DOI: 10.5061/dryad.c2fqz61kb
title: Electrophysiological recordings of prefrontal activity over learning in non-human primates

description: 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.
description: # Electrophysiological recordings of prefrontal activity during learning
 in non-human primates
 [https://doi.org/10.5061/dryad.c2fqz61kb](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](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: 1. **Data**: Contains smoothed firing rates in the format of `n_trials × n_neurons × 3500_timepoints`. 2. **Electrode Location (`cell_loc`)**: Indicates the brain area where each neuron's activity was recorded. 3. **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 × 3500_timepoints`. * **Timepoints**: Each trial consists of 3500 timepoints (ms) representing the smoothed firing rates. * **Colour Display**: The colour stimulus was presented between timepoints **1000** and **2000**. * **Shape and Width Display**: The shape and width features were presented between timepoints **1500** and **2000**. * **Reward Delivery**: The reward was delivered at time point **2000**.