Could a Neuroscientist Understand a Microprocessor?
Authors: Eric Jonas
Konrad Paul Kording
Journal: PLoS Computational Biology (2017)
Discipline: BIOLOGY & BIOCHEMISTRY
Keywords: neuroscience; data analysis algorithms; brain processing; datasets; microprocessor
Affiliations: Department of Electrical Engineering and Computer Science, University of California, Berkeley, Berkeley, California, United States of America., Department of Physical Medicine and Rehabilitation, Northwestern University and Rehabilitation Institute of Chicago, Chicago, Illinois, United States of America., Department of Physiology, Northwestern University, Chicago, Illinois, United States of America.

Abstract:  There is a popular belief in neuroscience that we are primarily data limited, and that producing large, multimodal, and complex datasets will, with the help of advanced data analysis algorithms, lead to fundamental insights into the way the brain processes information. These datasets do not yet exist, and if they did we would have no way of evaluating whether or not the algorithmically-generated insights were sufficient or even correct. To address this, here we take a classical microprocessor as a model organism, and use our ability to perform arbitrary experiments on it to see if popular data analysis methods from neuroscience can elucidate the way it processes information. Microprocessors are among those artificial information processing systems that are both complex and that we understand at all levels, from the overall logical flow, via logical gates, to the dynamics of transistors. We show that the approaches reveal interesting structure in the data but do not meaningfully describe the hierarchy of information processing in the microprocessor. This suggests current analytic approaches in neuroscience may fall short of producing meaningful understanding of neural systems, regardless of the amount of data. Additionally, we argue for scientists using complex non-linear dynamical systems with known ground truth, such as the microprocessor as a validation platform for time-series and structure discovery methods. 

Retracted: No

PubPeer comments:
 Concern about Figure 2B. * Orange boxes: the  Control and  ICA panels appear to show an overlap. I have marked that in the  Merge panels, but the overlap is also visible in the Nrf2 and Dapi single stain panels. ![file] , 
 More: ![file] , 
 Figs 4B, 6B. ![file] Are the loading control bands the same in these different combinations of conditions? , 
 We appreciate for your concern. We right now carefully re-check these data and seriously handle this issue. Then, we will explain for this overlap. At the same time, we will contact the editor of this journal and explain this issue. Thank you so much again. , 
 Compared the current publicated immunostaining picture with our raw data, we found that we mistook our selection on pictures and these pictures were correctly shown in our raw data. Thus, we had contacted with the editor of this journal and applied for the correction of these figures. Regarding the similarity of loading control bands, the similarity was quite higher. However, after we carefully checked and compared the bands, these two bands indeed came from different samples. We sincerely apologized for any inconvenience caused by our mistake. Once again, we sincerely appreciate for your reminder. , 
 #1 Compared the current publicated immunostaining picture with our raw data, we found that we mistook our selection on pictures and these pictures were correctly shown in our raw data. Thus, we had contacted with the editor of this journal and applied for the correction of these figures. , 
 #2 Compared the current publicated immunostaining picture with our raw data, we found that we mistook our selection on pictures and these pictures were correctly shown in our raw data. Thus, we had contacted with the editor of this journal and applied for the correction of these figures. , 
 #3 Regarding the similarity of loading control bands, the similarity was quite higher. However, after we carefully checked and compared the bands, these two bands indeed came from different samples. , 
 #7 Would you be so nice to upload your correct raw data images here to walk us through what had happened? Thank you. , 
 Thank you so much for your concerns. Attached below are the raw data. ![file] ![file] , 
 The authors regret for these mistakes in Figs. 2B and 6A in the original article. The specific changes are as follows: 1. In Fig. 2B, the images of control and ICA (0.1 u03bcM) groups are incorrect and the corrected Figure is provided below: ![file] 2. In Fig. 6A, the image of control group is incorrect and the correct Figure is provided below: ![file] The authors would like to apologise for any inconvenience caused. ,