Electrophysiological recordings of prefrontal activity over learning in non-human primates
Data files
Nov 12, 2024 version files 32.11 GB
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m1_ses1.zip
169.48 MB
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m1_ses10.zip
218.38 MB
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m1_ses11.zip
102.86 MB
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m1_ses12.zip
338.34 MB
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m1_ses13.zip
187.94 MB
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m1_ses14.zip
121.30 MB
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m1_ses15.zip
123.80 MB
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m1_ses16.zip
298.99 MB
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m1_ses17.zip
210.21 MB
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m1_ses18.zip
210.24 MB
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m1_ses19.zip
302.13 MB
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m1_ses2.zip
146.58 MB
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m1_ses20.zip
183.74 MB
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m1_ses21.zip
243.43 MB
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m1_ses22.zip
267.87 MB
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m1_ses23.zip
194.84 MB
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m1_ses24.zip
174.12 MB
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m1_ses25.zip
242.96 MB
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m1_ses3.zip
220.41 MB
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m1_ses4.zip
240.47 MB
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m1_ses5.zip
166.06 MB
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m1_ses6.zip
138.99 MB
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m1_ses7.zip
120.01 MB
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m1_ses8.zip
119.29 MB
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m1_ses9.zip
137.58 MB
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m2_ses1.zip
1.78 GB
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m2_ses10.zip
1.40 GB
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m2_ses11.zip
961.92 MB
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m2_ses12.zip
930.71 MB
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m2_ses13.zip
906.51 MB
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m2_ses14.zip
747.20 MB
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m2_ses15.zip
786.76 MB
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m2_ses16.zip
814.73 MB
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m2_ses17.zip
552.95 MB
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m2_ses18.zip
522.31 MB
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m2_ses19.zip
521.92 MB
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m2_ses2.zip
2.07 GB
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m2_ses20.zip
208.56 MB
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m2_ses21.zip
296.88 MB
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m2_ses22.zip
320.44 MB
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m2_ses23.zip
575.57 MB
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m2_ses24.zip
492.23 MB
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m2_ses25.zip
725.30 MB
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m2_ses3.zip
2.56 GB
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m2_ses4.zip
2.73 GB
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m2_ses5.zip
2.11 GB
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m2_ses6.zip
1.31 GB
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m2_ses7.zip
1.37 GB
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m2_ses8.zip
1.35 GB
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m2_ses9.zip
1.17 GB
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README.md
4.56 KB
Abstract
The relationship between the geometry of neural representations and the task being performed is a central question in neuroscience. The primate prefrontal cortex (PFC) is a primary focus of inquiry in this regard, as under different conditions, PFC can encode information with geometries that either rely on past experience or are experience agnostic. One hypothesis is that PFC representations should evolve with learning, from a format that supports exploration of all possible task rules to a format that minimises metabolic cost and supports generalisation. Here we test this idea by recording neural activity from PFC when learning a new rule (‘XOR rule’) from scratch. We show that PFC representations progress from being high dimensional and randomly mixed to low dimensional and rule selective, consistent with predictions from metabolically constrained optimised neural networks. We also find that this low-dimensional representation facilitates generalisation of the XOR rule to a new stimulus set. These results show that previously conflicting accounts of PFC representations can be reconciled by considering the adaptation of these representations across learning.
https://doi.org/10.5061/dryad.c2fqz61kb
Experiment Description
The dataset was collected in experiments where monkeys performed a passive object-association task designed to study learning dynamics. All details can be found in the methods section of the manuscript (https://www.biorxiv.org/content/10.1101/2023.04.24.538054v1).
Experiment 1
In the first experiment, the monkeys were presented with visual stimuli consisting of a colour and a shape. The reward was determined by a nonlinear combination (XOR) of these features. Neural recordings were collected from the very first session to capture the learning process as it unfolded.
Experiment 2
In the second experiment, an additional pair of colours was introduced to assess whether the rule learned in the first experiment could generalise to a new sensory domain.
In both experiments:
- The second object presented had two features:
- Shape: Relevant for reward prediction.
- Width: Irrelevant to reward prediction.
- The trial sequence was randomized.
- Trials with fixation errors were excluded from the dataset.
Files and variables
Each .zip
file in this repository corresponds to one experimental session for a specific animal. The naming convention for these files is as follows:
- Example:
m1ses24.zip
m1
denotes Monkey 1.ses24
stands for Session 24.
Each .zip
file contains three .npy
files, which provide detailed information about the session:
- Data: Contains smoothed firing rates in the format of
n_trials × n_neurons × 250_timepoints
. - Electrode Location (
cell_loc
): Indicates the brain area where each neuron’s activity was recorded. - Trial Information (
meta
): Provides a vector of integers corresponding to the trial identities in the data file.
Electrode Location Coding (cell_loc
)
The electrode locations are coded as follows:
- 1: Dorsal to Principal Sulcus (dlPFC)
- 2: Dorsal Principal Sulcus
- 3: Ventral Principal Sulcus
- 4: Ventral to Principal Sulcus (vlPFC)
- 5: Lateral Orbitofrontal Cortex (lateral OFC)
- 6: Beyond Superior Arcuate Sulcus
- 7: Beyond Inferior Arcuate Sulcus
Trial Information Coding (meta
)
The meta
file contains trial identities, coded as integers that correspond to the trials in the data file. The coding differs slightly between Experiment 1 and Experiment 2.
Experiment 1
- 1: Colour 1, Shape 1, Width 1, XOR 1 (Reward)
- 2: Colour 1, Shape 1, Width 0, XOR 1 (Reward)
- 3: Colour 1, Shape 2, Width 1, XOR 0 (No Reward)
- 4: Colour 1, Shape 2, Width 0, XOR 0 (No Reward)
- 5: Colour 2, Shape 1, Width 1, XOR 0 (No Reward)
- 6: Colour 2, Shape 1, Width 0, XOR 0 (No Reward)
- 7: Colour 2, Shape 2, Width 1, XOR 1 (Reward)
- 8: Colour 2, Shape 2, Width 0, XOR 1 (Reward)
Experiment 2
- 1: Colour 1, Shape 1, Width 1, XOR 1 (Reward)
- 2: Colour 1, Shape 1, Width 0, XOR 1 (Reward)
- 3: Colour 1, Shape 2, Width 1, XOR 0 (No Reward)
- 4: Colour 1, Shape 2, Width 0, XOR 0 (No Reward)
- 5: Colour 2, Shape 1, Width 1, XOR 0 (No Reward)
- 6: Colour 2, Shape 1, Width 0, XOR 0 (No Reward)
- 7: Colour 2, Shape 2, Width 1, XOR 1 (Reward)
- 8: Colour 2, Shape 2, Width 0, XOR 1 (Reward)
- 9: Colour 3, Shape 1, Width 1, XOR 1 (Reward)
- 10: Colour 3, Shape 1, Width 0, XOR 1 (Reward)
- 11: Colour 3, Shape 2, Width 1, XOR 0 (No Reward)
- 12: Colour 3, Shape 2, Width 0, XOR 0 (No Reward)
- 13: Colour 4, Shape 1, Width 1, XOR 0 (No Reward)
- 14: Colour 4, Shape 1, Width 0, XOR 0 (No Reward)
- 15: Colour 4, Shape 2, Width 1, XOR 1 (Reward)
- 16: Colour 4, Shape 2, Width 0, XOR 1 (Reward)
Data File Format
- Data Shape: The data array is structured as
n_trials × n_neurons × 250_timepoints
. - Timepoints: Each trial consists of 250 timepoints representing the smoothed firing rates.
- Colour Display: The colour stimulus was presented between timepoints 50 and 150.
- Shape and Width Display: The shape and width features were presented between timepoints 100 and 150.
- Reward Delivery: The reward was delivered at timepoint 150.