How should I structure the neural net based on my given input and output training data

I am trying to design a feedforward network that trains on a 4x5 matrix (5 samples of 4 separate inputs into the neural network) and its outputs are represented by a 4x5x1000 matrix (5 samples of 4 outputs where each component of the 4x1 output vector has 1000 points). This neural net is used to determine an optimal trajectory for a given terminal condition from a set of the same initial conditions . The code for this project will be placed below:

%% Neural Net Training Process
% Initial State
x1 = [0;0]; % Initial Positions
x2 = [1;1]; % Initial Velocities

xo = [x1;x2]; % 4x1 Initial State Vector

% Parsing Training Input Data
x_input = [xf1,xf2,xf4,xf5,xf6]; % 4x5 Terminal State Vector (each xf (4x1) represents a different terminal condition)

% Parsing Training Output Data
x_output = [];
for i=1:4
    x_output(i,1,:) = x1(:,i);
    x_output(i,2,:) = x2(:,i);
    x_output(i,3,:) = x4(:,i);
    x_output(i,4,:) = x5(:,i);
    x_output(i,5,:) = x6(:,i);
end                               % 4x5x1000 Terminal State Matrix

% Parsing Validation Data
xf_valid = xf3;
x_valid = x3';

% Neural Net Architecture Initialization
netconfig = 40;
net = feedforwardnet(netconfig);
net.numInputs = 4;

% Training the Network
for j=1:5
    curr_xin = x_input(:,j);
    curr_xout = x_output(:,j,:);
    net = train(net,curr_xin,curr_xout);
end

From here, I am receieve an error in line 89, where I get the following error: Error using nntraining.setup>setupPerWorker (line 96)

Targets T is not two-dimensional. Any advice from here would be appreciated. Thanks.

[Devin Hunter]

Also, if you need more details on how the data is exactly being collected, this previous thread showed how exactly the data itself was collected. (Ignore the way that I structured the training data in that previous example as I figured out that it was wrong)