Evidence map›Paper›PMID 42422235›Full record

ArticleFrontiers in computational neuroscience2026

The goo that binds us: how field resonance solves neuroscience's binding and criticality problems.

Tam Hunt

Abstract read
In one paragraph

Article in Frontiers in computational neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Tam HuntUniversity of California, Santa Barbara, Santa Barbara, CA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The binding problem and the criticality problem represent two of neuroscience's most persistent challenges: how do distributed neural processes create unified conscious experience, and how does the brain maintain optimal information processing at the critical boundary between order and chaos? This paper argues that both problems emerge from neuroscience's "prickly" bias toward discrete, computational approaches and dissolve when we embrace "gooey" electromagnetic field perspectives. Drawing on Alan Watts' philosophical dichotomy between "prickles" (precise, chopped-up particles) and "goo" (softer, continuous waves), I demonstrate how the EM field hypothesis provides natural solutions to spatial and temporal binding through cross-frequency coupling while simultaneously explaining neural criticality through volumetric field propagation. New evidence reveals that electromagnetic fields can entrain neural spike timing at thresholds as low as 0.74 mV/mm, establishing causal field-to-neuron communication. The 5,000-fold speed advantage of ephaptic field propagation (50 km/s vs. 10-100 m/s for spikes) enables rapid integration necessary for unified consciousness, while the volumetric nature of field propagation naturally generates the power-law scaling and critical avalanche dynamics observed across neural systems. Rather than requiring evolutionarily unstable fine-tuning of synaptic weights, criticality arises spontaneously from multi-scale electromagnetic field interactions. The implications extend beyond solving two technical problems to recognizing that cognition and consciousness are probably more gooey than prickly-not made ultimately of discrete computational events but continuous electromagnetic field dynamics produced by the brain and body.

Indexed as

binding problemconsciousnesscriticalitycross-frequency couplingEEG originselectromagnetic fieldsEM field hypothesisenergy modulation

Identifiers

PMID42422235
PMCPMC13341665

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.