1. Optimism vs. skepticism in cognitive neuroscience (Bechtel + Gallant’s lab vs. Uttal + Hardcastle)

2. Optimism I. Bechtel (‘11) “Heuristic identity theory” (fMRI) over 30 areas in for visual processing (occipital lobe, parietal and temporal cortex) (‘08) fMRI – notions “localization” “brain areas” re- conceptualized Bechtel’s alternative: mechanism + dynamical system = dynamical mechanisms In 2008 – B: reductionism + emergence Autonomy of system (from Bernard’s notion of “internal environment”, Cannon’s “homeostasis”, Varela’s “autopoiesis”)

3. “In fact, living systems has typically highly integrated despite the differentiation of operations between different organs and cell types. The mind/brain seems to be no different on this score – it consists of component processing areas that perform different computations which has nonetheless highly integrated with each other. Such a mechanism does not typically include encapsulated modules, and one is not likely to find them in the mind/brain.” (Bechtel 2009)

4. Mental mechanisms with specific functions could be localized, but he emphasizes the integration Sporns and Zwi’s (2004) “dual role of cortical connectivity”: (1) The functional specificity of certain cortical areas that manipulates specific information (2) The integration of this kind of information in a coherent behavior and cognitive states (“integration into coherent global states through oscillations in thalamic neurons play in producing global states”)

5. II. Gallant’s lab (1)Gallant 2008 + 2009 120 pictures in V1, V2, V3 Training set: fMRI signals to a larger (1,750) library of natural images and measured the fMRI responses produced by each of a number of voxels A representation of each picture - formed - spatial frequency and orientation information summarized as a “predicted activity pattern” for each of voxels associated with picture = Quantitative representation of fMRI responses to each image. (Uttal, p. 112) Based on similarities, the voxel pattern of each image (from those 120) was compared with information from library, the best fitting image being selected.

6. (2) “Reverse retinopy” Thiron et al (2006) and Miyawaki et al. (2008) (in Uttal, p. 114) Shape of simple geometrical forms is preserved enough in early retinotopic regions of visual system = Preservation of topology of original stimulus pattern and spatial resolvability of spatial pattern Examine spatial pattern of activated voxels, and infer shape of stimulus. (…) Spatial information is retinotopically persevered in early portion of the visual system. (Uttal, p. 113)

7. (3) Gallant et al. second work – not “reverse retinopy” method but “complex natural scenes from nonisomorphic fMRI images” Uttal: “a process of recognition, selection, or identification of an image from a known library of alternatives rather than a reconstruction in either the psychological or the neuroscientific sense.” (Uttal 2011, p. 114) Uttal: Reconstructed images - “not pictures - directly reconstructed from fMRI data but pictures produced by combining parts of pictures that were selected from the library of images, that is, the Bayesian priors on which the system was originally trained.” (p. 114)

8. They selected pictures from their library based on the pattern of activations This is not reconstruction per se; it is once again selecting from a predetermined “deck of cards”. Gallant 2011 fMRI, computer progamm = Quantitative modeling of brain activity measurements Reconstructed natural movies In the past, main problem: blood oxygen level- dependent (BOLD) signals measured by fMRI are much slower than neuronal activity in relationship with dynamic stimuli

9. “Motion-energy encoding” model has to fit two components: visual motion information and slow hemodynamics mechanisms V1, V2, V3 (occipitaltemporal visual cortex areas) = How spatial and temporal information are represented in thousands of voxels of visual cortex Watched several hours of movies – brain scanned fMRI --- measurements in computer Comparing fMRI data and details of each movie, computer program constructs “dictionaries” for shape, edge and motion. Each voxel has such a dictionary.

10. Second set of movies- new fMRI data --- reconstruction “The goal of movie reconstruction is to use the evoked activity to recreate the movie you observed. To do this, we create encoding models that describe how movies are transformed into brain activity, and then we use those models to decode brain activity and reconstruct the stimulus.” (Gallantlab.org) [Meaning + binding problem (oscillations)?]

11. Skepticism I. Hardcastle (2007) Cognition: More and more interests in development neurobiology (more and more molecular) or gene-environment interactions Perception: from where its stability? “… perceptual systems represent the external environment to us. Through complex computations we do not yet understand, our sensory systems derive stable images from the ever-fluctuating raw signals of our transducers.” (p. 296)

12. How and where are our sensory signals encoded and stored? How do we separate “figure” from “ground”? How are incoming signals “mixed” with our memories, attention, and our understanding of the world so that we get full-blown representa- tional experiences? How do we combine informa- tion from different sensory modalities? How do other brain systems transform and use this informa- tion? How do they modulate the represen- tations to meet our behavioral goals and biological needs? How do we use representations to regulate action, planning, and other outputs? (p.297)

13. The neuroscientists can record no more than simultaneously 150 neurons, they can summed LFP from no more than several thousands. “But brain areas have hundreds of thousands of neurons, several orders of magnitude more than they can access at any given time. And these neurons are of different types, with different response properties and different interconnections with other cells, including other similar neurons, neurons with significantly different response properties, and cells of other types completely.” (p. 304)

14. Problems with Recording activity of one cell inserting an electrode (feedback projections in the brain) Lesions and fMRI investigation (fMRI has quite well spatio-temporal limits) “Neuroscience is a victim of imprecise instrumentation. If scientists extrapolate from what they might learn with more sensitive measures, it can easily be seen that there will come a time when this whole approach just will not work anymore. Put in the harshest terms, brain imaging seems to support reductionism because the imaging technology is not very good yet.” (p. 306)

15. II. Uttal’s skepticism (2011) “In effect, we are doing what we can do when we cannot do what we should do.” (2011) Role of fMRI in mind-brain problem – status of cognitive neuroscience “explosive growth of [brain imaging] - No comprehensive and synoptic evaluation of huge number of studies” (p. 1) Against localization: any simple thought involves whole brain

16. Ontological Postulate (1) All mental processes are the outcome of neural activity. (2) All mental processes are the outcome of the microscopic interactions and actions of the great neuronal networks of the brain. fMRI grasp macro-level not micro-level Against localization: bidirectionality (+ complexity of brain) and degeneracy (Edelman) of neuronal areas

17. Epistemological postulates (1)Brain activity associated with mental activity is broadly distributed on and in the brain → Phrenological localization - replaced with broadly distributed neural systems for mental activity (2)Great complexity and number of neural networks → Not possible to find correlations neural-mental Brain imaging techniques do best - where the brain activity is observed when a stimulus is presented “neural network approach is computationally intractable” → Mind-body problem cannot be solved