Biology subjects

Gomes, C. A.

Publications and source records attributed to Gomes, C. A..

3 recordsLinked to original sources

bioRxiv2025

It's All In The Journey: Putative Strategies Extracted from Navigation Paths Predict Spatial Memory and Hippocampal Recruitment

Navigation in the real world may rely on a multitude of different strategies with distinct advantages and disadvantages. However, the characterization of spontaneous strategy use during wayfinding and underlying neural correlates are scarce. We explore data across three groups of participants who performed a virtual navigation task: (I) epilepsy patients undergoing invasive electrophysiological recordings of the hippocampus, and two groups who underwent fMRI scanning: (II) young adults at genetic risk for Alzheimers disease (APOE-e4 carriers) and (III) healthy controls. We establish three metrics by which to quantitatively characterize each taken path, with the aim of simultaneously reflecting the putative strategies used by humans to solve the task: 1. straightness of paths; 2. deviation towards the edge of the circular arena; and 3. overlap of individual paths leading to a specific object location, which putatively relate to reliance on allocentric (1) and egocentric reference frames (2 & 3). Extracted metrics were related to performance in the task and to hippocampal activity. We find that strategy use is variable within participant, changes across the experiment, and is adaptive in a group-dependent manner. While hippocampal BOLD activity and theta (gamma) power were generally inversely (positively) related, we found that the recruitment of the hippocampus was both group- and strategy- specific. Our results further our understanding of the heterogeneous and idiosyncratic nature of spatial navigation by revealing, how these behaviors are altered by disease and the subsequent compensatory neural dynamics, as well as the link between mesoscopic and macroscopic neural signals.

neuroscience↗

bioRxiv2025

Predicting individual differences of fear and cognitive learning and extinction

The abilities to acquire new information and to modify previously learned knowledge are critical in an ever-changing world. However, the efficacy of learning is notably variable among individuals, with extinction learning being the epitome of such variability. Abundant studies have identified a core network of brain regions including amygdala, hippocampus, dorsal anterior cingulate cortex (ACC), ventromedial prefrontal cortex (PFC) and, more recently, the cerebellum, as key players in learning and extinction. Yet, the precise interactions within this network and their relationship to individual learning abilities and extinction have remained largely unexplored. In the present study, we examined how functional (FC), effective (EC), and structural (SC) connectivity patterns in the core learning network allow predicting individual differences in the efficacy of learning, extinction, and renewal. Analysing a large dataset of over 500 participants across a multitude of paradigms, our results revealed that FC predicted better acquisition, with a central role of ACC and hippocampus, whereas SC, involving ACC and amygdala, predicted higher levels of extinction learning. EC results suggested a predominantly inhibitory coupling among core learning network nodes, with paradigm-specific EC connectivity patterns predicting learning. Our predictions not only generalised between fear and cognitive predictive learning paradigms but were also successful in predicting learning from task-related FC and simulated data. Together, these results describe the multimodal neural determinants of learning, extinction, and renewal, and may inform individualised interventions for affective disorders based on neural connectivity patterns.

neuroscience↗

bioRxiv2024

Characterizing BOLD activation patterns in the human hippocampus with laminar fMRI

The human hippocampus has been extensively studied at the macroscale using functional magnetic resonance imaging (fMRI) but the underlying microcircuits at the mesoscale (i.e., at the level of layers) are largely uninvestigated in humans. We target two questions fundamental to hippocampal laminar fMRI: How does the venous bias affect the interpretation of hippocampal laminar responses? And can we establish a benchmark laminar fMRI experiment which robustly elicits single-subject hippocampal activation utilizing the most widely applied GRE-BOLD contrast? We comprehensively characterized GRE-BOLD responses as well as T2*, tSNR and physiological noise as a function of cortical depth in individual subfields of the human hippocampus. Our results show that the vascular architecture differs between subfields leading to subfield-specific laminar biases of GRE-BOLD responses. Using an autobiographical memory paradigm, we robustly acquired depth-specific BOLD responses in hippocampal subfields. In the CA1 subregion, our results indicate a more pronounced trisynaptic path input rather than dominant direct inputs from entorhinal cortex during autobiographical memory retrival. Our study provides unique insights into the hippocampus at the mesoscale level, and will help interpreting hippocampal laminar fMRI responses and allow researchers to test mechanistic hypotheses of hippocampal function.

neuroscience↗