Type I and Type II error concerns in fMRI research: re-balancing the scale
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Statistical thresholding (i.e. P-values) in fMRI research has become increasingly conservative over the past decade in an attempt to diminish Type I errors (i.e. false alarms) to a level traditionally allowed in behavioral science research. In this article, we examine the unintended negative consequences of this single-minded devotion to Type I errors: increased Type II errors (i.e. missing true effects), a bias toward studying large rather than small effects, a bias toward observing sensory and motor processes rather than complex cognitive and affective processes and deficient meta-analyses. Power analyses indicate that the reductions in acceptable P-values over time are producing dramatic increases in the Type II error rate. Moreover, the push for a mapwide false discovery rate (FDR) of 0.05 is based on the assumption that this is the FDR in most behavioral research; however, this is an inaccurate assessment of the conventions in actual behavioral research. We report simulations demonstrating that combined intensity and cluster size thresholds such as P < 0.005 with a 10 voxel extent produce a desirable balance between Types I and II error rates. This joint threshold produces high but acceptable Type II error rates and produces a FDR that is comparable to the effective FDR in typical behavioral science articles (while a 20 voxel extent threshold produces an actual FDR of 0.05 with relatively common imaging parameters). We recommend a greater focus on replication and meta-analysis rather than emphasizing single studies as the unit of analysis for establishing scientific truth. From this perspective, Type I errors are self-erasing because they will not replicate, thus allowing for more lenient thresholding to avoid Type II errors.
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Results were considered significant at an uncorrected threshold of p < .001 with a minimum cluster size of 10 contiguous voxels to balance between Type 1 and Type 2 errors.
“Results were considered significant at an uncorrected threshold of p < .001 with a minimum cluster size of 10 contiguous voxels to balance between Type 1 and Type 2 errors (Lieberman and Cunningham 2009)”
From Chronic Childhood Peer Rejection is Associated with Heightened Neural Responses to Social Exclusion During Adolescence (2016) · cites this paper as Lieberman and Cunningham 2009
The Abstract says that combining an intensity threshold with a 10-voxel cluster extent can balance Type I and Type II errors. But the threshold it identifies is P < 0.005, not the cited sentence’s uncorrected P < 0.001. The 'Avoiding Type I Errors' section likewise compares P < 0.005 with 10 voxels against P < 0.001 alone; it does not establish the claimed combination. (LLM, conf=0.89)
Experimental — accuracy not yet measuredA threshold of P < 0.005 and a voxel extent of k = 60 were deemed adequate to maintain a balance between sensitivity and false-positive rates.
“Next, we performed a regression analysis with OXT methylation values entered as the predictor variable and contrast estimates (emotion perspectivetaking > shape match) as the criterion variable using a threshold of P < 0.005, voxel extent of k = 60, which is sufficient to preserve the balance between sensitivity and false-positive rates (55,56).”
From Epigenetic modification of <i>OXT</i> and human sociability (2016) · cites this paper as [55]
Lowering the threshold to an uncorrected voxel height of p < 0.005 with an extent cluster size of at least 20 voxels, the ASD group, compared to TDC and ADHD, showed diminished activation in ventral striatum in response to monetary reward.
“However, lowering the threshold to an uncorrected voxel height of p < 0.005 with an extent cluster size of at least 20 voxels (according to Scott-Van Zeeland et al., 2010), which still produces desirable balance between Types I and II errors comparable to false discovery rate (Lieberman and Cunningham, 2009), the ASD group, compared to TDC and ADHD, showed diminished activation in ventral striatum”
From Differentiating neural reward responsiveness in autism versus ADHD (2014) · cites this paper as Lieberman and Cunningham, 2009
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- Authors
- Lieberman, M. D., & Cunningham, W. A.
- Affiliations
- University of California, Los Angeles (US)
- Venue
- Social Cognitive and Affective Neuroscience
- Publisher
- Oxford University Press (OUP)
- Published
- 2009-12-01
- Volume
- 4
- Issue
- 4
- Pages
- 423-428
- ISSN
- 1749-5016 (ISSN-L)
- 1749-5024
- PMC
- PMC2799956
- OpenAlex
- W2117101773
- Cited by
- 1,342
- References
- 9
- Citations by year
- 2026: 33 · 2025: 35 · 2024: 51 · 2023: 50 · 2022: 62 · 2021: 73 · 2020: 119 · 2019: 92 · 2018: 94 · 2017: 113 · 2016: 111 · 2015: 119 · 2014: 126 · 2013: 97 · 2012: 80
- FWCI
- 26.55
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Social Cognitive and Affective Neuroscience (publishedVersion, cc-by-nc)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- type I error, type II error, false discovery rate, power analysis, effect size bias, replication, meta-analysis, cognitive and affective processes
- MeSH terms
- Brain, Brain Mapping, Data Interpretation, Statistical, False Positive Reactions, Humans, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Oxygen, Research Design, Meta-Analysis as Topic, Reproducibility of Results, Sample Size
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