Reorganization of Recurrent Layer 5 Corticospinal Networks Following Adult Motor Training

Abstract

Recurrent synaptic connections between neighboring neurons are a key feature of mammalian cortex, accounting for the vast majority of cortical inputs. Although computational models indicate that reorganization of recurrent connectivity is a primary driver of experiencedependent cortical tuning, the true biological features of recurrent network plasticity are not well identified. Indeed, whether rewiring of connections between cortical neurons occurs during behavioral training, as is widely predicted, remains unknown. Here, we probe M1 recurrent circuits following motor training in adult male rats and find robust synaptic reorganization among functionally related layer 5 neurons, resulting in a 2.5-fold increase in recurrent connection probability. This reorganization is specific to the neuronal subpopulation most relevant for executing the trained motor skill, and behavioral performance was impaired following targeted molecular inhibition of this subpopulation. In contrast, recurrent connectivity is unaffected among neighboring layer 5 neurons largely unrelated to the trained behavior. Training-related corticospinal cells also express increased excitability following training. These findings establish the presence of selective modifications in recurrent cortical networks in adulthood following training.Recurrent synaptic connections between neighboring neurons are characteristic of cortical architecture, and modifications to these circuits are thought to underlie in part learning in the adult brain. We now show that there are robust changes in recurrent connections in the rat motor cortex upon training on a novel motor task. Motor training results in a 2.5-fold increase in recurrent connectivity, but only within the neuronal subpopulation most relevant for executing the new motor behavior; recurrent connectivity is unaffected among adjoining neurons that do not execute the trained behavior. These findings demonstrate selective reorganization of recurrent synaptic connections in the adult neocortex following novel motor experience, and illuminate fundamental properties of cortical function and plasticity.

Induction of BDNF Expression in Layer II/III and Layer V Neurons of the Motor Cortex Is Essential for Motor Learning

“…Both motor learning and running wheel exercise might thus shape task-related activity in neuronal ensembles of layer II/III motor cortex, leading to activation of layer V neurons via intracortical connections. In line with this idea, a recent study showed that learning of motor tasks leads to enhanced activity of layer V pyramidal neurons (Biane et al, 2019) and that recurrent projections are involved in remodeling motor circuits. Such recurrent projections are required for motor learning and also target layer II/III neurons.…”

“…This could be important to forward altered modes of cortical activity to striatal MSNs which undergo changes in synaptic turnover and activity in a motor task-specific manner (Sheng et al, 2019). Finally, the subpopulation of BDNF expressing neurons in layer V might also project to the spinal cord or govern corticospinal projection neurons (Biane et al, 2019). Those neurons target spinal cord interneurons and send their collaterals to the striatum (Molyneaux et al, 2007).…”

Progressive Circuit Changes during Learning and Disease

“…Because activation of VIP neurons can powerfully inhibit the activity of other GABAergic neurons (particularly SST neurons), it has been suggested that their primary function is disinhibition (Figure 2B), a conclusion supported by both detailed electrophysiological recordings from in vivo recordings and correlation analysis (Lee et al, 2013;Pfeffer et al, 2013;Pi et al, 2013). Indeed, experimental evidence indicates that increased VIP or suppressed SST activity is required for the increase in visual responses following monocular deprivation in adults (Fu et al, 2015), although the (Audette et al, 2019;Biane et al, 2019). It is unknown how thalamic drive to or feedforward inhibition from PV neurons changes during the early stages of sensory or motor learning (gray).…”

Neural manifold under plasticity in a goal driven learning behaviour

“…We used computational modelling to study the relationship between neural manifold and learning. As motor learning can drive network rewiring in motor cortex on a short timescale [Xu et al, 2009, Biane et al, 2019, Tavor et al, 2019, Ohbayashi, 2020, we wanted to test whether local network rewiring can account for within-manifold, as well as outside-manifold learning.…”