Biology subjects

Gilmore, A. W.

Publications and source records attributed to Gilmore, A. W..

9 recordsLinked to original sources

bioRxiv2026

Functional organization underlying superior performance in a memory champion

Memory athletes can achieve superior performance (e.g., memorizing 339 digits in 5 minutes) with extensive daily training, by converting abstract information into vivid scenes, and placing them along a mental path, that is later retraced (Method of Loci). Understanding the brain mechanisms underlying such training-derived mastery would increase our understanding of the brains memory systems and could suggest novel approaches to improving cognition in other domains. As memory athletes use personalized training techniques, it has been challenging to study them with standard group paradigms. Fortunately, precision functional mapping (PFM) enables detailed investigation of individual brains through repeated sampling of resting-state functional connectivity and task fMRI. Here, we precisely mapped the brain organization of a 6-time U.S. Memory Champion (>13 hours fMRI). Relative to controls, the Memory Champions network functional connectivity (FC) was strengthened with the retrosplenial, extrastriate visual, and dorsal frontal cortex (area 55b), as well as with the caudate nucleus. The Memory Champion had modules related to scene and semantic processing not seen in controls, alongside stronger connectivity between the caudate and classical memory networks. During rote memorization, the Champions task fMRI patterns were typical, with the hippocampus active during encoding. This pattern was reversed when he used his Method of Loci technique, with greater hippocampal activity during recall than encoding. Hence, intense practice at converting abstract information into more memorable formats can develop a procedural memory skill that utilizes brain regions typically reserved for navigation, language, social cognition, and associative learning.

neuroscience↗

bioRxiv2025

Repetition-related reductions in neural activity support improved behavior through increases in oscillatory power

Repeatedly processing an object leads to subsequent behavioral improvements in its identification and reductions in associated neural activity, a form of neural processing efficiency that multiple theoretical models have attempted to explain. Using simultaneous fMRI-EEG in humans during object naming, we find that stimulus-driven oscillatory power from high (gamma) to low frequencies (theta) increases and resolves earlier with repetition in task-engaged frontal and occipitotemporal brain regions identified as showing repetition suppression in fMRI. Changes in gamma oscillatory power in these regions were correlated with behavioral priming across subjects and additionally with fMRI repetition suppression in left frontal cortex, providing multimodal support for a novel mixture of the previously proposed Synchrony and Facilitation models.

neuroscience↗

bioRxiv2025

Less is More: Lower Levels of Task-Induced Hippocampal Activation Predict Better Performance on a Separate Verbal Memory Evaluation

Memories that differ in content or duration differ in the extent to which they depend on the hippocampus, and also the part of the hippocampus, posterior (pHPC) or anterior (aHPC), that they implicate. Inter-individual differences in learning-related activation in different hippocampal subregions have been found to predict specific differences in memory abilities. The complexity of these relationships creates a setting that is ripe for theoretically informative investigation, but that can also lead to reports of spurious relationships that do not reflect underlying neurobiological associations. Across-study replication is therefore a critical first step toward understanding how differences in hippocampal activity drive individual differences in memory ability. In the domain of verbal memory, Wig et al. (2008) identified a negative relationship between task-induced activation in pHPC and out-of-scanner verbal memory test performance. Replicating this result in an independent sample of 86 participants, we identified the same negative correlation between pHPC activation during a Lithuanian word learning task and out-of-scanner California Verbal Learning Test (CVLT-II) performance. This replication represents a critical step toward understanding how pHPC supports verbal memory by answering the basic question of whether the relationship can be reliably observed.

neuroscience↗

bioRxiv2024

Atypical scene-selectivity in the retrosplenial complex in individuals with autism spectrum disorder

A small behavioral literature on individuals with autism spectrum disorder (ASD) has shown that they can be impaired when navigating using map-based strategies (i.e., memory-guided navigation), but not during visually guided navigation. Meanwhile, there is neuroimaging evidence in typically developing (TD) individuals demonstrating that the retrosplenial complex (RSC) is part of a memory-guided navigation system, while the occipital place area (OPA) is part of a visually-guided navigation system. A key identifying feature of the RSC and OPA is that they respond significantly more to pictures of places compared to faces or objects - i.e., they demonstrate scene-selectivity. Therefore, we predicted that scene-selectivity would be weaker in the RSC of individuals with ASD compared to a TD control group, while the OPA would not show such a difference between the groups. We used functional MRI to scan groups of ASD individuals and matched TD individuals while they viewed pictures of places and faces and performed a one-back task. As predicted, scene-selectivity was significantly lower in the RSC, but not OPA, in the ASD group compared to the TD group. These results suggest that impaired memory-guided navigation in individuals with ASD may, in part, be due to atypical functioning in the RSC. Lay summaryThe retrosplenial complex (RSC), a cortical region that is part of a neural system that supports our ability to form map-like mental representations of the environment and use them to navigate (i.e., memory-guided navigation), exhibits atypical responses to images of places in individuals with autism spectrum disorder (ASD). These results are a first step towards understanding the neural mechanisms responsible for understudied behavioral impairments in memory-guided navigation in individuals with ASD.

neuroscience↗

bioRxiv2021

A comparison of single and multi-echo processing of fMRI data during overt autobiographical recall

Recent years have seen an increase in the use of multi-echo fMRI designs by cognitive neuroscientists. Acquiring multiple echoes allows one to reduce thermal noise and identify nuisance signal components in BOLD data (Kundu et al., 2012). At the same time, multi-echo acquisitions increase data processing complexity and may incur a cost to the temporal and spatial resolution of the acquired data. Here, we re-examine a multi-echo dataset (Gilmore et al., 2021a) analyzed using multi-echo ICA (ME-ICA) and focused on hippocampal activity during the overly spoken recall of recent and remote autobiographical memories. The goal of the present series of analyses was to determine if ME-ICAs theoretical denoising benefits might lead to a practical difference in the overall conclusions reached. Compared to single echo data, ME-ICA led to qualitatively different conclusions regarding hippocampal contributions to autobiographical recall: whereas the single echo analysis largely failed to reveal hippocampal activity relative to an active baseline, ME-ICA results supported predictions of the Standard Model of Consolidation and a time limited hippocampal involvement (Alvarez and Squire, 1994). These data provide a practical example of the benefits multi-echo denoising in a naturalistic memory paradigm and demonstrate how they can be used to address long-standing theoretical questions.

neuroscience↗

bioRxiv2020

The human hippocampus plays a time-limited role in retrieving autobiographical memories

The necessity of the human hippocampus for remote autobiographical recall remains fiercely debated. The standard model of consolidation predicts a time-limited role for the hippocampus, but the competing multiple trace/trace transformation theories posit indefinite involvement. Lesion evidence remains inconclusive, and the inferences one can draw from fMRI have been limited by reliance on covert (silent) recall, which obscures dynamic, moment-to-moment content of retrieved memories. Here, we capitalized on advances in fMRI denoising to employ overtly spoken recall. Forty participants retrieved recent and remote memories, describing each for approximately two minutes. Details associated with each memory were identified and modeled in the fMRI timeseries data using a variant of the Autobiographical Interview procedure, and activity associated with the recall of recent and remote memories was then compared. Posterior hippocampal regions exhibited temporally-graded activity patterns (recent events > remote events), as did several regions of frontal and parietal cortex. Consistent with predictions of the standard model, recall-related hippocampal activity differed from a non-autobiographical control task only for recent, and not remote, events. Task-based connectivity between posterior hippocampal regions and others associated with mental scene construction also exhibited a temporal gradient, with greater connectivity accompanying the recall of recent events. These findings support predictions of the standard model of consolidation and demonstrate the potential benefits of overt recall in neuroimaging experiments.

neuroscience↗

bioRxiv2019

Brain regions with positive and negative task-evoked responses engage in cooperative rather than competitive interactions

Brain regions displaying task-induced decreases in activity, sometimes referred to as \"Task-Negative\", have been proposed to reflect cortico-cortical competition from regions showing task-induced increases in activity, sometimes referred to as \"Task-Positive\". If these functional networks are competitive, trial-level fMRI BOLD responses across voxels exhibiting Positive and Negative responses should be anti-correlated. Additionally, the correlation between the BOLD response and behavior in Positive and Negative regions should have opposite sign. Here, we test these predictions using trial-to-trial variability in an object naming task. In contrast to the negative coupling proposed by a competition model, we find positive coupling between Positive and Negative regions and show that this coupling aligns with trial-level behavioral correlations. We provide evidence that these cooperative interactions are not due to a non-specific global factor and discuss alternative proposals, such as thalamo-cortical gating.\n\nHighlightsO_LITested competitive interactions among positive and negative task-evoked regions\nC_LIO_LIPositive and negative regions exhibited positive coupling at trial and run levels\nC_LIO_LISmaller competitive effects seen in BOLD-behavior correlations\nC_LIO_LIStrong cooperative effects not due to a non-specific common global factor\nC_LI\n\neTOCCsumitta et al. show that positive and negative BOLD responses do not exhibit cortical competition among corresponding brain regions. Rather, these networks display positive coupling. The spatial distribution of positive coupling aligned with behavioral correlations, suggesting normal, cooperative network interactions.

neuroscience↗

bioRxiv2019

Distinct subdivisions of human medial parietal cortex are recruited differentially for memory recall of places and people

Human medial parietal cortex (MPC) is implicated in multiple cognitive processes including memory recall, visual scene processing and navigation. It is also considered a core component of the default mode network. Here, we combine fMRI data across three independent experiments to demonstrate distinct subdivisions of MPC that are selectively recruited during memory recall of either specific places or specific people. First, distinct regions of MPC were identified on the basis of differential functional connectivity with medial and lateral regions of anterior ventral temporal cortex (VTC). Second, these same medial regions exhibited differential responses to the visual presentation of different stimulus categories, with clear preferences for scenes and faces, respectively. Third, and most critically, these regions were selectively recruited during either place or people memory recall. These subdivisions also showed a striking relationship with ventral and dorsal divisions of the default mode network. Taken together, these data reveal distinct subdivisions within MPC for the recall of places and people and moreover, suggest that the organizing principle defining the medial-lateral axis of VTC is reflected in MPC, but in the context of memory recall.

neuroscience↗

bioRxiv2017

Brain networks, dimensionality, and global signal averaging in resting-state fMRI: Hierarchical network structure results in low-dimensional spatiotemporal dynamics

One of the most controversial practices in resting-state fMRI functional connectivity studies is whether or not to regress out the global average brain signal (GS) during artifact removal. Some groups have argued that it is absolutely essential to regress out the GS in order to fully remove head motion, respiration, and other global imaging artifacts. Others have argued that removing the GS distorts the resulting correlation matrices, qualitatively alters the results of group comparisons, and impairs relationships to behavior. At the core of this argument is the assessment of dimensionality in terms of the number of brain networks with uncorrelated time series. If the dimensionality is high, then the distortions due to GS removal could be effectively negligible. In the current paper, we examine the dimensionality of resting-state fMRI data using principal component analyses (PCA) and network clustering analyses. In two independent datasets (Set 1: N=62, Set 2: N=32), scree plots of the eigenvalues level off at or prior to 10 principal components, with prominent elbows at 3 and 7 components. While network clustering analyses have previously demonstrated that numerous networks can be distinguished with high thresholding of the voxel-wise correlation matrices, lower thresholding reveals a lower-dimensional hierarchical structure, with the first prominent branch at 2 networks (corresponding to the previously described \"task-positive\"/\"task-negative\" distinction) and further stable subdivisions at 4, 7 and 17. Since inter-correlated time series within these larger branches do not cancel to zero when averaged, the hierarchical nature of the correlation structure results in much lower effective dimensionality. Consistent with this, partial correlation analyses revealed that network-specific variance remains present in the GS at each level of the hierarchy, accounting for at least 18-20% of the overall GS variance in each dataset. These results demonstrate that GS regression is expected to remove substantial portions of neurogenic brain signals along with artifacts. We highlight alternative means of controlling for residual global artifacts when not removing the GS.

neuroscience↗