Katharina Bracher: Unbiased Detection of Neural Sequences
| When |
Jun 09, 2026
from 05:15 PM to 06:00 PM |
|---|---|
| Where | Bernstein Center Freiburg, Hansastr. 9a, 79104 Freiburg, Lecture Hall |
| Contact Name | Martina Bacher |
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ABSTRACT
The hippocampus plays a central role in learning and memory, yet the mechanisms by which neuronal activity reorganizes during learning remain incompletely understood. A key aspect of hippocampal dynamics are neuronal activity sequences, which have been extensively studied in relation to specific, memory-dependent behaviors. However, focusing only on predefined behavioral correlates constrains such analyses to activity directly linked to the observed behavior, potentially missing other functionally relevant sequence motifs. Recent evidence further suggests that additional, recurring sequence motifs may exist beyond those tied to specific behavioral interpretations. To overcome this limitation, we propose an unbiased method for detecting repeating sequence motifs directly from spiking activity, independent of behavioral variables. We validate the approach using simulated sequences generated from a parametric statistical model and identify a regime under which the method reliably recovers the underlying ground-truth sequence motifs.
This model further enables systematic exploration of how variability in firing statistics shapes detectable sequence patterns, for example showing that high spiking probabilities are required to reproduce correlation structures observed in hippocampal data. Applying the method to hippocampal CA1 recordings from rats performing either a memory guided or a non-memory control task, we find that both animals exhibit new motifs after task completion, indicating experience-dependent reorganization of sequence structure. Crucially, only in the memory-condition are the new motifs re-expressed at similar frequencies during subsequent rest, consistent with consolidation-related reactivation of task-relevant patterns.
Our approach provides new means to study how neural activity is restructured by learning, specifically how memory processes relate to the expression of novel sequences in the hippocampus, including those involving neurons with no or unclear spatial tuning.