Large-Vessel Venous Signal Confounds Apparent Amygdala Activation in BOLD fMRI
Diamandis, Z.; Tyszka, J. M.; Adolphs, R.
Show abstract
Amygdala responses are widely reported in BOLD fMRI studies of human emotions and mood disorders. Although modern acquisition methods have improved image quality, the hemodynamic nature of the BOLD signal continues to complicate interpretation of these responses. Across an array of both visual and auditory tasks, we here show that apparent amygdala BOLD signal is substantially confounded by signal from nearby deep veins, including the basal vein of Rosenthal. In contrast to prior work, we show that the amygdala, when engaged, is the leading but not exclusive contributor to this venous signal. Across the tested conditions, this signal was sensitive to, but not specific for, amygdala engagement. This confound mislocalizes apparent activation and prevents reliable attribution of signal to amygdala subnuclei with conventional BOLD fMRI. We further show that spatial smoothing exacerbates this mislocalization by merging peri-amygdalar venous signal with the anatomical amygdala. We reproduce our findings from precision imaging in a larger sample obtained from the Human Connectome Project. While broad conclusions about amygdala engagement remain largely valid when based on unsmoothed signal within the anatomical amygdala, further conclusions about subnuclear function drawn from conventional fMRI alone warrant considerable caution.
Matching journals
The top 2 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Vascular physiology drives functional brain networks 95%
- Partial information transfer from peripheral visual streams to foveal visual streams is mediated through local primary visual circuits 94%
- Comparing end-tidal CO2, respiration volume per time (RVT), and average gray matter signal for mapping cerebrovascular reactivity amplitude and delay with breath-hold task BOLD fMRI 94%
Similar papers in this journal
- The temporal specificity of BOLD fMRI is systematically related to anatomical and vascular features of the human brain 95%
- Evaluating the dependence of ADC-fMRI on haemodynamics inbreath-hold and resting-state conditions 94%
- Differentiating BOLD and non-BOLD signals in fMRI time series using cross-cortical depth delay patterns 94%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.