ArticleProceedings of the IEEE. Institute of Electrical and Electronics Engineers2010
The Neurobiological Basis of Cognition: Identification by Multi-Input, Multioutput Nonlinear Dynamic Modeling: A method is proposed for measuring and modeling human long-term memory formation by mathematical analysis and computer simulation of nerve-cell dynamics.
Article in Proceedings of the IEEE. Institute of Electrical and Electronics Engineers, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed, 69 citations in OpenAlex.
- Brain augmentation and neuroscience technologies: current applications, challenges, ethics and future prospects.Frontiers in systems neuroscience · 2022Review
- Multi-Input, Multi-Output Neuronal Mode Network Approach to Modeling the Encoding Dynamics and Functional Connectivity of Neural Systems.Neural computation · 2019Article
- Neurotechnologies for Human Cognitive Augmentation: Current State of the Art and Future Prospects.Frontiers in human neuroscience · 2019Review
- A Multi-Channel Asynchronous Neurostimulator With Artifact Suppression for Neural Code-Based Stimulations.Frontiers in neuroscience · 2019Article
- Memory Prosthesis: Is It Time for a Deep Neuromimetic Computing Approach?Frontiers in neuroscience · 2019Article
- Modeling Nonlinear Synaptic Dynamics: A Laguerre-Volterra Network Framework for Improved Computational Efficiency in Large Scale Simulations.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2018Article
- Acute in vivo testing of a conformal polymer microelectrode array for multi-region hippocampal recordings.Journal of neural engineering · 2018Article
- A Glutamatergic Spine Model to Enable Multi-Scale Modeling of Nonlinear Calcium Dynamics.Frontiers in computational neuroscience · 2018Article
- Identification of functional synaptic plasticity from spiking activities using nonlinear dynamical modeling.Journal of neuroscience methods · 2015Article
- Identifying and tracking simulated synaptic inputs from neuronal firing: insights from in vitro experiments.PLoS computational biology · 2015Article
- Volterra representation enables modeling of complex synaptic nonlinear dynamics in large-scale simulations.Frontiers in computational neuroscience · 2015Article
- The volterra functional series is a viable alternative to kinetic models for synaptic modeling--calibration and benchmarking.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2015Article
- On parsing the neural code in the prefrontal cortex of primates using principal dynamic modes.Journal of computational neuroscience · 2014Article
- Extraction and restoration of hippocampal spatial memories with non-linear dynamical modeling.Frontiers in systems neuroscience · 2014Article
- Identification of sparse neural functional connectivity using penalized likelihood estimation and basis functions.Journal of computational neuroscience · 2013Article
- A nonlinear autoregressive Volterra model of the Hodgkin-Huxley equations.Journal of computational neuroscience · 2013Article
- Nonlinear modeling of dynamic interactions within neuronal ensembles using Principal Dynamic Modes.Journal of computational neuroscience · 2013Article
- Design of optimal stimulation patterns for neuronal ensembles based on Volterra-type hierarchical modeling.Journal of neural engineering · 2012Article
- A hippocampal cognitive prosthesis: multi-input, multi-output nonlinear modeling and VLSI implementation.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2012Article
- Nonlinear dynamic modeling of neuron action potential threshold during synaptically driven broadband intracellular activity.IEEE transactions on bio-medical engineering · 2012Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
The successful development of neural prostheses requires an understanding of the neurobiological bases of cognitive processes, i.e., how the collective activity of populations of neurons results in a higher level process not predictable based on knowledge of the individual neurons and/or synapses alone. We have been studying and applying novel methods for representing nonlinear transformations of multiple spike train inputs (multiple time series of pulse train inputs) produced by synaptic and field interactions among multiple subclasses of neurons arrayed in multiple layers of incompletely connected units. We have been applying our methods to study of the hippocampus, a cortical brain structure that has been demonstrated, in humans and in animals, to perform the cognitive function of encoding new long-term (declarative) memories. Without their hippocampi, animals and humans retain a short-term memory (memory lasting approximately 1 min), and long-term memory for information learned prior to loss of hippocampal function. Results of more than 20 years of studies have demonstrated that both individual hippocampal neurons, and populations of hippocampal cells, e.g., the neurons comprising one of the three principal subsystems of the hippocampus, induce strong, higher order, nonlinear transformations of hippocampal inputs into hippocampal outputs. For one synaptic input or for a population of synchronously active synaptic inputs, such a transformation is represented by a sequence of action potential inputs being changed into a different sequence of action potential outputs. In other words, an incoming temporal pattern is transformed into a different, outgoing temporal pattern. For multiple, asynchronous synaptic inputs, such a transformation is represented by a spatiotemporal pattern of action potential inputs being changed into a different spatiotemporal pattern of action potential outputs. Our primary thesis is that the encoding of short-term memories into new, long-term memories represents the collective set of nonlinearities induced by the three or four principal subsystems of the hippocampus, i.e., entorhinal cortex-to-dentate gyrus, dentate gyrus-to-CA3 pyramidal cell region, CA3-to-CA1 pyramidal cell region, and CA1-to-subicular cortex. This hypothesis will be supported by studies using in vivo hippocampal multineuron recordings from animals performing memory tasks that require hippocampal function. The implications for this hypothesis will be discussed in the context of "cognitive prostheses"-neural prostheses for cortical brain regions believed to support cognitive functions, and that often are subject to damage due to stroke, epilepsy, dementia, and closed head trauma.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.