Tag: neuroscience

The Mind is What the Brain Does, and Very Strange

Having now clearly established memes as properties of objects and events in the external world, properties that provide crucial data for the operation of mental “machines,” I want to step aside from thinking about memes and cultural evolution as such and think a bit about the mind. I want to set this conversation up by, once again, quoting from Dennett’s recent interview, The Well-Tempered Mind, at The Edge:

The question is, what happens to your ideas about computational architecture when you think of individual neurons not as dutiful slaves or as simple machines but as agents that have to be kept in line and that have to be properly rewarded and that can form coalitions and cabals and organizations and alliances? This vision of the brain as a sort of social arena of politically warring forces seems like sort of an amusing fantasy at first, but is now becoming something that I take more and more seriously, and it’s fed by a lot of different currents.

A bit later:

It’s going to be a connectionist network. Although we know many of the talents of connectionist networks, how do you knit them together into one big fabric that can do all the things minds do? Who’s in charge? What kind of control system? Control is the real key, and you begin to realize that control in brains is very different from control in computers. Control in your commercial computer is very much a carefully designed top-down thing.

That’s the problem David Hays and I set ourselves in Principles and Development of Natural Intelligence (Journal of Social and Biological Systems 11, 293 – 322, 1988). While we had something to say about control in our discussion of the modal principle, we addressed the broader question of how to construct a mind from neurons that aren’t simple logical switches.

It is by no means clear to me how Dennett, and others of his mind-set, think about the mind. Yes, it’s computational. I can deal with that. But not, as I’ve said, if it’s taken to mean that the primitive operations of the nervous system are like the operations in digital computers, not if it’s taken to imply that the mind is constituted by ‘programs’ written in the ‘mentalese’ version of Fortran, Lisp, or C++. THAT was never a very plausible idea and the more we’ve come to know about the nervous system, the less plausible it becomes.

The upshot is that we need a much more fluid, a much more dynamic, conception of the mind. In Beethoven’s Anvil I talked of neural weather. Here’s how I set-up that metaphor (pp. 71-72): Continue reading “The Mind is What the Brain Does, and Very Strange”

What Makes Humans Unique? (I): The Evolution of the Human Brain

ResearchBlogging.org

Hello! This is my first post here at Replicated Typo and I thought I’d start with reposting a slightly modified version of a three-part series on the evolution of the human mind that I did last year over at my blog Shared Symbolic Storage.

So in this and my next posts I will have a look at how human cognition evolved from the perspective of cognitive science, especially ‘evolutionary linguistics,’ comparative psychology and developmental psychology.

In this post I’ll focus on the evolution of the human brain.

Human Evolution

We are evolved primates. (As are all other primates of course. So maybe it is better to say that we, like all other primates, are evolved beings with a unique set of specializations, adaptations and features. )

In our lineage, we share a common ancestor with orangutans (about 15 million years ago (mya)), gorillas (about 10mya), and most recently, chimpanzees and bonobos (5 to 7 mya). We not only share a significant amount of DNA with our primate cousins, but also major anatomical features (Gazzaniga 2008: 51f., Lewin 2005: 61) These include, for example, our basic skeletal anatomy, our facial muscles, or our fingernails (Lewin 2005: 218ff.).

What most distinguishes us as humans on an anatomical level are our bizarre hair distribution, our upright posture and the skeletal modifications necessary for it, including a propensity for endurance running, our opposable thumbs, fat deposits that are unusually extensive (Preuss 2004: 5), and an intestinal tract only 60% the size expected of primates our size (Gibbons 2007: 1558).

Finally, there is also a distinguishing feature that is a much more remarkable violation of expectations – a brain three times the size expected of a primate our size. This is all the more interesting as primates are already twice as encephalized as other mammals (Lewin 2005: 217). A direct comparison shows this difference in numbers: Whereas human brains have an average volume of 1251.8 cubic centimetres and weigh about 1300 gram, the brains of the other great apes only have an average volume of 316.7 cubic centimetres and weigh between 350-500 gram (Rilling 2006: 66, Preuss 2004: 8). In a human brain, there are approximately a hundred billion neurons, each of which is connected to about one thousand other neurons, comprising about one hundred trillion synaptic connections (Gazzaniga 2008: 291). If you would count all the connections in the napkin-sized cortex alone, you’d only be finished after 32 million years (Edelman 1992: 17).

Expensive Tissue

The human brain is also extremely “expensive tissue” (Aiello & Wheeler 1995): Although it only accounts for 2% of an adult’s body weight, it accounts for 20-25% of an adult’s resting oxygen and energy intake (Attwell & Laughlin 2001: 1143). In early life, the brain even makes up for up 60-70% of the body’s total energy requirements. A chimpanzee’s brain, in comparison, only consumes about 8-9% of its resting metabolism (Aiello & Wells 2002: 330). The human brain’s energy demands are about 8 to 10 times higher than those of skeletal muscles (Dunbar & Shultz 2007: 1344), and, in terms of energy consumption, it is equal to the rate of energy consumed by leg muscles of a marathon runner when running (Attwell & Laughlin 2001: 1143). All in all, its consumption rate is only topped by the energy intake of the heart (Dunbar & Shultz 2007: 1344).

Consequently, if we want to understand the evolutionary trajectory that led to human cognition there is the problem that

“because the cost of maintaining a large brain is so great, it is intrinsically unlikely that large brains will evolve merely because they can. Large brains will evolve only when the selection factor in their favour is sufficient to overcome the steep cost gradient“ (Dunbar 1998: 179).

This is especially important for people who want to come up with an “adaptive story” of how our brain got so big: they have to come up with a strong enough selection pressure operative in the Pleistocene “environment of evolutionary adaptedness” that would have allowed such “expensive tissue” to evolve in the first place (Bickerton 2009: 165f.).

What About the Brain is Uniquely Human?

If we look to the brain for possible hints, we first find that presently, there is “no good evidence that humans do, in fact, possess uniquely human cortical areas” (although the jury is still out) (Preuss 2004: 9). In addition, we find that there are functions specific to humans which are represented in areas homologous to areas of other primates. Instead, it seems that in the course of human evolution some of the areas of the brain expanded disproportionally, “especially higher-order cortical areas, including the prefrontal cortex” (Preuss 2004: 9, Deacon 1998: 435-438). This means that humans are not simply ‘better’ at thinking than other animals, but that they think differently (Preuss 2004: 7). The expansion and apparent specializations of only certain kinds of neuronal areas could indicate a qualitative shift in neuronal activity brought about by re-organization of existing features, leading to a wholly different style of cognition (Deacon 1998: 435-438 Rilling 2006: 75).

This scenario squares well with what we know about the way evolution works, namely that it always has to work with the raw materials that are available, and constantly co-opts and tinkers with existing structures, at times producing haphazard, cobbled-together, but functional results (Gould & Lewontin 1979, Gould & Vrba 1982). Given the relatively short time span for the evolution of the “most complex structure in the know universe”, as it is sometimes referred to, we have to acknowledge how preciously little time the evolutionary process had for ‘debugging.’ It could well be that make the human mind is so unique because it is an imperfect ‘Kluge:’ “a clumsy or inelegant – yet surprisingly effective – solution to a problem,” like the Apollo 13 CO2 filter or an on-the-spot invention by MacGyver (Marcus 2008: 3f.). It may thus well turn out that what we think makes us so special is a mental “oddity of our species’ way of understanding” the world around us (Povinelli & Vonk 2003: 160). It is reasonable then to assume that human cognition did not just simply get better across the board, but that instead we owe our unique style of thinking to quite specific specializations of the human mind.

With this in mind, we can now ask the question how these neurological differences must translate into psychological differences. But this is where the problem starts: Which features really distinguish us as humans and which are more derivative than others? A true candidate for what got uniquely human cognition off the ground has to pass this test and solve the problem how such “expensive tissue” could evolve in the first place.

In my next post I will have a look at six candidates for what makes human cognition unique.

References:

Aiello, L., & Wheeler, P. (1995). The Expensive-Tissue Hypothesis: The Brain and the Digestive System in Human and Primate Evolution Current Anthropology, 36 (2) DOI: 10.1086/204350

Aiello, L., & Wells, J. (2002). ENERGETICS AND THE EVOLUTION OF THE GENUS HOMO Annual Review of Anthropology, 31 (1), 323-338 DOI: 10.1146/annurev.anthro.31.040402.085403

Attwell, David and Simon B. Laughlin. (2001.) “An Energy Budget for Signaling in the Grey Matter of the Brain.” Journal of Cerebral Blood Flow and Metabolism 21:1133–1145.

Bickerton, Derek (2009): Adams Tongue: How Humans Made Language. How Language Made Humans. New York: Hill and Wang.

Deacon, Terrence William (1997). The Symbolic Species. The Co-evolution of Language and the Brain. New York / London: W.W. Norton.

Dunbar, Robin I.M. (1998): “The Social Brain Hypothesis Evolutionary Anthropology 6: 178-190.

Dunbar, R., & Shultz, S. (2007). Evolution in the Social Brain Science, 317 (5843), 1344-1347 DOI: 10.1126/science.1145463

Edelman, Gerald Maurice (1992) Bright and Brilliant Fire: On the Matters of the Mind. New York: Basic Books

Gazzaniga, Michael S. (2008): Human: The Science of What Makes us Unique. New York: Harper-Collins.

Gibbons, Ann. (2007) “Food for Thought.” Science 316: 1558-1560.

Gould, Stephen Jay and Richard Lewontin (1979): “The spandrels of San Marco and the Panglossian paradigm: a critique of the adaptationist programme.” Proclamations of the Royal. Society of London B: Biological Sciences 205 (1161): 581–98.

Gould, Stephen Jay, and Elizabeth S. Vrba (1982), “Exaptation — a missing term in the science of form.” Paleobiology 8 (1): 4–15.

Lewin, Roger (2005): Human Evolution: An Illustrated Introduction. Oxford: Blackwell.

Marcus, Gary (2008): Kluge: The Haphazard Evolution of the Human Mind. London: Faber and Faber.

Povinelli, Daniel J. and Jennifer Vonk (2003): “Chimpanzee minds: Suspiciously human?” Trends in Cognitive Sciences, 7.4, 157–160.

Preuss Todd M. (2004): What is it like to be a human? In: Gazzaniga MS, editor. The Cognitive Neurosciences III, Third Edition. Cambridge, MA: MIT Press: 5-22.

Rilling, J. (2006). Human and nonhuman primate brains: Are they allometrically scaled versions of the same design? Evolutionary Anthropology: Issues, News, and Reviews, 15 (2), 65-77 DOI: 10.1002/evan.20095

Recent Abstracts #1

In an effort to update this blog regularly, I’ve decided to take the lazy route and post up a list of abstracts. This will only happen once a week, but it’s a useful resource (for me at least), and will usually be an indicator of what articles I’m going to write about in the near future.

Continue reading “Recent Abstracts #1”

Answering Wallace's challenge: Relaxed Selection and Language Evolution

ResearchBlogging.orgHow does natural selection account for language? Darwin wrestled with it, Chomsky sidestepped it, and Pinker claimed to solve it. Discerning the evolution of language is therefore a much sought endeavour, with a vast number of explanations emerging that offer a plethora of choice, but little in the way of consensus. This is hardly new, and at times has seemed completely frivolous and trivial. So much so that in the 19th Century, the Royal Linguistic Society in London actually went as far as to ban any discussion and debate on the origins of language. Put simply: we don’t really know that much. Often quoted in these debates is Alfred Russell Wallace, who, in a letter to Darwin, argued that: “natural selection could only have endowed the savage with a brain a little superior to that of an ape whereas he possesses one very little inferior to that of an average member of our learned society”.

This is obviously relevant for those of us studying language evolution. If, as Wallace challenged, natural selection (and more broadly, evolution) is unable to account for our mental capacities and behavioural capabilities, then what is the source behind our propensity for language? Well, I think we’ve come far enough to rule out the spiritual explanations of Wallace (although it still persists on some corners of the web), and whilst I agree that biological natural selection alone is not sufficient to explain language, we can certainly place it in an evolutionary framework.

Such is the position of Prof Terrence Deacon, who, in his current paper for PNAS, eloquently argues for a role for relaxed selection in the evolution of the language capacity. He’s been making these noises for a while now, as I previously mentioned here, with him also recognising evolutionary-similar processes in development. However, with the publication of this paper I think it’s about time I disseminated his current ideas in more detail, which, in my humble opinion, offers a more nuanced position than the strict modular adaptationism previously championed by Pinker et al (I say previously, because Pinker also has a paper in this issue, and I’m going to read it before making any claims about his current position on the matter).

Continue reading “Answering Wallace's challenge: Relaxed Selection and Language Evolution”

The brain–artefact interface (BAI): a challenge for archaeology and cultural neuroscience

Just found an interesting paper on cultural neuroscience and the extended mind. Some of you might remember the author, Dr Lambros Malafouris, from Seed Magazine’s Revolutionary Minds series. I plan on providing a more thorough examination of paper at a later point. In the meantime, check out the abstract:

Cultural neuroscience provides a new approach for understanding the impact of culture on the human brain (and vice versa) opening thus new avenues for cross-disciplinary collaboration with archaeology and anthropology. Finding new meaningful and productive unit of analysis is essential for such collaboration. But what can archaeological preoccupation with material culture and long-term change contribute to this end? In this article, I introduce and discuss the notion of the brain–artefact interface (BAI) as a useful conceptual bridge between neuroplastisty and the extended mind. I argue that a key challenge for archaeology and cultural neuroscience lies in the cross-disciplinary understanding of the processes by which our plastic enculturated brains become constituted within the wider extended networks of non-biological artefacts and cultural practices that delineate the real spatial and temporal boundaries of the human cognitive map.

Some links #3

Of my random meanderings around the Internet, I think the coolest thing I’ve seen this past week certainly has to be the Steampunk sequencer:

With that out of the way, here are some links:

Broca's Area and Hierarchical Structure Building

Considering I devoted two blog posts (pt.1 & pt.2) to Broca’s area and its role in processing hierarchically organised sequences, I’m happy report the following from a Talking Brains post on Disentangling syntax and intelligibility:

Hierarchical structure building can be achieved without Broca’s area involvement.

I’ve only just finished reading the post and, despite having some thoughts on the topic, I’m going to read the actual paper in question (Disentangling syntax and intelligibility in auditory language comprehension) before commenting. Especially since the authors, Friederici et al, don’t seem to arrive at the same conclusions as the bloggers over at Talking Brains. Still, as far as I can tell, this is only looking at syntactic information within speech, and doesn’t really tell us anything about the processing of hierarchically organised sequences in other linguistic (e.g. written language) and non-linguistic (e.g. tool manufacturing) domains.

Here’s the abstract for the paper in question:

Studies of the neural basis of spoken language comprehension typically focus on aspects of auditory processing by varying signal intelligibility, or on higher-level aspects of language processing such as syntax. Most studies in either of these threads of language research report brain activation including peaks in the superior temporal gyrus (STG) and/or the superior temporal sulcus (STS), but it is not clear why these areas are recruited in functionally different studies. The current fMRI study aims to disentangle the functional neuroanatomy of intelligibility and syntax in an orthogonal design. The data substantiate functional dissociations between STS and STG in the left and right hemispheres: first, manipulations of speech intelligibility yield bilateral mid-anterior STS peak activation, whereas syntactic phrase structure violations elicit strongly left-lateralized mid STG and posterior STS activation. Second, ROI analyses indicate all interactions of speech intelligibility and syntactic correctness to be located in the left frontal and temporal cortex, while the observed right-hemispheric activations reflect less specific responses to intelligibility and syntax. Our data demonstrate that the mid-to-anterior STS activation is associated with increasing speech intelligibility, while the mid-to-posterior STG/STS is more sensitive to syntactic information within the speech.

Some links #1

Having now returned, I feel a long list of links is needed to kick start things:

Right, that’s all I’ve got time for at the moment. Laptop battery is dying and my bladder is urging me towards the toilet.

The arcuate fasciculus within the dual stream model pt.2

ResearchBlogging.org3.1 What is the dual stream model?

Given these separate anatomical accounts, attributing a function(s) to the arcuate is not clear cut, and any current account is far from the authoritative statement on the matter. Nonetheless, a vast majority of literature does place the arcuate as part of the dual stream model[1] of speech processing, although its exact role within these neural networks is still being disputed – and largely depends on which anatomical account you prescribe to.

The basic assumption of dual stream accounts is that phonological networks interact with both conceptual-semantic and motor-articulatory systems, leading to a distinction between the neural networks that process this speech information. These separate interactions are summarised under two processing streams: the dorsal stream and the ventral stream (Hickok and Poeppel, 2007). Connecting phonological networks with conceptual-semantic systems, using structures in the superior and middle portions of the temporal lobe, is the ventral stream. Meanwhile, the dorsal stream is linked via structures in the posterior frontal lobe to the posterior temporal lobe and parietal operculum, which connects phonological networks with motor-articulatory systems (ibid).

Continue reading “The arcuate fasciculus within the dual stream model pt.2”

Discerning the role of the arcuate fasciculus in speech processing pt.1

ResearchBlogging.orgOriginally identified by Reil (1809) and subsequently named by Burdach (1819), the arcuate fasciculus is a white-matter, neural pathway that intersects with both the lateral temporal cortex and frontal cortex via a “dorsal projection that arches around the Sylvain fissure.” (Rilling et al., 2008, pg. 426). Classical hypotheses saw this pathway as a critical component in connecting two centres of language: Broca’s area (speech production) and Wernicke’s area (speech comprehension) (Catani and Mesulam, 2008).

Much of these assumptions were based on a tentative relationship between language-impairment and damaged portions of the brain. Notably, damage to the arcuate fasciculus is implicated in a syndrome known as conduction aphasia, where an individual has difficulty in speech repetition. Often characterised by errors in spontaneous speech, an individual with conduction aphasia will be fully aware of their mistake, retaining well-preserved auditory comprehension and speech production while also being syntactically and grammatically correct (ibid).

Continue reading “Discerning the role of the arcuate fasciculus in speech processing pt.1”