MATLAB - FFT aliases occur sooner than expected
If you do a FFT in MATLAB, you get one complex valued output (bin) for every input sample. If you then take the magnitude of this complex vector, assuming your original input was real valued, you will see that half the magnitudes will be mirrored. However, the number of bins has nothing to do with the sample rate of the original waveform, only the number of samples in the input. Note that this is simply a function of how the DFT is defined. It looks like your original waveform was about 6400 samples, so that is probably what you are seeing in the first graph (the 6400 frequency bins due to computing a 6400 sample FFT).

If you want to view the FFT in units of frequency (and not bin #) you need to rescale the horizontal axis by the sampling frequency. That is, the frequency of bin n is: \$f_n=\frac{nf_s}{L}\$ where \$f_s\$ is the sampling frequency and \$L\$ is the length of the waveform.