What the success of brain imaging implies about the neural code
- University College London, United Kingdom
- The Alan Turing Institute, United Kingdom
Figures
Figure 1
The activity of neurons in the top-left panel gradually changes from left to right, whereas changes are more abrupt in the top-middle and top-right panels.
Each square in the grid represents a voxel which summates activity within its frame as shown in the bottom panels. For the smoother pattern of neural activity, the summation of each voxel (bottom …
Figure 2
As models become more complex with added layers, similarity structure becomes harder to recover, which might parallel function along the ventral stream.
(A) For the artificial neural network coding schemes, similarity to the prototype falls off with increasing distortion (i.e., noise). The models, numbered 1–11, are (1) vector space coding, (2) gain …
Figure 3
The effect of matrix multiplication followed by the function on the input stimulus.
The output of this one-layer network is shown, as well as the outcome of applying a non-linearity to the output of the matrix multiplication. In this example, functional smoothness is preserved …
Figure 4
Similarity structure becomes more difficult to recover in the more advanced layers of the DLN.
(A) The similarity structure in a middle layer of a DLN, Inception-v3 GoogLeNet. The mammals (lions and tigers) and birds (robins and partridges) correlate forming a high-level domain, rendering the …
Tables
Table 1
Design matrix for a full factorial design.
| I | A | B | C | AB | AC | BC | ABC |
|---|---|---|---|---|---|---|---|
