I know, to free will or not to free will, that is the hackneyed question debated in philosophical circles since we learned how to talk. But here’s a cognitive neuroscientist’s research on “how neuronal code underlies top-down mental causation.” It’s a long video, over 2 hours, and I have yet to complete it. Here is Peter Tse’s CV. Here is his book on the topic is. Here is a good summary of Tse’s work on the topic.
Several of us met on Labor Day with the goal of identifying topics for at least five future monthly meetings. (Thanks, Dave N, for hosting!) Being the overachievers we are, we pushed beyond the goal. Following are the resulting topics, which will each have its own article on this site where we can begin organizing references for the discussion:
- sex-related influences on emotional memory
- gross and subtle brain differences (e.g., “walls of the third ventricle – sexual nuclei”)
- “Are there gender-based brain differences that influence differences in perceptions and experience?”
- epigenetic factors (may need an overview of epigenetics)
- embodied cognition
- computational grounded cognition (possibly the overview and lead-in topic)
- neuro-reductionist theory vs. enacted theory of mind
- “Could embodied cognition influence brain differences?” (Whoever suggested this, please clarify.)
- brain-gut connection (relates to embodied cognition, but can stand on its own as a topic)
- behavioral priming (one or multiple discussions)
- neuroscience of empathy – effects on the brain, including on neuroplasticity
- comparative effects of various meditative practices on the brain
- comparative effects of various psychedelics on the brain
- effects of childhood poverty on the brain
If I missed anything, please edit the list (I used HTML in the ‘Text’ view to get sub-bullets). If you’re worried about the formatting, you can email your edits to email@example.com and Mark will post your changes.
Caltech researchers have identified the brain mechanisms that enable primates to quickly identify specific faces. In a feat of efficiency, surprisingly few feature-recognition neurons are involved in a process that may be able to distinguish among billions of faces. Each neuron in the facial-recognition system specializes in noticing one feature, such as the width of the part in the observed person’s hair. If the person is bald or has no part, the part-width-recognizing neuron remains silent. A small number of such specialized-recognizer neurons feed their inputs to other layers (patches) that integrate a higher-level pattern (e.g., hair pattern), and these integrate at yet higher levels until there is a total face pattern. This process occurs nearly instantaneously and works regardless of the view angle (as long as some facial features are visible). Also, by cataloging which neurons perform which functions and then mapping these to a relatively small set of composite faces, researchers were able to tell which face a macaque (monkey) was looking at.
These findings seem to correlate closely with Ray Kurzweil’s (Google’s Chief Technology Officer) pattern-recognition theory of mind.
BMCAI library file (site members only)
New Scientist article: Applying the mathematical field of topology to brain science suggests gaps in densely connected brain regions serve essential cognitive functions. Newly discovered densely connected neural groups are characterized by a gap in the center, with one edge of the ring (cycle) being very thin. It’s speculated that this architecture evolved to enable the brain to better time and sequence the integration of information from different functional areas into a coherent pattern.
Aspects of the findings appear to support Edelman’s and Tononi’s (2000, p. 83) theory of neuronal group selection (TNGS, aka neural Darwinism).
Edelman, G.M. and Tononi, G. (2000). A Universe of Consciousness: How Matter Becomes Imagination. Basic Books.
“Until recently, scientists had thought that most synapses of a similar type and in a similar location in the brain behaved in a similar fashion with respect to how experience induces plasticity,” Friedlander said. “In our work, however, we found dramatic differences in the plasticity response, even between neighboring synapses in response to identical activity experiences.”
“Individual neurons whose synapses are most likely to strengthen in response to a certain experience are more likely to connect to certain partner neurons, while those whose synapses weaken in response to a similar experience are more likely to connect to other partner neurons,” Friedlander said. “The neurons whose synapses do not change at all in response to that same experience are more likely to connect to yet other partner neurons, forming a more stable but non-plastic network.”