A long-range, recurrent neuronal network linking the emotion regions with the somatic motor cortex

Recurrent neural networks (RNNs) are designed to learn sequential patterns in silico, but it is unclear whether and how an RNN forms in the native networks of the mammalian brain. Here, we report an innate RNN, which is formed by the unidirectional connections from three basic units: input units arriving from emotion regions, a hidden unit in the medial prefrontal cortex (mPFC), and output units located at the somatic motor cortex (sMO). Specifically, the neurons from basal lateral amygdala (BLA) and the insular cortex (IC) project to the mPFC motor-cortex-projecting (MP) neurons. These MP neurons form a local self-feedback loop and target major projecting neurons of the sMO. Within the sMO, the neurons in the infragranular layers receive stronger input than the neurons in supragranular layers. Finally, we show in vivo evidence that the communications from the emotion regions to the sMO are abolished when MP neurons are chemogenetically silenced. [Display omitted] •mPFC MP neurons consist of L2/3 CC neurons and L5 PT-CStr neurons•MP neurons form a local, monosynaptic self-feedback loop in the mPFC•mPFC MP neurons are necessary for communication from emotion regions to the sMO•MP-PT-CStr neurons are the functional subtype in contacting emotion regions with the sMO Wang and Sun show that the unidirectional, recurrent neuronal network, linking with the emotion regions and the somatic motor cortex, is formed by three basic units: input units arriving from the emotion regions, a hidden unit composed of self-feedback connected medial prefrontal cortex (mPFC) neurons, and output units located at the somatic motor cortex (sMO).