To adjust expectations efficiently, prediction errors need to be associated with the precise features that gave rise to the unexpected outcome, but this credit assignment may be problematic if stimuli differ on multiple dimensions and it is ambiguous which feature dimension caused the outcome. Here, we report a potential solution: neurons in four recorded areas of the anterior fronto-striatal networks encode prediction errors that are specific to feature values of different dimensions of attended multidimensional stimuli. The most ubiquitous prediction error occurred for the reward-relevant dimension. Feature-specific prediction error signals a) emerge on average shortly after non-specific prediction error signals, b) arise earliest in the anterior cingulate cortex and later in dorsolateral prefrontal cortex, caudate and ventral striatum, and c) contribute to feature-based stimulus selection after learning. Thus, a widely-distributed feature-specific eligibility trace may be used to update synaptic weights for improved feature-based attention.

Cognitive flexibility depends on a fast neural learning mechanism for enhancing momentary relevant over irrelevant information. A possible neural mechanism realizing this enhancement uses fast spiking interneurons (FSIs) in the striatum to train striatal projection neurons to gate relevant and suppress distracting cortical inputs. We found support for such a mechanism in nonhuman primates during the flexible adjustment of visual attention in a reversal learning task. FSI activity was modulated by visual attention cues during feature-based learning. One FSI subpopulation showed stronger activation during learning, while another FSI subpopulation showed response suppression after learning, which could indicate a disinhibitory effect on the local circuit. Additionally, FSIs that showed response suppression to learned attention cues were activated by salient distractor events, suggesting they contribute to suppressing bottom-up distraction. These findings suggest that striatal fast spiking interneurons play an important role when cues are learned that redirect attention away from previously relevant to newly relevant visual information. This cue-specific activity was independent of motor-related activity and thus tracked specifically the learning of reward predictive visual features.

The anterior cingulate cortex (ACC) and lateral prefrontal cortex (lPFC) of the non-human primate show neural firing correlations and synchronize at theta and beta frequencies during the monitoring and shifting of attention. These functional interactions might be based on synaptic connectivity that is equally efficacious in both directions, but it might be that there are systematic asymmetries in connectivity consistent with reports of more effective inhibition within the ACC than lPFC, or with a preponderance of ACC projections synapsing onto inhibitory neurons in the lPFC. Here, we tested effective ACC-lPFC connectivity in awake monkeys and report systematic asymmetries in the temporal patterning and latencies of effective connectivity as measured using electrical microstimulation. We found that ACC stimulation triggered evoked fields (EFPs) were more likely to be multiphasic in the lPFC than in the reverse direction, with a large proportion of connections showing 2-4 inflection points resembling resonance in the 20-30 Hz beta frequency range. Stimulation of ACC → lPFC resulted, on average, in shorter-latency EFPs than lPFC → ACC. Overall, latencies and connectivity strength varied more than two-fold depending on the precise anterior-to-posterior location of the connections. These findings reveal systematic asymmetries in effective connectivity between ACC and lPFC in the awake non-human primate and document the spatial and temporal patchiness of effective synaptic connections. We speculate that measuring effective connectivity profiles will be essential for understanding how local synaptic efficacy and synaptic connectivity translates into functional neuronal interactions to support adaptive behaviors.

The anterior cingulate cortex (ACC) and lateral prefrontal cortex (lPFC) of the non-human primate show neural firing correlations and synchronize at theta and beta frequencies during the monitoring and shifting of attention. These functional interactions might be based on synaptic connectivity that is equally efficacious in both directions, but it might be that there are systematic asymmetries in connectivity consistent with reports of more effective inhibition within the ACC than lPFC, or with a preponderance of ACC projections synapsing onto inhibitory neurons in the lPFC. Here, we tested effective ACC-lPFC connectivity in awake monkeys and report systematic asymmetries in the temporal patterning and latencies of effective connectivity as measured using electrical microstimulation. We found that ACC stimulation triggered evoked fields (EFPs) were more likely to be multiphasic in the lPFC than in the reverse direction, with a large proportion of connections showing 2-4 inflection points resembling resonance in the 20-30 Hz beta frequency range. Stimulation of ACC → lPFC resulted, on average, in shorter-latency EFPs than lPFC → ACC. Overall, latencies and connectivity strength varied more than two-fold depending on the precise anterior-to-posterior location of the connections. These findings reveal systematic asymmetries in effective connectivity between ACC and lPFC in the awake non-human primate and document the spatial and temporal patchiness of effective synaptic connections. We speculate that measuring effective connectivity profiles will be essential for understanding how local synaptic efficacy and synaptic connectivity translates into functional neuronal interactions to support adaptive behaviors.

Cognitive flexibility depends on a fast neural learning mechanism for enhancing momentary relevant over irrelevant information. A possible neural mechanism realizing this enhancement uses fast-spiking interneurons (FSIs) in the striatum to train striatal projection neurons to gate relevant and suppress distracting cortical inputs. We found support for such a mechanism in nonhuman primates during the flexible adjustment of visual attention. FSIs gated visual attention cues during feature-based learning. One FSI population showed stronger inhibition during learning, while another FSI subpopulation showed weaker inhibition after learning signifying post-learning disinhibition.Additionally, a smaller neural subpopulation increased activity when salient distractor events were successfully suppressed. These findings highlight that fast behavioral learning of feature relevance is accompanied by fast neural learning of cell-type specific corticostriatal gating.Adaptive behavior depends on neural mechanisms that learn which objects in our environment have value and are relevant to achieve our goals. Knowing the value of objects is essential to not