scholarly journals Interneuron specific gamma synchronization indexes cue uncertainty and prediction errors in lateral prefrontal and anterior cingulate cortex

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Kianoush Banaie Boroujeni ◽  
Paul Tiesinga ◽  
Thilo Womelsdorf
Keyword(s):  
Anterior Cingulate Cortex ◽  
Cingulate Cortex ◽  
Suppressive Effect ◽  
Anterior Cingulate ◽  
Inhibitory Interneurons ◽  
Prediction Errors ◽  
Gamma Band Activity ◽  
Winner Take All ◽  
High Degree ◽  
Goal Directed Behavior

Inhibitory interneurons are believed to realize critical gating functions in cortical circuits, but it has been difficult to ascertain the content of gated information for well characterized interneurons in primate cortex. Here, we address this question by characterizing putative interneurons in primate prefrontal and anterior cingulate cortex while monkeys engaged in attention demanding reversal learning. We find that subclasses of narrow spiking neurons have a relative suppressive effect on the local circuit indicating they are inhibitory interneurons. One of these interneuron subclasses showed prominent firing rate modulations and (35-45 Hz) gamma synchronous spiking during periods of uncertainty in both, lateral prefrontal cortex (LPFC) and in anterior cingulate cortex (ACC). In LPFC this interneuron subclass activated when the uncertainty of attention cues was resolved during flexible learning, whereas in ACC it fired and gamma-synchronized when outcomes were uncertain and prediction errors were high during learning. Computational modeling of this interneuron-specific gamma band activity in simple circuit motifs suggests it could reflect a soft winner-take-all gating of information having high degree of uncertainty. Together, these findings elucidate an electrophysiologically-characterized interneuron subclass in the primate, that forms gamma synchronous networks in two different areas when resolving uncertainty during adaptive goal-directed behavior.

scholarly journals Interneuron Specific Gamma Synchronization Indexes Cue Uncertainty and Prediction Errors in Lateral Prefrontal and Anterior Cingulate Cortex

2020 ◽  
Author(s):  
Kianoush Banaie Boroujeni ◽  
Paul Tiesinga ◽  
Thilo Womelsdorf
Keyword(s):  
Prefrontal Cortex ◽  
Anterior Cingulate Cortex ◽  
Specific Activity ◽  
Cingulate Cortex ◽  
Anterior Cingulate ◽  
Specific Information ◽  
Inhibitory Interneurons ◽  
Prediction Errors ◽  
Firing Rates ◽  
Specific Computation

AbstractInhibitory interneurons are believed to realize critical gating functions in cortical circuits, but it has been difficult to ascertain the content of gated information for well characterized interneurons in primate cortex. Here, we address this question by characterizing putative interneurons in primate prefrontal and anterior cingulate cortex while monkeys engaged in attention demanding reversal learning. We find a subclass of narrow spiking neurons with relative suppressive effects on the local circuit indicating they are inhibitory interneurons. The activity of one subclass of these interneurons prominently indexed area-specific information in their firing rates and in event-triggered (35-45 Hz) gamma band synchronization. Firing rates and gamma synchrony of this interneuron subclass indexed in prefrontal cortex the uncertainty of attention cues, and in anterior cingulate cortex the unexpectedness of outcomes during learning. Computational analysis suggest that these interneuron-specific activity dynamics reflect in prefrontal cortex the gating of expected stimulus values into choice probabilities, and in anterior cingulate cortex the gating of chosen stimulus values and the received rewards into reward prediction errors. These findings elucidate an electrophysiologically characterized interneuron subclass in the primate, that forms gamma synchronous networks in two different areas while realizing an area-specific computation during adaptive goal-directed behavior.

scholarly journals Phase of Firing Coding of Learning Variables across Prefrontal Cortex, Anterior Cingulate Cortex and Striatum during Feature Learning

2019 ◽  
Author(s):  
Benjamin Voloh ◽  
Mariann Oemisch ◽  
Thilo Womelsdorf
Keyword(s):  
Prefrontal Cortex ◽  
Anterior Cingulate Cortex ◽  
Long Range ◽  
Cingulate Cortex ◽  
Temporal Coding ◽  
Anterior Cingulate ◽  
Prediction Errors ◽  
Lateral Prefrontal Cortex ◽  
Firing Rates ◽  
Reward Prediction

AbstractThe prefrontal cortex and striatum form a recurrent network whose spiking activity encodes multiple types of learning-relevant information. This spike-encoded information is evident in average firing rates, but finer temporal coding might allow multiplexing and enhanced readout across the connected the network. We tested this hypothesis in the fronto-striatal network of nonhuman primates during reversal learning of feature values. We found that neurons encoding current choice outcomes, outcome prediction errors, and outcome history in their firing rates also carried significant information in their phase-of-firing at a 10-25 Hz beta frequency at which they synchronized across lateral prefrontal cortex, anterior cingulate cortex and striatum. The phase-of-firing code exceeded information that could be obtained from firing rates alone, was strong for inter-areal connections, and multiplexed information at three different phases of the beta cycle that were offset from the preferred spiking phase of neurons. Taken together, these findings document the multiplexing of three different types of information in the phase-of-firing at an interareally shared beta oscillation frequency during goal-directed behavior.HighlightsLateral prefrontal cortex, anterior cingulate cortex and striatum show phase-of-firing encoding for outcome, outcome history and reward prediction errors.Neurons with phase-of-firing code synchronize long-range at 10-25 Hz.Spike phases encoding reward prediction errors deviate from preferred synchronization phases.Anterior cingulate cortex neurons show strongest long-range effects.

scholarly journals Neural Representation of Costs and Rewards in Decision Making

2021 ◽  
Vol 11 (8) ◽  
pp. 1096
Author(s):  
Yixuan Chen
Keyword(s):  
Decision Making ◽  
Anterior Cingulate Cortex ◽  
Orbitofrontal Cortex ◽  
Internal State ◽  
Cingulate Cortex ◽  
Brain Regions ◽  
Anterior Cingulate ◽  
Neural Representation ◽  
Prediction Errors ◽  
The Brain

Decision making is crucial for animal survival because the choices they make based on their current situation could influence their future rewards and could have potential costs. This review summarises recent developments in decision making, discusses how rewards and costs could be encoded in the brain, and how different options are compared such that the most optimal one is chosen. The reward and cost are mainly encoded by the forebrain structures (e.g., anterior cingulate cortex, orbitofrontal cortex), and their value is updated through learning. The recent development on dopamine and the lateral habenula’s role in reporting prediction errors and instructing learning will be emphasised. The importance of dopamine in powering the choice and accounting for the internal state will also be discussed. While the orbitofrontal cortex is the place where the state values are stored, the anterior cingulate cortex is more important when the environment is volatile. All of these structures compare different attributes of the task simultaneously, and the local competition of different neuronal networks allows for the selection of the most appropriate one. Therefore, the total value of the task is not encoded as a scalar quantity in the brain but, instead, as an emergent phenomenon, arising from the computation at different brain regions.

scholarly journals Phase of firing coding of learning variables across the fronto-striatal network during feature-based learning

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Benjamin Voloh ◽  
Mariann Oemisch ◽  
Thilo Womelsdorf
Keyword(s):  
Prefrontal Cortex ◽  
Anterior Cingulate Cortex ◽  
Information Gain ◽  
Cingulate Cortex ◽  
Temporal Coding ◽  
Anterior Cingulate ◽  
Prediction Errors ◽  
Significant Information ◽  
Lateral Prefrontal Cortex ◽  
Firing Rates

Abstract The prefrontal cortex and striatum form a recurrent network whose spiking activity encodes multiple types of learning-relevant information. This spike-encoded information is evident in average firing rates, but finer temporal coding might allow multiplexing and enhanced readout across the connected network. We tested this hypothesis in the fronto-striatal network of nonhuman primates during reversal learning of feature values. We found that populations of neurons encoding choice outcomes, outcome prediction errors, and outcome history in their firing rates also carry significant information in their phase-of-firing at a 10–25 Hz band-limited beta frequency at which they synchronize across lateral prefrontal cortex, anterior cingulate cortex and anterior striatum when outcomes were processed. The phase-of-firing code exceeds information that can be obtained from firing rates alone and is evident for inter-areal connections between anterior cingulate cortex, lateral prefrontal cortex and anterior striatum. For the majority of connections, the phase-of-firing information gain is maximal at phases of the beta cycle that were offset from the preferred spiking phase of neurons. Taken together, these findings document enhanced information of three important learning variables at specific phases of firing in the beta cycle at an inter-areally shared beta oscillation frequency during goal-directed behavior.

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

2018 ◽  
Author(s):  
Mariann Oemisch ◽  
Stephanie Westendorff ◽  
Marzyeh Azimi ◽  
Seyed Ali Hassani ◽  
Salva Ardid ◽  
...  
Keyword(s):  
Prefrontal Cortex ◽  
Anterior Cingulate Cortex ◽  
Prediction Error ◽  
Ventral Striatum ◽  
Cingulate Cortex ◽  
Anterior Cingulate ◽  
Prediction Errors ◽  
Lateral Prefrontal Cortex ◽  
Feature Based ◽  
Specific Prediction

SummaryPrediction 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.HighlightsNeural reward prediction errors carry information for updating feature-based attention in all areas of the fronto-striatal network.Feature specific neural prediction errors emerge earliest in anterior cingulate cortex and later in lateral prefrontal cortex.Ventral striatum neurons encode feature specific surprise strongest for the goal-relevant feature.Neurons encoding feature-specific prediction errors contribute to attentional selection after learning.

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