An identified ensemble within a neocortical circuit encodes essential information for genetically-enhanced visual shape learning.

Advanced cognitive tasks are encoded in distributed neocortical circuits that span multiple forebrain areas. Nonetheless, synaptic plasticity and neural network theories hypothesize that essential information for performing these tasks is encoded in specific ensembles within these circuits. Relatively simpler subcortical areas contain specific ensembles that encode learning, suggesting that neocortical circuits contain such ensembles. Previously, using localized gene transfer of a constitutively active protein kinase C (PKC), we established that a genetically-modified circuit in rat postrhinal cortex, part of the hippocampal formation, can encode some essential information for performing specific visual shape discriminations. However, these studies did not identify any specific neurons that encode learning; the entire circuit might be required. Here, we show that both learning and recall require fast neurotransmitter release from an identified ensemble within this circuit, the transduced neurons; we blocked fast release from these neurons by coexpressing a Synaptotagmin I siRNA with the constitutively active PKC. During learning or recall, specific signaling pathways required for learning are activated in this ensemble; during learning, calcium/calmodulin-dependent protein kinase II, MAP kinase, and CREB are activated; and, during recall, dendritic protein synthesis and CREB are activated. Using activity-dependent gene imaging, we showed that during learning, activity in this ensemble is required to recruit and activate the circuit. Further, after learning, during image presentation, blocking activity in this ensemble reduces accuracy, even though most of the rest of the circuit is activated. Thus, an identified ensemble within a neocortical circuit encodes essential information for performing an advanced cognitive task.

CaMKII, MAPK, and CREB are coactivated in identified neurons in a neocortical circuit required for performing visual shape discriminations.

Current theories postulate that the essential information for specific cognitive tasks is widely dispersed in multiple forebrain areas. Nonetheless, synaptic plasticity and neural network theories hypothesize that activation of specific signaling pathways, in specific neurons, modifies synaptic strengths, thereby encoding essential information for performance in localized circuits. Consistent with these latter theories, we have shown that gene transfer of a constitutively active protein kinase C into several hundred glutamatergic and GABAergic neurons in rat postrhinal cortex enhances choice accuracy in visual shape discriminations, and the genetically-modified circuit encodes some of the essential information for performance. However, little is known about the role of specific signaling pathways required for learning, in specific neurons within a critical circuit. Here we show that three learning-associated signaling pathways are coactivated in the transduced neurons during both learning and performance. After gene transfer, but before learning a new discrimination, the calcium/calmodulin-dependent protein kinase (CaMKII), MAP kinase, and CREB pathways were inactive. During learning, these three pathways were coactivated in the transduced neurons. During later performance of the discrimination, CaMKII activity declined, but MAP kinase and CREB activity persisted. Because the transduced neurons are part of a circuit that encodes essential information for performance, activation of these learning-associated signaling pathways, in these identified neurons, is likely important for both learning and performance.

Characteristic and intermingled neocortical circuits encode different visual object discriminations.

Synaptic plasticity and neural network theories hypothesize that the essential information for advanced cognitive tasks is encoded in specific circuits and neurons within distributed neocortical networks. However, these circuits are incompletely characterized, and we do not know if a specific discrimination is encoded in characteristic circuits among multiple animals. Here, we determined the spatial distribution of active neurons for a circuit that encodes some of the essential information for a cognitive task. We genetically activated protein kinase C pathways in several hundred spatially-grouped glutamatergic and GABAergic neurons in rat postrhinal cortex, a multimodal associative area that is part of a distributed circuit that encodes visual object discriminations. We previously established that this intervention enhances accuracy for specific discriminations. Moreover, the genetically-modified, local circuit in POR cortex encodes some of the essential information, and this local circuit is preferentially activated during performance, as shown by activity-dependent gene imaging. Here, we mapped the positions of the active neurons, which revealed that two image sets are encoded in characteristic and different circuits. While characteristic circuits are known to process sensory information, in sensory areas, this is the first demonstration that characteristic circuits encode specific discriminations, in a multimodal associative area. Further, the circuits encoding the two image sets are intermingled, and likely overlapping, enabling efficient encoding. Consistent with reconsolidation theories, intermingled and overlapping encoding could facilitate formation of associations between related discriminations, including visually similar discriminations or discriminations learned at the same time or place.