Distributed Temporal Coding of Visual Memory Categories in Human Hippocampal Neurons Revealed by an Interpretable Decoding Model

The hippocampus is crucial for forming new episodic memories. While its role in encoding spatial and temporal information (where and when) is well understood, how it encodes objects (what) remains unclear due to the high dimensionality of object space. Rather than encoding each object separately, the hippocampus may encode object categories to reduce complexity. Here, an experimental-modeling approach to investigate how the hippocampus encodes visual memory categories in humans is developed. Spikes are recorded from hippocampal CA3 and CA1 neurons in 24 epilepsy patients performing a delayed match-to-sample task involving five image categories. An interpretable memory decoding model is employed to decode memory categories from hippocampal spiking activity and identify the spatio-temporal characteristics of hippocampal encoding. Using this model, the optimal temporal resolutions for decoding each visual memory category per neuron are estimated. Results indicate that visual memory categories can be decoded from hippocampal spike patterns, supporting the presence of category-specific coding. Hippocampal neuron ensembles encode memory categories in a distributed manner, akin to a population code, while individual neurons use a temporal code. Additionally, CA3 and CA1 neurons exhibit similar and redundant memory category information, likely due to strong and diffuse feedforward synaptic connections from CA3 to CA1 regions.