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Chris Chatham
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by Chris Chatham in Developing Intelligence
When reading the title of this post, your knowledge of the world was sufficient to let you interpret the phrase "when pigs fly," but also alerted you to the fact that it is inconsistent with much of that world knowledge: clearly, pigs don't fly. A new study by Menenti, Petersson, Scheeringa & Hagoort localizes the neural basis of this "anomaly processing" to a particular region of the prefrontal cortex - the inferior frontal gyri - and finds that the local context surrounding such anomalies (say, that you're told hell has frozen over) has much stronger effects in one hemisphere than the other.
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Laura Menenti, Karl Magnus Petersson, René Scheeringa, & Peter Hagoort. (2008) When Elephants Fly: Differential Sensitivity of Right and Left Inferior Frontal Gyri to Discourse and World Knowledge. Journal of Cognitive Neuroscience, Early Access(Early Access), 2147483647-11. DOI: 10.1162/jocn.2008.21163
by Chris Chatham in Developing Intelligence
A lot has been written about domain-general processing in prefrontal cortex, and a very old lesson often gets overlooked: there are very basic hemispheric asymmetries (particularly in PFC) that divide information processing by modality. A very nice study by Morimoto et al provide a nice reminder of this important feature of neuronal organization, and illustrates that very specific regions of PFC are the only ones to show such hemispheric specialization in tasks that require cognitive control.
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Hiroki M. Morimoto, Satoshi Hirose, Junichi Chikazoe, Koji Jimura, Tomoki Asari, Ken-ichiro Yamashita, Yasushi Miyashita, & Seiki Konishi. (2008) On Verbal/Nonverbal Modality Dependence of Left and Right Inferior Prefrontal Activation during Performance of Flanker Interference Task. Journal of Cognitive Neuroscience, 20(11), 2006-2014. DOI: 10.1162/jocn.2008.20138
by Chris Chatham in Developing Intelligence
It's been said that psychology is a primitive discipline - stuck in the equivalent of pre-Newtonian physics. Supposedly we haven't discovered the basic principles underlying cognition, and are instead engaged in a kind of stamp collecting: arguing about probabilities that various pseudo-regularities are real, without having any overarching theory.
Some of this criticism is deserved, and some of it applies more widely to the life sciences. Perhaps the only underlying principle in biology is "why use just one solution when using many works just as well?" (Natural selection is no exception to the rule - see biased gene conversion). This thwarts any Newton-esque induction of underlying principles in the life sciences, and holds double for cognition, an emergent phenomenon of myriad interacting complex biological systems.
Nonetheless, the naysayers may have a look at Brown, Neath & Chater's 2007 Psychological Review article, "A Temporal Ratio Model of Memory" (freely available here). Brown et al. propose a theory they call SIMPLE - for "scale-independent memory, perception and learning" - and it's likely to organize a number of stamp collections.
The basic principles are these:
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Gordon D. A. Brown, Ian Neath, & Nick Chater. (2007) A temporal ratio model of memory. Psychological Review, 114(3), 539-576. DOI: 10.1037/0033-295X.114.3.539
Richard Shiffrin, Michael Lee, Woojae Kim, & Eric-Jan Wagenmakers. (2008) A Survey of Model Evaluation Approaches With a Tutorial on Hierarchical Bayesian Methods. Cognitive Science: A Multidisciplinary Journal, 32(8), 1248-1284. DOI: 10.1080/03640210802414826
by Chris Chatham in Developing Intelligence
Reductionism in the neurosciences has been incredibly productive, but it has been difficult to reconstruct how high-level behaviors emerge from the myriad biological mechanisms discovered with such reductionistic methods. This is most clearly true in the case of the motor system, which has long been studied as the programming of motor actions (at its least reductionistic). However, as pointed out by Mars et al., the brain is almost constantly enacting motor plans, and so the initiation of actions is more likely preceded by motor reprogramming than anything else. However, that process has only been studied in the domain of response inhibition, in the sense that previously-programmed actions must presumably be inhibited in order for "reprogramming" to take place.
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R. B. Mars, C. Piekema, M. G. H. Coles, W. Hulstijn, & I. Toni. (2007) On the Programming and Reprogramming of Actions. Cerebral Cortex, 17(12), 2972-2979. DOI: 10.1093/cercor/bhm022
by Chris Chatham in Developing Intelligence
An astonishing recent discovery in computational neuroscience is the relationship between dopamine and the "temporal differences" reinforcement learning algorithm (which Jake describes wonderfully here, and I've described in a little more detail here). The essential principle is that the difference between expected and received reward can be used to drive learning, and that this abstract learning theory can be tracked by the spikes and dips of dopamine in vivo (for under-expectation and over-expectation of reward, respectively).
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I. G. Dobbins. (2005) Domain-general and Domain-sensitive Prefrontal Mechanisms for Recollecting Events and Detecting Novelty. Cerebral Cortex, 15(11), 1768-1778. DOI: 10.1093/cercor/bhi054
by Chris Chatham in Developing Intelligence
Synaesthesia refers to the phenomenon where certain perceptual stimuli induce an unrelated and illusory perception - for example, a digit-color synaesthete may experience a sensation of the color green whenever exposed to the number 3. The relationships between the inducers and the induced synaesthetic experience are widely considered random; one anecodotal explanation is that letter-color synaesthesia could reflect a childhood memory of the particular colors used inrefrigerator magnet letters.
A recent Current Biology article from Kadosh, Henik and Walsh turns this common wisdom on its head. By breaking colors down into their underlying psychometric dimensions (luminance, saturation, and hue), Kadosh et al demonstrate a linear relationship between the value of a digit and the luminance of the synaesthetically-induced color, as illustrated in the graph below the fold:
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R COHENKADOSH, A HENIK, & V WALSH. (2007) Small is bright and big is dark in synaesthesia. Current Biology, 17(19). DOI: 10.1016/j.cub.2007.07.048
by Chris Chatham in Developing Intelligence
"Priming" refers to a pervasive phenomenon in which the repetition of a particular stimulus, response, or thought process facilitates its subsequent use. Might this phenomenon extend to more "executive" capacities as well? Read the rest of this post... | Read the comments on this post...... Read more »
Frederick Verbruggen, Gordon D. Logan, Baptist Liefooghe, & André Vandierendonck. (2008) Short-term aftereffects of response inhibition: Repetition priming or between-trial control adjustments?. Journal of Experimental Psychology: Human Perception and Performance, 34(2), 413-426. DOI: 10.1037/0096-1523.34.2.413
by Chris Chatham in Developing Intelligence
There's little evidence that "staging" the training of neural networks on language-like input - feeding them part of the problem space initially, and scaling that up as they learn - confers any consistent benefit in terms of their long term learning (as reviewed yesterday).
To summarize that post, early computational demonstrations of the importance of starting small were subsequently cast into doubt by numerous replication failures, with one exception: the importance of starting small is replicable when the training data lack temporal correlations. This leads to slow learning of the importance of longer timescales by simple recurrent networks, but learning can be sped up by "shaping" the type of input the network sees early in its learning.
Typically, these investigations have focused on grammar-like input data, in which a recursive phrase can be embedded between a noun and verb (e.g., the cat [who ate the bird [who had chicklings [who ate a worm [who...]]]] chased the dog.) A new paper from Krueger & Dayan uses training data from a very different context - the 12AXCPT - and illustrates that as in cases with uncorrelated embeddings, networks learning the 12AXCPT benefit from developmental staging, or shaping, of the input data. Interestingly, however, the 12AXCPT does involve correlations between the embeddings , thus not fitting the conditions (as laid out by Rohde and Plaut) that should generate an advantage from "starting small."
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Krueger KA, Dayan P. (2009) Flexible shaping: How learning in small steps helps. Cognition.
by Chris Chatham in Developing Intelligence
A new artificial neural network revives an old debate on the benefits of constraints in learning.... Read more »
Krueger KA, Dayan P. (2009) Flexible shaping: How learning in small steps helps. Cognition.
by Chris Chatham in Developing Intelligence
We often assume that true understanding is conveyed through spoken speech rather than gesture, but new research shows that "talking with your hands" can not only reveal different information than spoken language, it can be both more correct and yield better learning. Read the rest of this post... | Read the comments on this post...... Read more »
Sara Broaders, Susan Wagner Cook, Zachary Mitchell, & Susan Goldin-Meadow. (2007) Making children gesture brings out implicit knowledge and leads to learning. Journal of Experimental Psychology: General, 136(4), 539-550. DOI: 10.1037/0096-3445.136.4.539
by Chris Chatham in Developing Intelligence
When do we learn to imagine the future, and how is that capacity based on imagining the past? How does this kind of "mental time travel" develop? Lagatutta's recent article in Child Development tracks the development of this impressive feat, thought by some to be uniquely human. Read the rest of this post... | Read the comments on this post...... Read more »
Kristin Lagattuta . (2007) Thinking About the Future Because of the Past: Young Children’s Knowledge About the Causes of Worry and Preventative Decisions. Child Development, 78(5), 1492-1509. info:PMID/17883444
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