Showing papers by "Edmund T. Rolls published in 2015"

Autism: reduced connectivity between cortical areas involved in face expression, theory of mind, and the sense of self.

Abstract: Whole-brain voxel-based unbiased resting state functional connectivity was analysed in 418 subjects with autism and 509 matched typically developing individuals. We identified a key system in the middle temporal gyrus/superior temporal sulcus region that has reduced cortical functional connectivity (and increased with the medial thalamus), which is implicated in face expression processing involved in social behaviour. This system has reduced functional connectivity with the ventromedial prefrontal cortex, which is implicated in emotion and social communication. The middle temporal gyrus system is also implicated in theory of mind processing. We also identified in autism a second key system in the precuneus/superior parietal lobule region with reduced functional connectivity, which is implicated in spatial functions including of oneself, and of the spatial environment. It is proposed that these two types of functionality, face expression-related, and of one’s self and the environment, are important components of the computations involved in theory of mind, whether of oneself or of others, and that reduced connectivity within and between these regions may make a major contribution to the symptoms of autism.

Invariant Visual Object and Face Recognition: Neural and Computational Bases, and a Model, VisNet

Abstract: Neurophysiological evidence for invariant representations of objects and faces in the primate inferior temporal visual cortex is described. Then a computational approach to how invariant representations are formed in the brain is described that builds on the neurophysiology. A feature hierarchy model in which invariant representations can be built by self-organizing learning based on the temporal and spatial statistics of the visual input produced by objects as they transform in the world is described. VisNet can use temporal continuity in an associative synaptic learning rule with a short-term memory trace, and/or it can use spatial continuity in continuous spatial transformation learning which does not require a temporal trace. The model of visual processing in the ventral cortical stream can build representations of objects that are invariant with respect to translation, view, size, and also lighting. The model has been extended to provide an account of invariant representations in the dorsal visual system of the global motion produced by objects such as looming, rotation, and object-based movement. The model has been extended to incorporate top-down feedback connections to model the control of attention by biased competition in, for example, spatial and object search tasks. The approach has also been extended to account for how the visual system can select single objects in complex visual scenes, and how multiple objects can be represented in a scene. The approach has also been extended to provide, with an additional layer, for the development of representations of spatial scenes of the type found in the hippocampus.

Invariant visual object recognition: biologically plausible approaches

Abstract: Key properties of inferior temporal cortex neurons are described, and then, the biological plausibility of two leading approaches to invariant visual object recognition in the ventral visual system is assessed to investigate whether they account for these properties. Experiment 1 shows that VisNet performs object classification with random exemplars comparably to HMAX, except that the final layer C neurons of HMAX have a very non-sparse representation (unlike that in the brain) that provides little information in the single-neuron responses about the object class. Experiment 2 shows that VisNet forms invariant representations when trained with different views of each object, whereas HMAX performs poorly when assessed with a biologically plausible pattern association network, as HMAX has no mechanism to learn view invariance. Experiment 3 shows that VisNet neurons do not respond to scrambled images of faces, and thus encode shape information. HMAX neurons responded with similarly high rates to the unscrambled and scrambled faces, indicating that low-level features including texture may be relevant to HMAX performance. Experiment 4 shows that VisNet can learn to recognize objects even when the view provided by the object changes catastrophically as it transforms, whereas HMAX has no learning mechanism in its S---C hierarchy that provides for view-invariant learning. This highlights some requirements for the neurobiological mechanisms of high-level vision, and how some different approaches perform, in order to help understand the fundamental underlying principles of invariant visual object recognition in the ventral visual stream.

Cognitive Informatics and Computational Intelligence: From Information Revolution to Intelligence Revolution

Abstract: Cognitive Informatics CI is a contemporary multidisciplinary field spanning across computer science, information science, cognitive science, brain science, intelligence science, knowledge science, cognitive linguistics, and cognitive philosophy. Cognitive Computing CC is a novel paradigm of intelligent computing methodologies and systems based on CI that implements computational intelligence by autonomous inferences and perceptions mimicking the mechanisms of the brain. This paper reports a set of position statements presented in the plenary panel of IEEE ICCI*CC'14 on Cognitive Informatics and Cognitive Computing. The summary is contributed by invited panelists who are part of the world's renowned researchers and scholars in the transdisciplinary field of cognitive informatics and cognitive computing.

Diluted connectivity in pattern association networks facilitates the recall of information from the hippocampus to the neocortex

Abstract: The recall of information stored in the hippocampus involves a series of corticocortical backprojections via the entorhinal cortex, parahippocampal gyrus, and one or more neocortical stages. Each stage is considered to be a pattern association network, with the retrieval cue at each stage the firing of neurons in the previous stage. The leading factor that determines the capacity of this multistage pattern association backprojection pathway is the number of connections onto any one neuron, which provides a quantitative basis for why there are as many backprojections between adjacent stages in the hierarchy as forward projections. The issue arises of why this multistage backprojection system uses diluted connectivity. One reason is that a multistage backprojection system with expansion of neuron numbers at each stage enables the hippocampus to address during recall the very large numbers of neocortical neurons, which would otherwise require hippocampal neurons to make very large numbers of synapses if they were directly onto neocortical neurons. The second reason is that as shown here, diluted connectivity in the backprojection pathways reduces the probability of more than one connection onto a receiving neuron in the backprojecting pathways, which otherwise reduces the capacity of the system, that is the number of memories that can be recalled from the hippocampus to the neocortex. For similar reasons, diluted connectivity is advantageous in pattern association networks in other brain systems such as the orbitofrontal cortex and amygdala; for related reasons, in autoassociation networks in, for example, the hippocampal CA3 and the neocortex; and for the different reason that diluted connectivity facilitates the operation of competitive networks in forward-connected cortical systems.

Neural Integration of Taste, Smell, Oral Texture, and Visual Modalities

Abstract: The aims of this chapter are to describe how taste, olfactory, visual, oral sensory, and other sensory inputs are combined in the brain, how a representation of reward value is produced, and how cognition and selective attention influence this processing.

Neurobiological foundations of art and aesthetics

Abstract: A theory of the neurobiological foundations of aesthetics and art is described. This has its roots in emotion, in which what is pleasant or unpleasant, a reward or punisher, is the result of an volutionary process in which genes define the (pleasant or unpleasant) goals for action (Rolls 2005, 2013a). It is argued that combinations of multiple such factors provide part of the basis for aesthetics. To this is added the operation of the reasoning syntactic brain system which evolved to help solve difficult multi-step problems, and the use of which is encouraged by pleasant feelings when elegant, simple, and hence aesthetic solutions are found that are advantageous because they are parsimonious, and follow Occam’s Razor. The combination of these two systems, and the interactions between them provide an approach to understanding aesthetics that is rooted in evolution and its effects on brain design and function (Rolls 2011a, 2012).

Emotion, Neural Basis of

Abstract: Emotions can usefully be defined as states produced by rewards and punishers. Emotions prepare the body for action, but perhaps their most important function is to enable appropriate actions to be produced to stimuli and events that are rewards or punishers. The rewarding stimuli or events can be innate (gene-specified) or learned. The orbitofrontal cortex is especially important in emotion, because it represents rewards and punishers, and learns about which previously neutral stimuli are associated with rewards and punishers, and when these associations change. For this fundamental reason, parts of the brain such as the orbitofrontal cortex are important in social and emotional behavior. The anterior cingulate cortex receives from the orbitofrontal cortex and is involved in learning goal-directed actions to obtain reward or avoid punishers. The amygdala is an evolutionarily older system also involved in some responses to emotional stimuli.

Taste and smell, psychology of

Abstract: There are five types of taste receptor cell, sweet, salt, bitter, sour, and umami (protein taste). There are 1000 olfactory receptor genes each specifying a different type of receptor each for a set of odors. Tastes are primary, unlearned, rewards and punishers, and are important in emotion. Pheromones and some other olfactory stimuli are primary reinforcers, but for many odors the reward value is learned by stimulus–reinforcer association learning. 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, these sensory inputs are for some neurons combined by learning with olfactory and visual inputs, and these neurons encode food reward value 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 taste, odor, and flavor in the orbitofrontal cortex and a region to which it projects, the anterior cingulate cortex. Further, there are individual differences in the representation of the reward value of food in the orbitofrontal cortex. Overeating and obesity are related in many cases to an increased reward value of the sensory inputs produced by foods, and their modulation by cognition and attention that override existing satiety signals

Taste, flavor, and appetite

Abstract: 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 associative 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 selective attention to affective value modulate the representation of the reward value of taste and olfactory stimuli in the OFC 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.

The neuronal representation of information in the human brain

Abstract: The responses of single neurons provide evidence that is essential to understanding what information is encoded in a brain area, and how it is encoded, for the information conveyed by a single neuron is almost independent of that conveyed by others in the same population. The differences in the firing rate response profiles of single neurons to a set of stimuli or events encode most of the information about that stimulus or event. The representation is sparsely distributed, with neurons often having an approximately exponential firing rate distribution, with high firing rates to a few stimuli, and smaller and smaller responses to other stimuli in the set, and no response to most of the stimuli. It is in this way that information about particular stimuli is represented. For example, in the inferior temporal visual cortex, neurons encode in this manner which particular face or object is being shown (Rolls and Treves, 2011). Evidence of this type is crucial to understanding the operation of the brain, for by reading the code from different connected brain areas, it is possible to start to understand what is being performed (or computed) by each brain region. This in turn is important for understanding neurological and psychiatric disorders and their symptoms, and for suggesting treatments based on what each brain region is performing, and developing hypotheses about how each cortical area operates (Rolls, 2008, 2016). Much of the evidence on what is represented in different cortical areas comes from single neuron studies in macaques, including concepts about the roles of cortical areas that correspond to those in humans. The book Single Neuron Studies of the Human Brain - Probing Cognition edited by Fried, Rutishauser, Cerf and Kreiman is therefore important, for it reviews what is now being discovered from recordings from single …