Biology subjects

Hassani, S. A.

Publications and source records attributed to Hassani, S. A..

2 recordsLinked to original sources

bioRxiv2018

Asymmetric effective connectivity between primate anterior cingulate and lateral prefrontal cortex revealed by electrical microstimulation.

The anterior cingulate cortex (ACC) and lateral prefrontal cortex (IPFC) 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 IPFC, or with a preponderance of ACC projections synapsing onto inhibitory neurons in the IPFC. Here, we tested effective ACC-IPFC 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 IPFC 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 [->] IPFC resulted, on average, in shorter-latency EFPs than IPFC [->] 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 IPFC 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.

neuroscience↗

bioRxiv2018

Feature Specific Prediction Errors and Surprise across Macaque Fronto-Striatal Circuits during Attention and Learning

Prediction errors signal unexpected outcomes indicating that expectations need to be adjusted. For adjusting expectations efficiently prediction errors need to be associated with the precise features that gave rise to the unexpected outcome. For many visual tasks this credit assignment proceeds in a multidimensional feature space that makes it ambiguous which object defining features are relevant. Here, we report of a potential solution by showing that neurons in all areas of the medial and lateral fronto-striatal networks encode prediction errors that are specific to separate features of attended multidimensional stimuli, with the most ubiquitous prediction error occurring for the reward relevant features. These feature specific prediction error signals (1) are different from a non-specific prediction error signal, (2) arise earliest in the anterior cingulate cortex and later in lateral prefrontal cortex, caudate and ventral striatum, and (3) contribute to feature-based stimulus selection after learning. These findings provide strong evidence for a widely-distributed feature-based eligibility trace that can be used to update synaptic weights for improved feature-based attention.\n\nHighlightsO_LINeural reward prediction errors carry information for updating feature-based attention in all areas of the fronto-striatal network.\nC_LIO_LIFeature specific neural prediction errors emerge earliest in anterior cingulate cortex and later in lateral prefrontal cortex.\nC_LIO_LIVentral striatum neurons encode feature specific surprise strongest for the goal-relevant feature.\nC_LIO_LINeurons encoding feature-specific prediction errors contribute to attentional selection after learning.\nC_LI

neuroscience↗