Biology subjects

Franch, M.

Publications and source records attributed to Franch, M..

6 recordsLinked to original sources

bioRxiv2025

The neural basis of emotional generalization in empathy

The essence of empathy is generalization of emotion across persons. Here, we leverage recent theoretical advances in the neuroscience of generalization to help us understand empathy. We measured brain activity in human neurosurgical patients performing two tasks, one focused on identifying their own emotional response and one identifying emotional responses in others. We quantified the representational geometry of local field potential (LFP) high-gamma activity in four regions: the medial temporal lobe, anterior cingulate cortex, orbitofrontal cortex, and insula. We found encoding of both self- and other-emotions in all four regions, but codes for emotion and person are disentangled (that is, factorized) in the insula, but not the other regions. This factorized representation allows for cross-person generalization of emotion in a way that tangled (non-factorized) representations do not. Together, these results support the hypothesis that the insula uniquely contributes to social mirroring processes by which we understand emotions across individuals.

neuroscience↗

bioRxiv2025

Mirror manifolds: partially overlapping neural subspaces for speaking and listening

We utilize internal representations of meaning for two purposes: to understand the words we hear and to generate our own speech. This dual requirement necessitates abstract, modality-agnostic representations. Building on work identifying it as a hub for relational mapping, we hypothesized that the hippocampus supports abstract, cross-person representations, and uses shared semantic geometries to do so. We tested this hypothesis by examining hippocampal activity in a remarkable single-neuron dataset derived from conversational speech. Neurons robustly encoded meanings of both spoken and heard words, and used common geometric embeddings for both, leading to abstract meaning performance. Speaker identity was aligned with meaning via partial subspace alignment, which affords speaker-meaning binding by partitioning meaning by speaker while maintaining cross-speaker generalization. Degrees of subspace rotation varied on a single word level and depended systematically on semantic category. Together, these findings indicate how geometric principles allow for abstract cross-personal meanings while preserving binding to speaker identity.

neuroscience↗

bioRxiv2025

Human neuronal firing is modulated by the frequency of local field potential oscillations

Neural oscillations play a critical role in shaping neuronal firing patterns. While phase-locked neuronal firing ("phase tuning") has been extensively studied in animal models and human invasive recordings, much less is known about whether neurons show preferential firing at specific oscillatory frequencies, termed frequency tuning. Here, we employ human intracranial recordings across several brain regions including hippocampus, entorhinal cortex, anterior and posterior cingulate cortex, and orbitofrontal cortex to test the hypothesis that neurons exhibit frequency-specific firing. We analyzed 357 single units recorded simultaneously with local field potentials in 19 neurosurgical patients during awake resting. We estimated the instantaneous frequency of the LFP using adaptive spectral decomposition and assessed frequency tuning of each neuron while controlling for changes in firing rate unrelated to frequency changes. We found 27% neurons exhibited increased or decreased firing within specific frequencies, most commonly within the low-theta range (<10 Hz). Neurons exhibiting frequency tuning were distinct from those displaying phase tuning, and both types of tuning were observed across multiple brain regions with no anatomical preference. Together, our results demonstrate that the instantaneous frequency of neural oscillations modulates neuronal firing which may serve as an additional mechanism for information processing in the human brain, opening new avenues for frequency-targeted neural stimulation.

neuroscience↗

bioRxiv2025

Complementary roles for hippocampus and anterior cingulate in composing continuous choice

Naturalistic, goal directed behavior often requires continuous actions directed at dynamically changing goals. In this context, the closest analogue to choice is a strategic reweighting of multiple goal-specific control policies in response to shifting environmental pressures. To understand the algorithmic and neural bases of choice in continuous contexts, we examined behavior and brain activity in humans performing a continuous prey-pursuit task. Using a newly developed control-theoretic decomposition of behavior, we find pursuit strategies are well described by a meta-controller dictating a mixture of lower-level controllers, each linked to specific pursuit goals. We find that hippocampal neurons encode the policy blending variable in a value-invariant manner and monitor policy switches after they occur. ACC neurons encode policy switches in a value-dependent manner, with value related modulation detectable several hundred ms before the switch, alongside a ramping increase in mean firing rate toward the switch. Meanwhile, OFC activity is consistent with an encoding of the current value structure of the task, rather than policy switching. Together these results are consistent with a tripartite functional division in which hippocampus serves as a controller over behavior, ACC serves as a meta-controller, and OFC provides a value context signal. Overall, our results shed light onto the complex processes associated with choice during naturalistic continuous interactive behavior.

neuroscience↗

bioRxiv2025

Independent Continuous Tracking of Multiple Agents in the Human Hippocampus

The pursuit of fleeing prey is a core element of many species behavioral repertoires. It poses the difficult problem of continuous tracking of multiple agents, including both self and others. To understand how this tracking is implemented neurally, we examined responses of hippocampal neurons while humans performed a joystick-controlled continuous prey-pursuit task involving two simultaneously fleeing prey (and, in some cases, a predator) in a virtual open field. We found neural maps encoding the positions of all the agents. All maps were multiplexed in single neurons and were disambiguated by the use of the population coding principle of semi-orthogonal subspaces, which can facilitate cross-agent generalization. Some neurons, more common in the posterior hippocampus, had narrow tuning functions reminiscent of place cells, lower firing rates, and high information per spike; others, which were found in both anterior and posterior hippocampus, had broad tuning functions, higher firing rates, and less information per spike. Semi-orthogonalization was selectively associated with the broadly tuned neurons. These results suggest an answer to the problem of navigational individuation, that is, how mapping codes can distinguish different agents, and establish the neuronavigational foundations of pursuit.

neuroscience↗

bioRxiv2025

A vectorial code for semantics in human hippocampus

As we listen to speech, our brains track the meanings of the words we hear. Recent successes of large language models suggest that distributed population geometry can capture rich semantic relationships between words. Motivated by this idea, we hypothesized that semantic information in the brain may likewise be expressed in distributed patterns of activity across neurons, rather than in the activity of neurons narrowly tuned to a specific word. We recorded responses of hundreds of neurons in the human hippocampus while participants listened to narrative speech. We find encoding of contextual word meaning in the simultaneous activity of neurons whose individual selectivities span multiple unrelated semantic categories. Decoding and population geometry analyses revealed distinct neural coding principles for low-versus high-frequency words, likely reflecting the greater polysemy of common words. Similar to embedding vectors in semantic language models, distance between neural population responses correlates with semantic distance; however, this effect was only observed in contextual embedding models (GPT-2 and BERT), suggesting that the semantic distance effect depends critically on contextualization. Consistent with this, we find that neural population activity supports a multidimensional semantic subspace that aligns most closely with the contextual structure captured by GPT-2. Moreover, for semantically similar words, even contextual embedders showed an inverse correlation between semantic and neural distances; we attribute this pattern to the noise-mitigating benefits of contrastive coding. Ultimately, these results provide a neurocomputational account for understanding how neural populations track word meaning.

neuroscience↗