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schizophrenia attractor

Jordan P Hamm, Darcy S Peterka, Joseph A Gogos, Rafael Yuste
In schizophrenia, brain-wide alterations have been identified at the molecular and cellular levels, yet how these phenomena affect cortical circuit activity remains unclear. We studied two mouse models of schizophrenia-relevant disease processes: chronic ketamine (KET) administration and Df(16)A+/- , modeling 22q11.2 microdeletions, a genetic variant highly penetrant for schizophrenia. Local field potential recordings in visual cortex confirmed gamma-band abnormalities similar to patient studies. Two-photon calcium imaging of local cortical populations revealed in both models a deficit in the reliability of neuronal coactivity patterns (ensembles), which was not a simple consequence of altered single-neuron activity...
April 5, 2017: Neuron
Edmund T Rolls
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...
January 2010: Wiley Interdisciplinary Reviews. Cognitive Science
Rodrigo Pavão, Adriano B L Tort, Olavo B Amaral
The search for biological causes of mental disorders has up to now met with limited success, leading to growing dissatisfaction with diagnostic classifications. However, it is questionable whether most clinical syndromes should be expected to correspond to specific microscale brain alterations, as multiple low-level causes could lead to similar symptoms in different individuals. In order to evaluate the potential multifactoriality of alterations related to psychiatric illness, we performed a parametric exploration of published computational models of schizophrenia...
July 2015: Schizophrenia Bulletin
Edmund T Rolls
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. There are many decision-making networks in the brain. Some decision systems operate to choose between gene-specified rewards such as taste, touch, and beauty (in for example the peacock's tail)...
2012: Frontiers in Integrative Neuroscience
Itamar Lerner, Shlomo Bentin, Oren Shriki
One of the most pervasive findings in studies of schizophrenics with thought disorders is their peculiar pattern of semantic priming, which presumably reflects abnormal associative processes in the semantic system of these patients. Semantic priming is manifested by faster and more accurate recognition of a word-target when preceded by a semantically related prime, relative to an unrelated prime condition. Compared to control, semantic priming in schizophrenics is characterized by reduced priming effects at long prime-target Stimulus Onset Asynchrony (SOA) and, sometimes, augmented priming at short SOA...
2012: PloS One
Gustavo Deco, Edmund T Rolls, Larissa Albantakis, Ranulfo Romo
Phenomenological models of decision-making, including the drift-diffusion and race models, are compared with mechanistic, biologically plausible models, such as integrate-and-fire attractor neuronal network models. The attractor network models show how decision confidence is an emergent property; and make testable predictions about the neural processes (including neuronal activity and fMRI signals) involved in decision-making which indicate that the medial prefrontal cortex is involved in reward value-based decision-making...
April 2013: Progress in Neurobiology
Edmund T Rolls
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...
February 2012: Pharmacology, Biochemistry, and Behavior
Edmund T Rolls, Gustavo Deco
Computational neuroscience integrate-and-fire attractor network models can be used to understand the factors that alter the stability of cortical networks in the face of noise caused for example by neuronal spiking times. 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...
August 2011: Neuroscience and Biobehavioral Reviews
Peter J Siekmeier
The manner in which hippocampus processes neural signals is thought to be central to the memory encoding process. A theoretically oriented literature has suggested that this is carried out via "attractors" or distinctive spatio-temporal patterns of activity. However, these ideas have not been thoroughly investigated using computational models featuring both realistic single-cell physiology and detailed cell-to-cell connectivity. Here we present a 452 cell simulation based on Traub et al.'s pyramidal cell [Traub RD, Jefferys JG, Miles R, Whittington MA, Toth K...
June 8, 2009: Behavioural Brain Research
Marco Loh, Edmund T Rolls, Gustavo Deco
We propose a top-down approach to the symptoms of schizophrenia based on a statistical dynamical framework. We show that a reduced depth in the basins of attraction of cortical attractor states destabilizes the activity at the network level due to the constant statistical fluctuations caused by the stochastic spiking of neurons. In integrate-and-fire network simulations, a decrease in the NMDA receptor conductances, which reduces the depth of the attractor basins, decreases the stability of short-term memory states and increases distractibility...
November 2007: PLoS Computational Biology
D Todder, S Avissar, G Schreiber
Speech analyses are usually focused on words as signifiers ignoring inter-words time intervals (IWIs), which are related to the 'form' of speech, rather than to its 'content'. Applying the method of power spectrum analysis to inter-vocalizations time intervals of bird singing, underlying periodic processes were detected. In contrast, human IWIs revealed non-periodicity, which may be random or chaotic. To differentiate between these two possibilities, the non-linear dynamic methods of unstable periodic orbits and correlation dimension were applied to show that IWIs are characterized by a low dimensional chaotic attractor...
December 2001: Medical Hypotheses
L H Finkel
The techniques of computational simulation have begun to be applied to modeling neurological disease and mental illness. Such neuroengineering models provide a conceptual bridge between molecular/cellular pathology and cognitive performance. We consider models of Alzheimer's disease, Parkinson's disease, and schizophrenia. Each of these diseases involves a disorder of neuromodulation coupled with underlying neuronal pathology. Parallels arising between these models suggests that a common set of computational mechanisms may account for functional loss across a spectrum of brain diseases...
2000: Annual Review of Biomedical Engineering
R E Hoffman, T H McGlashan
There is considerable neurobiological evidence suggesting that schizophrenia is associated with reduced corticocortical connectivity. The authors describe two neural network computer simulations that explore functional consequences of these abnormalities. The first utilized an "attractor" neural network capable of content-addressable memory. Application of a pruning rule that eliminated weaker connections over longer distances produced functional fragmentation and the emergence of localized, "parasitic" attractors that intruded into network dynamics...
October 2001: Neuroscientist: a Review Journal Bringing Neurobiology, Neurology and Psychiatry
Y J Lee, Y S Zhu, Y H Xu, M F Shen, H X Zhang, N V Thakor
OBJECTIVE: The aim of this study is to detect non-linearity in the EEG of schizophrenia with a modified method of surrogate data. We also want to identify if dimension complexity (correlation dimension using spatial embedding) could be used as a discriminating statistic to demonstrate non-linearity in the EEG. The difference between the attractor dimension of healthy subjects and schizophrenic subjects is expected to be interpreted as reflecting some mechanisms underlying brain wave by views of non-linear dynamics analysis may reflect mechanistic differences...
July 2001: Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology
L Pezard, J L Nandrino
For the last thirty years, progress in the field of physics, known as "Chaos theory"--or more precisely: non-linear dynamical systems theory--has increased our understanding of complex systems dynamics. This framework's formalism is general enough to be applied in other domains, such as biology or psychology, where complex systems are the rule rather than the exception. Our goal is to show here that this framework can become a valuable tool in scientific fields such as neuroscience and psychiatry where objects possess natural time dependency (i...
May 2001: L'Encéphale
Z J Kowalik, A Schnitzler, H Freund, O W Witte
OBJECTIVE: In terms of dynamical system theory the rapid alteration of electromagnetic brain signal properties observed with transition from interictal into ictal epileptic activity implies an alteration between at least two dynamical states (attractors). We explored whether such a multistability is reflected also in the dynamical characteristics of the interictal signal. METHODS: A combined method consisting of structural MRI, multichannel magnetoencephalography (MEG) and the non-linear dynamics was applied for the detection of subthreshold interictal activity in temporal lobe epilepsy...
January 2001: Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology
E Ruppin
This paper presents the hypothesis that NMDA receptor delayed maturation (NRDM) may lead to the pathogenesis of schizophrenic psychotic symptoms. This hypothesis is further analyzed in the language of a neural modeling formulation. This formulation points to a possible chain of pathological events, leading from molecular-level NRDM to over-increased synaptic plasticity, and to the formation of pathological attractors, a putative macroscopic-level correlate of schizophrenic positive symptoms. The relations of the NRDM hypothesis to other alterations which are assumed to take place in schizophrenia are discussed, together with possible ways to test this hypothesis...
May 2000: Medical Hypotheses
R E Hoffman
Recent studies have suggested that reduced corticocortical connectivity is associated with schizophrenia. My colleagues and I have used neural network simulations to explore parallel, distributed processing systems with reduced connectivity. These systems often behaved in a "schizophrenic-like" manner. Excessively pruned attractor networks became functionally fragmented, suggesting "loose associations," and produced recurrent, intrusive representations suggestive of delusions. Pruning backpropagation simulations of speech perception networks produced spontaneous output, which provided a model of auditory hallucination or "voices...
May 1997: M.D. Computing: Computers in Medical Practice
D Horn, E Ruppin
We investigate the effect of synaptic compensation on the dynamic behavior of an attractor neural network receiving its input stimuli as external fields projecting on the network. It is shown how, in the face of weakened inputs, memory performance may be preserved by strengthening internal synaptic connections and increasing the noise level. Yet, these compensatory changes necessarily have adverse side effects, leading to spontaneous, stimulus-independent retrieval of stored patterns. These results can support Stevens' recent hypothesis that the onset of schizophrenia is associated with frontal synaptic regeneration, occurring subsequent to the degeneration of temporal neurons projecting on these areas...
January 1995: Neural Computation
B A Huberman
In this paper, I have introduced and solved a simple deterministic model of eye tracking that produces rich dynamical behavior. Some of its main features, notably the existence of a chaotic regime, are reminiscent of the anomalies reported in smooth pursuit eye tracking experiments with schizophrenia patients. By obtaining the state diagram of such a model as a function of target frequency and amplitude, we showed the existence of a chaotic regime characterized by a strange attractor in phase-space and associated random velocity arrests in the eye dynamics...
1987: Annals of the New York Academy of Sciences
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