scholarly journals Mechanisms of Economic Decisions under Sequential Offers

2019 ◽  
Author(s):  
Sébastien Ballesta ◽  
Camillo Padoa-Schioppa
Keyword(s):  
Orbitofrontal Cortex ◽  
Neural Circuit ◽  
Time Windows ◽  
Neuronal Responses ◽  
Mutual Inhibition ◽  
Economic Decisions ◽  
Neuronal Mechanisms ◽  
Binary Choices ◽  
Decision Mechanisms

AbstractBinary choices between goods are thought to take place in orbitofrontal cortex (OFC). However, current notions emerged mostly from studies where two offers were presented simultaneously, and other work suggested that choices under sequential offers rely on fundamentally different mechanisms. Here we recorded from the OFC of macaques choosing between two juices offered sequentially. Analyzing neuronal responses across time windows, we discovered different groups of neurons that closely resemble those identified under simultaneous offers, suggesting that decisions in the two modalities are formed in the same neural circuit. Building on this result, we examined four hypotheses on the decision mechanisms. OFC neurons encoded goods and values in a juice-based representation (labeled lines). Contrary to previous assessments, decisions did not involve mutual inhibition between pools of offer value cells. Instead, decisions involved mechanisms of circuit inhibition, whereby each offer value indirectly inhibits neurons encoding the opposite choice outcome. These results reconcile disparate findings and provide a unitary account for the neuronal mechanisms underlying economic decisions.

Orbitofrontal cortex neurons: role in olfactory and visual association learning

1996 ◽  
Vol 75 (5) ◽  
pp. 1970-1981 ◽  
Author(s):  
E. T. Rolls ◽  
H. D. Critchley ◽  
R. Mason ◽  
E. A. Wakeman
Keyword(s):  
Orbitofrontal Cortex ◽  
Discrimination Task ◽  
Neuronal Responses ◽  
Olfactory Neurons ◽  
Rapid Learning ◽  
Association Learning ◽  
Visual Cells ◽  
New Associations ◽  
Olfactory Responses ◽  
Neuronal Mechanisms

1. The orbitofrontal cortex is implicated in the rapid learning of new associations between visual stimuli and primary reinforcers such as taste. It is also the site of convergence of information from olfactory, gustatory, and visual modalities. To investigate the neuronal mechanisms underlying the formation of odor-taste associations, we made recordings from olfactory neurons in the orbitofrontal cortex during the performance of an olfactory discrimination task and its reversal in macaques. 2. It was found that 68% of odor-responsive neurons modified their responses after the changes in the taste reward associations of the odorants. Full reversal of the neuronal responses was seen in 25% of these neurons. Extinction of the differential neuronal responses after task reversal was seen in 43% of these neurons. 3. For comparison, visually responsive orbitofrontal neurons were tested during reversal of a visual discrimination task. Seventy-one percent of these visual cells showed rapid full reversal of the visual stimulus to which they responded, when the association of the visual with taste was reversed in the reversal task. 4. These demonstrate that of many orbitofrontal cortex olfactory neurons on the taste with which the odor is associated. 5. This modification is likely to be important for setting the motivational value of olfactory for feeding and other rewarded behavior. However, it is less complete, and much slower, than the modifications found or orbit frontal visual during visual-taste reversal. This relative inflexibility of olfactory responses is consistent with the need for some stability is odor-taste associations to facilitate the formation and perception of flavors.

scholarly journals A neuro-computational model of economic decisions

2015 ◽  
Vol 114 (3) ◽  
pp. 1382-1398 ◽  
Author(s):  
Aldo Rustichini ◽  
Camillo Padoa-Schioppa
Keyword(s):  
Decision Process ◽  
Neural Circuit ◽  
Neuronal Populations ◽  
The Third ◽  
Economic Decisions ◽  
Input And Output ◽  
Neuronal Mechanisms ◽  
Lesion Studies ◽  
Key Aspects ◽  
Open Question

Neuronal recordings and lesion studies indicate that key aspects of economic decisions take place in the orbitofrontal cortex (OFC). Previous work identified in this area three groups of neurons encoding the offer value, the chosen value, and the identity of the chosen good. An important and open question is whether and how decisions could emerge from a neural circuit formed by these three populations. Here we adapted a biophysically realistic neural network previously proposed for perceptual decisions (Wang XJ. Neuron 36: 955–968, 2002; Wong KF, Wang XJ. J Neurosci 26: 1314–1328, 2006). The domain of economic decisions is significantly broader than that for which the model was originally designed, yet the model performed remarkably well. The input and output nodes of the network were naturally mapped onto two groups of cells in OFC. Surprisingly, the activity of interneurons in the network closely resembled that of the third group of cells, namely, chosen value cells. The model reproduced several phenomena related to the neuronal origins of choice variability. It also generated testable predictions on the excitatory/inhibitory nature of different neuronal populations and on their connectivity. Some aspects of the empirical data were not reproduced, but simple extensions of the model could overcome these limitations. These results render a biologically credible model for the neuronal mechanisms of economic decisions. They demonstrate that choices could emerge from the activity of cells in the OFC, suggesting that chosen value cells directly participate in the decision process. Importantly, Wang's model provides a platform to investigate the implications of neuroscience results for economic theory.

scholarly journals Orbitofrontal Cortex: A Neural Circuit for Economic Decisions

Neuron ◽  
2017 ◽  
Vol 96 (4) ◽  
pp. 736-754 ◽  
Author(s):  
Camillo Padoa-Schioppa ◽  
Katherine E. Conen
Keyword(s):  
Orbitofrontal Cortex ◽  
Neural Circuit ◽  
Economic Decisions

scholarly journals Economic Choices under Simultaneous or Sequential Offers Rely on the Same Neural Circuit

2021 ◽  
Author(s):  
Weikang Shi ◽  
Sebastien Ballesta ◽  
Camillo Padoa-Schioppa
Keyword(s):  
Neural Circuit ◽  
Time Windows ◽  
Building Blocks ◽  
Binary Choice ◽  
Neuronal Responses ◽  
Cell Groups ◽  
Decision Circuit ◽  
Economic Choices ◽  
Specific Sequences ◽  
Lines Of Evidence

A series of studies in which monkeys chose between two juices offered in variable amounts identified in the orbitofrontal cortex (OFC) different groups of neurons encoding the value of individual options (offer value), the binary choice outcome (chosen juice) and the chosen value. These variables capture both the input and the output of the choice process, suggesting that the cell groups identified in OFC constitute the building blocks of a decision circuit. Several lines of evidence support this hypothesis. However, in previous experiments offers were presented simultaneously, raising the question of whether current notions generalize to when goods are presented or are examined in sequence. Recently, Ballesta and Padoa-Schioppa (2019) examined OFC activity under sequential offers. An analysis of neuronal responses across time windows revealed that a small number of cell groups encoded specific sequences of variables. These sequences appeared analogous to the variables identified under simultaneous offers, but the correspondence remained tentative. Thus in the present study we examined the relation between cell groups found under sequential versus simultaneous offers. We recorded from the OFC while monkeys chose between different juices. Trials with simultaneous and sequential offers were randomly interleaved in each session. We classified cells in each choice modality and we examined the relation between the two classifications. We found a strong correspondence; in other words, the cell groups measured under simultaneous offers and under sequential offers were one and the same. This result indicates that economic choices under simultaneous or sequential offers rely on the same neural circuit.

scholarly journals THE NEURAL CIRCUIT FOR THE CALCULATION OF ECONOMIC CHOICE AND COMPARISON OF SUBJECTIVE VALUES

2021 ◽  
Vol 10 (34) ◽  
Author(s):  
K.M BORODINA ◽  
Keyword(s):  
Orbitofrontal Cortex ◽  
Neural Circuit ◽  
Correct Choice ◽  
Anterior Lobe ◽  
Brain Functions ◽  
Economic Decisions ◽  
Economic Choice ◽  
Economic Decision Making ◽  
Material Component ◽  
The Brain

Economic choice in human behavior involves a reliable calculation by accepting subjective values. The purpose of our study is to study the neural circuit of the brain in order to assess the adoption of specific economic decisions to improve the material component of each subject of the study. Economic choice is calculated and compared with subjective values by using an experiment. The hypothesis is that the anterior lobe of the brain is responsible for the correctness of economic decisions,and the center for making economic choices is oriented directly in the orbitofrontal cortex. The results obtained in other areas of the brain are consistent with the idea that correct economic choice decisions are made in the orbitofrontal cortex, and indicate that value signals influence many brain functions that determine the main economic principles. Thus, based on the research data, we can draw conclusions about the direct relationship of the cerebral cortex, economic decision-making and the influence of subjective values. This research is of great importance in increasing the success of any person, namely their material security, economically correct choice and acceptance of motivation in any given situation.

scholarly journals Perceptual detection depends on spike count integration

2019 ◽  
Author(s):  
Jackson J. Cone ◽  
Morgan L. Bade ◽  
Nicolas Y. Masse ◽  
Elizabeth A. Page ◽  
David J. Freedman ◽  
...  
Keyword(s):  
Neural Networks ◽  
Cerebral Cortex ◽  
Visual Cortex ◽  
Recurrent Neural Networks ◽  
Neural Circuit ◽  
Visual Detection ◽  
Spike Count ◽  
Neuronal Responses ◽  
Neuronal Populations ◽  
And Behavior

AbstractWhenever the retinal image changes some neurons in visual cortex increase their rate of firing, while others decrease their rate of firing. Linking specific sets of neuronal responses with perception and behavior is essential for understanding mechanisms of neural circuit computation. We trained mice to perform visual detection tasks and used optogenetic perturbations to increase or decrease neuronal spiking primary visual cortex (V1). Perceptual reports were always enhanced by increments in V1 spike counts and impaired by decrements, even when increments and decrements were delivered to the same neuronal populations. Moreover, detecting changes in cortical activity depended on spike count integration rather than instantaneous changes in spiking. Recurrent neural networks trained in the task similarly relied on increments in neuronal activity when activity was costly. This work clarifies neuronal decoding strategies employed by cerebral cortex to translate cortical spiking into percepts that can be used to guide behavior.

scholarly journals What, if anything, is the true neurophysiological significance of “rotational dynamics”?

2019 ◽  
Author(s):  
Mikhail A. Lebedev ◽  
Alexei Ossadtchi ◽  
Nil Adell Mill ◽  
Núria Armengol Urpí ◽  
Maria R. Cervera ◽  
...  
Keyword(s):  
Neuronal Population ◽  
Rotational Dynamics ◽  
Neuronal Responses ◽  
Linear Transformations ◽  
Experimental Conditions ◽  
Temporal Shift ◽  
Firing Rates ◽  
Motor Behaviors ◽  
Neuronal Populations ◽  
Neuronal Mechanisms

AbstractBack in 2012, Churchland and his colleagues proposed that “rotational dynamics”, uncovered through linear transformations of multidimensional neuronal data, represent a fundamental type of neuronal population processing in a variety of organisms, from the isolated leech central nervous system to the primate motor cortex. Here, we evaluated this claim using Churchland’s own data and simple simulations of neuronal responses. We observed that rotational patterns occurred in neuronal populations when (1) there was a temporal shift in peak firing rates exhibited by individual neurons, and (2) the temporal sequence of peak rates remained consistent across different experimental conditions. Provided that such a temporal order of peak firing rates existed, rotational patterns could be easily obtained using a rather arbitrary computer simulation of neural activity; modeling of any realistic properties of motor cortical responses was not needed. Additionally, arbitrary traces, such as Lissajous curves, could be easily obtained from Churchland’s data with multiple linear regression. While these observations suggest that temporal sequences of neuronal responses could be visualized as rotations with various methods, we express doubt about Churchland et al.’s exaggerated assessment that such rotations are related to “an unexpected yet surprisingly simple structure in the population response”, which “explains many of the confusing features of individual neural responses.” Instead, we argue that their approach provides little, if any, insight on the underlying neuronal mechanisms employed by neuronal ensembles to encode motor behaviors in any species.

scholarly journals Dynamics of a mutual inhibition between pyramidal neurons compared to human perceptual competition

2020 ◽  
Author(s):  
N. Kogo ◽  
F. B. Kern ◽  
T. Nowotny ◽  
R. van Ee ◽  
R. van Wezel ◽  
...  
Keyword(s):  
Pyramidal Neurons ◽  
Neural Circuit ◽  
Real Life ◽  
Theoretical Research ◽  
Emergent Properties ◽  
Mutual Inhibition ◽  
Brain Functioning ◽  
Active Selection ◽  
Selection Processes ◽  
Neural Competition

AbstractNeural competition plays an essential role in active selection processes of noisy and ambiguous input signals and it is assumed to underlie emergent properties of brain functioning such as perceptual organization and decision making. Despite ample theoretical research on neural competition, experimental tools to allow neurophysiological investigation of competing neurons have not been available. We developed a “hybrid” system where real-life neurons and a computer-simulated neural circuit interacted. It enabled us to construct a mutual inhibition circuit between two real life pyramidal neurons. We then asked what dynamics this minimal unit of neural competition exhibits and compared them to the known behavioral-level dynamics of neural competition. We found that the pair of neurons shows bi-stability when activated simultaneously by current injections. The addition of modelled noise and changes in the activation strength showed that the dynamics of the circuit are strikingly similar to the known properties of bi-stable visual perception.

scholarly journals Value signals in orbitofrontal cortex predict economic decisions on a trial-to-trial basis

2021 ◽  
Author(s):  
Vincent B. McGinty ◽  
Shira M. Lupkin
Keyword(s):  
Neural Activity ◽  
Orbitofrontal Cortex ◽  
Population Level ◽  
Weighted Sum ◽  
Decision Behavior ◽  
Economic Decisions ◽  
Trial Basis ◽  
Individual Value ◽  
Value Coding ◽  
First Time

ABSTRACTNeuroeconomics seeks to explain how neural activity contributes to decision behavior. For value-based decisions, the primate orbitofrontal cortex (OFC) is thought to have a key role; however, the mechanism by which single OFC cells contribute to choices is still unclear. Here, we show for the first time a trial-to-trial relationship between choices and population-level value representations in OFC, defined by the weighted sum of activity from many individual value-coding neurons.

scholarly journals Analysis of neuronal ensemble activity reveals the pitfalls and shortcomings of rotation dynamics

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Mikhail A. Lebedev ◽  
Alexei Ossadtchi ◽  
Nil Adell Mill ◽  
Núria Armengol Urpí ◽  
Maria R. Cervera ◽  
...  
Keyword(s):  
Neuronal Population ◽  
Neuronal Responses ◽  
Linear Transformations ◽  
Experimental Conditions ◽  
Firing Rates ◽  
Motor Behaviors ◽  
Neuronal Ensembles ◽  
Neuronal Populations ◽  
Activity Modeling ◽  
Neuronal Mechanisms

AbstractBack in 2012, Churchland and his colleagues proposed that “rotational dynamics”, uncovered through linear transformations of multidimensional neuronal data, represent a fundamental type of neuronal population processing in a variety of organisms, from the isolated leech central nervous system to the primate motor cortex. Here, we evaluated this claim using Churchland’s own data and simple simulations of neuronal responses. We observed that rotational patterns occurred in neuronal populations when (1) there was a temporal sequence in peak firing rates exhibited by individual neurons, and (2) this sequence remained consistent across different experimental conditions. Provided that such a temporal order of peak firing rates existed, rotational patterns could be easily obtained using a rather arbitrary computer simulation of neural activity; modeling of any realistic properties of motor cortical responses was not needed. Additionally, arbitrary traces, such as Lissajous curves, could be easily obtained from Churchland’s data with multiple linear regression. While these observations suggest that temporal sequences of neuronal responses could be visualized as rotations with various methods, we express doubt about Churchland et al.’s bold assessment that such rotations are related to “an unexpected yet surprisingly simple structure in the population response”, which “explains many of the confusing features of individual neural responses”. Instead, we argue that their approach provides little, if any, insight on the underlying neuronal mechanisms employed by neuronal ensembles to encode motor behaviors in any species.

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