Imagine you’re at a museum, staring at a painting. As you examine the intricate details and colors, your brain is hard at work. A recent study used mice to better understand how visual stimuli are processed in the brain. The researchers measured something called Neurophysiological Differentiation (ND), which tells us how many different activity states the neural population goes through when perceiving an image. This metric gives us insight into how meaningful or subjectively perceived the visual stimuli are. By recording the activity of thousands of neurons in different areas of the mouse brain, the researchers discovered that naturalistic images lead to higher ND than artificial ones. This suggests that our brains respond differently to real-world scenes compared to artificially generated ones. Interestingly, when the mice were trained to detect changes in images, their brains showed even higher ND during successful detection trials. This indicates that the cells involved in perceiving the stimulus are more active when we successfully process visual changes. These findings not only deepen our understanding of perception but also highlight the potential role of specific cell populations in subjective perception. If you’re curious to learn more about how mouse brains decode visual information, check out the full research article!

Neurophysiological differentiation (ND), a measure of the number of distinct activity states that a neural population visits over a time interval, has been used as a correlate of meaningfulness or subjective perception of visual stimuli. ND has largely been studied in non-invasive human whole-brain recordings where spatial resolution is limited. However, it is likely that perception is supported by discrete neuronal populations rather than the whole brain. Therefore, here we use Neuropixels recordings from the mouse brain to characterize the ND metric across a wide range of temporal scales, within neural populations recorded at single-cell resolution in localized regions. Using the spiking activity of thousands of simultaneously recorded neurons spanning 6 visual cortical areas and the visual thalamus, we show that the ND of stimulus-evoked activity of the entire visual cortex is higher for naturalistic stimuli relative to artificial ones. This finding holds in most individual areas throughout the visual hierarchy. Moreover, for animals performing an image change detection task, ND of the entire visual cortex (though not individual areas) is higher for successful detection compared to failed trials, consistent with the assumed perception of the stimulus. Together, these results suggest that ND computed on cellular-level neural recordings is a useful tool highlighting cell populations that may be involved in subjective perception.

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