Distinct attentional characteristics of neurons with visual feature coding in the primate brain
Data files
Mar 03, 2025 version files 4.41 GB
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brain.jpg
43.67 KB
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cell_list6.zip
146.87 KB
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cell_list8.zip
121.70 KB
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Code.zip
17.80 KB
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Connectivity.zip
124.76 MB
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fov_accuracy.zip
124.39 MB
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Granger.mat
1.28 MB
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peri_accuracy.zip
11.15 MB
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README.md
7.31 KB
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Response_fov.mat
2.50 GB
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Response_peri.mat
33.63 MB
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Response.zip
1.62 GB
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tsne.zip
16.22 KB
Abstract
Visual attention and object recognition are two critical cognitive functions that shape our perception of the world. While these neural processes converge in the temporal cortex, the nature of their interactions remains largely unclear. Here, we systematically investigated the interplay between visual attention and object feature coding by training macaques to perform a free-gaze visual search task with natural stimuli. Recording from a large number of units across multiple brain areas, we found that units exhibiting visual feature coding showed stronger attentional modulation of responses and spike-LFP coherence than units without feature coding. Across brain areas, attention directed towards search targets enhanced the neuronal pattern separation of stimuli, with this enhancement more pronounced for units encoding visual features. Together, our results suggest a complex interplay between visual feature and attention coding in the primate brain, likely driven by interactions between brain areas engaged in these processes.
https://doi.org/10.5061/dryad.c866t1ghm
We have submitted the responses of all units to both the target and distractor, averaged across stimuli, along with the strength and significance of axis-coding for all units (Response_fov.mat & Response_peri.mat), the responses of all units to the cue, target, and distractor, sorted by stimulus (Response), the Granger causality between each pair of unit and local field potential (LFP; Granger.mat), parameters related to the axis-coding of each unit (fov accuracy & peri accuracy), spike-LFP coherence between each pair of unit and LFP (Connectivity.zip), metadata for each unit (cell list6 & cell list 8), the t-SNE of the neural representation of the stimuli (tsne), an image of an example macaque brain (brain.jpg), and the MATLAB script (Code.zip).
Description of the data and file structure
Response_fov
brains (3 x 6)
- Row 1: Neurons in V4 with a foveal receptive field.
- Row 2: Neurons in TE with a foveal receptive field.
- Row 3: Neurons in TEO with a foveal receptive field.
- Column 1: p-value for axis-coding significance.
- Column 2: Correlation coefficient (r-value) for axis-coding strength.
- Column 3: Identifier for each unit.
- Column 4 (n x 301): Responses to the target stimulus, where n is the trial number and 301 is the number of time steps. The time range is from -50 ms to 250 ms after fixation onset.
- Column 5 (n x 301): Responses to the distractor stimulus, where n is the trial number and 301 is the number of time steps. The time range is from -50 ms to 250 ms after fixation onset.
- Column 6: Identifier for each unit.
Response_peri
brains (1 x 6)
- Row: Neurons in V4 with a peripheral receptive field.
- Columns: Follow the same conventions as described for Response_fov.
Granger
axis_cell (16 x 1): Each row represents the Granger causality between the spikes of axis-coding units and LFPs from specific brain areas.
non_axis_cell (16 x 1): Each row represents the Granger causality between the spikes of non-axis-coding units and LFPs from specific brain areas.
regions (16 x 1): Names of brain areas corresponding to pairs of units and LFPs.
fov accuracy
File Naming Convention
In this folder, files are organized by task variable (e.g., 'cue': Cue stimulus in the receptive field, 'tar': Target in the receptive field, 'dis': Distractor in the receptive field, 'ide': Identification task instead of categorization task), unit brain area (V4, TE, TEO, and Orbitofrontal Cortex (OFC)), unit type (face, house, and non for selectivity), and monkey (6 and 8 representing the two monkeys). The files are named according to this organization. For example, cue_OFCface6.mat indicates an OFC face-selective neuron from monkey 6 during cue presentation.
File Content
cell_name (n x 1): The name of each unit.
p (1 x n): p-value from a permutation test with 1000 runs, used to determine whether a unit encoded a significant axis-coding model.
r (1 x n): The strength of axis coding.
peri accuracy
Follow the convention for fov accuracy.
Connectivity
File Naming Convention
In this folder, files are organized by monkey (m6 and m8 representing the two monkeys), unit brain area (V4, TE, and TEO), unit type (face, house, and non for selectivity), and LFP brain area (V4, TE, TEO, OFC, and Ventral Prefrontal Area (VPA)). The files are named according to this organization. For example, m6_TEfacespk_TElfp_hann_200.mat indicates the coherence of all pairs of TE face-selective units and TE LFPs from monkey 6.
File Content
pair_name (2 x n): The name of each pair. Row1 represents the unit, and Row 2 represents the LFP.
f (1 x 51): 51 frequency values.
pop_in (51 x n): Coherence values at each frequency during target fixation.
pop_out (51 x n): Coherence values at each frequency during distractor fixation.
pop_in_shuffle (51 x n): Coherence values at each frequency during target fixation with shuffled spikes and LFPs.
pop_out_shuffle (51 x n): Coherence values at each frequency during distractor fixation with shuffled spikes and LFPs.
Response
File Naming Convention
In this folder, files are organized by unit brain area (V4, TE, and TEO), unit type (face, house, and non for selectivity), and monkey (6 and 8 representing the two monkeys). The files are named according to this organization. For example, foveal_TEface6.mat indicates an TE face-selective unit from monkey 6.
File Content
cell_name (n x 1): The name of each unit.
cell_rsp_cue (160 x 300 x n): Responses to cue stimulus, where 160 is the stimuli number, 300 is the number of time steps, and n is the unit number. The time range is from -50 ms to 249 ms after fixation onset.
cell_rsp_dis (160 x 300 x n): Responses to target stimulus, where 160 is the stimuli number, 300 is the number of time steps, and n is the unit number. The time range is from -50 ms to 249 ms after fixation onset.
cell_rsp_tar (160 x 300 x n): Responses to distractor stimulus, where 160 is the stimuli number, 300 is the number of time steps, and n is the unit number. The time range is from -50 ms to 249 ms after fixation onset.
tsne
File Naming Convention
In this folder, files are organized by unit brain area (V4, TE, and TEO) and time window (early and late, representing the two time windows used in the paper). The files are named according to this organization. For example, tsneTEearly.mat indicates t-SNE calculated using the responses of TE units during the early time window.
File Content
image2analyze (n x 1): The image is used to calculate t-SNE.
dis2dim (n x 2): The first two dimension values of t-SNE for distractor stimuli.
tar2dim (n x 2): The first two dimension values of t-SNE for target stimuli.
cell list6
This folder contains meta information for each unit from monkey 6. The files are organized by unit brain area (V4, TE, TEO, OFC and VPA).
cell list8
This folder contains meta information for each unit from monkey 8. The files are organized by unit brain area (V4, TE, TEO, OFC and VPA).
Code/software
The Code folder includes MATLAB codes that generate the main results. The scripts were created using MATLAB version R2023b 64-bit (maca64).
Coding_prop: The proportion of units demonstrating axis-based feature coding for each brain area. . Generate Fig. 2E.
Coding_pred: Strength of axis coding for each brain area. Generate Fig. 2F-K.
AI_r_SI: Population summary of attention-selective and axis-coding units, along with the correlation between the strength of visual feature coding and attention coding. Generate Fig. 3A-H.
Attention: Firing rate and attentional effects of axis-coding and non-axis-coding units. Generate Fig. 3I-T.
Geometry: Attentional modulation of neuronal representational geometry for axis-coding and non-axis-coding units. Generate Fig. 4&5.
Coherence: Spike-LFP coherence. Generate Fig. 6.
Granger: Granger causality. Generate Fig. 7C-E.
Access information
Other publicly accessible locations of the data: