Neural mechanisms underlying the hierarchical construction of perceived aesthetic value.

Little is known about how the brain computes the perceived aesthetic value of complex stimuli such as visual art. Here, we used computational methods in combination with functional neuroimaging to provide evidence that the aesthetic value of a visual stimulus is computed in a hierarchical manner via a weighted integration over both low and high level stimulus features contained in early and late visual cortex, extending into parietal and lateral prefrontal cortices. Feature representations in parietal and lateral prefrontal cortex may in turn be utilized to produce an overall aesthetic value in the medial prefrontal cortex. Such brain-wide computations are not only consistent with a feature-based mechanism for value construction, but also resemble computations performed by a deep convolutional neural network. Our findings thus shed light on the existence of a general neurocomputational mechanism for rapidly and flexibly producing value judgements across an array of complex novel stimuli and situations.

Aesthetic preference for art can be predicted from a mixture of low- and high-level visual features.

It is an open question whether preferences for visual art can be lawfully predicted from the basic constituent elements of a visual image. Here, we developed and tested a computational framework to investigate how aesthetic values are formed. We show that it is possible to explain human preferences for a visual art piece based on a mixture of low- and high-level features of the image. Subjective value ratings could be predicted not only within but also across individuals, using a regression model with a common set of interpretable features. We also show that the features predicting aesthetic preference can emerge hierarchically within a deep convolutional neural network trained only for object recognition. Our findings suggest that human preferences for art can be explained at least in part as a systematic integration over the underlying visual features of an image.

Distinct hypothalamic control of same- and opposite-sex mounting behaviour in mice.

Animal behaviours that are superficially similar can express different intents in different contexts, but how this flexibility is achieved at the level of neural circuits is not understood. For example, males of many species can exhibit mounting behaviour towards same- or opposite-sex conspecifics1, but it is unclear whether the intent and neural encoding of these behaviours are similar or different. Here we show that female- and male-directed mounting in male laboratory mice are distinguishable by the presence or absence of ultrasonic vocalizations (USVs)2-4, respectively. These and additional behavioural data suggest that most male-directed mounting is aggressive, although in rare cases it can be sexual. We investigated whether USV+ and USV- mounting use the same or distinct hypothalamic neural substrates. Micro-endoscopic imaging of neurons positive for oestrogen receptor 1 (ESR1) in either the medial preoptic area (MPOA) or the ventromedial hypothalamus, ventrolateral subdivision (VMHvl) revealed distinct patterns of neuronal activity during USV+ and USV- mounting, and the type of mounting could be decoded from population activity in either region. Intersectional optogenetic stimulation of MPOA neurons that express ESR1 and vesicular GABA transporter (VGAT) (MPOAESR1∩VGAT neurons) robustly promoted USV+ mounting, and converted male-directed attack to mounting with USVs. By contrast, stimulation of VMHvl neurons that express ESR1 (VMHvlESR1 neurons) promoted USV- mounting, and inhibited the USVs evoked by female urine. Terminal stimulation experiments suggest that these complementary inhibitory effects are mediated by reciprocal projections between the MPOA and VMHvl. Together, these data identify a hypothalamic subpopulation that is genetically enriched for neurons that causally induce a male reproductive behavioural state, and indicate that reproductive and aggressive states are represented by distinct population codes distributed between MPOAESR1 and VMHvlESR1 neurons, respectively. Thus, similar behaviours that express different internal states are encoded by distinct hypothalamic neuronal populations.