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Doeller, C. F.

Publications and source records attributed to Doeller, C. F..

47 records · Page 3Linked to original sources

Structuring time: The hippocampus constructs sequence memories that generalize temporal relations across experiences

The hippocampal-entorhinal region supports memory for episodic details, such as temporal relations of sequential events, and mnemonic constructions combining experiences for inferential reasoning. However, it is unclear whether hippocampal event memories reflect temporal relations derived from mnemonic constructions, event order, or elapsing time, and whether these sequence representations generalize temporal relations across similar sequences. Here, participants mnemonically constructed times of events from multiple sequences using infrequent cues and their experience of passing time. After learning, event representations in the anterior hippocampus reflected temporal relations based on constructed times. Temporal relations were generalized across sequences, revealing distinct representational formats for events from the same or different sequences. Structural knowledge about time patterns, abstracted from different sequences, biased the construction of specific event times. These findings demonstrate that mnemonic construction and the generalization of relational knowledge combine in the hippocampus, consistent with the simulation of scenarios from episodic details and structural knowledge.

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MR-based camera-less eye tracking using deep neural networks

Viewing behavior provides a window into many central aspects of human cognition and health, and it is an important variable of interest or confound in many fMRI studies. To make eye tracking freely and widely available for MRI research, we developed DeepMReye: a convolutional neural network that decodes gaze position from the MR-signal of the eyeballs. It performs camera-less eye tracking at sub-imaging temporal resolution in held-out participants with little training data and across a broad range of scanning protocols. Critically, it works even in existing datasets and when the eyes are closed. Decoded eye movements explain network-wide brain activity also in regions not associated with oculomotor function. This work emphasizes the importance of eye tracking for the interpretation of fMRI results and provides an open-source software solution that is widely applicable in research and clinical settings.

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An immersive first-person navigation task for abstract knowledge acquisition

Advances in virtual reality (VR) technology have greatly benefited spatial navigation research. By presenting space in a controlled manner, changing aspects of the environment one at a time or manipulating the gain from different sensory inputs, the mechanisms underlying spatial behaviour can be investigated. In parallel, a growing body of evidence suggests that the processes involved in spatial navigation extend to non-spatial domains. Here, we leverage VR technology advances to test whether participants can navigate abstract knowledge. We designed a two-dimensional quantity space - presented using a head-mounted display - to test if participants can navigate abstract knowledge using a first-person perspective navigation paradigm. To investigate the effect of physical movement, we divided participants into two groups: one walking and rotating on a motion platform, the other group using a gamepad to move through the abstract space. We found that both groups learned to navigate using a first-person perspective and formed accurate representations of the abstract space. Interestingly, navigation in the quantity space resembled behavioural patterns observed in navigation studies using environments with natural visuospatial cues. Notably, both groups demonstrated similar patterns of learning. Taken together, these results imply that both self-movement and remote exploration can be used to learn the relational mapping between abstract stimuli.

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DeepInsight: A general framework for interpreting wide-band neural activity

AO_SCPLOWBSTRACTC_SCPLOWRapid progress in technologies such as calcium imaging and electrophysiology has seen a dramatic increase in the size and extent of neural recordings. Even so, interpretation of this data often depends on manual operations and requires considerable knowledge about the nature of the representation. Decoding provides a means to infer the information content of such recordings but typically requires highly processed data and prior knowledge of the encoding scheme. Here, we developed a deep-learning-framework able to decode sensory and behavioural variables directly from wide-band neural data. The network requires little user input and generalizes across stimuli, behaviours, brain regions, and recording techniques. Once trained, it can be analysed to determine elements of the neural code that are informative about a given variable. We validated this approach using data from rodent auditory cortex and hippocampus, identifying a novel representation of head direction encoded by putative CA1 interneurons.

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Behavior-dependent directional tuning in the human visual-navigation network

The brain derives cognitive maps from sensory experience that guide memory formation and behavior. Despite extensive efforts, it still remains unclear how the underlying population activity relates to active behavior and memory performance. To examine these processes, we here combined 7T-fMRI with a kernel-based encoding model of virtual navigation to map world-centered directional tuning across the human cortex. First, we present an in-depth analysis of directional tuning in visual, retrosplenial, parahippocampal and medial temporal cortices. Second, we show that tuning strength, width and topology of this directional code during memory-guided navigation depend on successful encoding of the environment. Finally, we show that participants locomotory state influences this tuning in sensory and mnemonic regions such as the hippocampus. We demonstrate a direct link between neural population tuning and human cognition and show that high-level memory processing interacts with network-wide environmental coding in the service of behavior.

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The role of hippocampal spatial representations in contextualization and generalization of fear

Using contextual information to predict aversive events is a critical ability that protects from generalizing fear responses to safe contexts. Animal models have demonstrated the importance of spatial context representations within the hippocampal formation in contextualization of fear learning. The ventromedial prefrontal cortex (vmPFC) is known to play an important role in safety learning, possibly also through the incorporation of context information. However, if contextual representations are related to context-dependent expression of fear memory in humans remains unclear. Twenty-one healthy participants underwent functional MRI combined with a cue-context conditioning paradigm within a self-navigated virtual reality environment. The environment included two buildings (Threat and Safe context), which had distinct features outside but were identical inside. Within each context, participants saw two cues (CS+, CS-). The CS+ was consistently (100% reinforcement rate) paired with an electric shock in the Threat context, but never in the Safe context. The CS- was never paired with a shock. We found robust differential skin conductance responses (SCRs; CS+ > CS-) in the Threat context, but also within the Safe context, indicating fear generalization. Within the Safe context, vmPFC responses to the CS+ were larger than those in the Threat context. We furthermore found environment-specific representantions for the two contexts in the training paradigm (i.e., before conditioning took place) in the hippocampus to be related to fear expression and generalization. Namely, participants with a weak context representation (z-score < 1.65) showed stronger fear generalization compared to participants with a strong context representation (z-score > 1.65). Thus, a low neural representation of spatial context may explain overgeneralization of memory to safe contexts. In addition, our findings demonstrate that context-dependent regulation of fear expression engages ventromedial prefrontal pathways suggesting this involves a similar mechanism that is known to be involved in retrieval of extinction memory.

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Structuring Time in Human Lateral Entorhinal Cortex

Remembering event sequences is central to episodic memory and thought to be supported by the hippocampal-entorhinal region. We previously demonstrated that the hippocampus maps spatial and temporal distances between events encountered along a fixed route through a virtual city (Deuker et al., 2016), but the content of entorhinal mnemonic representations remains unclear. Here, we demonstrate that, after learning, multi-voxel representations in the anterior-lateral entorhinal cortex (alEC) specifically reflect the temporal event structure. Holistic representations of the temporal structure related to memory recall and the temporal event structure could be reconstructed from entorhinal multi-voxel patterns. Our findings demonstrate representations of temporal structure in the alEC in line with temporal information carried by population signals in the lateral entorhinal cortex of navigating rodents and activations of its human homologue during temporal memory retrieval. Our results provide novel evidence for the role of the human alEC in representing time for episodic memory.

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Deforming the metric of cognitive maps distorts memory

Environmental boundaries anchor cognitive maps that support memory. However, trapezoidal boundary geometry distorts the regular firing patterns of entorhinal grid cells proposedly providing a metric for cognitive maps. Here, we test the impact of trapezoidal boundary geometry on human spatial memory using immersive virtual reality. Consistent with reduced regularity of grid patterns in rodents and a grid-cell model based on the eigenvectors of the successor representation, human positional memory was degraded in a trapezoid compared to a square environment; an effect particularly pronounced in the trapezoids narrow part. Congruent with spatial frequency changes of eigenvector grid patterns, distance estimates between remembered positions were persistently biased; revealing distorted memory maps that explained behavior better than the objective maps. Our findings demonstrate that environmental geometry affects human spatial memory similarly to rodent grid cell activity -- thus strengthening the putative link between grid cells and behavior along with their cognitive functions beyond navigation.

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Theta phase coordinated memory reactivation reoccurs in a slow-oscillatory rhythm during NREM sleep

It has been proposed that sleeps contribution to memory consolidation is to reactivate prior encoded information. To elucidate the neural mechanisms carrying reactivation-related mnemonic information, we investigated whether content-specific memory signatures associated with memory reactivation during wakefulness reoccur during subsequent sleep. We show that theta oscillations orchestrate the reactivation of memories, irrespective of the physiological state. Reactivation patterns during sleep autonomously re-emerged at a rate of 1 Hz, indicating a coordination by slow oscillatory activity.

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Optimal decision making using grid cells under spatial uncertainty

Minimizing spatial uncertainty is essential for navigation, but the neural mechanisms remain elusive. Here we combine predictions of a simulated grid cell system with behavioural and fMRI measures in humans during virtual navigation. First, we showed that polarising cues produce anisotropy in motion parallax. Secondly, we simulated entorhinal grid cells in an environment with anisotropic information and found that self-location is decoded best when grid-patterns are aligned with the axis of greatest information. Thirdly, when exposing human participants to polarised virtual reality environments, we found that navigation performance is anisotropic, in line with the use of parallax. Eye movements showed that participants preferentially viewed polarising cues, which correlated with navigation performance. Finally, using fMRI we found that the orientation of grid-cell-like representations in entorhinal cortex anchored to the environmental axis of greatest parallax information, orthogonal to the polarisation axis. In sum, we demonstrate a crucial role of the entorhinal grid system in reducing uncertainty in representations of self-location and find evidence for adaptive spatial computations underlying entorhinal representations in service of optimal navigation.

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Saccades phase-locked to alpha oscillations in the occipital and medial temporal lobe enhance memory encoding

Efficient sampling of visual information requires a coordination of eye movements and ongoing brain oscillations. Using intracranial and MEG recordings, we show that saccades are locked to the phase of visual alpha oscillations, and that this coordination supports mnemonic encoding of visual scenes. Furthermore, parahippocampal and retrosplenial cortex involvement in this coordination reflects effective vision-to-memory mapping, highlighting the importance of neural oscillations for the interaction between visual and memory domains.

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