ReviewiScience2024
Lattice physics approaches for neural networks.
Review in iScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- Quantum-Inspired and Non-Classical Approaches to Consciousness: Models, Evidence and Constraints.Brain sciences · 2026Review
- Quantum-like architecture of the social atom: mental marker coherence and the triple-resonance mechanism of cognitive activation.Frontiers in human neuroscience · 2026Article
- Fractal Neural Dynamics and Memory Encoding Through Scale Relativity.Brain sciences · 2025Article
- Out of the single-neuron straitjacket: Neurons within assemblies change selectivity and their reconfiguration underlies dynamic coding.The Journal of physiology · 2025Article
- A multiscale brain emulation-based artificial intelligence framework for dynamic environments.Scientific reports · 2025Article
- Home-Cage Training for Non-Human Primates: An Opportunity to Reduce Stress and Study Natural Behavior in Neurophysiology Experiments.Animals : an open access journal from MDPI · 2025Review
- Overcoming quadratic hardware scaling for a fully connected digital oscillatory neural network.Frontiers in neuroscience · 2025Article
- Inhibition of return emerges with non-predictive spatial cueing of the stop-signal.Frontiers in human neuroscience · 2025Article
- Quantum-like representation of neuronal networks' activity: modeling "mental entanglement".Frontiers in human neuroscience · 2025Article
- Neural Activity in Quarks Language: Lattice Field Theory for a Network of Real Neurons.Entropy (Basel, Switzerland) · 2024Article
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Modern neuroscience has evolved into a frontier field that draws on numerous disciplines, resulting in the flourishing of novel conceptual frames primarily inspired by physics and complex systems science. Contributing in this direction, we recently introduced a mathematical framework to describe the spatiotemporal interactions of systems of neurons using lattice field theory, the reference paradigm for theoretical particle physics. In this note, we provide a concise summary of the basics of the theory, aiming to be intuitive to the interdisciplinary neuroscience community. We contextualize our methods, illustrating how to readily connect the parameters of our formulation to experimental variables using well-known renormalization procedures. This synopsis yields the key concepts needed to describe neural networks using lattice physics. Such classes of methods are attention-worthy in an era of blistering improvements in numerical computations, as they can facilitate relating the observation of neural activity to generative models underpinned by physical principles.
Indexed as
Identifiers
What Socratic 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 Socratic graph.