Supplemental Material for Altered Face Scanning and Arousal After Orbitofrontal Cortex Lesion in Adult Rhesus Monkeys

2020 ◽  
Vol 134 (1) ◽  
pp. 45-58 ◽  
Author(s):  
Anne-Pierre S. Goursaud ◽  
Jocelyne Bachevalier

Author(s):  
Sébastien Ballesta ◽  
Weikang Shi ◽  
Katherine E. Conen ◽  
Camillo Padoa-Schioppa

AbstractIt has long been hypothesized that economic choices rely on the assignment and comparison of subjective values. Indeed, when agents make decisions, neurons in orbitofrontal cortex encode the values of offered and chosen goods. Moreover, neuronal activity in this area suggests the formation of a decision. However, it is unclear whether these neural processes are causally related to choices. More generally, the evidence linking economic choices to value signals in the brain remains correlational. We address this fundamental issue using electrical stimulation in rhesus monkeys. We show that suitable currents bias choices by increasing the value of individual offers. Furthermore, high-current stimulation disrupts both the computation and the comparison of subjective values. These results demonstrate that values encoded in orbitofrontal cortex are causal to economic choices.


2021 ◽  
Author(s):  
Weikang Shi ◽  
Sebastien Ballesta ◽  
Camillo Padoa-Schioppa

Economic choices are characterized by a variety of biases. Understanding their origins is a long-term goal for neuroeconomics, but progress on this front has been limited. Here we examined choice biases observed when two goods are offered sequentially. In the experiments, rhesus monkeys chose between different juices offered simultaneously or in sequence. Choices under sequential offers were less accurate (higher variability). They were also biased in favor of the second offer (order bias) and in favor of the preferred juice (preference bias). Analysis of neuronal activity recorded in orbitofrontal cortex revealed that these phenomena emerged at different computational stages. The lower choice accuracy reflected weaker offer value signals (valuation stage), the order bias emerged during value comparison (decision stage), and the preference bias emerged late in the trial (post-comparison). Our approach, leveraging recent notions on the neural mechanisms of economic decisions, may shed light on other aspects of choice behavior.


1982 ◽  
Vol 18 (2) ◽  
pp. 222-228 ◽  
Author(s):  
Morton J. Mendelson ◽  
Marshall M. Haith ◽  
Patricia S. Goldman-Rakic

1996 ◽  
Vol 75 (3) ◽  
pp. 1190-1205 ◽  
Author(s):  
M. Meunier ◽  
W. Hadfield ◽  
J. Bachevalier ◽  
E. A. Murray

1. We assessed the visual recognition abilities, as measured by delayed nonmatching-to-sample with trial-unique objects, of rhesus monkeys with hippocampectomy (i.e., removal of the hippocampal formation plus parahippocampal gyrus) combined with ablations of the rhinal cortex (i.e., entorhinal cortex plus perirhinal cortex). 2. Relative to unoperated controls, monkeys with combined hippocampectomy and rhinal cortex ablation (H+Rh) were significantly impaired in visual recognition. 3. Comparison of the scores of the monkeys in the present H+Rh group, which sustained near-complete rhinal cortex damage, with the scores of monkeys in an earlier H+Rh group in which the rostral part of the rhinal cortex had been spared indicates that the magnitude of the impairment is greater in the group with the more complete rhinal cortex damage. This finding is consistent with the idea that the rhinal cortex is critical for visual recognition. 4. Comparison of the present results with those from an earlier study on visual recognition that employed lesions limited to the rhinal cortex (Rh group) shows, paradoxically, that adding removal of the hippocampal formation and parahippocampal gyrus to a rhinal cortex lesion significantly reduces the recognition impairment produced by rhinal cortex lesions alone. 5. Our findings do not fit the view that the hippocampal formation, parahippocampal gyrus, and rhinal cortex constitute parts of a single functional system, such that the greater the damage to the entire system, the more severe the impairment. Instead, the results are consistent with the view that there are multiple functional subdivisions within the medial temporal lobe.


2015 ◽  
Vol 114 (3) ◽  
pp. 1367-1381 ◽  
Author(s):  
Katherine E. Conen ◽  
Camillo Padoa-Schioppa

Neuroeconomic models assume that economic decisions are based on the activity of offer value cells in the orbitofrontal cortex (OFC), but testing this assertion has proven difficult. In principle, the decision made on a given trial should correlate with the stochastic fluctuations of these cells. However, this correlation, measured as a choice probability (CP), is small. Importantly, a neuron's CP reflects not only its individual contribution to the decision (termed readout weight), but also the intensity and the structure of correlated variability across the neuronal population (termed noise correlation). A precise mathematical relation between CPs, noise correlations, and readout weights was recently derived by Haefner and colleagues (Haefner RM, Gerwinn S, Macke JH, Bethge M. Nat Neurosci 16: 235–242, 2013) for a linear decision model. In this framework, concurrent measurements of noise correlations and CPs can provide quantitative information on how a population of cells contributes to a decision. Here we examined neuronal variability in the OFC of rhesus monkeys during economic decisions. Noise correlations had similar structure but considerably lower strength compared with those typically measured in sensory areas during perceptual decisions. In contrast, variability in the activity of individual cells was high and comparable to that recorded in other cortical regions. Simulation analyses based on Haefner's equation showed that noise correlations measured in the OFC combined with a plausible readout of offer value cells reproduced the experimental measures of CPs. In other words, the results obtained for noise correlations and those obtained for CPs taken together support the hypothesis that economic decisions are primarily based on the activity of offer value cells.


2016 ◽  
Vol 296 ◽  
pp. 379-383 ◽  
Author(s):  
Rodrigo O. Sierra ◽  
Laura P. Nítola ◽  
Johanna M. Duran ◽  
Daysi R. Prieto ◽  
Laura A. León ◽  
...  

2010 ◽  
Vol 116 (2-3) ◽  
pp. 266-273 ◽  
Author(s):  
Marion Larquet ◽  
Giorgio Coricelli ◽  
Gaëlle Opolczynski ◽  
Florence Thibaut

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