scholarly journals Same or Different? A Neural Circuit Mechanism of Similarity-Based Pattern Match Decision Making

2011 ◽  
Vol 31 (19) ◽  
pp. 6982-6996 ◽  
Author(s):  
T. A. Engel ◽  
X.-J. Wang
Keyword(s):  
Decision Making ◽  
Neural Circuit ◽  
Pattern Match

scholarly journals Social Status–Dependent Shift in Neural Circuit Activation Affects Decision Making

2017 ◽  
Vol 37 (8) ◽  
pp. 2137-2148 ◽  
Author(s):  
Thomas H. Miller ◽  
Katie Clements ◽  
Sungwoo Ahn ◽  
Choongseok Park ◽  
Eoon Hye Ji ◽  
...  
Keyword(s):  
Decision Making ◽  
Social Status ◽  
Neural Circuit

scholarly journals From Retrospective to Prospective: Integrated Value Representation in Frontal Cortex for Predictive Choice Behavior

2021 ◽  
Author(s):  
Kosuke Hamaguchi ◽  
Hiromi Takahashi-Aoki ◽  
Dai Watanabe
Keyword(s):  
Decision Making ◽  
Frontal Cortex ◽  
Choice Behavior ◽  
State Transition ◽  
Neural Circuit ◽  
The Past ◽  
Preparatory Activity ◽  
Action Value ◽  
The Brain ◽  
Different Sources

Animals must flexibly estimate the value of their actions to successfully adapt in a changing environment. The brain is thought to estimate action-value from two different sources, namely the action-outcome history (retrospective value) and the knowledge of the environment (prospective value). How these two different estimates of action-value are reconciled to make a choice is not well understood. Here we show that as a mouse learns the state-transition structure of a decision-making task, retrospective and prospective values become jointly encoded in the preparatory activity of neurons in the frontal cortex. Suppressing this preparatory activity in expert mice returned their behavior to a naive state. These results reveal the neural circuit that integrates knowledge about the past and future to support predictive decision-making.

Dynamical Foundations of the Neural Circuit for Bayesian Decision Making

2009 ◽  
Vol 102 (1) ◽  
pp. 1-6 ◽  
Author(s):  
Kenji Morita
Keyword(s):  
Decision Making ◽  
Bayesian Inference ◽  
Neural Circuits ◽  
Neural Circuit ◽  
Bayesian Decision ◽  
Biophysical Modeling ◽  
Perceptual Decision Making ◽  
Basic Ideas ◽  
Bayesian Decision Making ◽  
The Brain

On the basis of accumulating behavioral and neural evidences, it has recently been proposed that the brain neural circuits of humans and animals are equipped with several specific properties, which ensure that perceptual decision making implemented by the circuits can be nearly optimal in terms of Bayesian inference. Here, I introduce the basic ideas of such a proposal and discuss its implications from the standpoint of biophysical modeling developed in the framework of dynamical systems.

scholarly journals GABAergic motor neurons bias locomotor decision-making in C. elegans

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Ping Liu ◽  
Bojun Chen ◽  
Zhao-Wen Wang
Keyword(s):  
Decision Making ◽  
Motor Neurons ◽  
Gaba Receptor ◽  
Single Neuron ◽  
Neural Circuit ◽  
Electrical Coupling ◽  
C Elegans ◽  
Sensory Modalities ◽  
Motor Information ◽  
Molecular Bases

Abstract Proper threat-reward decision-making is critical to animal survival. Emerging evidence indicates that the motor system may participate in decision-making but the neural circuit and molecular bases for these functions are little known. We found in C. elegans that GABAergic motor neurons (D-MNs) bias toward the reward behavior in threat-reward decision-making by retrogradely inhibiting a pair of premotor command interneurons, AVA, that control cholinergic motor neurons in the avoidance neural circuit. This function of D-MNs is mediated by a specific ionotropic GABA receptor (UNC-49) in AVA, and depends on electrical coupling between the two AVA interneurons. Our results suggest that AVA are hub neurons where sensory inputs from threat and reward sensory modalities and motor information from D-MNs are integrated. This study demonstrates at single-neuron resolution how motor neurons may help shape threat-reward choice behaviors through interacting with other neurons.

scholarly journals Specific plasticity loci and their synergism mediate operant conditioning

2021 ◽  
Author(s):  
Yuto Momohara ◽  
Curtis L. Neveu ◽  
Hsin-Mei Chen ◽  
Douglas A. Baxter ◽  
John H. Byrne
Keyword(s):  
Decision Making ◽  
Feeding Behavior ◽  
Operant Conditioning ◽  
Neuronal Excitability ◽  
Neural Circuit ◽  
Electrical Coupling ◽  
Behavioral Changes ◽  
Intrinsic Excitability ◽  
Inhibitory Connection ◽  
Induced Changes

AbstractDespite numerous studies examining the mechanisms of operant conditioning (OC), the diversity of plasticity loci and their synergism have not been examined sufficiently. In the well-characterized feeding neural circuit of Aplysia, appetitive OC increases neuronal excitability and electrical coupling among several neurons. Here we found OC decreased the intrinsic excitability of B4 and the strength of its inhibitory connection to a key decision-making neuron, B51. The OC-induced changes were specific without affecting the B4-to-B8 inhibitory connection or excitability of another neuron critical for feeding behavior, B8. A conductance-based circuit model indicated certain sites of plasticity mediated the OC phenotype more effectively and that plasticity loci acted synergistically. This synergy was specific in that only certain combinations of loci synergistically enhanced feeding. Taken together, these results suggest modifications of diverse loci work synergistically to mediate OC.Significance StatementThe diversity and synergism of plasticity loci mediating operant conditioning (OC) is poorly understood. Here we found that OC decreased the intrinsic excitability of a critical neuron mediating Aplysia feeding behavior and specifically reduced the strength of one of its inhibitory connections to a key decision-making neuron. A conductance-based computational model indicated that the known plasticity loci showed a surprising level of synergism to mediate the behavioral changes associated with OC. These results highlight the importance of understanding the diversity, specificity and synergy among different types of plasticity that encode memory. Also, because OC in Aplysia is mediated by dopamine (DA), the present study provides insights into specific and synergistic mechanisms of DA-mediated reinforcement of behaviors.

scholarly journals Tonic dopamine, uncertainty and basal ganglia action selection

2020 ◽  
Author(s):  
Tom Gilbertson ◽  
Douglas Steele
Keyword(s):  
Decision Making ◽  
Basal Ganglia ◽  
Neural Circuit ◽  
Optimal Solution ◽  
Action Selection ◽  
Selection Function ◽  
Cortical Input ◽  
Optimal Decisions ◽  
Multiple Alternative ◽  
The Relationship

AbstractTo make optimal decisions in uncertain circumstances flexible adaption of behaviour is required; exploring alternatives when the best choice is unknown, exploiting what is known when that is best. Using a detailed computational model of the basal ganglia, we propose that switches between exploratory and exploitative decisions can be mediated by the interaction between tonic dopamine and cortical input to the basal ganglia. We show that a biologically detailed action selection circuit model of the basal ganglia, endowed with dopamine dependant striatal plasticity, can optimally solve the explore-exploit problem, estimating the true underlying state of a noisy Gaussian diffusion process. Critical to the model’s performance was a fluctuating level of tonic dopamine which increased under conditions of uncertainty. With an optimal range of tonic dopamine, explore-exploit decision making was mediated by the effects of tonic dopamine on the precision of the model action selection mechanism. Under conditions of uncertain reward pay-out, the model’s reduced selectivity allowed disinhibition of multiple alternative actions to be explored at random. Conversely, when uncertainly about reward pay-out was low, enhanced selectivity of the action selection circuit was enhanced, facilitating exploitation of the high value choice. When integrated with phasic dopamine dependant influences on cortico-striatal plasticity, the model’s performance was at the level of the Kalman filter which provides an optimal solution for the task. Our model provides an integrative account of the relationship between phasic and tonic dopamine and the action selection function of the basal ganglia and supports the idea that this subcortical neural circuit may have evolved to facilitate decision making in non-stationary reward environments, allowing a number of experimental predictions with relevance to abnormal decision making in neuropsychiatric and neurological disease.

scholarly journals Residual dynamics resolves recurrent contributions to neural computation

2021 ◽  
Author(s):  
Aniruddh R Galgali ◽  
Maneesh Sahani ◽  
Valerio Mante
Keyword(s):  
Decision Making ◽  
Large Scale ◽  
Neural Circuit ◽  
Neural Population ◽  
Perceptual Decision Making ◽  
Neural Recordings ◽  
Fine Grained ◽  
Neural Computations ◽  
Population Trajectory ◽  
The Mean

Relating neural activity to behavior requires an understanding of how neural computations arise from the coordinated dynamics of distributed, recurrently connected neural populations. However, inferring the nature of recurrent dynamics from partial recordings of a neural circuit presents significant challenges. Here, we show that some of these challenges can be overcome by a fine-grained analysis of the dynamics of neural residuals, i.e. trial-by-trial variability around the mean neural population trajectory for a given task condition. Residual dynamics in macaque pre-frontal cortex (PFC) in a saccade-based perceptual decision-making task reveals recurrent dynamics that is time-dependent, but consistently stable, and implies that pronounced rotational structure in PFC trajectories during saccades are driven by inputs from upstream areas. The properties of residual dynamics restrict the possible contributions of PFC to decision-making and saccade generation, and suggest a path towards fully characterizing distributed neural computations with large-scale neural recordings and targeted causal perturbations.

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