Decision-making, errors, and confidence in the brain.

To provide a fundamental basis for understanding decision-making and decision confidence, we analyze a neuronal spiking attractor-based model of decision-making. The model predicts probabilistic decision-making with larger neuronal responses and larger functional magnetic resonance imaging (fMRI) blood-oxygen-level-dependent (BOLD) responses on correct than on error trials because the spiking noise-influenced decision attractor state of the network is consistent with the external evidence. Moreover, the model predicts that the neuronal activity and the BOLD response will become larger on correct trials as the discriminability ΔI increases and confidence increases and will become smaller as confidence decreases on error trials as ΔI increases.

Taste, olfactory and food texture reward processing in the brain and obesity.

Complementary neuronal recordings 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 the orbitofrontal cortex (OFC), these sensory inputs are for some neurons combined by learning with olfactory and visual inputs, and these neurons encode food reward in that they only respond to food when hungry, and in that activations correlate with subjective pleasantness. Cognitive factors, including word-level descriptions, and attention, modulate the representation of the reward value of food in the OFC.

Choice, difficulty, and confidence in the brain.

To provide a neurobiological basis for understanding decision-making and decision confidence, we describe and analyze a neuronal spiking attractor-based model of decision-making that makes predictions about synaptic and neuronal activity, the fMRI BOLD response, and behavioral choice as a function of the easiness of the decision, and thus decision confidence. The spiking network model predicts probabilistic decision-making with faster and larger neuronal responses on easy versus difficult choices, that is as the discriminability DeltaI between the choices increases, and these and the synaptic currents in turn predict larger BOLD responses as the discriminability increases. Confidence, which increases with discriminability, thus emerges from the firing rates of the decision-making neurons in the choice attractor network.

A computational theory of episodic memory formation in the hippocampus.

A quantitative computational theory of the operation of the hippocampus as an episodic memory system is described. The CA3 system operates as a single attractor or autoassociation network to enable rapid, one-trial associations between any spatial location (place in rodents or spatial view in primates) and an object or reward and to provide for completion of the whole memory during recall from any part. The theory is extended to associations between time and object or reward to implement temporal order memory, also important in episodic memory.

Attractor networks.

An attractor network is a network of neurons with excitatory interconnections that can settle into a stable pattern of firing. This article shows how attractor networks in the cerebral cortex are important for long-term memory, short-term memory, attention, and decision making. The article then shows how the random firing of neurons can influence the stability of these networks by introducing stochastic noise, and how these effects are involved in probabilistic decision making, and implicated in some disorders of cortical function such as poor short-term memory and attention, schizophrenia, and obsessive-compulsive disorder.

Functional neuroimaging of umami taste: what makes umami pleasant?

The cortical processing of umami shows what makes it pleasant and appetitive. The pleasantness of umami reflects and is correlated with processing in the secondary taste cortex in the orbitofrontal cortex and tertiary taste cortex in the anterior cingulate cortex, whereas processing in the primary (insular) taste cortex reflects physical properties such as intensity. However, glutamate presented alone as a taste stimulus is not highly pleasant and does not act synergistically with other tastes (sweet, salt, bitter, and sour).

Neural systems underlying decisions about affective odors.

Decision-making about affective value may occur after the reward value of a stimulus is represented and may involve different brain areas to those involved in decision-making about the physical properties of stimuli, such as intensity. In an fMRI study, we delivered two odors separated by a delay, with instructions on different trials to decide which odor was more pleasant or more intense or to rate the pleasantness and intensity of the second odor without making a decision. The fMRI signals in the medial prefrontal cortex area 10 (medial PFC) and in regions to which it projects, including the anterior cingulate cortex (ACC) and insula, were higher when decisions were being made compared with ratings, implicating these regions in decision-making.

Prediction of subjective affective state from brain activations.

Decoding and information theoretic techniques were used to analyze the predictions that can be made from functional magnetic resonance neuroimaging data on individual trials. The subjective pleasantness produced by warm and cold applied to the hand could be predicted on single trials with typically in the range 60-80% correct from the activations of groups of voxels in the orbitofrontal and medial prefrontal cortex and pregenual cingulate cortex, and the information available was typically in the range 0.1-0.

Computational models of schizophrenia and dopamine modulation in the prefrontal cortex.

Computational neuroscience models can be used to understand the diminished stability and noisy neurodynamical behaviour of prefrontal cortex networks in schizophrenia. These neurodynamical properties can be captured by simulated neural networks with randomly spiking neurons that introduce noise into the system and produce trial-by-trial variation of postsynaptic potentials. Theoretical and experimental studies have aimed to understand schizophrenia in relation to noise and signal-to-noise ratio, which are promising concepts for understanding the symptoms that characterize this heterogeneous illness.

An attractor hypothesis of obsessive-compulsive disorder.

We propose a top-down approach to the symptoms of obsessive-compulsive disorder (OCD) based on a statistical dynamical framework. An increased depth in the basins of attraction of attractor network states in the brain makes each state too stable, so that it tends to remain locked in that state and can not easily be moved on to another state. We suggest that the different symptoms that may be present in OCD could be related to changes of this type in different brain regions.