Biology subjects

Ranganath, C.

Publications and source records attributed to Ranganath, C..

At least 19 recordsLinked to original sources

bioRxiv2026

Post-Learning Reactivation of Memories for Naturalistic Continuous Experiences

Memories are not static records of the past; rather, the act of remembering can change how an event is recalled. Intriguingly, several studies also suggest that memories may be reactivated during rest. However, reactivation has largely been studied for spatial tasks and discrete stimuli, and we know little about whether spontaneous reactivation occurs for long timescale naturalistic events and how reactivation affects retention. Using fMRI, we show that neural activity patterns in the hippocampus and the Default Mode Network during encoding of narrative events were spontaneously reactivated during rest. Contrary to predictions, reactivation did not strengthen recall of movie details, and instead exploratory analyses suggested that reactivation in the hippocampus was associated with more gist-like recall one week later. These findings support the idea that memories for complex events may be spontaneously reactivated, but they suggest that rather than simply strengthening episodic memories, reactivation might help transform them.

neuroscience↗

bioRxiv2026

Self-guided search in immersive VR reveals active hierarchical planning

Despite the ubiquitous nature of visual search in our daily lives, our knowledge of the underlying mechanisms is almost entirely derived from studies using simple, synthetic stimuli briefly flashed on a computer monitor. In real life, however, visual search occurs in three-dimensional environments over much longer timescales and involves the dynamic coordination of attention, memory, and action planning, generating novel predictions that cannot be tested with traditional approaches. Here, we examined how self-guided visual search unfolds under naturalistic conditions that extend over space and time. We asked participants (N=80) to find specific objects (e.g., a green lamp, an orange shelf) in an immersive, visually rich virtual reality environment using range-limited teleportation (2 m steps). Consistent with our hypotheses, we found that self-guided search engaged a hierarchical information-seeking policy characterized at each stage by recurring plan-and-execute cycles paired with subgoal-specific attentional priorities. Subgoal priorities progressed from wayfinding to identification of clusters of target-similar objects, and then to specific target features. These search priorities progressively narrowed the search space through coordinated eye, head, and body movements that recurred throughout the task. We conclude that naturalistic search is hierarchical, built from sequential subgoals with shifting attentional priorities that single-level tasks cannot capture. Moreover, immersive VR with eye-head-body tracking dissociates motor planning from execution moments and reveals how looking content shifts with each task subgoal while the person moves through space, something desktop tasks cannot capture.

animal behavior and cognition↗

bioRxiv2026

Causal network structure predicts memory organization and neural reinstatement across events

Endel Tulving proposed that episodic memory is organized by spatiotemporal relationships, and current theories center the role of time and space in organizing memory. However, these theories are supported by paradigms that eliminate other forms of relationships, like causality. Here, we used fMRI to reveal the organization of neural representations that support episodic memory with a paradigm that decoupled time and causal relationships. Participants were scanned while watching and recalling a TV show featuring five temporally interleaved storylines. Behaviorally, the order of recalled events was best predicted by the strongest cause-effect relationship relative to temporal, spatial, or semantic associations. Neural similarity across different events in regions of the default mode network (DMN) reflected causal structure, and DMN patterns at event boundaries specifically reactivated prior, causally related events, suggesting causality allows us to stitch together related events across temporal gaps. Additionally, causal network distance between successive events predicted the strength of DMN pattern changes across event boundaries, suggesting causality also predicts stronger representational switching between unrelated events. Together, these findings suggest that the DMN supports the construction of the complex causal networks that play a central role in organizing how we understand and remember events.

neuroscience↗

bioRxiv2025

Fronto-Hippocampal Synchronization in Rapid Spatial Learning in Humans

Achieving goals in real-life situations--from fetching a glass of water to landing a dream job--often requires planning based on experience and executing a sequence of actions. Neurophysiological research in animal models has indicated that the orbitofrontal cortex (OFC) mediates relationships between memory, actions, and outcomes and the hippocampus and other medial temporal lobe (MTL) regions are known to be critical for rapid learning, but little is known about how these areas interact to support rapid learning and retrieval of goal-directed action sequences in humans. Here, we leverage a rare opportunity to investigate human OFC gamma oscillations and examine the coordination between the OFC and MTL during a continuous multi-step task that requires applying recently acquired experience to guide behavior. We used multisite intracranial electroencephalography (iEEG) recordings while participants searched for a hidden goal in an animated game to study neural activity in both brain areas during goal-directed behavior. Hippocampal ripples--brief high-frequency oscillations reflecting synchronized neuronal firing--are known to support memory consolidation during sleep, but their role during active memory retrieval and updating remains unclear. We found that OFC gamma activity was modulated by both memory demands and ripples in the hippocampus and adjacent structures. Notably, ripple-coupled OFC gamma during exploration was associated with subsequent task performance. We propose that hippocampal ripples mark a narrow window, supporting hippocampal-cortical communication required for successful goal encoding for future behaviors.

neuroscience↗

bioRxiv2025

Not a global map, but a local hash: grid cells decorrelate the representation of position and scramble long-range distance information

Grid cells in the medial entorhinal cortex construct an intriguing multiperiodic representation of space whose properties have been the subject of much theoretical speculation. Here we combine modeling with analyses of neural population data from mice and rats to show that the grid cell representation is ideally set up to decorrelate and assign easily distinguishable labels to inputs, thus acting as a pattern separation device, much like a hash function in computing rather than a global map or metric. The multiple modules of the grid cell system allow the threshold for pattern separation to be controlled. We also extend these arguments to show how grid cells can perform pattern separation in abstract and higher-dimensional spaces. This pattern separation ability may serve to enhance episodic memory in the hippocampal formation by reducing interference between similar patterns.

neuroscience↗

bioRxiv2025

Natural language processing captures memory content associated with shared neural patterns at encoding

People can experience the same event yet form distinct memories shaped by individual interpretations. Prior research shows that multivariate activity patterns in the Default Mode Network (DMN) are correlated across individuals during shared experiences, suggesting a role in representing high-level event features. However, it remains unclear whether these shared neural patterns reflect similarity in subsequent memory content. Here, we examined whether memory similarity correlates with intersubject spatial patterns in the DMN. Using topic modeling, we transformed verbal recall into vectors of latent topics to quantify memory similarity across participants. Twenty-four individuals watched and recounted two cartoon movies during fMRI scanning. We found that greater similarity in recalled content was associated with stronger shared activation patterns at encoding, particularly in the posterior medial cortex. These findings highlight the utility of natural language processing tools in linking memory representations to brain activity and underscore the DMNs role in encoding and interpreting complex event features.

neuroscience↗

bioRxiv2024

Recurrent Inhibitory Dynamics in the Entorhinal Cortex Support Pattern Separation

The entorhinal cortex (EC) provides the major input to the hippocampus (HPC). Numerous computational models on the EC propose that its grid cells serve as a spatial metric, supporting path integration and efficient generalization. However, little is known about how these cells could contribute to episodic memory, which emphasizes episode-specific representations that align with pattern separation. Taking into consideration anatomical specifications of EC inputs to the HPC and computational principles underlying the EC-HPC memory system, we argue that EC layer IIa (EC2a) supports pattern separation and EC layer IIb/III (EC2b/3) supports generalization. Utilizing recurrent inhibition and the nature of single EC2a neurons binding converging inputs from the neocortex (i.e., conjunctive coding), we built a biologically-based neural network model of the EC-HPC system for episodic memory. By examining how EC2a transformed its cortical inputs and output them to the trisynaptic pathway (EC2a - Dentate Gyrus - CA3 - CA1), we found that instead of systematically generalizing across similar inputs, recurrent inhibition and conjunctive coding in EC2a neurons support strong pattern separation and increase mnemonic discrimination. Furthermore, lesioning EC2a neurons in the model resembled memory impairments found in people with Alzheimers Disease, suggesting an intertwined relationship between memory and the majority of pure grid cells in the EC. On the other hand, the topographically organized monosynaptic pathway (EC2b/3 - CA1) is computationally more suitable for efficient factorization and generalization. This model provides novel anatomically-based predictions regarding the computational roles of EC cells in pattern separation and generalization, which together form a critical computational framework for both episodic memory and spatial navigation.

neuroscience↗

bioRxiv2024

Seeing the Future: Anticipatory Eye Gaze as a Marker of Memory

Human memory is typically studied by direct questioning, and the recollection of events is investigated through verbal reports. Thus, current research confounds memory per-se with its report. Critically, the ability to investigate memory retrieval in populations with deficient verbal ability is limited. Here, using the MEGA (Memory Episode Gaze Anticipation) paradigm, we show that monitoring anticipatory gaze using eye tracking can quantify memory retrieval without verbal report. Upon repeated viewing of movie clips, eye gaze patterns anticipating salient events can quantify their memory traces seconds before these events appear on the screen. A series of five experiments with a total of 145 participants using either tailor-made animations or naturalistic movies consistently reveal that accumulated gaze proximity to the event can index memory. Machine learning-based classification can identify whether a given viewing is associated with memory for the event based on single-trial data of gaze features. Detailed comparison to verbal reports establishes that anticipatory gaze marks recollection of associative memory about the event, whereas pupil dilation captures familiarity. Finally, anticipatory gaze reveals beneficial effects of sleep on memory retrieval without verbal report, illustrating its broad applicability across cognitive research and clinical domains.

neuroscience↗

bioRxiv2023

Curiosity as an amplifier of reward-related feedback processing

Successful learning depends on various factors such as depth of processing, motivation, or curiosity about information. A strong drive to learn something or the expectation of receiving a reward can be crucial to enhance learning. However, the influence of curiosity on the processing of new information and its similarity with reward processing is not well understood. This study examined whether states of curiosity influence specific event-related-potentials (ERPs) associated with reward processing and whether these ERPs are related with later memory benefits. In an initial screening phase, participants indicated their curiosity and confidence in prior knowledge about answers to various trivia questions. In a subsequent study phase, we targeted different time windows related to reward processing during the presentation of trivia answers containing the Reward-Positivity (RewP; 250 - 350 ms), the P3 (250 - 500 ms), and the Late-Positive-Potential (LPP; 600 - 1000 ms). In a following surprise memory test, we found that participants recalled more high- than low-curiosity answers. The RewP, P3 and LPP showed greater positive mean amplitudes for high compared to low curiosity, reflecting increased reward processing. In addition, we found that the RewP and the P3 showed more positive mean amplitudes for later recalled compared to later forgotten answers, but curiosity did not modulate this encoding-related results. These findings support the view that the satisfaction of curiosity resembles reward processing, indicated by event-related-potentials.

neuroscience↗

bioRxiv2023

Proximity to Boundaries Reveals Spatial Context Representation in Human Hippocampal CA1

Recollection of real-world events is often accompanied by a sense of being in the place where the event transpired. Convergent evidence suggests the hippocampus plays a key role in supporting episodic memory by associating information with the time and place it was originally encountered. This representation is reinstated during memory retrieval. However, little is known about the roles of different subfields of the human hippocampus in this process. Research in humans and non-human animal models have suggested that spatial environmental boundaries have a powerful influence on spatial and episodic memory, as well as hippocampal representations of contexts and events. Here, we used high-resolution fMRI to investigate how boundaries influence hippocampal activity patterns during the recollection of objects encountered in different spatial contexts. During the encoding phase, participants viewed objects once in a naturalistic virtual reality task, in which they passively explored two rooms in one of two houses. Following the encoding phase, participants were scanned while they recollected items in the absence of any spatial contextual information. Our behavioral results demonstrated that spatial context memory was enhanced for objects encountered near a boundary. Activity patterns in CA1 carried information about the spatial context associated with each of these boundary items. Exploratory analyses revealed that memory for the room in which each object was studied was correlated with the fidelity of retrieved spatial context representations in anterior parahippocampal cortex and subiculum. Our results highlight the privileged role of boundaries in CA1 and suggest more generally a close relationship between memory for spatial contexts and representations in the hippocampus and parahippocampal region.

neuroscience↗

bioRxiv2022

Memory out of context: Spacing effects and decontextualization in a computational model of the medial temporal lobe

Some neural representations change across multiple timescales. Here we argue that modeling this "drift" could help explain the spacing effect (the long-term benefit of distributed learning), whereby differences between stored and current temporal context activity patterns produce greater error-driven learning. We trained a neurobiologically realistic model of the entorhinal cortex and hippocampus to learn paired associates alongside temporal context vectors that drifted between learning episodes and/or before final retention intervals. In line with spacing effects, greater drift led to better model recall after longer retention intervals. Dissecting model mechanisms revealed that greater drift increased error-driven learning, strengthened weights in slower-drifting temporal context neurons (temporal abstraction), and improved direct cue-target associations (decontextualization). Intriguingly, these results suggest that decontextualization -- generally ascribed only to the neocortex -- can occur within the hippocampus itself. Altogether, our findings provide a mechanistic formalization for established learning concepts such as spacing effects and errors during learning.

neuroscience↗

bioRxiv2022

Integration of event experiences to build relational knowledge in the human brain

We investigated how the human brain integrates experiences of specific events to build general knowledge about typical event structure. We examined an episodic area important for temporal relations, anterior-lateral entorhinal cortex (alEC), and a semantic area important for action concepts, middle temporal gyrus (MTG). Participants underwent fMRI while watching sequences of novel events and recalling their temporal relations over two sessions one week apart. Across different contexts, the roles of these events could either be consistent, or conflict; integrative representations should weaken in the conflicting condition. We found integrative representations that emerged quickly in alEC, and only subsequently in MTG, which showed a significant change across sessions. Thus, alEC is important in building integrative representations early in learning and may be a gateway to semantic knowledge in MTG. We suggest that both episodic and semantic systems participate in integrating new information when it is aligned with their content specializations.

neuroscience↗

bioRxiv2022

A Role for the Fornix in Temporal Sequence Memory

Converging evidence from studies of human and nonhuman animals suggests that the hippocampus contributes to sequence learning by using temporal context to bind sequentially occurring items. The fornix is a white matter pathway containing the major input and output pathways of the hippocampus, including projections from medial septum, and to diencephalon, striatum, and prefrontal cortex. If the fornix meaningfully contributes to hippocampal function, then individual differences in fornix microstructure might predict sequence memory. Here, we tested this prediction by performing tractography in 51 healthy adults who had undertaken a sequence memory task. Microstructure properties of the fornix were compared with those of tracts connecting medial temporal lobe regions, but not predominantly the hippocampus: the Parahippocampal Cingulum bundle (PHC) (conveying retrosplenial projections to parahippocampal cortex) and the Inferior Longitudinal Fasciculus (ILF) (conveying occipital projections to perirhinal cortex). Using principal components analysis, we combined Diffusion Tensor Imaging and Neurite Orientation Dispersion and Density Imaging measures obtained from multi-shell diffusion MRI into two informative indices, the first (PC1) capturing axonal packing/myelin, the second (PC2) capturing microstructural complexity. We found a significant correlation between fornix PC2 and implicit reaction-time indices of sequence memory, indicating that greater fornix microstructural complexity is associated with better sequence memory. No such relationship was found with measures from the PHC and ILF. This study highlights the importance of the fornix in aiding memory for objects within a temporal context, potentially reflecting a role in mediating network communication within an extended hippocampal system.

neuroscience↗

bioRxiv2021

Correcting the Hebbian Mistake: Toward a Fully Error-Driven Hippocampus

The hippocampus plays a critical role in the rapid learning of new episodic memories. Many computational models propose that the hippocampus is an autoassociator that relies on Hebbian learning (i.e., "cells that fire together, wire together"). However, Hebbian learning is computationally suboptimal as it modifies weights unnecessarily beyond what is actually needed to achieve effective retrieval, causing more interference and resulting in a lower learning capacity. Our previous computational models have utilized a powerful, biologically plausible form of error-driven learning in hippocampal CA1 and entorhinal cortex (EC) (functioning as a sparse autoencoder) by contrasting local activity states at different phases in the theta cycle. Based on specific neural data and a recent abstract computational model, we propose a new model called Theremin (Total Hippocampal ERror MINimization) that extends error-driven learning to area CA3 -- the mnemonic heart of the hippocampal system. In the model, CA3 responds to the EC monosynaptic input prior to the EC disynaptic input through dentate gyrus (DG), giving rise to a temporal difference between these two activation states, which drives error-driven learning in the EC[->]CA3 and CA3{leftrightarrow}CA3 projections. In effect, DG serves as a teacher to CA3, correcting its patterns into more pattern-separated ones, thereby reducing interference. Results showed that Theremin, compared with our original model, has significantly increased capacity and learning speed. The model makes several novel predictions that can be tested in future studies. Author SummaryExemplified by the famous case of patient H.M. (Henry Molaison) who had his hippocampus surgically removed, the hippocampus is critical for learning and remembering about everyday events -- what is typically called "episodic memory." The dominant theory for how it learns is based on the intuitive principle stated by Donald Hebb in 1949, that neurons that "fire together, wire together" -- when two neurons are active at the same time, the strength of their connection increases. We show in this paper that using a different form of learning based on correcting errors (error-driven learning) results in significantly improved episodic memory function in a biologically-based computational model of the hippocampus. This model also provides a significantly better account of behavioral data on the testing effect, where learning by testing with partial cues is better than learning with the complete set of information.

neuroscience↗

bioRxiv2021

Relationships between individual differences in dual process and electrophysiological signatures of familiarity and recollection during retrieval

Our everyday memories can vary in terms of accuracy and phenomenology. According to one theoretical account, these differences hinge on whether the memories contain information about both an item itself as well as associated details (remember) versus those that are devoid of these associated contextual details (familiar). This distinction has been supported by computational modeling of behavior, studies in patients, and neuroimaging work including differences both in electrophysiological and functional magnetic resonance imaging. At present, however, little evidence has emerged to suggest that neurophysiological measures track individual differences in estimates of recollection and familiarity. Here, we conducted electrophysiological recordings of brain activity during a recognition memory task designed to differentiate between behavioral indices of recollection and familiarity. Non-parametric cluster-based permutation analyses revealed associations between electrophysiological signatures of familiarity and recollection with their respective behavioral estimates. These results support the idea that recollection and familiarity are distinct phenomena and is the first, to our knowledge, to identify distinct electrophysiological signatures that track individual differences in these processes.

neuroscience↗

bioRxiv2021

Goal-oriented predictive representations in the human hippocampus

Recent work in cognitive and systems neuroscience has suggested that the hippocampus might support planning, imagination, and navigation by forming "cognitive maps" that capture the structure of physical spaces, tasks, and situations. Critically, navigation involves planning within a context and disambiguating similar contexts to reach a goal. We examined hippocampal activity patterns in humans during a goal-directed navigation task to examine how contextual and goal information are incorporated in the construction and execution of navigational plans. Results demonstrate that, during planning, the hippocampus carries a context-specific representation of a future goal. Importantly, this effect could not be explained by stimulus or spatial information alone. During navigation, we observed reinstatement of activity patterns in the hippocampus ahead of participants required actions, which was strongest for behaviorally relevant points in the sequence. These results suggest that, rather than simply representing overlapping associations, hippocampal activity patterns are powerfully shaped by context and goals.

neuroscience↗

bioRxiv2021

Contextual expectations shape cortical reinstatement of sensory representations

When making a turn at a familiar intersection, we know what items and landmarks will come into view. These perceptual expectations, or predictions, come from our knowledge of the context, however its unclear how memory and perceptual systems interact to support the prediction and reactivation of sensory details in cortex. To address this, human participants learned the spatial layout of animals positioned in a cross maze. During fMRI, participants navigated between animals to reach a target, and in the process saw a predictable sequence of five animal images. Critically, to isolate activity patterns related to item predictions, rather than bottom-up inputs, one quarter of trials ended early, with a blank screen presented instead. Using multivariate pattern similarity analysis, we reveal that activity patterns in early visual cortex, posterior medial regions, and the posterior hippocampus showed greater similarity when seeing the same item compared to different items. Further, item effects in posterior hippocampus were specific to the sequence context. Critically, activity patterns associated with seeing an item in visual cortex and posterior medial cortex, were also related to activity patterns when an item was expected, but omitted, suggesting sequence predictions were reinstated in these regions. Finally, multivariate connectivity showed that patterns in the posterior hippocampus at one position in the sequence were related to patterns in early visual cortex and posterior medial cortex at a later position. Together, our results support the idea that hippocampal representations facilitate sensory processing by modulating visual cortical activity in anticipation of expected items.

neuroscience↗

bioRxiv2021

Connectivity between the hippocampus and default mode network during the relief, but not elicitation, of curiositysupports curiosity-enhanced memory enhancements

Consistent with the idea that curiosity enhances information seeking, it has been shown that activity within both the dopaminergic circuit and hippocampus supports curiosity-enhanced learning. However, the role of whole-brain mechanisms involved in cognitive control (fronto-parietal network; FPN) and memory integration (default mode network; DMN) that might underpin curiosity states and their effects on memory remain elusive. We hypothesised that the FPN and DMN should distinguish between high- and low-curiosity conditions and be recruited more heavily for later remembered information associated with high-curiosity. Here, we used functional magnetic resonance imaging whilst participants completed a trivia paradigm, in which we presented trivia questions associated with high- and low-curiosity, followed by the associated answer. After a short delay, we tested memory for trivia answers. We adopted a network-based parcellation of the brain into subnetworks of the FPN and DMN to examine how neural activity within, and functional connectivity between, each subnetwork predicts curiosity-enhanced memory. Across elicitation and relief of curiosity, we found focal recruitment of FPNA and widespread recruitment of DMN subnetworks in support of curiosity and curiosity-enhanced memory. Most importantly, during the elicitation of curiosity, functional subcortical connectivity and across cortical networks, but not subcortical-cortical coupling, correlated with curiosity-enhanced memory. However, during the relief of curiosity, coupling between subcortical regions and DMNA emerged in support of curiosity-enhanced memory. Taken together, our results provide the first evidence about how neuromodulatory mechanisms via the hippocampal-dopaminergic circuit trigger states of curiosity and thereby communicate to higher-order cortical regions to facilitate curiosity-enhanced memory. Significant statementDoes neural activity within, and functional connectivity between, the dopaminergic-hippocampal network, fronto-parietal network (FPN), and default mode network (DMN) underpin curiosity states and their effects on memory? Here, we show how the dopaminergic system together with the hippocampus interact specifically with subnetwork DMNA potentially reflecting how subcortical regions support the enhancement of memory intergration of semantic information associated with curiosity. As DMNA (the core DMN subnetwork) was also functionally coupled with the whole DMN network and the semantic control network (FPNA), these findings provide a plausible neuromodulatory mechanism through which hippocampal-dopaminergic input triggers curiosity and then communicates to higher-order brain regions via DMNA to facilitate curiosity-enhanced memory.

neuroscience↗