Non-linear dimensionality reduction on extracellular waveforms reveals cell type diversity in premotor cortex

Cortical circuits are thought to contain a large number of cell types that coordinate to produce behavior. Current in vivo methods rely on clustering of specified features of extracellular waveforms to identify putative cell types, but these capture only a small amount of variation. Here, we develop a new method (WaveMAP) that combines non-linear dimensionality reduction with graph clustering to identify putative cell types. We apply WaveMAP to extracellular waveforms recorded from dorsal premotor cortex of macaque monkeys performing a decision-making task. Using WaveMAP, we robustly establish eight waveform clusters and show that these clusters recapitulate previously identified narrow- and broad-spiking types while revealing previously unknown diversity within these subtypes. The eight clusters exhibited distinct laminar distributions, characteristic firing rate patterns, and decision-related dynamics. Such insights were weaker when using feature-based approaches. WaveMAP therefore provides a more nuanced understanding of the dynamics of cell types in cortical circuits.https://elifesciences.org/articles/67490Published versio

Cultural differences in the use of acoustic cues for musical emotion experience.

Does music penetrate cultural differences with its ability to evoke emotion? The ragas of Hindustani music are specific sequences of notes that elicit various emotions: happy, romantic, devotion, calm, angry, longing, tension and sad. They can be presented in two modes, alaap and gat, which differ in rhythm, but match in tonality. Participants from Indian and Non-Indian cultures (N = 144 and 112, respectively) rated twenty-four pieces of Hindustani ragas on eight dimensions of emotion, in a free response task. Of the 192 between-group comparisons, ratings differed in only 9% of the instances, showing universality across multiple musical emotions. Robust regression analyses and machine learning methods revealed tonality best explained emotion ratings for Indian participants whereas rhythm was the primary predictor in Non-Indian listeners. Our results provide compelling evidence for universality in emotions in the auditory domain in the realm of musical emotion, driven by distinct acoustic features that depend on listeners' cultural backgrounds