Population coding of valence in the basolateral amygdala

Mapping Intimacies ◽

10.1101/321232 ◽

2018 ◽

Cited By ~ 1

Author(s):

Xian Zhang ◽

Bo Li

Keyword(s):

Associative Learning ◽

Reversal Learning ◽

Basolateral Amygdala ◽

Population Coding ◽

Neuronal Responses ◽

Conditioned Stimuli ◽

Reward And Punishment

AbstractThe basolateral amygdala (BLA) plays an important role in associative learning, by representing both conditioned stimuli (CSs) and unconditioned stimuli (USs) of positive and negative valences, and by forming associations between CSs and USs. However, how such associations are formed and updated during learning remains unclear. Here we show that associative learning driven by reward and punishment profoundly alters BLA neuronal responses at population levels, reducing noise correlations and transforming the representations of CSs to resemble the distinctive valence-specific representations of USs. This transformation is accompanied by the emergence of prevalent inhibitory CS and US responses, and by the plasticity of CS responses in individual BLA neurons. During reversal learning wherein the expected valences are reversed, BLA population CS representations are remapped onto ensembles representing the opposite valences and track the switching in valence-specific behavioral actions. Our results reveal how signals predictive of opposing valences in the BLA evolve during reward and punishment learning, and how these signals might be updated and used to guide flexible behaviors.

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Heritabilities and co-variation among cognitive traits in red junglefowl

Philosophical Transactions of the Royal Society B Biological Sciences ◽

10.1098/rstb.2017.0285 ◽

2018 ◽

Vol 373 (1756) ◽

pp. 20170285 ◽

Cited By ~ 20

Author(s):

Enrico Sorato ◽

Josefina Zidar ◽

Laura Garnham ◽

Alastair Wilson ◽

Hanne Løvlie

Keyword(s):

Individual Differences ◽

Associative Learning ◽

Genetic Control ◽

Reversal Learning ◽

Cognitive Abilities ◽

Learning Performance ◽

Discriminative Learning ◽

Red Junglefowl ◽

Judgement Bias ◽

Cognitive Traits

Natural selection can act on between-individual variation in cognitive abilities, yet evolutionary responses depend on the presence of underlying genetic variation. It is, therefore, crucial to determine the relative extent of genetic versus environmental control of these among-individual differences in cognitive traits to understand their causes and evolutionary potential. We investigated heritability of associative learning performance and of a cognitive judgement bias (optimism), as well as their covariation, in a captive pedigree-bred population of red junglefowl ( Gallus gallus , n > 300 chicks over 5 years). We analysed performance in discriminative and reversal learning (two facets of associative learning), and cognitive judgement bias, by conducting animal models to disentangle genetic from environmental contributions. We demonstrate moderate heritability for reversal learning, and weak to no heritability for optimism and discriminative learning, respectively. The two facets of associative learning were weakly negatively correlated, consistent with hypothesized trade-offs underpinning individual cognitive styles. Reversal, but not discriminative learning performance, was associated with judgement bias; less optimistic individuals reversed a previously learnt association faster. Together these results indicate that genetic and environmental contributions differ among traits. While modular models of cognitive abilities predict a lack of common genetic control for different cognitive traits, further investigation is required to fully ascertain the degree of covariation between a broader range of cognitive traits and the extent of any shared genetic control. This article is part of the theme issue ‘Causes and consequences of individual differences in cognitive abilities’.

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Establishing the Dopamine Dependency of Human Striatal Signals During Reward and Punishment Reversal Learning

Cerebral Cortex ◽

10.1093/cercor/bhs344 ◽

2012 ◽

Vol 24 (3) ◽

pp. 633-642 ◽

Cited By ~ 55

Author(s):

Marieke E. van der Schaaf ◽

Martine R. van Schouwenburg ◽

Dirk E.M. Geurts ◽

Arnt F.A. Schellekens ◽

Jan K. Buitelaar ◽

...

Keyword(s):

Reversal Learning ◽

Reward And Punishment

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Laminar dependence of neuronal correlations in visual cortex

Journal of Neurophysiology ◽

10.1152/jn.00846.2012 ◽

2013 ◽

Vol 109 (4) ◽

pp. 940-947 ◽

Cited By ~ 85

Author(s):

Matthew A. Smith ◽

Xiaoxuan Jia ◽

Amin Zandvakili ◽

Adam Kohn

Keyword(s):

Visual Cortex ◽

Field Potential ◽

Low Frequency ◽

Population Coding ◽

Neuronal Responses ◽

Cortical Function ◽

Area V2 ◽

Complementary Pattern ◽

Deep Layers ◽

Slow Timescale

Neuronal responses are correlated on a range of timescales. Correlations can affect population coding and may play an important role in cortical function. Correlations are known to depend on stimulus drive, behavioral context, and experience, but the mechanisms that determine their properties are poorly understood. Here we make use of the laminar organization of cortex, with its variations in sources of input, local circuit architecture, and neuronal properties, to test whether networks engaged in similar functions but with distinct properties generate different patterns of correlation. We find that slow timescale correlations are prominent in the superficial and deep layers of primary visual cortex (V1) of macaque monkeys, but near zero in the middle layers. Brief timescale correlation (synchrony), on the other hand, was slightly stronger in the middle layers of V1, although evident at most cortical depths. Laminar variations were also apparent in the power of the local field potential, with a complementary pattern for low frequency (<10 Hz) and gamma (30–50 Hz) power. Recordings in area V2 revealed a laminar dependence similar to V1 for synchrony, but slow timescale correlations were not different between the input layers and nearby locations. Our results reveal that cortical circuits in different laminae can generate remarkably different patterns of correlations, despite being tightly interconnected.

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Cortical Hemodynamic Mechanisms of Reversal learning using High-Resolution Functional Near-Infrared Spectroscopy: A Pilot Study

10.21203/rs.3.rs-379282/v1 ◽

2021 ◽

Author(s):

charlotte piau ◽

Mahdi Mahmoudzadeh ◽

Astrid Kibleur ◽

Mircea Polosan ◽

Olivier David ◽

...

Keyword(s):

Frontal Cortex ◽

Reversal Learning ◽

Near Infrared ◽

Brain Activity ◽

Inferior Frontal Gyrus ◽

Behavioral Flexibility ◽

Reward Processing ◽

Functional Near Infrared Spectroscopy ◽

Behavioral Abnormalities ◽

Reward And Punishment

Abstract Background: Reversal learning is widely used to analyze cognitive flexibility and characterize behavioral abnormalities associated with impulsivity and disinhibition. Recent studies using fMRI have focused on regions involved in reversal learning with negative and positive reinforcers. Although the frontal cortex has been consistently implicated in reversal learning, few studies have focused on whether reward and punishment may have different effects on lateral frontal structures in these tasks. Here, in eight healthy subjects, we used functional near infra-red spectroscopy (fNIRS) to characterize brain activity dynamics and differentiate the involvement of frontal structures in learning driven by reward and punishment. Results: We observed functional hemispheric asymmetries between punishment and reward processing by fNIRS following reversal of a learned rule. Moreover, the left dorsolateral prefrontal cortex (l-DLPFC) and inferior frontal gyrus (IFG) were activated under the reward condition only, whereas the orbito-frontal cortex (OFC) was significantly activated under the punishment condition, with a tendency towards activation for the right cortical hemisphere (r-DLPFC and r-IFG). Our results are compatible with the suggestion that the DLPFC is involved in the detection of contingency change. We propose a new representation for reward and punishment, with left lateralization for the reward process. Conclusions: These results provide insights into the indirect neural mechanisms of reversal learning and behavioral flexibility and confirm the use of fNIRS imaging in reversal-learning tasks as a translational strategy, particularly in subjects who cannot undergo fMRI recordings.

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