161 results match your criteria: "Oxford Centre for Computational Neuroscience[Affiliation]"

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

Brain

May 2015

1 Centre for Computational Systems Biology, Fudan University, Shanghai, PR China 2 Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK

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.

View Article and Find Full Text PDF

Stochastic cortical neurodynamics underlying the memory and cognitive changes in aging.

Neurobiol Learn Mem

February 2015

Universitat Pompeu Fabra, Theoretical and Computational Neuroscience, Roc Boronat 138, 08018 Barcelona, Spain; Institucio Catalana de Recerca i Estudis Avancats (ICREA), Spain.

The relatively random spiking times of individual neurons provide a source of noise in the brain. We show how this noise interacting with altered depth in the basins of attraction of networks involved in short-term memory, attention, and episodic memory provide an approach to understanding some of the cognitive changes in normal aging. The effects of the neurobiological changes in aging that are considered include reduced synaptic modification and maintenance during learning produced in part through reduced acetylcholine in normal aging, reduced dopamine which reduces NMDA-receptor mediated effects, reduced noradrenaline which increases cAMP and thus shunts excitatory synaptic inputs, and the effects of a reduction in acetylcholine in increasing spike frequency adaptation.

View Article and Find Full Text PDF

A computational theory of hippocampal function, and tests of the theory: new developments.

Neurosci Biobehav Rev

January 2015

Oxford Centre for Computational Neuroscience, Oxford, UK; University of Warwick, Department of Computer Science, Coventry CV4 7AL, UK. Electronic address:

The aims of the paper are to update Rolls' quantitative computational theory of hippocampal function and the predictions it makes about the different subregions (dentate gyrus, CA3 and CA1), and to examine behavioral and electrophysiological data that address the functions of the hippocampus and particularly its subregions. Based on the computational proposal that the dentate gyrus produces sparse representations by competitive learning and via the mossy fiber pathway forces new representations on the CA3 during learning (encoding), it has been shown behaviorally that the dentate gyrus supports spatial pattern separation during learning. Based on the computational proposal that CA3-CA3 autoassociative networks are important for episodic memory, it has been shown behaviorally that the CA3 supports spatial rapid one-trial learning, learning of arbitrary associations where space is a component, pattern completion, spatial short-term memory, and spatial sequence learning by associations formed between successive items.

View Article and Find Full Text PDF

In order to analyze functional connectivity in untreated and treated patients with schizophrenia, resting-state fMRI data were obtained for whole-brain functional connectivity analysis from 22 first-episode neuroleptic-naïve schizophrenia (NNS), 61 first-episode neuroleptic-treated schizophrenia (NTS) patients, and 60 healthy controls (HC). Reductions were found in untreated and treated patients in the functional connectivity between the posterior cingulate gyrus and precuneus, and this was correlated with the reduction in volition from the Positive and Negative Symptoms Scale (PANSS), that is in the willful initiation, sustenance, and control of thoughts, behavior, movements, and speech, and with the general and negative symptoms. In addition in both patient groups interhemispheric functional connectivity was weaker between the orbitofrontal cortex, amygdala and temporal pole.

View Article and Find Full Text PDF

Networks for memory, perception, and decision-making, and beyond to how the syntax for language might be implemented in the brain.

Brain Res

September 2015

Universitat Pompeu Fabra, Theoretical and Computational Neuroscience, Roc Boronat 138, 08018 Barcelona, Spain; Institucio Catalana de Recerca i Estudis Avancats (ICREA), Spain.

Neural principles that provide a foundation for memory, perception, and decision-making include place coding with sparse distributed representations, associative synaptic modification, and attractor networks in which the storage capacity is in the order of the number of associatively modifiable recurrent synapses on any one neuron. Based on those and further principles of cortical computation, hypotheses are explored in which syntax is encoded in the cortex using sparse distributed place coding. Each cortical module 2-3 mm in diameter is proposed to be formed of a local attractor neuronal network with a capacity in the order of 10,000 words (e.

View Article and Find Full Text PDF

Searching for and recognizing objects in complex natural scenes is implemented by multiple saccades until the eyes reach within the reduced receptive field sizes of inferior temporal cortex (IT) neurons. We analyze and model how the dorsal and ventral visual streams both contribute to this. Saliency detection in the dorsal visual system including area LIP is modeled by graph-based visual saliency, and allows the eyes to fixate potential objects within several degrees.

View Article and Find Full Text PDF

Emotion and decision-making explained: response to commentators.

Cortex

January 2015

Oxford Centre for Computational Neuroscience, Oxford, UK; University of Warwick, Department of Computer Science, Coventry, UK. Electronic address:

View Article and Find Full Text PDF

When we see a human sitting down, standing up, or walking, we can recognize one of these poses independently of the individual, or we can recognize the individual person, independently of the pose. The same issues arise for deforming objects. For example, if we see a flag deformed by the wind, either blowing out or hanging languidly, we can usually recognize the flag, independently of its deformation; or we can recognize the deformation independently of the identity of the flag.

View Article and Find Full Text PDF

Emotion and decision-making explained: a précis.

Cortex

October 2014

Oxford Centre for Computational Neuroscience, Oxford, UK; University of Warwick, Department of Computer Science, Coventry, UK. Electronic address:

View Article and Find Full Text PDF

Limbic systems for emotion and for memory, but no single limbic system.

Cortex

January 2015

Oxford Centre for Computational Neuroscience, Oxford, UK; University of Warwick, Department of Computer Science, Coventry, UK. Electronic address:

The concept of a (single) limbic system is shown to be outmoded. Instead, anatomical, neurophysiological, functional neuroimaging, and neuropsychological evidence is described that anterior limbic and related structures including the orbitofrontal cortex and amygdala are involved in emotion, reward valuation, and reward-related decision-making (but not memory), with the value representations transmitted to the anterior cingulate cortex for action-outcome learning. In this 'emotion limbic system' a computational principle is that feedforward pattern association networks learn associations from visual, olfactory and auditory stimuli, to primary reinforcers such as taste, touch, and pain.

View Article and Find Full Text PDF

The mechanisms for pattern completion and pattern separation in the hippocampus.

Front Syst Neurosci

October 2013

Oxford Centre for Computational Neuroscience Oxford, UK ; Department of Computer Science, University of Warwick Coventry, UK.

The mechanisms for pattern completion and pattern separation are described in the context of a theory of hippocampal function in which the hippocampal 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 factors important in the pattern completion in CA3 together with a large number of independent memories stored in CA3 include a sparse distributed representation which is enhanced by the graded firing rates of CA3 neurons, representations that are independent due to the randomizing effect of the mossy fibers, heterosynaptic long-term depression as well as long-term potentiation in the recurrent collateral synapses, and diluted connectivity to minimize the number of multiple synapses between any pair of CA3 neurons which otherwise distort the basins of attraction. Recall of information from CA3 is implemented by the entorhinal cortex perforant path synapses to CA3 cells, which in acting as a pattern associator allow some pattern generalization.

View Article and Find Full Text PDF

A quantitative theory of the functions of the hippocampal CA3 network in memory.

Front Cell Neurosci

June 2013

Oxford Centre for Computational Neuroscience Oxford, UK ; Department of Computer Science, University of Warwick Coventry, UK.

A quantitative computational theory of the operation of the hippocampal CA3 system as an autoassociation or attractor network used in episodic memory system is described. In this theory, 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.

View Article and Find Full Text PDF

Human short term memory has a capacity of several items maintained simultaneously. We show how the number of short term memory representations that an attractor network modeling a cortical local network can simultaneously maintain active is increased by using synaptic facilitation of the type found in the prefrontal cortex. We have been able to maintain 9 short term memories active simultaneously in integrate-and-fire simulations where the proportion of neurons in each population, the sparseness, is 0.

View Article and Find Full Text PDF

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 (OFC). The same effect occurs in a second cortical tier for emotion, the anterior cingulate cortex (ACC). Similar effects are found for selective attention, to for example the pleasantness vs.

View Article and Find Full Text PDF

Complementary neuronal recordings and functional neuroimaging in human subjects 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 and a region to which it projects, the anterior cingulate cortex.

View Article and Find Full Text PDF

It is shown that the randomness of the firing times of neurons in decision-making attractor neuronal networks that is present before the decision cues are applied can cause statistical fluctuations that influence the decision that will be taken. In this rigorous sense, it is possible to partially predict decisions before they are made. This raises issues about free will and determinism.

View Article and Find Full Text PDF

The hypothesis of communication through coherence proposes that coherent or synchronous oscillations in connected neural systems can promote communication. It has been applied mainly to how oscillations interact in connected networks. We tested by simulations whether information transmission about an external stimulus from one network to a second network is influenced by gamma oscillations, by whether the oscillations are coherent, and by their phase.

View Article and Find Full Text PDF

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.

View Article and Find Full Text PDF

The brain areas that represent taste including the primary taste cortex and the orbitofrontal cortex 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-specific not chemo-specific.

View Article and Find Full Text PDF

Taste is a primary reinforcer. Olfactory-taste and visual-taste association learning takes place in the primate including human orbitofrontal cortex to build representations of flavor. Rapid reversal of this learning can occur using a rule-based learning system that can be reset when an expected taste or flavor reward is not obtained, that is by negative reward prediction error, to which a population of neurons in the orbitofrontal cortex responds.

View Article and Find Full Text PDF

We describe the results of quantitative information theoretic analyses of neural encoding, particularly in the primate visual, olfactory, taste, hippocampal, and orbitofrontal cortex. Most of the information turns out to be encoded by the firing rates of the neurons, that is by the number of spikes in a short time window. This has been shown to be a robust code, for the firing rate representations of different neurons are close to independent for small populations of neurons.

View Article and Find Full Text PDF

The connectivity of the cerebral cortex is diluted, with the probability of excitatory connections between even nearby pyramidal cells rarely more than 0.1, and in the hippocampus 0.04.

View Article and Find Full Text PDF

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.

View Article and Find Full Text PDF

Can decisions be predicted from brain activity? It is frequently difficult in neuroimaging studies to determine this, because it is not easy to establish when the decision has been taken. In a rigorous approach to this issue, we show that in a neurally plausible integrate-and-fire attractor-based model of decision-making, the noise generated by the randomness in the spiking times of neurons can be used to predict a decision for 0.5 s or more before the decision cues are applied.

View Article and Find Full Text PDF

Decision time, slow inhibition, and theta rhythm.

J Neurosci

October 2010

Department of Physics, Università di Parma, 43100 Parma, Italy, Oxford Centre for Computational Neuroscience, Oxford OX1 2UD, United Kingdom.

In this paper, we examine decision making in a spiking neuronal network and show that longer time constants for the inhibitory neurons can decrease the reaction times and produce theta rhythm. We analyze the mechanism and find that the spontaneous firing rate before the decision cues are applied can drift, and thereby influence the speed of the reaction time when the decision cues are applied. The drift of the firing rate in the population that will win the competition is larger if the time constant of the inhibitory interneurons is increased from 10 to 33 ms, and even larger if there are two populations of inhibitory neurons with time constants of 10 and 100 ms.

View Article and Find Full Text PDF