Evolution of neural activity in circuits bridging sensory and abstract knowledge
- Gatsby Computational Neuroscience Unit, University College London, United Kingdom
- Center for Brain Science, Harvard University, United States
Figures
Figure 1
Schematics of tasks and circuit model used in the study.
(A) Illustration of the two categorization tasks. In the simple categorization task, half the stimuli are associated with category A and the other half with category B. In the context-dependent …
Figure 2 with 4 supplements
Characterization of activity evolution during the simple categorization task.
Results from simulations. The first column (A–D) shows a naive circuit (pre-learning); the second (E–H) and third (I–L) columns show two trained circuits (post-learning), characterized by different …
Figure 2—figure supplement 1
Characterization of activity evolution during the simple categorization task; additional results, part I.
(A) Extensive results from simulations. Each point represents a model. We simulated 5000 different models, with parameters drawn randomly and uniformly from the following ranges: the number of …
Figure 2—figure supplement 2
Characterization of activity evolution during the simple categorization task; additional results, part II.
(A–D) Population response to categories A and B averaged over stimuli. Each dot represents a neuron. Panels A, B and C, D display two sample circuits, different from those displayed in Figure 2. …
Figure 2—figure supplement 3
Learning curves.
Behaviour of the loss function (Equation 9) over learning epochs in four sample networks. (A, B) refer to the simple categorization task; parameters are, respectively, as in Figure 2E–H and Figure …
Figure 2—figure supplement 4
Simple categorization task with structured inputs and heterogeneity.
Analysis of category correlation for a naive circuit (A), and two trained ones (B, C). Details are, respectively, as in Figure 2C–D, G–H and K–L. (D) Extensive analysis of average category …
Figure 3 with 2 supplements
Analysis of activity evolution during the simple categorization task.
Results from mathematical analysis. (A–C) Cartoons illustrating how activity evolves over learning. The three columns are as in Figure 2: pre-learning (first column) and post-learning for two …
Figure 3—figure supplement 1
Comparison between finite-size networks and approximate mathematical description for the simple categorization task, part I.
Dashed lines show the theoretical predictions; dots show the average over 400 simulations where both the initial connectivity and the sensory inputs were drawn at random. Error bars show the …
Figure 3—figure supplement 2
Comparison between finite-size networks and approximate mathematical description for the simple categorization task, part II.
Details in (A-C) are as in Figure 3—figure supplement 1. We used different parameters (see Table 2), which lead to positive category correlation.
Figure 4
Category correlation depends on circuit and task properties.
(A) Category correlation as a function of the threshold and gain of the readout neuron. Grey arrows indicate the threshold and gain that are used in panels C and D. The learning rate ratio, , is …
Figure 5
Magnitude of category selectivity depends on connectivity with the readout neuron.
(A–C) Category selectivity as a function of the initial readout connectivity (in absolute value). The three columns are as in Figure 2: pre-learning (first column) and post-learning for two …
Figure 6 with 3 supplements
Characterization of activity evolution during the context-dependent categorization task.
Results from simulations. The first column (A–C) shows a naive circuit (pre-learning); the second (D–F) and third (G–I) columns show two trained circuits (post-learning), characterized by different …
Figure 6—figure supplement 1
Characterization of activity evolution during the context-dependent categorization task; additional results, part I.
(A) Extensive results from simulations. Each point represents a model. We simulated 5000 different models, with parameters drawn randomly. Details as in Figure 2—figure supplement 1A, except that …
Figure 6—figure supplement 2
Characterization of activity evolution during the context-dependent categorization task; additional results, part II.
(A, B) Population response to categories A and B, averaged over trials. Each dot represents a neuron. Panels A and B correspond to two sample circuits, characterized by different values of the …
Figure 6—figure supplement 3
Characterization of activity evolution during the context-dependent categorization task; additional results, part III.
(A-B) Changes in category (panel A) and context (panel B) selectivity as a function of the components on the category and context directions, and (in absolute value). The latter are defined in …
Figure 7 with 1 supplement
Analysis of activity evolution during the context-dependent categorization task.
Results from mathematical analysis. (A–C) Cartoons illustrating how activity evolves over learning. Orange and blue symbols are associated with categories A and B, respectively; circles and squares …
Figure 7—figure supplement 1
Comparison between finite-size networks and approximate mathematical description for the context-dependent categorization task.
Details are as in Figure 3—figure supplement 1. In all panels, the top and bottom plots show, respectively, results for the synaptic drive and the activity . (A) Average category selectivity. …
Figure 8
Patterns of pure and mixed selectivity to category and context.
(A) Changes in category selectivity (left) and context selectivity (right) as a function of the initial readout connectivity, (in absolute value). Details as in Figure 5B, C. (B) Changes in …
Tables
Table 1
Table of parameters for figures in the main text.
| Figure | |||||||
|---|---|---|---|---|---|---|---|
| Figures 2, 3 and 5, first and second columns | 200 | 20 | 0.0 | 1.0 | 2.0 | 1.0 | 0.0 |
| Figures 2, 3 and 5, third column | 200 | 20 | 0.0 | 1.0 | 2.0 | 1.0 | 2.0 |
| Figure 4A | 200 | 20 | 0.4 | 2.0 | 2.0 | varies | varies |
| Figure 4B | 200 | 20 | 0.4 | varies | varies | 1.0 | 2.0 |
| Figure 4C | 200 | 20 | varies | 2.0 | 2.0 | 1.0 | varies |
| Figure 4D | 200 | varies | 0.4 | 2.0 | 2.0 | 1.0 | varies |
| Figure 6A–C, first and second columns | 600 | 8 (P = 64) | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 |
| Figure 6A–C, third column | 600 | 8 (P=64) | 0.0 | 1.0 | 0.0 | 1.0 | 4.0 |
| Figure 7D | 600 | 8 (P = 64) | 0.2 | 2.5 | 2.0 | varies | varies |
| Figure 7E | 600 | 8 (P = 64) | varies | 2.5 | 2.0 | 1.0 | varies |
| Figure 7F | 600 | varies | 0.2 | 2.5 | 2.0 | 1.0 | varies |
Table 2
Table of parameters for figure supplements.
| Figure supplement | |||||||
|---|---|---|---|---|---|---|---|
| Figure 2—figure supplement 1A | 200 | varies | varies | varies | varies | varies | varies |
| Figure 2—figure supplement 2E | 200 | 20 | 0.0 | 1.0 | 2.0 | 1.0 | 0.0 |
| Figure 3—figure supplement 1, first column | varies | 20 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 |
| Figure 3—figure supplement 1, second column | 200 | 20 | varies | 1.0 | 0.0 | 1.0 | 0.0 |
| Figure 3—figure supplement 1, third column | 200 | 20 | 0.0 | 1.0 | varies | 1.0 | 0.0 |
| Figure 3—figure supplement 2, first column | varies | 20 | 0.0 | 1.0 | 0.0 | 1.0 | 2.0 |
| Figure 3—figure supplement 2, second column | 200 | 20 | varies | 1.0 | 0.0 | 1.0 | 2.0 |
| Figure 3—figure supplement 2, third column | 200 | 20 | 0.0 | 1.0 | varies | 1.0 | 2.0 |
| Figure 2—figure supplement 4A, B | 200 | 12 | 0.0 | 1.0 | 2.0 | 1.0 | 0.0 |
| Figure 2—figure supplement 4C | 200 | 12 | 0.0 | 1.0 | 2.0 | 1.0 | 2.0 |
| Figure 2—figure supplement 4D, E, first column | 200 | 12 | 0.1 | 2.0 | varies | 1.0 | varies |
| Figure 2—figure supplement 4D, E, second column | 200 | 12 | varies | 2.0 | 2.0 | 1.0 | varies |
| Figure 2—figure supplement 4D, E, third column | 200 | varies | 0.1 | 2.0 | 2.0 | 1.0 | varies |
| Figure 6—figure supplement 1A, B | 600 | varies | varies | varies | varies | varies | varies |
| Figure 6—figure supplement 2A | 600 | 8 (P = 64) | 0.0 | 1.0 | 3.0 | 1.0 | 0.0 |
| Figure 6—figure supplement 2B | 600 | 8 (P = 64) | 0.0 | 1.0 | 3.0 | 1.0 | 4.0 |
| Figure 6—figure supplement 2C | 600 | varies | varies | varies | varies | varies | varies |
| Figure 7—figure supplement 1A–C | 600 | varies | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 |
| Figure 7—figure supplement 1D–F | 600 | varies | 0.0 | 1.0 | 0.0 | 1.0 | 4.0 |
