patterns of brain activity presents a unique ability for precise neuromodulation. Recent applications of this technique, known as decoded neurofeedback, have manipulated fear conditioning, visual perception, confidence judgements and facial preference. However, there has yet to be an empirical justification of the timing and data processing parameters of these experiments. Suboptimal parameter settings could impact the efficacy of neurofeedback learning and contribute to the 'non-responder' effect. The goal of this study was to investigate how design parameters of decoded neurofeedback experiments affect decoding accuracy and neurofeedback performance. Subjects participated in three fMRI sessions: two 'finger localizer' sessions to identify the fMRI patterns associated with each of the four fingers of the right hand, and one 'finger finding' neurofeedback session to assess neurofeedback performance. Using only the localizer data, we show that real-time decoding can be degraded by poor experiment timing or ROI selection. To set key parameters for the neurofeedback session, we used offline simulations of decoded neurofeedback using data from the localizer sessions to predict neurofeedback performance. We show that these predictions align with real neurofeedback performance at the group level and can also explain individual differences in neurofeedback success. Overall, this work demonstrates the usefulness of offline simulation to improve the success of real-time decoded neurofeedback experiments.

neuroscience↗

bioRxiv2018

More is less: increased processing of unwanted memories facilitates forgetting

The intention to forget can produce long-lasting effects. This ability has been linked to suppression of both rehearsal and retrieval of unwanted memories - processes that are mediated by prefrontal cortex and hippocampus. Here, we describe an alternative account of deliberate forgetting in which the intention to forget is associated with increased engagement with the unwanted information. We used pattern classifiers to decode functional magnetic resonance imaging (fMRI) data from a task in which participants viewed a series of pictures and were instructed to remember or forget each one. Pictures followed by a forget instruction elicited higher levels of processing in ventral temporal cortex compared to those followed by a remember instruction. This boost in processing led to more forgetting, particularly for items that showed moderate (vs. weak or strong) activation. This result is consistent with the non-monotonic plasticity hypothesis, which predicts weakening and forgetting of memories that are moderately activated.

neuroscience↗