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Lillicrap, T. P.

Publications and source records attributed to Lillicrap, T. P..

2 recordsLinked to original sources

Learning from unexpected events in the neocortical microcircuit

Scientists have long conjectured that the neocortex learns the structure of the environment in a predictive, hierarchical manner. According to this conjecture, expected, predictable features are differentiated from unexpected ones by comparing bottom-up and top-down streams of information. It is theorized that the neocortex then changes the representation of incoming stimuli, guided by differences in the responses to expected and unexpected events. In line with this conjecture, different responses to expected and unexpected sensory features have been observed in spiking and somatic calcium events. However, it remains unknown whether these unexpected event signals occur in the distal apical dendrites where many top-down signals are received, and whether these signals govern subsequent changes in the brains stimulus representations. Here, we show that both somata and distal apical dendrites of cortical pyramidal neurons exhibit distinct unexpected event signals that systematically change over days. These findings were obtained by tracking the responses of individual somata and dendritic branches of layer 2/3 and layer 5 pyramidal neurons over multiple days in primary visual cortex of awake, behaving mice using two-photon calcium imaging. Many neurons in both layers 2/3 and 5 showed large differences between their responses to expected and unexpected events. Interestingly, these responses evolved in opposite directions in the somata and distal apical dendrites. These differences between the somata and distal apical dendrites may be important for hierarchical computation, given that these two compartments tend to receive bottom-up and top-down information, respectively.

neuroscience

Rotational dynamics in motor cortex are consistent with a feedback controller

Recent studies hypothesize that motor cortical (MC) dynamics are generated largely through its recurrent connections based on observations that MC activity exhibits rotational structure. However, behavioural and neurophysiological studies suggest that MC behaves like a feedback controller where continuous sensory feedback and interactions with other brain areas contribute substantially to MC processing. We investigated these apparently conflicting theories by building recurrent neural networks that controlled a model arm and received sensory feedback about the limb. Networks were trained to counteract perturbations to the limb and to reach towards spatial targets. Network activities and sensory feedback signals to the network exhibited rotational structure even when the recurrent connections were removed. Furthermore, neural recordings in monkeys performing similar tasks also exhibited rotational structure not only in MC but also in somatosensory cortex. Our results argue that rotational structure may reflect dynamics throughout voluntary motor circuits involved in online control of motor actions. HighlightsO_LINeural networks with sensory feedback generate rotational dynamics during simulated posture and reaching tasks C_LIO_LIRotational dynamics are observed even without recurrent connections in the network C_LIO_LISimilar dynamics are observed not only in motor cortex, but also in somatosensory cortex of non-huma n primates as well as sensory feedback signals C_LIO_LIResults highlight rotational dynamics may reflect internal dynamics, external inputs or any combination of the two. C_LI

neuroscience