Do Linear layers have neurons inside of their features like Conv2d layer channels?

Extracting the center neuron of a channel from a Conv2d layer an is pretty straightforward and simple:

# Extract center neuron of Conv2d channel         
x = input.size(2) // 2
y = input.size(3) // 2
input = input[:, channel, y:y+1, x:x+1] #  (B, C, H, W)

But it appears like the same technique does not work for Linear layer channels/features as there is nothing after the channel to crop:

input = input[:, channel] # (B, C)

Is there a way to extract neurons from Linear layer channels/features?

I might misunderstand your code snippet, but it seems you are indexing the input, not any “neurons”.
If you want to get the filters in the conv layer or weight connections in the linear layer, you can access them via layer.weight.