scholarly journals Computational Roles of Intrinsic Synaptic Dynamics

2021 ◽  
Author(s):  
Genki Shimizu ◽  
Kensuke Yoshida ◽  
Haruo Kasai ◽  
Taro Toyoizumi
Keyword(s):  
Information Processing ◽  
Network Performance ◽  
Information Storage ◽  
List Type ◽  
Stable Performance ◽  
Synaptic Dynamics ◽  
Experimental Findings ◽  
The Brain ◽  
Stable Network

AbstractConventional theories assume that long-term information storage in the brain is implemented by modifying synaptic efficacy. Recent experimental findings challenge this view by demonstrating that dendritic spine sizes, or their corresponding synaptic weights, are highly volatile even in the absence of neural activity. Here we review previous computational works on the roles of these intrinsic synaptic dynamics. We first present the possibility for neuronal networks to sustain stable performance in their presence and we then hypothesize that intrinsic dynamics could be more than mere noise to withstand, but they may actually improve information processing in the brain.Highlights- Synapses exhibit changes due to intrinsic as well as extrinsic dynamics- Computational frameworks suggest stable network performance despite intrinsic changes- Intrinsic dynamics might be beneficial to information processing

scholarly journals Transitions in brain-network level information processing dynamics are driven by alterations in neural gain

2019 ◽  
Author(s):  
Mike Li ◽  
Yinuo Han ◽  
Matthew J. Aburn ◽  
Michael Breakspear ◽  
Russell A. Poldrack ◽  
...  
Keyword(s):  
Information Processing ◽  
Information Transfer ◽  
Large Scale ◽  
Functional Integration ◽  
Brain Network ◽  
Information Storage ◽  
Transfer Entropy ◽  
Arousal System ◽  
Neural Gain ◽  
The Brain

AbstractA key component of the flexibility and complexity of the brain is its ability to dynamically adapt its functional network structure between integrated and segregated brain states depending on the demands of different cognitive tasks. Integrated states are prevalent when performing tasks of high complexity, such as maintaining items in working memory, consistent with models of a global workspace architecture. Recent work has suggested that the balance between integration and segregation is under the control of ascending neuromodulatory systems, such as the noradrenergic system. In a previous large-scale nonlinear oscillator model of neuronal network dynamics, we showed that manipulating neural gain led to a ‘critical’ transition in phase synchrony that was associated with a shift from segregated to integrated topology, thus confirming our original prediction. In this study, we advance these results by demonstrating that the gain-mediated phase transition is characterized by a shift in the underlying dynamics of neural information processing. Specifically, the dynamics of the subcritical (segregated) regime are dominated by information storage, whereas the supercritical (integrated) regime is associated with increased information transfer (measured via transfer entropy). Operating near to the critical regime with respect to modulating neural gain would thus appear to provide computational advantages, offering flexibility in the information processing that can be performed with only subtle changes in gain control. Our results thus link studies of whole-brain network topology and the ascending arousal system with information processing dynamics, and suggest that the constraints imposed by the ascending arousal system constrain low-dimensional modes of information processing within the brain.Author summaryHigher brain function relies on a dynamic balance between functional integration and segregation. Previous work has shown that this balance is mediated in part by alterations in neural gain, which are thought to relate to projections from ascending neuromodulatory nuclei, such as the locus coeruleus. Here, we extend this work by demonstrating that the modulation of neural gain alters the information processing dynamics of the neural components of a biophysical neural model. Specifically, we find that low levels of neural gain are characterized by high Active Information Storage, whereas higher levels of neural gain are associated with an increase in inter-regional Transfer Entropy. Our results suggest that the modulation of neural gain via the ascending arousal system may fundamentally alter the information processing mode of the brain, which in turn has important implications for understanding the biophysical basis of cognition.

Cannabis and the Brain

1996 ◽  
Vol 30 (2) ◽  
pp. 179-183 ◽  
Author(s):  
David J. Castle ◽  
Frances R. Ames
Keyword(s):  
Information Processing ◽  
Literature Review ◽  
Human Brain ◽  
Cannabis Sativa ◽  
Cerebral Damage ◽  
Functional Psychoses ◽  
Precise Relationship ◽  
Relationship Of ◽  
The Brain

Objective: The aim of the paper is to review the effects of Cannabis sativa on the human brain. Method: A selective literature review was undertaken. Results/Conclusions: Cannabis sativa causes an acute and, with regular heavy ingestion, a subacute encephalopathy. There is no evidence of irreversible cerebral damage resulting from its use, although impairment of information processing might be a long-term consequence of heavy prolonged use. The precise relationship of cannabis to the functional psychoses such as schizophrenia has yet to be clarified.

scholarly journals Long-Lasting Effects of GABA Infusion Into the Cerebral Cortex of the Rat

2000 ◽  
Vol 7 (1-2) ◽  
pp. 1-8 ◽  
Author(s):  
Teresa Montiel ◽  
Daniel Almeida ◽  
Iván Arango ◽  
Eduardo Calixto ◽  
César Casasola ◽  
...  
Keyword(s):  
Protein Synthesis ◽  
Long Term Potentiation ◽  
Information Storage ◽  
Protein Synthesis Inhibitor ◽  
Synthesis Inhibitor ◽  
Receptor Stimulation ◽  
Paroxysmal Activity ◽  
The Brain

In electrophysiological terms, experimental models of durable information storage in the brain include long-term potentiation (LTP), long-term depression, and kindling. Protein synthesis correlates with these enduring processes. We propose a fourth example of long-lasting information storage in the brain, which we call the GABA-withdrawal syndrome (GWS). In rats, withdrawal of a chronic intracortical infusion of GABA, a ubiquitous inhibitory neurotransmitter, induced epileptogenesis at the infusion site. This overt GWS lasted for days. Anisomycin, a protein synthesis inhibitor, prevented the appearance of GWSin vivo. Hippocampal and neocortical slices showed a similar post-GABA hyperexcitabilityin vitroand an enhanced susceptibility to LTP induction. One to four months after the epileptic behavior disappeared, systemic administration of a subconvulsant dose of pentylenetetrazol produced the reappearance of paroxysmal activity. The long-lasting effects of tonicGABAAreceptor stimulation may be involved in long-term information storage processes at the cortical level, whereas the cessation ofGABAAreceptor stimulation may be involved in chronic pathological conditions, such as epilepsy. Furthermore, we propose that GWS may represent a common key factor in the addiction to GABAergic agents (for example, barbiturates, benzodiazepines, and ethanol). GWS represents a novel form of neurono-glial plasticity. The mechanisms of this phenomenon remain to be understood.

The Cognitive Informatics Theory and Mathematical Models of Visual Information Processing in the Brain

2011 ◽  
pp. 215-224
Author(s):  
Yingxu Wang
Keyword(s):  
Information Processing ◽  
Visual Information ◽  
Visual Information Processing ◽  
Human Vision ◽  
Long Term Memory ◽  
Cognitive Informatics ◽  
Visual Frame ◽  
Cognitive Principles ◽  
The Brain

It is recognized that the internal mechanisms for visual information processing are based on semantic inferences where visual information is represented and processed as visual semantic objects rather than direct images or episode pictures in the long-term memory. This article presents a cognitive informatics theory of visual information and knowledge processing in the brain. A set of cognitive principles of visual perception is reviewed particularly the classic gestalt principles, the cognitive informatics principles, and the hypercolumn theory. A visual frame theory is developed to explain the visual information processing mechanisms of human vision, where the size of a unit visual frame is tested and calibrated based on vision experiments. The framework of human visual information processing is established in order to elaborate mechanisms of visual information processing and the compatibility of internal representations between visual and abstract information and knowledge in the brain.

Evaluation of a Neural Network Model of Amnesia in Diffuse Cerebral Atrophy

1993 ◽  
Vol 163 (2) ◽  
pp. 217-222 ◽  
Author(s):  
James R. G. Carrie
Keyword(s):  
Neural Network ◽  
Distributed Storage ◽  
Memory Function ◽  
Cerebral Atrophy ◽  
Information Storage ◽  
Memory Storage ◽  
Distributed Network ◽  
Cerebral Disease ◽  
The Brain

A digital computer program generating a simulated neural network was used to construct a model which can show behaviour resembling human associative memory. The experimental network uses distributed storage, and, in this respect, its functional organisation resembles that suggested by reported observations of neuronal activity in the human temporal lobe during memory storage and recall. Inactivation of increasing numbers of randomly distributed network units simulated advancing cerebral atrophy. This caused progressive impairment of performance, resembling the gradual deterioration of memory function observed in chronic diffuse cerebral degeneration. Unit inactivation had similar effects on recall whether the same units were inactivated before or after learning. This differs from most relevant observations of amnesia resulting from diffuse cerebral disease. While the model may functionally resemble long-term information storage sites in the brain, other cerebral mechanisms participating in learning and remembering are also damaged by diffuse cerebral atrophy.

scholarly journals A neural network account of memory replay and knowledge consolidation

2021 ◽  
Author(s):  
Daniel N Barry ◽  
Bradley C Love
Keyword(s):  
Neural Network ◽  
Network Performance ◽  
Occipital Cortex ◽  
Long Term Memory ◽  
Visual Stream ◽  
Functional Roles ◽  
Early Visual Cortex ◽  
Past Experiences ◽  
The Brain

Replay can consolidate memories by offline neural reactivation related to past experiences. Category knowledge is learned across multiple experiences and subsequently generalised to new situations. This ability to generalise is promoted by offline consolidation and replay during rest and sleep. However, aspects of replay are difficult to determine from neuroimaging studies alone. Here, we provide a comprehensive account of how category replay may work in the brain by simulating these processes in a neural network which assumed the functional roles of the human ventral visual stream and hippocampus. We showed that generative replay, akin to imagining entirely new instances of a category, facilitated generalisation to new experiences. This invites a reconsideration of the nature of replay more generally, and suggests that replay helps to prepare us for the future as much as remember the past. We simulated generative replay at different network locations finding it was most effective in later layers equivalent to the lateral occipital cortex, and less effective in layers corresponding to early visual cortex, thus drawing a distinction between the observation of replay in the brain and its relevance to consolidation. We modelled long-term memory consolidation in humans and found that category replay is most beneficial for newly acquired knowledge, at a time when generalisation is still poor, a finding which suggests replay helps us adapt to changes in our environment. Finally, we present a novel mechanism for the frequent observation that the brain selectively consolidates weaker information, and showed that a reinforcement learning process in which categories were replayed according to their contribution to network performance explains this well-documented phenomenon, thus reconceptualising replay as an active rather than passive process.

scholarly journals Computational Models of Neuron-Astrocyte Interactions Lead to Improved Efficacy in the Performance of Neural Networks

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Alberto Alvarellos-González ◽  
Alejandro Pazos ◽  
Ana B. Porto-Pazos
Keyword(s):  
Neural Network ◽  
Information Processing ◽  
Network Performance ◽  
Computational Models ◽  
Classification Problem ◽  
Artificial Neuron ◽  
Network Function ◽  
Problem Resolution ◽  
Artificial Neurons ◽  
The Brain

The importance of astrocytes, one part of the glial system, for information processing in the brain has recently been demonstrated. Regarding information processing in multilayer connectionist systems, it has been shown that systems which include artificial neurons and astrocytes (Artificial Neuron-Glia Networks) have well-known advantages over identical systems including only artificial neurons. Since the actual impact of astrocytes in neural network function is unknown, we have investigated, using computational models, different astrocyte-neuron interactions for information processing; different neuron-glia algorithms have been implemented for training and validation of multilayer Artificial Neuron-Glia Networks oriented toward classification problem resolution. The results of the tests performed suggest that all the algorithms modelling astrocyte-induced synaptic potentiation improved artificial neural network performance, but their efficacy depended on the complexity of the problem.

scholarly journals Cannabis points to the synaptic pathology of mental disorders: how aberrant synaptic components disrupt the highest psychological functions

2020 ◽  
Vol 22 (3) ◽  
pp. 251-258
Keyword(s):  
Information Processing ◽  
Cognitive Deficits ◽  
Dendritic Spines ◽  
Psychiatric Genetics ◽  
Neuronal Dynamics ◽  
Psychotic Reaction ◽  
Synaptic Pathology ◽  
Psychological Functions ◽  
The Brain

Cannabis can elicit an acute psychotic reaction, and its long-term use is a risk factor for schizophrenia. The main active psychoactive ingredient ∆9-tetrahydrocannabinol (Δ9 -THC) activates cannabinoid 1 (CB1) receptors, which are localized to the terminals of glutamate and GABA neurons in the brain. The endogenous cannabinoids are involved in information processing and plasticity at synapses in the hippocampus, basal ganglia, and cerebral cortex. Exogenously applied CB1 receptor agonists disrupt neuronal dynamics and synaptic plasticity, resulting in cognitive deficits and impairment of the highest psychological functions. Various other pro-psychotic drugs, such as ketamine and methamphetamine, exert their effects in the same microdomain of synaptic spines as Δ9 -THC. Additionally, many of the most robust findings in psychiatric genetics include components that localize to dendritic spines and have important roles in information processing and plasticity.

scholarly journals Long vs short-term synaptic learning rules after optogenetic spike-timing-dependent plasticity

2019 ◽  
Author(s):  
Margarita Anisimova ◽  
Bas van Bommel ◽  
Marina Mikhaylova ◽  
J. Simon Wiegert ◽  
Thomas G. Oertner ◽  
...  
Keyword(s):  
Spike Timing ◽  
Information Storage ◽  
Spike Timing Dependent Plasticity ◽  
Dependent Plasticity ◽  
Neuronal Populations ◽  
Learning Rules ◽  
Blocking Activity ◽  
Synaptic Learning ◽  
The Brain

AbstractSpike-timing-dependent plasticity (STDP) is a candidate mechanism for information storage in the brain. However, it has been practically impossible to assess the long-term consequences of STDP because recordings from postsynaptic neurons last at most one hour. Here we introduce an optogenetic method to, with millisecond precision, independently control action potentials in two neuronal populations with light. We apply this method to study spike-timing-dependent plasticity (oSTDP) in the hippocampus and reproduce previous findings that depression or potentiation depend on the sequence of pre- and postsynaptic spiking. However, 3 days after induction, oSTDP results in potentiation regardless of the exact temporal sequence, frequency or number of pairings. Blocking activity between induction and readout prevented the synaptic potentiation, indicating that strengthened synapses have to be used to get strong. Our findings indicate that STDP potentiates synapses and that the change in synaptic strength persist to behaviorally relevant timescales.

scholarly journals Relative humidity predominantly determines long-term biocrust-forming lichen survival under climate change

2020 ◽  
Author(s):  
Selina Baldauf ◽  
Philipp Porada ◽  
José Raggio ◽  
Fernando T. Maestre ◽  
Britta Tietjen
Keyword(s):  
Climate Change ◽  
Relative Humidity ◽  
Biological Soil Crust ◽  
Ecosystem Functions ◽  
List Type ◽  
Lichen Cover ◽  
Underlying Mechanisms ◽  
Experimental Findings ◽  
Fertilization Effects

AbstractManipulative experiments show a decrease in dryland biological soil crust cover and altered species composition under climate change. However, the underlying mechanisms are not fully understood, and long-term interacting effects of different drivers are largely unknown due to the short-term nature of the studies conducted so far.We addressed this gap and successfully parameterized a process-based model for the biocrust-forming lichen Diploschistes diacapsis as a common and globally distributed representative of biocrust communities to quantify how changing atmospheric CO2, temperature, rainfall amount and relative humidity affect its photosynthetic activity and cover. We also mimicked a long-term manipulative climate change experiment to understand the mechanisms underlying observed patterns in the field.The model reproduced observed experimental findings: warming reduced lichen cover whereas less rainfall had no effect. This warming effect was caused by the associated decrease in relative humidity and non-rainfall water inputs as major water sources for lichens. Warming alone, however, increased cover because higher temperatures promoted photosynthesis during the cool morning hours with high lichen activity. When combined, climate variables showed non-additive effects on lichen cover, and fertilization effects of CO2 leveled off with decreasing levels of relative humidity.Synthesis. Our results show that a decrease in relative humidity, rather than an increase in temperature may be the key factor for the survival of dryland lichens under climate change and that CO2 fertilization effects might be offset by a reduction in non-rainfall water inputs in the future. Because of a global trend towards warmer and thus drier air, this will affect lichen-dominated dryland biocrust communities and their role in regulating ecosystem functions, worldwide.

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