Emotion and Decision-making Explained

Rolls, Edmund T.

doi:10.1093/acprof:oso/9780199659890.001.0001

Cited by 208 publications

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“…As Broca's area is important for syntactic functions, 47 we suggest that this increased connectivity may be related to the thought disorders in schizophrenia, as syntax is important in multi-step thinking. 48 It is interesting to note that the predisposition to schizophrenia may be a component of a Homo sapiens-specific variation associated with the capacity for language. 49 Our results are consistent with this hypothesis.…”

Section: Discussionmentioning

confidence: 99%

Brain-Wide Analysis of Functional Connectivity in First-Episode and Chronic Stages of Schizophrenia

Wang

Zhang

et al. 2016

SCHBUL

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Published reports of functional abnormalities in schizophrenia remain divergent due to lack of staging point-of-view and whole-brain analysis. To identify key functional-connectivity differences of first-episode (FE) and chronic patients from controls using resting-state functional MRI, and determine changes that are specifically associated with disease onset, a clinical staging model is adopted. We analyze functionalconnectivity differences in prodromal, FE (mostly drug naïve), and chronic patients from their matched controls from 6 independent datasets involving a total of 789 participants (343 patients). Brain-wide functional-connectivity analysis was performed in different datasets and the results from the datasets of the same stage were then integrated by meta-analysis, with Bonferroni correction for multiple comparisons. Prodromal patients differed from controls in their pattern of functionalconnectivity involving the inferior frontal gyri (Broca's area). In FE patients, 90% of the functional-connectivity changes involved the frontal lobes, mostly the inferior frontal gyrus including Broca's area, and these changes were correlated with delusions/blunted affect. For chronic patients, functionalconnectivity differences extended to wider areas of the brain, including reduced thalamo-frontal connectivity, and increased thalamo-temporal and thalamo-sensorimoter connectivity that were correlated with the positive, negative, and general symptoms, respectively. Thalamic changes became prominent at the chronic stage. These results provide evidence for distinct patterns of functional-dysconnectivity across FE and chronic stages of schizophrenia. Importantly, abnormalities in the frontal language networks appear early, at the time of disease onset. The identification of stage-specific pathological processes may help to understand the disease course of schizophrenia and identify neurobiological markers crucial for early diagnosis.

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Section: Discussionmentioning

confidence: 99%

Brain-Wide Analysis of Functional Connectivity in First-Episode and Chronic Stages of Schizophrenia

Wang

Zhang

et al. 2016

SCHBUL

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144

132

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“…The aim of the research described here is to investigate the neuronal mechanisms that may underlie the computation of non-reward in the primate including human orbitofrontal cortex , Rolls 2014. This is a fundamentally important process involved in changing behavior when an expected reward is not received.…”

Section: Accepted Manuscriptmentioning

confidence: 99%

“…In the investigation described here, we develop hypotheses about the mechanisms involved in the computation of non-reward in the orbitofrontal cortex (Section 3) based on neurophysiological, functional neuroimaging, and neuropsychological evidence on the orbitofrontal cortex (Section 2). (These hypotheses are based on the functions of the orbitofrontal cortex in primates including humans, given the evidence that most of the orbitofrontal part that is present in rodents is agranular, and does not correspond to most of the primate including human orbitofrontal cortex (Wise 2008, Passingham and Wise 2012, Rolls 2014). ) We then develop an integrate-and-fire neuronal network model of how the non-reward signal is computed, and simulate the model to elucidate its properties, and to examine the parameters for the correct operation of the model (Sections 3 and 4).…”

Section: Accepted Manuscriptmentioning

confidence: 99%

“…These neurons do not respond when an expected punishment is received, for example the taste of salt from a correctly labelled dispenser. Different non-reward neurons may respond in different tasks, providing the potential for behaviour to reverse in one task, but not in all tasks , Rolls 2014. The existence of neurons in the middle part of the macaque orbitofrontal cortex that respond to non-reward ) (originally described by Thorpe, Maddison and Rolls (1979) and Rolls (1981)) is confirmed by recordings that revealed 10 such non-reward neurons (of 140 recorded, or approximately 7%) found in delayed match to sample and delayed response tasks by Joaquin Fuster and colleagues (Rosenkilde, Bauer and Fuster 1981).…”

Section: A C C E P T E D Accepted Manuscriptmentioning

confidence: 99%

“…The orbitofrontal cortex is likely to be where non-reward is computed, for not only does it contain non-reward neurons, but it also contains neurons that encode the signals from which non-reward is computed. These signals include a representation of Expected Reward, and Reward Outcome (Rolls 2014). Expected reward is represented in the primate orbitofrontal cortex in that many neurons respond to the sight of a food reward , learn to respond to any visual stimulus associated with a food reward (Rolls, Critchley, Mason and Wakeman 1996), very rapidly reverse the stimulus to which they respond when the reward outcome associated with each stimulus changes (Rolls, Critchley, Mason and Wakeman 1996), and represent reward value in that they stop responding to a visual stimulus when the reward is devalued by satiation (Critchley and Rolls 1996a).…”

Section: A C C E P T E D Accepted Manuscriptmentioning

confidence: 99%

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Non-reward neural mechanisms in the orbitofrontal cortex

Rolls

Deco

2016

Cortex

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Single neurons in the primate orbitofrontal cortex respond when an expected reward is not obtained, and behavior must change. The human lateral orbitofrontal cortex is activated when non-reward, or loss occurs. The neuronal computation of this negative reward prediction error is fundamental for the emotional changes associated with non-reward, and with changing behavior. Little is known about the neuronal mechanism. Here we propose a mechanism, which we formalize into a neuronal network model, which is simulated to enable the operation of the mechanism to be investigated. A single attractor network has a Reward population (or pool) of neurons that is activated by Expected Reward, and maintain their firing until, after a time, synaptic depression reduces the firing rate in this neuronal population. If a Reward Outcome is not received, the decreasing firing in the Reward neurons releases the inhibition implemented by inhibitory neurons, and this results in a second population of Non-Reward neurons to start and continue firing encouraged by the spiking-related noise in the network. If a Reward Outcome is received, this keeps the Reward attractor active, and this through the inhibitory neurons prevents the Non-Reward attractor neurons from being activated. If an Expected Reward has been signalled, and the Reward Attractor neurons are active, their firing can be directly inhibited by a Non-Reward Outcome, and the Non-Reward neurons become activated because the inhibition on them is released. The neuronal mechanism in the orbitofrontal cortex for computing negative reward prediction error are important, for this system may be over-reactive in depression, under-reactive in impulsive behavior, and may influence the dopaminergic 'prediction error' neurons.

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Olfactory Memory

White

Møller

Köster³

et al. 2015

Handbook of Olfaction and Gustation

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Chapter 46 Neural Integration of Taste, Smell, Oral Texture, and Visual Modalities Investigations in Primates including Humans TASTE PROCESSING IN THE PRIMATE BRAIN PathwaysA diagram of the taste and related olfactory, somatosensory, and visual pathways in primates is shown in Figure 46.1. Taste Processing in the Primate Brain 1031The multimodal convergence that enables single neurons to respond to different combinations of taste, olfactory, texture, temperature, and visual inputs to represent different flavors produced often by new combinations of sensory input is a theme of that will be addressed.

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Emotion and Decision-making Explained

Cited by 208 publications

References 0 publications

Brain-Wide Analysis of Functional Connectivity in First-Episode and Chronic Stages of Schizophrenia

Brain-Wide Analysis of Functional Connectivity in First-Episode and Chronic Stages of Schizophrenia

Non-reward neural mechanisms in the orbitofrontal cortex

Olfactory Memory

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