Fronto-Striatal Circuits Optimize Feature-based Attention and Learning

Our new publication (Oemisch et al. (2018) Feature Specific Prediction Errors and Surprise across Macaque Fronto-Striatal Circuits during Attention and Learning) provides the first 4-brain-area survey of how prediction error information in the anterior cingulate – ventral striatum and lateral prefrontal – caudate fronto-striatal loops relate to feature-based attention and learning. We found prediction errors that encode the specific stimulus feature that was reward relevant. This coding took place with stimuli having multiple feature dimensions. Reporting that neurons track the specific reward relevant feature suggests an attractive solution of credit assignment through a distributed feature-specific eligibility trace enabling ‘goal-directed’ synaptic plasticity changes across the entire fronto-striatal network.

Related News

Effective Connectivity Shows Asymmetries in Resonance and Latencies between Medial and Lateral Prefrontal Cortex Connections

The lab has a first article published about the strength, latency and resonance patterns of connections between the anterior cingulate cortex and lateral prefrontal cortex of the macaque. This work was led by postdoc Veronica Nacher and is published in Brain Structure and Function. The paper identifies a novel electrical microstimulation protocol that can be […]

Theta and Beta Frequency

Theta and beta frequency range coherence between anterior cingulate cortex and frontal eye field indexes the successful preparation for anti-saccades and maintenance of working memory content – with larger ACC to FEF direction of granger causal information flow! These important findings is now published in Nature Communications by Sahand Babapoor-Farrokhran and Stefan Everling with contributions […]

The phase of firing of fronto-striatal neurons encodes learning variables

Our new paper shows that neurons in the striatum, anterior cingulate and prefrontal cortex encode learning variables in the phase of firing. We outline a powerful regression based analysis pipeline that revealed spiking activity of neurons relative to the phase of beta oscillations carries significant learning information during reversal learning. The paper can be downloaded […]