Abstract
The formation of a visual percept and its retention over a short delay entail coordinated neuronal activity generated from cortical circuits. For instance, past research suggests that the number of spikes within a population of neurons can convey information about a visual item, while the variability in firing rate across neurons constrains the perceptual and mnemonic precision of this item. Conventionally, because this rate-coding scheme is often assumed to follow a Poisson process, the exact timing of spikes is considered inconsequential. Here, we test against this widely-accepted assumption by directly recording from the human temporal lobe using microelectrode arrays as participants performed a retro-cue working memory task. On each trial, participants tried to remember and then later recall one out of two previously presented facial stimuli indicated by a retrospective cue. This design allows us to better isolate and then examine the relationship between perceptually and mnemonically evoked neuronal activity. As the stimuli used in the current study were randomly sampled from a computer-generated circular face spectrum, we also modeled participants’ mnemonic precision based on their recall errors across trials. We find that the onset of facial stimuli evokes temporally organized packets of population activity lasting ~150 ms. The structure of these packets is partially stereotypical, with the variation in spike timing across neurons (hence sequence) conveying information about the identity of a face. Similar packets also occur during the retention interval following the retrospective cue. Furthermore, the consistency in spiking sequences between perceptually and mnemonically evoked neuronal activity is predictive of participants’ subsequent recall precision. Together, these results suggest that temporally organized packets of neuronal activity may constitute basic building blocks of cortical coding across visual perception and memory. As these findings cast some doubts on pure rate-based models, our data highlight a novel neuronal mechanism for visual cognition.