@article {68918,
	title = {Nonlinear manifolds underlie neural population activity during behaviour.},
	journal = {bioRxiv},
	year = {2023},
	month = {2023 Jul 21},
	abstract = {<p>There is rich variety in the activity of single neurons recorded during behaviour. Yet, these diverse single neuron responses can be well described by relatively few patterns of neural co-modulation. The study of such low-dimensional structure of neural population activity has provided important insights into how the brain generates behaviour. Virtually all of these studies have used linear dimensionality reduction techniques to estimate these population-wide co-modulation patterns, constraining them to a flat "neural manifold". Here, we hypothesised that since neurons have nonlinear responses and make thousands of distributed and recurrent connections that likely amplify such nonlinearities, neural manifolds should be intrinsically nonlinear. Combining neural population recordings from monkey motor cortex, mouse motor cortex, mouse striatum, and human motor cortex, we show that: 1) neural manifolds are intrinsically nonlinear; 2) the degree of their nonlinearity varies across architecturally distinct brain regions; and 3) manifold nonlinearity becomes more evident during complex tasks that require more varied activity patterns. Simulations using recurrent neural network models confirmed the proposed relationship between circuit connectivity and manifold nonlinearity, including the differences across architecturally distinct regions. Thus, neural manifolds underlying the generation of behaviour are inherently nonlinear, and properly accounting for such nonlinearities will be critical as neuroscientists move towards studying numerous brain regions involved in increasingly complex and naturalistic behaviours.</p>
},
	doi = {10.1101/2023.07.18.549575},
	url = {https://doi.org/10.1101/2023.07.18.549575},
	author = {Fortunato, C{\'a}tia and Bennasar-V{\'a}zquez, Jorge and Park, Junchol and Chang, Joanna C and Miller, Lee E and Dudman, Joshua T and Perich, Matthew G and Gallego, Juan A}
}
@article {69075,
	title = {Preserved neural dynamics across animals performing similar behaviour.},
	journal = {Nature},
	year = {2023},
	month = {2023 Nov 08},
	abstract = {<p>Animals of the same species exhibit similar behaviours that are advantageously adapted to their body and environment. These behaviours are shaped at the species level by selection pressures over evolutionary timescales. Yet, it remains unclear how these common behavioural adaptations emerge from the idiosyncratic neural circuitry of each individual. The overall organization of neural circuits is preserved across individuals because of their common evolutionarily specified developmental programme. Such organization at the circuit level may constrain neural activity, leading to low-dimensional latent dynamics across the neural population. Accordingly, here we suggested that the shared circuit-level constraints within a species would lead to suitably preserved latent dynamics across individuals. We analysed recordings of neural populations from monkey and mouse motor cortex to demonstrate that neural dynamics in individuals from the same species are surprisingly preserved when they perform similar behaviour. Neural population dynamics were also preserved when animals consciously planned future movements without overt behaviour and enabled the decoding of planned and ongoing movement across different individuals. Furthermore, we found that preserved neural dynamics extend beyond cortical regions to the dorsal striatum, an evolutionarily older structure. Finally, we used neural network models to demonstrate that behavioural similarity is necessary but not sufficient for this preservation. We posit that these emergent dynamics result from evolutionary constraints on brain development and thus reflect fundamental properties of the neural basis of behaviour.</p>
},
	issn = {1476-4687},
	doi = {10.1038/s41586-023-06714-0},
	author = {Safaie, Mostafa and Chang, Joanna C and Park, Junchol and Miller, Lee E and Dudman, Joshua T and Perich, Matthew G and Gallego, Juan A}
}
