2026

ABSTRACT

 Cochlear implants (CIs) are the most successful neural prostheses, with more than one million users worldwide. They restore hearing by electrically stimulating the auditory nerve. Recently, we demonstrated that CI electrodes can also function as in vivo electrochemical sensors, enabling monitoring of the implant’s microenvironment, such as intracochlear oxygen levels and electrode condition. This sensing approach could provide insight into inflammatory processes and foreign body responses after implantation, adding monitoring capabilities beyond standard impedance measurements without requiring hardware modifications. Here, we investigate the feasibility of long-term electrochemical sensing using standard CI electrodes in awake rats. Deaf, bilaterally implanted rats were trained in a sound lateralization task.

 Electrochemical measurements using combined amperometric and potentiometric sensing methods were performed under anesthetized and awake conditions while monitoring dissolved oxygen levels in real time. Our preliminary results show that intracochlear sensing is feasible in both states, yielding stable and repeatable measurements without affecting auditory performance. These findings demonstrate the feasibility of long-term intracochlear electrochemical sensing using standard CI electrodes, even in awake animals, and represent an important step toward future clinical application in CI patients.  

About Alina and her research

Hosted by Vladislav

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.

About Katharina and her research

Hosted by Aline

ABSTRACT

will come soon

About Yue and her research

ABSTRACT

will come soon

About Philippa and her research

ABSTRACT

will come soon

About Christos and his research

ABSTRACT

will come soon

About Lukas and his research

ABSTRACT

will come soon

About Marsela and her research

ABSTRACT

will come soon

About Richmond and his research

ABSTRACT

will come soon

About Ady and his research