Archive for Biology of language

The evolution of metaphors?

Today's Frazz has a nice metaphor about life cycles:

Which called to mind an odd (to me) new theory about the language of Neanderthals, presented in a 5/20/2024 review essay by Stephen Mithen, "How Neanderthal language differed from modern human – they probably didn’t use metaphors":

[T]he evidence points to key differences in the brains of our species and those of Neanderthals that allowed modern humans (H. sapiens) to come up with abstract and complex ideas through metaphor – the ability to compare two unrelated things. For this to happen, our species had to diverge from the Neanderthals in our brain architecture.

Some experts interpret the skeletal and archaeological evidence as indicating profound differences. Others believe there were none. And some take the middle ground. […]

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AI-assisted substitute vocal cords

This is what the device looks like and how it is made:

Jun Chen Lab/UCLA
The two components — and five layers — of the device allow it to turn muscle
movement into electrical signals which, with the help of machine learning,
are ultimately converted into speech signals and audible vocal expression.

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Mushroom language?

Michael Blatt, Geoffrey Pullum, Andreas Draguhn, Barry Bowman, David Robinson, and Lincoln Taiz , "Does electrical activity in fungi function as a language?", Fungal Ecology 2024:

Abstract: All cells generate electrical energy derived from the movements of ions across membranes. In animal neurons, action potentials play an essential role in the central nervous system. Plants utilize a variety of electrical signals to regulate a wide range of physiological processes, including wound responses, mimosa leaf movements, and cell turgor changes, such as those involved in stomatal movements. Although fungal hyphae exhibit electrical fluctuations, their regulatory role(s), if any, is still unknown. In his paper “Language of fungi derived from their electrical spiking activity”, Andrew Adamatzky, based on a quantitative analysis of voltage fluctuations in fungal mycelia, concludes that the patterns of electrical fluctuations he detects can be grouped into “words” analogous to those found in human languages. He goes on to speculate that this “fungal language” is used “to communicate and process information” between different parts of the mycelium. Here we argue on methodological grounds that the presumption of a fungal language is premature and unsupported by the evidence presented, that the voltage fluctuations he detects are likely to originate as nonbiological noise and experimental artifacts, and that the measured electrical patterns show no similarity to any properties of human language.

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Genes and tone languages, yet again

Below is a guest post by Bob Ladd.

Long-time readers of Language Log may recall a couple of posts from 2007 (here and here) about a possible link between population genetics and tone languages. That year, Dan Dediu and I published a paper in PNAS showing that there’s a significant geographical correlation between the distribution of tone languages and the distribution of older and newer variants (alleles) of two genes known to be involved in brain development, ASPM and Microcephalin 1.  For ASPM in the Old World (where tone languages are found predominantly in sub-Saharan Africa and Southeast Asia), you can eyeball the correlation on the map below: the lighter the dot, the rarer the new variant of the gene.  Our PNAS paper put this eyeballing on a reasonably sound statistical basis.

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"Drunk in the club after covid"

Kylie Scott lipsyncs a passage from one of our president's recent press events:

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New approaches to Alzheimer's Disease

This post is another pitch for our on-going effort to develop simple, easy, and effective ways to track neurocognitive health through short interactions with a web app.  Why do we want this? Two reasons: first, early detection of neurodegenerative disorders through near-universal tracking; and second, easy large-scale evaluation of interventions, whether those are drugs or lifestyle changes. You can participate by enrolling at, and suggesting it to your friends and acquaintances as well.

Today, diagnosis generally depends on scoring below a certain value on cognitive tests such as the MMSE, which usually won't even be given until you've started experiencing life-changing symptoms — and at that point, the degenerative process has probably been at work for a decade or more. This may well be too late for interventions to make a difference, which may help explain the failure of dozens of Alzheimer's disease drug trials. And it's difficult and expensive to evaluate an intervention, in part because it requires a series of clinic visits, making it hard to fund support for trials that don't involve a patented drug.

If people could accurately track their neurocognitive health with a few minutes a week on a web app, they could be alerted to potential problems by the rate of change in their scores, even if they're many years away from a diagnosis by today's methods. Of course, this will be genuinely useful only when we have ways to slow or reverse the process — but the same approach can be used to evaluate such interventions inexpensively on a large scale.

More background is here: "Towards tracking neurocognitive health", 3/24/2020. As that post explains, this is just the first step on what may be a long journey — but we will be making the data available to all interested researchers, so that the approaches that have worked elsewhere in AI research over the past 30 years can be be applied to this problem as well.

Again, you can participate by enrolling at . And please spread the word!

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The life cycle of unicorns

Maybe the tide is turning against "Gene for X" thinking — Ed Yong, "A Waste of 1,000 Research Papers", 5/17/2019:

Decades of early research on the genetics of depression were built on nonexistent foundations. How did that happen?

In 1996, a group of European researchers found that a certain gene, called SLC6A4, might influence a person’s risk of depression.


But a new study—the biggest and most comprehensive of its kind yet—shows that this seemingly sturdy mountain of research is actually a house of cards, built on nonexistent foundations.

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Blue Cell Dyslexia

An article about dyslexia appeared last week in the prestigious Proceedings of the Royal Society B (“The [British] Royal Society's flagship biological research journal, dedicated to the fast publication and worldwide dissemination of high-quality research”).  A week is a long time in blog-years, I know, but impact of the article is rippling far and wide. The authors claim to have identified a visual basis for dyslexia: an anomaly involving the distribution of a type of receptor in a part of the retina.  This anomaly may provide “the biological and anatomical basis of reading and spelling disabilities”, with “important implications in both fundamental and biomedical sciences.” They also seemed to demonstrate that the anomaly could be easily eliminated by changing lighting conditions.

As might be expected, the media picked this up as scientists maybe having at long last found the cause of dyslexia.

Dyslexics, their families and teachers, reading researchers and treatment specialists, and the organizations that represent them are asking: did someone just discover the cause and cure for dyslexia?  (I know this: I get email.) As someone who has conducted research in the area, my question is different:  how did this terrible article get published and how can its harmful impact be counteracted?

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On whether prairie dogs can talk

Ferris Jabr recently published in the New York Times Magazine an interesting article about the field research of Con Slobodchikoff, professor emeritus of biology at Northern Arizona University, on prairie dog alarm calls. The article title is "Can Prairie Dogs Talk?"

It is an interesting question. People who have read my earlier posts on animal communication have been pressing me to say something about my reaction to it. In this post I will do that. I will not be able to cover all the implications and ramifications of the question, of course; for one interesting discussion that has already appeared in the blogosphere, see this piece by Edmund Blair Bolles. But I will try to be careful and scholarly, and in an unusual departure (disappointingly, perhaps, to those who relished my bitterly sarcastic remarks on cow naming behavior), I will attempt to be courteous. Nonetheless, I will provide a clear and explicit answer to Jabr's question.

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Advances in birdsong modeling

Eve Armstrong and Henry Abarbanel, "Model of the songbird nucleus HVC as a network of central pattern generators", Journal of neurophysiology, 2016:

We propose a functional architecture of the adult songbird nucleus HVC in which the core element is a "functional syllable unit" (FSU). In this model, HVC is organized into FSUs, each of which provides the basis for the production of one syllable in vocalization. Within each FSU, the inhibitory neuron population takes one of two operational states: (A) simultaneous firing wherein all inhibitory neurons fire simultaneously, and (B) competitive firing of the inhibitory neurons. Switching between these basic modes of activity is accomplished via changes in the synaptic strengths among the inhibitory neurons. The inhibitory neurons connect to excitatory projection neurons such that during state (A) the activity of projection neurons is suppressed, while during state (B) patterns of sequential firing of projection neurons can occur. The latter state is stabilized by feedback from the projection to the inhibitory neurons. Song composition for specific species is distinguished by the manner in which different FSUs are functionally connected to each other.

Ours is a computational model built with biophysically based neurons. We illustrate that many observations of HVC activity are explained by the dynamics of the proposed population of FSUs, and we identify aspects of the model that are currently testable experimentally. In addition, and standing apart from the core features of an FSU, we propose that the transition between modes may be governed by the biophysical mechanism of neuromodulation.

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Annals of Spectacularly Misleading Media

If you were scanning science-related stories in the mass media over the past 10 days or so, you saw some extraordinary news. A few examples:

"Scientists discover a ‘universal human language’".
"The hidden sound patterns that could overturn years of linguistic theory" ("In a surprising new study, researchers have uncovered powerful associations between sounds and meanings across thousands of unrelated languages").
"Global human language? Scientists find links between sound and meaning" ("A new linguistic study suggests that biology could play a role in the invention of human languages").
"In world's languages, scientists discover shared links between sound and meaning" ("Sifting through two-thirds of the world’s languages, scientists have discovered a strange pattern: Words with the same meanings in different languages often seem to share the same sounds").
"Words with same meanings in different languages often seem to share same sounds" ("After analyzing two-thirds of the languages worldwide, scientists have noticed an odd pattern. They have found that the words with same meaning in different languages often apparently have the same sounds").
"Unrelated Languages Often Use Same Sounds for Common Objects and Ideas, Research Finds".
"Researchers Find the Sounds We Build Words From Have Built-In Meanings".

The trouble is, many of these reports are complete nonsense: no one "discovered a universal human language" or "overturned years of linguistic theory" or showed that "world languages have a common ancestor" or demonstrated that "the sounds we build words from have built-in meanings". And other stories simply trumpet as news something that has been known, argued, or assumed for millennia: "biology could play a role in the invention of human language", "words with the same meaning in different languages often have the same sounds", etc.) There may be a story out there that soberly presents the actual content and significance of the research — but if so, I haven't found it.

How did this happen? It seems to be the same old sad tale. Science writers, in search of sensational headlines and lacking adequate background to read and evaluate actual scientific papers, re-wrote wildly irresponsible press releases.  And as usual, it's not clear how complicit the scientists were, but there's little evidence that they tried very hard to tone down the hoopla.

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Ecology and phonology

Ian Maddieson and Christophe Coupé, "Human spoken language diversity and the acoustic adaptation hyothesis", ASA 2015

Bioacousticians have argued that ecological feedback mechanisms contribute to shaping the acoustic signals of a variety of species and anthropogenic changes in soundscapes have been shown to generate modifications to the spectral envelope of bird songs. Several studies posit that part of the variation in sound structure across spoken human languages could likewise reflect adaptation to the local ecological conditions of their use. Specifically, environments in which higher frequencies are less faithfully transmitted (such as denser vegetation or higher ambient temperatures) may favor greater use of sounds characterized by lower frequencies. Such languages are viewed as “more sonorous”. This paper presents a variety of tests of this hypothesis.  

Data on segment inventories and syllable structure is taken from LAPSyD, a database on phonological patterns of a large worldwide sample of languages. Correlations are examined with measures of temperature, precipitation, vegetation, and geomorphology reflecting the mean values for the area in which each language is traditionally spoken. Major world languages, typically spoken across a range of environments, are excluded. Several comparisons show a correlation between ecological factors and the ratio of sonorant to obstruent segments in the languages examined offering support for the idea that acoustic adaptation applies to human languages.

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Modeling repetitive behavior

A recent conversation with Didier Demolin about animal vocalizations motivated me to return to a an issue discussed in "Finch linguistics", 7/15/2011. (See also "Markov's heart of darkness", 7/18/2011, "Non-Markovian yawp", 9/18/2011, and "The long get longer", 12/4/2013.)

The point is this: In modeling the structure of simple repetitive behavior, considerations from (traditional) formal language theory can obscure rather than clarify the issues. These threats to insight include the levels of the Chomsky-Schützenberger hierarchy, the "recursion" controversy, and so on.

What follows is an attempt at a simple illustrated explanation.

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