Discontinuity between human and nonhuman minds?

In a recent issue of Brain and Behavioral Science (BBS) Penn, Holyoak and Povinelli argue for a profound difference in kind, not degree, between human and animal minds. Their suggestions elicit mainly vigorous opposition as well as some support from an array of commentators. Several of the commentators point out evidence for flexible relational capabilities within a physical symbol system exhibited by dolphins and birds. As I read through the debate and its mind-numbing detail I give up on trying to convey a succinct summary, but here is their abstract. (You might compare this with the work of Hauser et al, that I mentioned in a previous post.):

Over the last quarter century, the dominant tendency in comparative cognitive psychology has been to emphasize the similarities between human and nonhuman minds and to downplay the differences as “one of degree and not of kind” (Darwin 1871). In the present target article, we argue that Darwin was mistaken: the profound biological continuity between human and nonhuman animals masks an equally profound discontinuity between human and nonhuman minds. To wit, there is a significant discontinuity in the degree to which human and nonhuman animals are able to approximate the higher-order, systematic, relational capabilities of a physical symbol system (PSS) (Newell 1980). We show that this symbolic-relational discontinuity pervades nearly every domain of cognition and runs much deeper than even the spectacular scaffolding provided by language or culture alone can explain. We propose a representational-level specification as to where human and nonhuman animals' abilities to approximate a PSS are similar and where they differ. We conclude by suggesting that recent symbolic-connectionist models of cognition shed new light on the mechanisms that underlie the gap between human and nonhuman minds.

Your lips in my brain...

The title of the Kriegstein et al. article is: "Simulation of talking faces in the human brain improves auditory speech recognition." It turns out that observing a specific person talking for 2 min improves our subsequent auditory-only speech and speaker recognition for this person. This shows that, in auditory-only speech, the brain exploits previously encoded audiovisual correlations to optimize communication. The authors suggest that this optimization is based on speaker-specific audiovisual internal models, which are used to simulate a talking face. From the author's introduction:

Human face-to-face communication works best when one can watch the speaker's face. This becomes obvious when someone speaks to us in a noisy environment, in which the auditory speech signal is degraded. Visual cues place constraints on what our brain expects to perceive in the auditory channel. These visual constraints improve the recognition rate for audiovisual speech, compared with auditory speech alone. Similarly, speaker identity recognition by voice can be improved by concurrent visual information. Accordingly, audiovisual models of human voice and face perception posit that there are interactions between auditory and visual processing streams

Neurophysiological face processing studies indicate that distinct brain areas are specialized for processing time-varying information [facial movements, superior temporal sulcus (STS), and time-constant information (face identity, fusiform face area (FFA). If speech and speaker recognition are neuroanatomically dissociable, and the improvement by audiovisual learning uses learned dependencies between audition and vision, the STS should underpin the improvement in speech recognition in both controls and prosopagnosics. A similar improvement in speaker recognition should be based on the FFA in controls but not prosopagnosics. Such a neuroanatomical dissociation would imply that visual face processing areas are instrumental for improved auditory-only recognition.

The authors in fact obtained these results when they used functional magnetic resonance imaging (fMRI) to show the response properties of these two areas.

More on language and perception...

Christine Kenneally writes a nice summary of current work on how language can nudge our perception. One interesting result demonstrates that labeling different categories enhances one's ability to discriminate between them. She discusses the work of Boroditsky mentioned in my Feb. 22 post, and work showing that in giving us symbols for spatial patterns, spatial language helps us carve up the world in specific ways. It appears that the ability to count is necessary to deal with large, specific numbers. And the only way to count past a certain point is with language.

Brain changes in dyslexia - different in Hong Kong and Chicago

Siok et al show that the brain changes associated with dyslexia in an alphabetic versus an ideographic language can be different. In alphabetic language, a reader sees a letter and associates it with a sound. Chinese characters correspond to syllables and require much more memorization. Both Chinese and English dyslexics find it harder to make their way through even fairly simple written material. This study suggests that their brain mechanics as they try to read may be as different as Chinese is from English. Here is their abstract:

Developmental dyslexia is a neurobiologically based disorder that affects approximately 5–17% of school children and is characterized by a severe impairment in reading skill acquisition. For readers of alphabetic (e.g., English) languages, recent neuroimaging studies have demonstrated that dyslexia is associated with weak reading-related activity in left temporoparietal and occipitotemporal regions, and this activity difference may reflect reductions in gray matter volume in these areas. Here, we find different structural and functional abnormalities in dyslexic readers of Chinese, a nonalphabetic language. Compared with normally developing controls, children with impaired reading in logographic Chinese exhibited reduced gray matter volume in a left middle frontal gyrus region previously shown to be important for Chinese reading and writing. Using functional MRI to study language-related activation of cortical regions in dyslexics, we found reduced activation in this same left middle frontal gyrus region in Chinese dyslexics versus controls, and there was a significant correlation between gray matter volume and activation in the language task in this same area. By contrast, Chinese dyslexics did not show functional or structural (i.e., volumetric gray matter) differences from normal subjects in the more posterior brain systems that have been shown to be abnormal in alphabetic-language dyslexics. The results suggest that the structural and functional basis for dyslexia varies between alphabetic and nonalphabetic languages.

Language evolution and the arcuate fasciculus

Did language evolve gradually via communication precursors in the primate lineage or did it arise spontaneously through a fortuitous confluence of neuroanatomical changes that are found only in humans? Rilling et al., reviewed by Ghazanfar, have used diffusion-tensor imaging to track putative differences in white matter connectivity between the frontal and temporal lobes, a pathway that is essential for language, by comparing humans, chimpanzees and macaque monkeys. They focused on the arcuate fasciculus,the fiber tract connecting the temporal to the frontal lobes in humans, which is essential for language in humans. Lesions to this pathway result in conduction aphasia, in which, among other deficits, patients can comprehend speech, but cannot repeat what was said. Rilling et al found that the organization of cortical terminations between the temporal and frontal lobes was strongly modified in the course of human evolution, and, crucially, this modification was gradual. They also noted a prominent temporal lobe projection of the human arcuate fasciculus that is much smaller or absent in nonhuman primates. This human specialization may be relevant to the evolution of language.


Figure from the News and Views summary by Ghazanfar (click to enlarge) - Chimpanzees are phylogenetically between macaques and humans in the primate lineage, and the similarly 'in between' pattern of their arcuate pathway terminations strongly suggest a gradual evolution of this pathway.(a) Changing patterns of connections between frontal cortical areas and the temporal lobe in humans, chimpanzees and macaque monkeys. AS, arcuate sulcus; CS, central sulcus; IFS, inferior frontal sulcus; IPS, intraparietal sulcus; PS, principal sulcus; PrCS, precentral sulcus; STS, superior temporal sulcus. (b) The voice area in the rhesus macaque relative to other auditory cortical areas and where the voice area would be if it were in a similar location as the human voice area. LS, lateral sulcus; IOS, inferior occipital sulcus; STS, superior temporal sulcus; other labels refer to cytoarchitectonic areal designations. The lateral sulcus is cut open to reveal the superior temporal plane. In this plane, the core region is thought to contain 'primary-like' areas, responding best to pure tones, whereas the surrounding belt areas are more responsive to complex sounds. The voice area in macaques is anterior to the core and belt regions. INS, insula; IT, inferotemporal cortex; Tpt, temporoparietal area.

Infants to adults, color perception switches from right to left hemisphere

An interesting article by Franklin et al. shows that our perception of color categories (CP) starts in the right hemisphere, but then switches to the left hemisphere as it develops the lexical color codes of language. They suggest that language-driven CP in adults may not build on prelinguistic CP, but that language instead imposes its categories on a left hemisphere that is not categorically prepartitioned.

Influence of language on brain activity underlying perceptual decisions

Following up on my Feb. 22 post on the same topic, I pass on the abstract of work by Tan et al., showing that language-processing areas of the brain are directly involved in visual perceptual decisions:

Well over half a century ago, Benjamin Lee Whorf [Carroll JB (1956) Language, Thought, and Reality: Selected Writings of Benjamin Lee Whorf (MIT Press, Cambridge, MA)] proposed that language affects perception and thought and is used to segment nature, a hypothesis that has since been tested by linguistic and behavioral studies. Although clear Whorfian effects have been found, it has not yet been demonstrated that language influences brain activity associated with perception and/or immediate postperceptual processes (referred hereafter as "perceptual decision"). Here, by using functional magnetic resonance imaging, we show that brain regions mediating language processes participate in neural networks activated by perceptual decision. When subjects performed a perceptual discrimination task on easy-to-name and hard-to-name colored squares, largely overlapping cortical regions were identified, which included areas of the occipital cortex critical for color vision and regions in the bilateral frontal gyrus. Crucially, however, in comparison with hard-to-name colored squares, perceptual discrimination of easy-to-name colors evoked stronger activation in the left posterior superior temporal gyrus and inferior parietal lobule, two regions responsible for word-finding processes, as demonstrated by a localizer experiment that uses an explicit color patch naming task. This finding suggests that the language-processing areas of the brain are directly involved in visual perceptual decision, thus providing neuroimaging support for the Whorf hypothesis.

Figure legend (Click on figure to enlarge it). Brain activations elicited by color perception and explicit color naming. (A and B) Areas showing significant activation during perceptual discrimination of easy-to-name colors in comparison with perceptual discrimination of hard-to-name colors. A and B are lateral view and axial sections, respectively. Two regions of greatest interest are the left posterior superior temporal gyrus (BA 22; x = –57, y = –38, z = 18) and the left inferior parietal lobule (BA 40; x = –61, y = –32, z = 27). (C and D) Percentage BOLD signal change (± SEM) at voxels of maximal difference between the two color-discrimination conditions in the two regions of interest. (E and F) Areas showing significant activation in explicit color naming against color word naming as baseline. E and F are lateral view and axial sections, respectively. The left posterior superior temporal gyrus and the left inferior parietal lobule are critically engaged by the color naming task.

A voice region in the monkey brain

Both human and monkey brains have visual regions that are activated most strongly by the faces of conspecifics. Our brains also have have a region that is specialized for processing human voices that is located anteriorly on the temporal lobe, on the upper bank of the superior-temporal sulcus. Logothetis and his colleagues have now found a corresponding region in monkey brains. Their abstract and a portion of one of the figures:

For vocal animals, recognizing species-specific vocalizations is important for survival and social interactions. In humans, a voice region has been identified that is sensitive to human voices and vocalizations. As this region also strongly responds to speech, it is unclear whether it is tightly associated with linguistic processing and is thus unique to humans. Using functional magnetic resonance imaging of macaque monkeys (Old World primates, Macaca mulatta) we discovered a high-level auditory region that prefers species-specific vocalizations over other vocalizations and sounds. This region not only showed sensitivity to the 'voice' of the species, but also to the vocal identify of conspecific individuals. The monkey voice region is located on the superior-temporal plane and belongs to an anterior auditory 'what' pathway. These results establish functional relationships with the human voice region and support the notion that, for different primate species, the anterior temporal regions of the brain are adapted for recognizing communication signals from conspecifics.

Figure - The color code from orange to red indicates voxels with a clear and significant preference for macaque vocalizations. The cyan-to-blue color code identifies voxels with no preference for MVocs. The slice orientation and position are shown in the lower inset

Languages shape the nuts and bolts of our perception.

The debate over whether language nudges the way we actually see the world is being resolved, and what has been the prevailing dogma - that basic parts of perception are too low-level, too hard-wired, too constrained by the constants of physics and physiology to be affected by language - is breaking down. Lera Boroditsky at Standford comments on this.

I used to think that languages and cultures shape the ways we think. I suspected they shaped they ways we reason and interpret information. But I didn't think languages could shape the nuts and bolts of perception, the way we actually see the world. That part of cognition seemed too low-level, too hard-wired, too constrained by the constants of physics and physiology to be affected by language.

Then studies started coming out claiming to find cross-linguistic differences in color memory. For example, it was shown that if your language makes a distinction between blue and green (as in English), then you're less likely to confuse a blue color chip for a green one in memory. In a study like this you would see a color chip, it would then be taken away, and then after a delay you would have to decide whether another color chip was identical to the one you saw or not.

Of course, showing that language plays a role in memory is different than showing that it plays a role in perception. Things often get confused in memory and it's not surprising that people may rely on information available in language as a second resort. But it doesn't mean that speakers of different languages actually see the colors differently as they are looking at them. I thought that if you made a task where people could see all the colors as they were making their decisions, then there wouldn't be any cross-linguistic differences.

I was so sure of the fact that language couldn't shape perception that I went ahead and designed a set of experiments to demonstrate this. In my lab we jokingly referred to this line of work as "Operation Perceptual Freedom." Our mission: to free perception from the corrupting influences of language.

We did one experiment after another, and each time to my surprise and annoyance, we found consistent cross-linguistic differences. They were there even when people could see all the colors at the same time when making their decisions. They were there even when people had to make objective perceptual judgments. They were there when no language was involved or necessary in the task at all. They were there when people had to reply very quickly. We just kept seeing them over and over again, and the only way to get the cross-linguistic differences to go away was to disrupt the language system. If we stopped people from being able to fluently access their language, then the cross-linguistic differences in perception went away.

I set out to show that language didn't affect perception, but I found exactly the opposite. It turns out that languages meddle in very low-level aspects of perception, and without our knowledge or consent shape the very nuts and bolts of how we see the world.

Pinker et al. on the logic of indirect speech.

Pinker, Nowak, and Lee do an interesting perspectives article in PNAS that looks more rigorously at why we don't just blurt out what we mean, as in:

- Would you like to come up and see my etchings? [a sexual come-on]
- If you could pass the guacamole, that would be awesome. [a polite request]
- Nice store you got there. Would be a real shame if something happened to it. [a threat]
- We're counting on you to show leadership in our Campaign for the Future. [a solicitation for a donation]
- Gee, officer, is there some way we could take care of the ticket here? [a bribe]

Here is their abstract:

When people speak, they often insinuate their intent indirectly rather than stating it as a bald proposition. Examples include sexual come-ons, veiled threats, polite requests, and concealed bribes. We propose a three-part theory of indirect speech, based on the idea that human communication involves a mixture of cooperation and conflict. First, indirect requests allow for plausible deniability, in which a cooperative listener can accept the request, but an uncooperative one cannot react adversarially to it. This intuition is supported by a game-theoretic model that predicts the costs and benefits to a speaker of direct and indirect requests. Second, language has two functions: to convey information and to negotiate the type of relationship holding between speaker and hearer (in particular, dominance, communality, or reciprocity). The emotional costs of a mismatch in the assumed relationship type can create a need for plausible deniability and, thereby, select for indirectness even when there are no tangible costs. Third, people perceive language as a digital medium, which allows a sentence to generate common knowledge, to propagate a message with high fidelity, and to serve as a reference point in coordination games. This feature makes an indirect request qualitatively different from a direct one even when the speaker and listener can infer each other's intentions with high confidence.

A Mea Culpa - Pinker and his critics

I think in general that Steven Pinker goes way overboard on the nativist angle, and so recently approvingly passed on this Churchland review in the Nov. 1 issue of Nature critical of Pinker's new book, "The Language of Thought." - I hadn't actually read the book. These retorts by Marc Hauser and Pinker himself in the Dec. 6 issue make me realize that I should have. I have zapped my original post, and I'm now going to read the book......(one thing about doing a blog is that you read fewer good long books). I admit to a residual grumpyness about Pinker (a brilliant man) from his visit to Wisconsin a number of years ago as a featured speaker. He was dragged through the usual torture of serial 30 minute interviews with local "prominent persons" (I was the Zoology Chair at that time), and during our conversation I found him to be quite remote. At his talk he read from a typescript - word for word - a lecture that I had already heard twice before.

Single cells in monkey brain trained to associate numbers with their symbols

An interesting study from Diester and Nieder showing single nerve cell activity that might be the primitive cognitive precursor that ultimately has given rise to symbolic thinking in linguistic humans. Their abstract:

The utilization of symbols such as words and numbers as mental tools endows humans with unrivalled cognitive flexibility. In the number domain, a fundamental first step for the acquisition of numerical symbols is the semantic association of signs with cardinalities. We explored the primitives of such a semantic mapping process by recording single-cell activity in the monkey prefrontal and parietal cortices, brain structures critically involved in numerical cognition. Monkeys were trained to associate visual shapes with varying numbers of items in a matching task. After this long-term learning process, we found that the responses of many prefrontal neurons to the visual shapes reflected the associated numerical value in a behaviorally relevant way. In contrast, such association neurons were rarely found in the parietal lobe. These findings suggest a cardinal role of the prefrontal cortex in establishing semantic associations between signs and abstract categories, a cognitive precursor that may ultimately give rise to symbolic thinking in linguistic humans.

Brain location of verbal information storage varies between people

A group at Wisconsin has made the interesting observation that group averaged analyses of the sort frequently reported in brain imaging studies may give misleading results if the brain location of the process being studied varies from one individual to the next. Here is their abstract:

What are the precise brain regions supporting the short-term retention of verbal information? A previous functional magnetic resonance imaging (fMRI) study suggested that they may be topographically variable across individuals, occurring, in most, in regions posterior to prefrontal cortex (PFC), and that detection of these regions may be best suited to a single-subject (SS) approach to fMRI analysis. In contrast, other studies using spatially normalized group-averaged (SNGA) analyses have localized storage-related activity to PFC. To evaluate the necessity of the regions identified by these two methods, we applied repetitive transcranial magnetic stimulation (rTMS) to SS- and SNGA-identified regions throughout the retention period of a delayed letter-recognition task. Results indicated that rTMS targeting SS analysis-identified regions of left perisylvian and sensorimotor cortex impaired performance, whereas rTMS targeting the SNGA-identified region of left caudal PFC had no effect on performance. Our results support the view that the short-term retention of verbal information can be supported by regions associated with acoustic, lexical, phonological, and speech-based representation of information. They also suggest that the brain bases of some cognitive functions may be better detected by SS than by SNGA approaches to fMRI data analysis.

Figure: Example from subject 7 of SS and SNGA rTMS targets (orange markers; anterior, SNGA; posterior, SS). White blobs on the brain are load-sensitive regions identified by the SS analysis, which have been merged onto this subject's high-resolution T1-weighted anatomical scan, and are visible at this depth of scalp "peeling."

Origin of language from cortical motor systems - evidence from fMRI imaging

Meister and Iacoboni offer some interesting observations supporting the idea that language evolved as an exaptation from motor cortical systems. Here is some of their text and a central figure from the paper.

It has been suggested that cortical neural systems for language evolved from motor cortical systems, in particular from those fronto-parietal systems responding also to action observation. While previous studies have shown shared cortical systems for action – or action observation - and language, they did not address the question of whether linguistic processing of visual stimuli occurs only within a subset of fronto-parietal areas responding to action observation. If this is true, the hypothesis that language evolved from fronto-parietal systems matching action execution and action observation would be strongly reinforced

...functional magnetic resonance imaging (fMRI) was used while subjects watched video stimuli of hand-object-interactions and control photo stimuli of the objects and performed linguistic (conceptual and phonological), and perceptual tasks. Since stimuli were identical for linguistic and perceptual tasks, differential activations had to be related to task demands. The results revealed that the linguistic tasks activated left inferior frontal areas that were subsets of a large bilateral fronto-parietal network activated during action perception. Not a single cortical area demonstrated exclusive – or even simply higher - activation for the linguistic tasks compared to the action perception task.

The results show that linguistic tasks do not only share common neural representations but essentially activate a subset of the action observation network if identical stimuli are used. Our findings strongly support the evolutionary hypothesis that fronto-parietal systems matching action execution and observation were co-opted for language, a process known as exaptation.

Figure 3. a) cortical networks activated by the decision task relating to action observation vs rest (Vd-Perc vs rest, red) and action observation vs perceptual decisions on photos of the same objects (Vd-Perc vs Ph-Perc, blue). The large bihemispheric networks found for both contrasts were very similar, suggesting that the fMRI activations found here mainly were related to action observation and not to processes of decision making or object perception required during these tasks, as well. b) Cortical networks activated during the phonological (blue) and the conceptual decision task (red) on photos of manipulable objects. The networks activated by these two linguistic tasks were entirely part of the action observation network depicted in Fig. 3a, in accordance with the hypothesis that development of language out of the mirror neuron system was driven by a process of exaptation.

Language Evolution: An invisible hand.

A slightly edited "Editor's Summary" from the Oct. 11 Nature:

As a language evolves, grammatical rules emerge and exceptions die out. Lieberman et al. have calculated the rate at which a language grows more regular, based on 1,200 years of English usage. Of 177 irregular verbs, 79 became regular in the last millennium. And the trend follows a simple rule: a verb's half-life scales as the square root of its frequency. Irregular verbs that are 100 times as rare regularize 10 times faster. The emergence of a rule (such as adding –ed for the past tense) spells death for exceptional forms...In a separate study, Pagel et al. looked at changing word meanings. Across the Indo-European languages, words like 'tail' or 'bird' evolve rapidly and are expressed by many unrelated words. Others, like 'two', are expressed by closely related word forms across the whole language family. Data from over 80 modern languages show that the more a word is used, the less it changes.

And, from Fitch's review of the two papers:

The words of language are not inherited biologically, but are passed on culturally through learning. This process of 'cultural evolution' generates a hierarchical tree of relationships among languages, here illustrated by the Indo-European family. Just as descent with modification in biological evolution (phylogeny) leads to phylogenetic trees, so the analogous process in language change (glossogeny) can lead to glossogenetic trees.

Where should we look to gain a deeper understanding of the invisible hand in the cultural evolution of language? A promising future direction is provided by recent attempts to fuse theoretical models of cultural evolution to experimental investigations of social learning in the laboratory. Experimental investigations of 'iterated learning' — similar to the game of Chinese whispers, where one participant's output serves as input for the next — can provide empirical data to inspire, and constrain, our theories. Sophisticated new theoretical models enable language-learning 'agents' to have both innate biases (in the form of so-called bayesian priors) and powerful statistical learning systems capable of discovering and using environmental regularities. Such models demonstrate the possibility of a very indirect and sometimes non-intuitive relationship between the regularities emerging at the level of a whole population and the underlying generating forces. These forces are individual behaviour and learning (social usage) and innate constraints (in Chomsky's terms, a 'language acquisition device', often called universal grammar).

..some of the most persistent 'cultural replicators' — memes — evolve as slowly as some genes. By documenting and quantifying such effects, this work opens the door to a diverse range of theoretical and empirical investigations. If there is ever to be a science of memetics o rival that of genetics, it should proceed along these lines: combining careful quantitative analysis of well-documented linguistic changes with sophisticated theoretical models capable of taking into account the multilayered complexity of cultural evolution.

Parallel Distributed Processing and Semantic Cognition

Timothy T. Rogers and James L. McClelland have distilled the essence of the arguments in their book "Semantic Cognition: A Parallel Distributed Processing Approach" for an article (PDF here) to appear in Brain and Behavioral Sciences with peer commentary. Here is their abstract:

In our recent book, we present a parallel distributed processing theory of the acquisition, representation and use of human semantic knowledge. The theory proposes that semantic abilities arise from the flow of activation amongst simple, neuron-like processing units, as governed by the strengths of interconnecting weights; and that acquisition of new semantic information involves the gradual adjustment of weights in the system in response to experience. These simple ideas explain a wide range of empirical phenomena from studies of categorization, lexical acquisition, and disordered semantic cognition. In this précis we focus on phenomena central to the reaction against similarity-based theories that arose in the 1980's and that subsequently motivated the "theory-theory" approach to semantic knowledge. Specifically, we consider i) how concepts differentiate in early development, ii) why some groupings of items seem to form "good" or coherent categories while others do not, iii) why different properties seem central or important to different concepts, iv) why children and adults sometimes attest to beliefs that seem to contradict their direct experience, v) how concepts reorganize between the ages of 4 and 10, and vi) the relationship between causal knowledge and semantic knowledge. The explanations for these phenomena are illustrated with reference to a simple feed-forward connectionist model; and the relationship between this simple model, the broader theory, and more general issues in cognitive science are discussed.

What the F***?

An article by Steven Pinker on cursing.

Ape language slips reveal category knowledge storage.

Michael Erard summarizes efforts (PDF here) to analyze 'language' errors of apes for insight into the covert mental processes of animals - analogous to such work done on human language errors He focuses on the work of Lyn, who was the first to apply the study of errors to bonobos . Kanzi and a female bonobo, Panbanisha, who now live at the Great Ape Trust in Des Moines, Iowa, can comprehend instructions and descriptions in spoken English, and they can respond by using 384 lexigrams, which they touch on a keyboard.

Lyn found that Kanzi and Panbanisha have arranged hundreds of lexigrams in their minds in a complex, hierarchical manner based mainly on their meaning. She coded the relations between all 1497 sample-error pairs along seven dimensions, including whether the lexigrams looked alike, had English words that sounded alike, or referred to objects in the same category. She found that the errors were not random but patterned. If the lexigram stood for "blackberry," the error was more likely than chance to sound like blackberry, be edible, be a fruit, or be physically similar. Errors were also more likely to be associated with more than one category. For example, "cherries" are both edibles and fruits, and the word sounds like the correct one, "blackberries." All this indicated to Lyn that mental representations of the lexigrams must be stored not as simple one-to-one associations but in more complex arrangements. This suggests that, given the chance, bonobos and other apes can acquire systems of meaning that are closer than anyone has thought to what humans do, and that some aspects of language acquisition are not unique to humans.

A "language gene" in echolocating bats

Slightly altered abstract from Li et al.:

FOXP2 is a transcription factor implicated in the development and neural control of orofacial coordination, particularly with respect to vocalisation. [Thus, it is not really a "language gene" as indicated in many popular press reports.] Observations that orthologues show almost no variation across vertebrates yet differ by two amino acids between humans and chimpanzees have led to speculation that recent evolutionary changes might relate to the emergence of language. Echolocating bats face especially challenging sensorimotor demands, using vocal signals for orientation and often for prey capture. To determine whether mutations in the FoxP2 gene could be associated with echolocation, we sequenced FoxP2 from echolocating and non-echolocating bats as well as a range of other mammal species. We found that contrary to previous reports, FoxP2 is not highly conserved across all nonhuman mammals but is extremely diverse in echolocating bats. We detected divergent selection (a change in selective pressure) at FoxP2 between bats with contrasting sonar systems, suggesting the intriguing possibility of a role for FoxP2 in the evolution and development of echolocation. We speculate that observed accelerated evolution of FoxP2 in bats supports a previously proposed function in sensorimotor coordination.

Did Alex really "want" a cracker?

New York Times science writer George Johnson, who is one very intelligent guy, has done a nice piece on the capabilities and history of Alex the parrot (PDF here). I was unaware of several of the behaviors that had been noted in Alex:

“Want a nut!” Alex demanded. The interview was over. “Want a nut!” he repeated. “Nnn ... uh ... tuh.”...Dr. Pepperberg was flabbergasted. “Not only could you imagine him thinking, ‘Hey, stupid, do I have to spell it for you?’ ” she said. “This was in a sense his way of saying to us, ‘I know where you’re headed! Let’s get on with it.’ ”....She is quick to concede the impossibility of proving that the bird was actually verbalizing its internal deliberations. Only Alex knew for sure.

Next to infinity, one of the hardest concepts to grasp is zero. Toward the end of his life Alex may have been coming close. In a carnival shell game, an experimenter would put a nut under one of three cups and then shuffle them around. Alex would pick up the cup where the prize was supposed to be. If it wasn’t there he’d go a little berserk — a small step, maybe, toward understanding nothingness.

A bigger leap came in an experiment about numbers, in which the parrot was shown groups of two, three and six objects. The objects within each set were colored identically, and Alex was asked, “What color three?”.... “Five,” he replied perversely (he was having a bad attitude day), repeating the answer until the experimenter finally asked, “O.K., Alex, tell me, ‘What color five?’ ”....“None,” the parrot said....Bingo. There was no group of five on the tray. It was another of those high huneker moments. Alex had learned the word “none” years before in a different context. Now he seemed to be using it more abstractly....Dr. Pepperberg reported the result with appropriate understatement: “That zero was represented in some way by a parrot, with a walnut-sized brain whose ancestral evolutionary history with humans likely dates from the dinosaurs, is striking.”