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YOU DON’T NEED WORDS TO THINK  
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Gary Stix
October 17, 2024
Scientific American
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_ Brain studies show that language is not essential for the cognitive
processes that underlie thought _

"Thinker thinks about how to take sun burst shot", by davidyuweb,
licensed under CC BY-NC 2.0

 

Scholars have long contemplated the connection between language and
thought
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to what degree the two are intertwined—by asking whether language is
somehow an essential prerequisite for thinking
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British philosopher and mathematician Bertrand Russell answered the
question with a flat yes, asserting that language’s very purpose is
“to make possible thoughts which could not exist without it.” But
even a cursory glance around the natural world suggests why Russell
may be wrong: No words are needed for animals to perform all sorts of
problem-solving challenges
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demonstrate high-level cognition. Chimps can outplay humans in a
strategy game
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and New Caledonian Crows
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their own tools that enable them to capture prey.

Still, humans perform cognitive tasks at a level of sophistication not
seen in chimps—we can solve differential equations or compose
majestic symphonies. Is language needed in some form for these
species-specific achievements? Do we require words or syntax as
scaffolding to construct the things we think about? Or do the
brain’s cognitive regions devise fully baked thoughts that we then
convey using words as a medium of communication?

Evelina Fedorenko, a neuroscientist who studies language at the
McGovern Institute for Brain Research at the Massachusetts Institute
of Technology, has spent many years trying to answer these questions.
She remembers being a Harvard University undergraduate in the early
2000s, when the language-begets-thought hypothesis was still highly
prominent in academia. She herself became a believer.

When Fedorenko began her research 15 years ago, a time when new
brain-imaging techniques had become widely available, she wanted to
evaluate this idea with the requisite rigor. She recently co-authored
a perspective article in _Nature_ that includes a summary of her
findings [[link removed]] over
the ensuing years. It makes clear that the jury is no longer out, in
Fedorenko’s view: language and thought are, in fact, distinct
entities that the brain processes separately. The highest levels of
cognition—from novel problem-solving to social reasoning—can
proceed without an assist from words or linguistic structures.

Language works a little like telepathy in allowing us to communicate
our thoughts to others and to pass to the next generation the
knowledge and skills essential for our hypersocial species to
flourish. But at the same time, a person with aphasia, who are
sometimes unable to utter a single word, can still engage in an array
of cognitive tasks fundamental to thought. _Scientific
American_ talked to Fedorenko about the language-thought divide and
the prospects of artificial intelligence tools such as large language
models for continuing to explore interactions between thinking and
speaking.

[_An edited transcript of the interview follows._]

HOW DID YOU DECIDE TO ASK THE QUESTION OF WHETHER LANGUAGE AND THOUGHT
ARE SEPARATE ENTITIES?

Honestly, I had a very strong intuition that language is pretty
critical to complex thought. In the early 2000s I really was drawn to
the hypothesis that maybe humans have some special machinery that is
especially well suited for computing hierarchical structures.And
language is a prime example of a system based on hierarchical
structures: words combine into phrases and phrases combine into
sentences.

And a lot of complex thought is based on hierarchical structures. So I
thought, ‘Well, I’m going to go and find this brain region that
processes hierarchical structures of language.’ There had been a few
claims at the time that some parts of the left frontal cortex are that
structure.

But a lot of the methods that people were using to examine overlap in
the brain between language and other domains weren’t that great. And
so I thought I would do it better. And then, as often happens in
science, things just don’t work the way you imagine they might. I
searched for evidence for such a brain region—and it doesn’t
exist.

You find this very clear separation between brain regions that compute
hierarchical structures in language and brain regions that help you do
the same kind of thing in math or music. A lot of science starts out
with some hypotheses that are often based on intuitions or on prior
beliefs.

My original training was in the [tradition of linguist Noam Chomsky]
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where the dogma has always been that we use language for thinking: to
think is why language evolved in our species. And so this is the
expectation I had from that training. But you just learn, when you do
science, that most of the time you’re wrong—and that’s great
because we learn how things actually work in reality.

WHAT EVIDENCE DID YOU FIND THAT THOUGHT AND LANGUAGE ARE SEPARATE
SYSTEMS?

The evidence comes from two separate methods. One is basically a very
old method that scientists have been using for centuries: looking at
deficits in different abilities—for instance, in people with brain
damage.

Using this approach, we can look at individuals who have impairments
in language—some form of aphasia. Aphasia has been studied as a
condition for centuries. For the question of how language relates to
systems of thought, the most informative cases are cases of really
severe impairments, so-called global aphasia, where individuals
basically lose completely their ability to understand and produce
language as a result of massive damage to the left hemisphere of the
brain. You can ask whether people who have these severe language
impairments can perform tasks that require thinking. You can ask them
to solve some math problems or to perform a social reasoning test, and
all of the instructions, of course, have to be nonverbal because they
can’t understand linguistic information anymore. Scientists have a
lot of experience working with populations that don’t have
language—studying preverbal infants or studying nonhuman animal
species. So it’s definitely possible to convey instructions in a way
that’s nonverbal. And the key finding from this line of work is that
there are people with severe language impairments who nonetheless seem
totally fine on all cognitive tasks that we’ve tested them on so
far.

There are individuals who have been now tested on many, many different
kinds of tasks, including tasks that involve what you may call
thinking, such as solving math problems or logic puzzles or reasoning
about what somebody else believes or reasoning about the physical
world. So that’s one big chunk of evidence from these populations of
people with aphasia.

WHAT IS THE OTHER METHOD?

A nicely complementary approach, which started in the 1980s and 1990s,
is a brain-imaging approach. We can measure blood flow changes when
people engage in different tasks and ask questions about whether the
two systems are distinct or overlapping—for example, whether your
language regions overlap with regions that help you solve math
problems. These brain-imaging tools are really good for these
questions. But before I could ask these questions, I needed a way to
robustly and reliably identify language areas in individual brains, so
I spent the first bunch of years of my career developing tools to do
this.

And once we have a way of finding these language regions, and we know
that these are the regions that, when damaged in adulthood, lead to
conditions such as aphasia, we can then ask whether these language
regions are active when people engage in various thinking tasks. So
you can come into the lab, and I can put you in the scanner, find your
language regions by asking you to perform a short task that takes a
few minutes—and then I can ask you to do some logic puzzles or
sudoku or some complex working memory tasks or planning and
decision-making. And then I can ask whether the regions that we know
process language are working when you’re engaging in these other
kinds of tasks. There are now dozens of studies that we’ve done
looking at all sorts of nonlinguistic inputs and tasks, including many
thinking tasks. We find time and again that the language regions are
basically silent when people engage in these thinking activities.

SO WHAT _IS_ THE ROLE OF LANGUAGE, IF NOT FOR THINKING?

What I’m doing right now is sharing some knowledge that I have that
you may have only had a partial version of—and once I transmit it to
you through language, you can update your knowledge and have that in
your mind as well. So it’s basically like a shortcut for telepathy.
We can’t read each other’s mind. But we can use this tool called
language, which is a flexible way to communicate our inner states, to
transmit information to each other.

And in fact, most of the things that you probably learned about the
world, you learned through language and not through direct experience
with the world. So language is very useful. You can easily imagine how
it would confer evolutionary advantages: by facilitating cooperative
activities, transmitting knowledge about how to build tools and
conveying social knowledge. As people started living in larger groups,
it became more important to keep track of various social
relationships. For example, I can tell you, “Oh, I don’t trust
that guy.” Also, it’s very hard to transmit knowledge to future
generations, and language allows us to do that very effectively.

In line with the idea that we have language to communicate, there is
accumulating evidence from the past few decades that shows that
various properties that human languages have—there are about 7,000
of them spoken and signed across the world—are optimized for
efficiently transmitting information, making things easy to perceive,
easy to understand, easy to produce and easy to learn for kids.

IS LANGUAGE WHAT MAKES HUMANS SPECIAL?

We know from brain evolution that many parts of the cortical sheet
[the outer layer of the brain] expanded a lot in humans. These parts
of the brain contain several distinct functional systems. Language is
one of them. But there’s also a system that allows us to reason
about other minds. There’s a system that supports novel
problem-solving. There’s a system that allows us to integrate
information across extended contexts in time—for example, chaining a
few events together. It’s most likely that what makes us human is
not one “golden ticket,” as some call it. It’s not one thing
that happened; it’s more likely that a whole bunch of systems got
more sophisticated, taking up larger chunks of cortex and allowing for
more complex thoughts and behaviors.

DO THE LANGUAGE AND THINKING SYSTEMS INTERACT WITH EACH OTHER?

There aren’t great tools in neuroscience to study intersystem
interactions between language and thought. But there are interesting
new opportunities that are opening up with advances in AI where we now
have a model system to study language, which is in the form of these
large language models such as GPT-2 and its successors. These models
do language really well, producing perfectly grammatical and
meaningful sentences. They’re not so good at thinking, which is
nicely aligning with the idea that the language system by itself is
not what makes you think.

But we and many other groups are doing work in which we take some
version of an artificial neural network language model as a model of
the human language system. And then we try to connect it to some
system that is more like what we think human systems of thought look
like—for example, a symbolic problem-solving system such as a math
app. With these artificial intelligence tools, we can at least ask,
“What are the ways in which a system of thought, a system of
reasoning, can interact with a system that stores and uses linguistic
representations?” These so-called neurosymbolic approaches provide
an exciting opportunity to start tackling these questions.

SO WHAT DO LARGE LANGUAGE MODELS DO TO HELP US UNDERSTAND THE
NEUROSCIENCE OF HOW LANGUAGE WORKS?

They’re basically the first model organism for researchers studying
the neuroscience of language. They are not a biological organism, but
until these models came about, we just didn’t have anything other
than the human brain that does language. And so what’s happening is
incredibly exciting. You can do stuff on models that you can’t do on
actual biological systems that you’re trying to understand. There
are many, many questions that we can now ask that had been totally out
of reach: for example, questions about development.

In humans, of course, you cannot manipulate linguistic input that
children get. You cannot deprive kids of language, or restrict their
input in some way, and see how they develop. But you can build these
models that are trained on only particular kinds of linguistic input
or are trained on speech inputs as opposed to textual inputs. And then
you can see whether models trained in particular ways better
recapitulate what we see in humans with respect to their linguistic
behavior or brain responses to language.

So just as neuroscientists have long used a mouse or a macaque as a
model organism, we can now use these in silico models, which are not
biological but very powerful in their own way, to try to understand
some aspects of how language develops or is processed or decays in
aging or whatnot.

We have a lot more access to these models’ internals. The methods we
have for messing with the brain, at least with the human brain, are
much more limited compared with what we can do with these models.

_GARY STIX [[link removed]],
senior editor of mind and brain at Scientific American, edits and
reports on emerging advances that have propelled brain science to the
forefront of the biological sciences. Stix has edited or written cover
stories, feature articles and news on diverse topics, ranging from
what happens in the brain when a person is immersed in thought to the
impact of brain implant technology that alleviates mood disorders such
as depression. Before taking over the neuroscience beat, Stix,
as Scientific American's special projects editor, oversaw the
magazine's annual single-topic special issues, conceiving of and
producing issues on Albert Einstein, Charles Darwin, climate change
and nanotechnology. One special issue he edited on the topic of time
in all of its manifestations won a National Magazine Award. With his
wife Miriam Lacob, Stix is co-author of a technology primer
called Who Gives a Gigabyte? A Survival Guide for the Technologically
Perplexed._

_More by Gary Stix
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_Founded 1845, Scientific American
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is the oldest continuously published magazine in the United States. It
has published articles by more than 200 Nobel Prize winners._

_Scientific American
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covers the most important and exciting research, ideas and knowledge
in science, health, technology, the environment and society. It is
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