Biology subjects

Kehl, M. S.

Publications and source records attributed to Kehl, M. S..

5 recordsLinked to original sources

bioRxiv2026

Human medial temporal lobe neurons link future reward coding with intertemporal choice and impulsivity

The ability to delay gratification emerges early in life and is linked to long-term health and economic success. Conversely, high impulsivity, marked by a preference for immediate rewards, can be associated with psychiatric disorders. Although processes underlying human delay discounting have been studied at behavioural and macroscopic neural levels, they remain elusive at the single-neuron level. Specifically, it remains unknown how human neurons encode extended reward delays, predict intertemporal choices, and how these processes vary with impulsivity. Here, we record single-neuron activity in the human medial temporal lobe (MTL) to explore decision and delay coding. We identify neurons that predict upcoming decisions in the amygdala and hippocampus. Neurons in the entorhinal cortex and hippocampus encode reward delays, with particularly hippocampal population activity coding prospective temporal periods. Importantly, neuronal activity in impulsive individuals shows diminished prospective temporal coding and predicts decisions only shortly before choices are reported. Our findings reveal how distinct MTL regions contribute to intertemporal decisions and provide insight into the neuronal signatures underlying impulsivity.

neuroscience↗

bioRxiv2026

Sleep ripples drive single-neuron reactivation for human memory consolidation

Sleep transforms fragile experiences into lasting memories, but the neuronal basis of this process in humans has remained elusive. In rodents, hippocampal ripples orchestrate the replay of place cell sequences, establishing a cellular mechanism for consolidation - though with limited generalizability to human memory. In humans, neuroimaging has revealed large-scale offline reactivation, but these coarse signals leave open whether individual neurons are reactivated and how ripples might mediate this process. Here, we bridge this gap by directly recording 1,466 medial temporal lobe (MTL) neurons and intracranial electroencephalography during learning, post-learning wakefulness, and sleep. We show that ripples robustly drive neuronal firing, with sleep ripples eliciting stronger activation than wake ripples. Critically, neurons tuned to items that were later remembered fired more strongly during ripples than those coding for forgotten items, and this memory-linked reactivation was selectively observed during sleep. Finally, ripple-associated neuronal MTL bursts were detectable across widespread cortical activity, pointing to a mechanism for systems-level consolidation. Together, these findings provide the first direct evidence that ripple-driven single-neuron reactivation supports human episodic memory consolidation and reveal why sleep -- compared to wakefulness -- offers a privileged window for stabilizing memories.

neuroscience↗

bioRxiv2025

Semantic Tuning of Single Neurons in the Human Medial Temporal Lobe

The Medial Temporal Lobe (MTL) is key to human cognition, supporting memory, emotional processing, navigation, and semantic coding. Rare direct human MTL recordings revealed concept cells, which were proposed as episodic memory building blocks due to their context- and modality-invariant response. However, there is a long-standing debate whether concept cells encode information in a discrete, all-or-none fashion, or as a graded, continuous function of semantic dimensions. To resolve this, we developed a closed-loop protocol that analyzes neuronal spiking in real time and adaptively presents new stimuli based on semantic similarity to response-eliciting previous ones. We found that human concept cells show graded responses, following semantic tuning curves. Furthermore, the tuning width and steepness of MTL neurons vary, with the hippocampus exhibiting the steepest tuning. Regional analysis of these tuning curves yields region-specific categorical response profiles (e.g., food responses in the amygdala). Finally, we show that at the population level, MTL activity is best captured by continuous semantic vector models, which outperform categorical and network-based metrics. Together, these findings establish that concept cells exhibit semantic tuning curves, providing new mechanistic insights into the neural organization of semantic information in the human brain.

neuroscience↗

bioRxiv2025

Sleep strengthens successor representations of learned sequences

Experiences reshape our internal representations of the world. However, the neural and cognitive dynamics of this process are largely unknown. Here, we investigated how sequence learning reorganizes neural representations and how sleep-dependent consolidation contributes to this transformation. Using high-density electroencephalography and multivariate decoding, we found that learning temporal sequences of visual information led to the incorporation of successor representations during a subsequent perceptual task, despite temporal information being task-irrelevant. Importantly, individuals with better sequence memory performance exhibited stronger successor incorporation during the perceptual task. Representational similarity analyses comparing neural patterns with different layers of a deep neural network revealed a learning-induced shift in representational format, from low-level visual features to higher-level abstract properties. Critically, both the strength and transformation of successor representations correlated with the proportion of slow-wave sleep during a post-learning nap. These findings support the idea that sequence learning induces lasting changes in visual representational geometry and that sleep strengthens these changes, providing mechanistic insights into how the brain updates internal models after exposure to environmental regularities.

neuroscience↗

bioRxiv2024

Decoding movie content from neuronal population activity in the human medial temporal lobe

The human medial temporal lobe (MTL), a region implicated in memory and high-level cognition, contains neurons that respond selectively to stimuli belonging to specific categories, such as individual people, landmarks, or objects. However, these neurons have been largely studied via static, isolated presentations of stimuli. Therefore, it is unclear how neurons in the MTL respond to rich stimuli such as movies, and which dynamical stimulus features can be retrieved from neuronal population spiking activity. We studied single-unit responses from 2286 neurons recorded from the amygdala, hippocampus, entorhinal cortex, and parahippocampal cortex of 29 intracranially implanted patients during the presentation of an 83-minute movie. We found only a few individual neurons that exhibited a classic selective response to semantic features. However, we successfully decoded the presence of characters, settings, and visual transitions from neuronal population activity. The information relevant for decoding varies across regions depending on the feature category, as visual transitions could be decoded from subsets of neurons with selective responses, whereas character and location features relied on distributed representations. Our results demonstrate an approach for reliably decoding movie features in the human MTL, and suggest that the brain uses a population code when representing character and location features.

neuroscience↗