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A New Theory Ties Memory to Emotion, and Leaves AI Out in the Cold

In A Nutshell

  • A new review paper argues that neuroscience has misunderstood memory by focusing almost entirely on neurons while ignoring other brain cells and structures.
  • The researchers propose a “Tripartite Mechanism” in which astrocytes, a surrounding molecular scaffold, and chemical messengers work together to encode memory, though the idea remains an untested hypothesis.
  • The model ties memory directly to emotion, arguing that biological memory carries feelings the way computer data never could.
  • The authors conclude that AI, lacking this biological chemistry, cannot become truly conscious no matter how advanced it gets.

A familiar song can bring back a memory from decades ago. A certain smell can call up a person or place. A frightening memory can trigger a physical reaction almost instantly, heart racing before the mind even catches up. Computers can store and retrieve information too, but two researchers argue biological memory works on a fundamentally different level, one built from chemistry, not just circuitry.

In a review paper published in the International Journal of Psychiatry Research, Gerard Marx of MX Biotech Ltd. in Jerusalem and Chaim Gilon of the Hebrew University of Jerusalem argue that neuroscience has been examining memory with an incomplete picture of the brain. Their critique is blunt: most previous attempts to explain consciousness left out key biological players, and in doing so, left the real mystery untouched.

Marx and Gilon reviewed more than a dozen major academic works on consciousness, from philosophical treatises to neuroscience texts, and found a recurring problem they describe as the “naked neuron” assumption: researchers were studying neurons in isolation, ignoring the web of other cells and biological scaffolding wrapped around them.

Neuroscience Has Been Missing a Cell

One major oversight, they argue, is the dismissal of astrocytes, star-shaped brain cells physically intertwined with neurons. Another is the neglect of a dense mesh of proteins and sugars that coats all brain cells, what the authors call the brain’s surrounding molecular scaffold. Rounding out the ignored elements are chemical messengers, including neurotransmitters and signaling molecules released by non-neuron brain cells.

“A formula or equation that ignores 3 parameters out of a 6 parametric model cannot be solved,” the authors write, comparing incomplete brain theories to a math problem missing half its variables. Leave out astrocytes, the surrounding scaffold, and the chemical messengers, they argue, and any theory of consciousness is built on a broken foundation.

thoughts infographic
A new theory says memory may be written in brain chemistry, not just electricity, and that AI could never truly feel it. (Image by StudyFinds)

A New Theory of How Memories Get Made

To fill the gap, Marx and Gilon propose what they call a “Tripartite Mechanism” of memory. Rather than picturing memory as something stored inside neurons the way a computer stores data on a chip, they argue that memory is physically encoded in the protein-and-sugar mesh surrounding brain cells. The idea remains a hypothesis rather than a demonstrated mechanism of memory: no laboratory experiment in this paper measures the process directly.

Storage alone, though, does not create memory in their model. It requires three cooperating parts: astrocytes paired with neurons, the surrounding molecular mesh, and chemical signals that include both metals and neurotransmitters. Together, this trio encodes experiences into the mesh in a way that carries emotional weight alongside information.

That emotional dimension is central to the authors’ argument. A computer can store and retrieve data, but it cannot encode grief, joy, or fear alongside that data. Biological memory does exactly that, they contend, because the chemical messengers involved in encoding are the same ones tied to emotion. Marx and Gilon describe this as cognitive information with “emotive context,” and argue it separates true memory from mere data storage.

In this model, astrocytes are far from passive bystanders. Marx and Gilon position them as the primary drivers of thought and memory, with neurons playing a supporting role as the brain’s wiring for input and output, carrying signals in from the senses and commands out to muscles and glands. The astrocyte clusters, the authors argue, are what actually read, write, and interpret the memory code.

A Machine, the Authors Argue, Cannot Feel a Memory

Artificial intelligence gets a clear verdict from Marx and Gilon. No matter how sophisticated its circuits or algorithms, an AI system is, in their words, inherently “demotive,” meaning it cannot experience the emotional states baked into biological memory. In their view, it cannot be conscious and cannot be genuinely intelligent in the biological sense, regardless of how advanced its computing power becomes.

Marx and Gilon extend their thinking to intelligence more broadly. Consciousness, they suggest, appears even in simple organisms like bacterial colonies that can remember favorable and unfavorable environments. Intelligence, by contrast, requires the more elaborate machinery of neural networks working alongside astrocytes to draw on past experience. In humans, that shows up as musical talent or mathematical ability. In animals, it shows up as tool use, group coordination, or communication.

The Mystery Remains

Marx and Gilon are careful not to overclaim. Their tripartite model, they acknowledge, may represent only “a fragment from the entangled mysteries of consciousness, memory, and intelligence.” What drives the actual felt experience of being alive remains beyond the reach of their mechanism or anyone else’s. Still, by identifying specific physical components that can be measured and tested, the authors argue the field needs to move beyond what they see as largely philosophical descriptions and toward testable biochemical mechanisms. Consciousness may remain an enigma, but they contend it is one that has to be solved with biochemistry, not metaphor.


Paper Notes

Limitations

This paper is a theoretical review and proposal rather than an experimental study. No new laboratory data were collected or reported. The tripartite mechanism put forward by the authors is a conceptual model built on existing research and analogy, most notably a comparison to how information is physically encoded in computer memory chips. The model has not been tested in a controlled experimental setting as described in this paper. Because no clinical trials, animal studies, or human subject research was conducted for this publication, standard limitations around sample size, demographics, or statistical power do not apply. The authors themselves acknowledge that the “eternal enigma of Life remains” and that their mechanism may represent only a partial explanation.

Funding and Disclosures

No external funding sources are listed in the paper. Regarding conflicts of interest, Gerard Marx is identified as a founder of MX Biotech Ltd., a company with the stated commercial goal of developing “memory materials” and devices. Chaim Gilon is identified as an emeritus professor at the Institute of Chemistry at the Hebrew University of Jerusalem, where he is active in developing technologies related to oral drug delivery from peptides and proteins. The authors state that “the ideas forwarded here are scientifically genuine and presented in good faith, without commercial clouding of the concepts expressed therein.”

Publication Details

Authors: Gerard Marx (MX Biotech Ltd., Jerusalem, Israel) and Chaim Gilon (Institute of Chemistry, Hebrew University, Jerusalem, Israel) Journal: International Journal of Psychiatry Research Paper Title: Consciousness, Memory and Intelligence: A Mechanistic Perspective Volume/Issue: Volume 9, Issue 4, pages 1–7 Published: August 4, 2026 Received: June 19, 2026; Accepted: July 23, 2026 ISSN: 2641-4317 Citation: Gerard Marx, Chaim Gilon. Consciousness, Memory and Intelligence: A Mechanistic Perspective. Int J Psychiatr Res. 2026; 9(4): 1–7. Contact: [email protected] | DOI: 10.33425/2641-4317.1251

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