Biophysics of Computation: Information Processing in Single Neurons
E906305
Biophysics of Computation: Information Processing in Single Neurons is a seminal book that rigorously explains how individual neurons perform complex information processing using biophysical and computational principles.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Biophysics of Computation: Information Processing in Single Neurons canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T11108805 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Biophysics of Computation: Information Processing in Single Neurons Context triple: [Christof Koch, notableWork, Biophysics of Computation: Information Processing in Single Neurons]
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A.
The Computational Brain
The Computational Brain is an influential book that explores how principles of computation and neural networks can explain brain function and cognition.
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B.
Neural Computation
Neural Computation is a peer-reviewed scientific journal focusing on theoretical and computational aspects of neural systems, machine learning, and artificial intelligence.
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C.
Biological and Artificial Computation
Biological and Artificial Computation is a scholarly work by Terrence Sejnowski that explores how principles of biological neural systems can inform and inspire computational and artificial intelligence models.
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D.
analog VLSI for neural systems
Analog VLSI for neural systems is a pioneering approach to designing low-power, hardware-based neural network and neuromorphic circuits that mimic biological computation using analog very-large-scale integration technology.
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E.
Hodgkin–Huxley model
The Hodgkin–Huxley model is a mathematical description of how action potentials in neurons are initiated and propagated through voltage-gated ion channels in the cell membrane.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Biophysics of Computation: Information Processing in Single Neurons Target entity description: Biophysics of Computation: Information Processing in Single Neurons is a seminal book that rigorously explains how individual neurons perform complex information processing using biophysical and computational principles.
-
A.
The Computational Brain
The Computational Brain is an influential book that explores how principles of computation and neural networks can explain brain function and cognition.
-
B.
Neural Computation
Neural Computation is a peer-reviewed scientific journal focusing on theoretical and computational aspects of neural systems, machine learning, and artificial intelligence.
-
C.
Biological and Artificial Computation
Biological and Artificial Computation is a scholarly work by Terrence Sejnowski that explores how principles of biological neural systems can inform and inspire computational and artificial intelligence models.
-
D.
analog VLSI for neural systems
Analog VLSI for neural systems is a pioneering approach to designing low-power, hardware-based neural network and neuromorphic circuits that mimic biological computation using analog very-large-scale integration technology.
-
E.
Hodgkin–Huxley model
The Hodgkin–Huxley model is a mathematical description of how action potentials in neurons are initiated and propagated through voltage-gated ion channels in the cell membrane.
- F. None of above. chosen
Statements (48)
| Predicate | Object |
|---|---|
| instanceOf |
computational neuroscience book
ⓘ
neuroscience book ⓘ non-fiction book ⓘ scientific book ⓘ |
| aim | to explain how individual neurons perform complex information processing ⓘ |
| approach |
computational modeling of neurons
ⓘ
rigorous biophysical analysis ⓘ |
| author | Christof Koch ⓘ |
| field |
biophysics
ⓘ
computational neuroscience ⓘ neuroscience ⓘ theoretical neuroscience ⓘ |
| genre |
academic literature
ⓘ
textbook ⓘ |
| hasPart |
chapters on dendritic processing
ⓘ
chapters on spike generation ⓘ chapters on synaptic integration ⓘ mathematical appendices ⓘ |
| influencedField |
computational neuroscience
ⓘ
theoretical neuroscience ⓘ |
| intendedAudience |
graduate students
ⓘ
researchers in biophysics ⓘ researchers in computational neuroscience ⓘ researchers in neuroscience ⓘ |
| language | English ⓘ |
| medium |
hardcover
ⓘ
print ⓘ |
| notableFor |
integration of biophysics and information processing
ⓘ
rigorous treatment of single-neuron computation ⓘ |
| publisher | Oxford University Press ⓘ |
| topic |
Hodgkin–Huxley models
ⓘ
linked to:
Hodgkin–Huxley model
action potential generation ⓘ biophysical mechanisms of neural computation ⓘ cable theory ⓘ compartmental neuron models ⓘ dendritic computation ⓘ information processing in single neurons ⓘ ion channels ⓘ neural coding ⓘ noise in neural computation ⓘ nonlinear dynamics in neurons ⓘ spike generation ⓘ stochastic processes in neurons ⓘ synaptic integration ⓘ synaptic plasticity ⓘ |
| uses |
biophysical principles
ⓘ
differential equations ⓘ mathematical modeling ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Biophysics of Computation: Information Processing in Single Neurons Description of subject: Biophysics of Computation: Information Processing in Single Neurons is a seminal book that rigorously explains how individual neurons perform complex information processing using biophysical and computational principles.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.