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Rolls E.T.,Oxford Center for Computational Neuroscience
Pharmacology Biochemistry and Behavior | Year: 2012

A computational neuroscience approach to the symptoms of obsessive-compulsive disorder based on a stochastic neurodynamical framework is described. An increased depth in the basins of attraction of attractor neuronal network states in the brain makes each state too stable, so that it tends to remain locked in that state, and cannot easily be moved on to another state. It is suggested that the different symptoms that may be present in obsessive - compulsive disorder could be related to changes of this type in different brain regions. In integrate-and-fire network simulations, an increase in the NMDA and/or AMPA receptor conductances, which increases the depth of the attractor basins, increases the stability of attractor networks, and makes them less easily moved on to another state by a new stimulus. Increasing GABA-receptor activated currents can partly reverse this overstability. There is now some evidence for overactivity in glutamate transmitter systems in obsessive-compulsive disorder, and the hypothesis presented here shows how some of the symptoms of obsessive-compulsive disorder could be produced by the increase in the stability of attractor networks that is produced by increased glutamatergic activity. In schizophrenia, a reduction of the firing rates of cortical neurons caused for example by reduced NMDA receptor function, present in schizophrenia, can lead to instability of the high firing rate attractor states that normally implement short-term memory and attention, contributing to the cognitive and negative symptoms of schizophrenia. Reduced cortical inhibition caused by a reduction of GABA neurotransmission, present in schizophrenia, can lead to instability of the spontaneous firing states of cortical networks, leading to a noise-induced jump to a high firing rate attractor state even in the absence of external inputs, contributing to the positive symptoms of schizophrenia. © 2011 Elsevier Inc. All rights reserved. Source


Rolls E.T.,Oxford Center for Computational Neuroscience
Frontiers in Human Neuroscience | Year: 2013

Cognition can influence emotion by biasing neural activity in the first cortical region in which the reward value and subjective pleasantness of stimuli is made explicit in the representation, the orbitofrontal cortex. The same effect occurs in a second cortical tier for emotion, the anterior cingulate cortex. Similar effects are found for selective attention, to for example the pleasantness vs the intensity of stimuli, which modulates representations of reward value and affect in the orbitofrontal and anterior cingulate cortices. The mechanisms for the effects of cognition and attention on emotion are top-down biased competition and top-down biased activation. Affective and mood states can in turn influence memory and perception, by backprojected biasing influences. Emotion-related decision systems operate to choose between gene-specified rewards such as taste, touch, and beauty. Reasoning processes capable of planning ahead with multiple steps held in working memory in the explicit system can allow the gene-specified rewards not to be selected, or to be deferred. The stochastic, noisy, dynamics of decision-making systems in the brain may influence whether decisions are made by the selfish-gene-specified reward emotion system, or by the cognitive reasoning system that explicitly calculates reward values that are in the interests of the individual, the phenotype. © 2013 Rolls. Source


Rolls E.T.,Oxford Center for Computational Neuroscience
Journal of Texture Studies | Year: 2011

The brain areas that represent taste also provide a representation of oral texture. Fat texture is represented by neurons independently of viscosity: some neurons respond to fat independently of viscosity, and other neurons encode viscosity. The neurons that respond to fat also respond to silicone and paraffin oil, indicating that the sensing is texture- not chemo-specific. This fat sensing is not related to free fatty acids such as linoleic acid; a few other neurons with responses to free fatty acids typically do not respond to fat in the mouth. Fat texture-sensitive neurons are found in the primary taste cortex, the secondary taste cortex in the orbitofrontal cortex where the pleasantness of food is represented, and in the amygdala. Different neurons respond to different combinations of texture, taste, oral temperature, and in the orbitofrontal cortex to olfactory and visual properties of food. Complementary human functional neuroimaging studies are described. PRACTICAL APPLICATIONS: This research has implications for understanding how fat in the mouth is sensed. It therefore has implications for the design of foods that may mimic the mouthfeel of fat, but not its energy content. © 2011 Wiley Periodicals, Inc. Source


Rolls E.T.,Oxford Center for Computational Neuroscience
Progress in Neurobiology | Year: 2015

Complementary neuronal recordings in primates, and functional neuroimaging in humans, show that the primary taste cortex in the anterior insula provides separate and combined representations of the taste, temperature, and texture (including fat texture) of food in the mouth independently of hunger and thus of reward value and pleasantness. One synapse on, in a second tier of processing, in the orbitofrontal cortex, these sensory inputs are for some neurons combined by associative learning with olfactory and visual inputs, and these neurons encode food reward value on a continuous scale in that they only respond to food when hungry, and in that activations correlate linearly with subjective pleasantness. Cognitive factors, including word-level descriptions, and selective attention to affective value, modulate the representation of the reward value of taste and olfactory stimuli in the orbitofrontal cortex and a region to which it projects, the anterior cingulate cortex, a tertiary taste cortical area. The food reward representations formed in this way play an important role in the control of appetite, and food intake. Individual differences in these reward representations may contribute to obesity, and there are age-related differences in these value representations that shape the foods that people in different age groups find palatable. In a third tier of processing in medial prefrontal cortex area 10, decisions between stimuli of different reward value are taken, by attractor decision-making networks. © 2015 Elsevier Ltd. Source


Rolls E.T.,Oxford Center for Computational Neuroscience
Annual Review of Nutrition | Year: 2016

The taste cortex in the anterior insula provides separate and combined representations of the taste, temperature, and texture of food in the mouth independently of hunger and thus of reward value and pleasantness. One synapse on, in the orbitofrontal cortex, these sensory inputs are combined by associative learning with olfactory and visual inputs for some neurons, and these neurons encode food reward value in that they respond to food only when hunger is present and in that activations correlate linearly with subjective pleasantness. Cognitive factors, including word-level descriptions and selective attention to affective value, modulate the representation of the reward value of taste, olfactory, and flavor stimuli in the orbitofrontal cortex and a region to which it projects, the anterior cingulate cortex. These food reward representations are important in the control of appetite and food intake. Individual differences in reward representations may contribute to obesity, and there are age-related differences in these reward representations. Implications of how reward systems in the brain operate for understanding, preventing, and treating obesity are described. Copyright © 2016 by Annual Reviews. All rights reserved. Source

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