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SPM-30 years and beyond.

Peter Zeidman¹, John Ashburner¹, Gareth Barnes¹

¹Functional Imaging Laboratory (FIL), Department of Imaging Neuroscience, University College London, 12 Queen Square, London WC1N 3AR, United Kingdom.

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|September 10, 2025

Summary

This summary is machine-generated.

This review celebrates 30 years of Statistical Parametric Mapping (SPM) and Cerebral Cortex, reflecting on cognitive neuroscience's origins. It examines SPM's development, successes, and future improvements for brain imaging research.

Keywords:

EEG MEG MRI SPM statistical parametric mapping

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Area of Science:

Neuroscience
Cognitive Neuroscience
Neuroimaging

Background:

The paper commemorates the 30th anniversary of Statistical Parametric Mapping (SPM) software.
It also marks three decades since the founding of the journal Cerebral Cortex.
These milestones signify the beginning of cognitive neuroscience as a field.

Purpose of the Study:

To reflect on the development and impact of Statistical Parametric Mapping (SPM) software over the past 30 years.
To gather insights from SPM contributors regarding its successes and areas for improvement.
To provide context for current neuroimaging research and suggest future directions for cognitive neuroscience.

Main Methods:

A retrospective analysis of the Statistical Parametric Mapping (SPM) software's evolution.
Contributions and perspectives from selected authors who have been involved with SPM.
Discussion of lessons learned and future development needs for SPM.

Main Results:

SPM has been a foundational tool in cognitive neuroscience for three decades.
The review highlights both the achievements of SPM and identifies areas needing enhancement.
Contributors offer valuable insights into the software's past, present, and future trajectory.

Conclusions:

The paper provides a historical perspective on SPM and its role in advancing neuroimaging.
It emphasizes the importance of continuous development and adaptation of tools like SPM.
The insights aim to guide future research and development in cognitive neuroscience and neuroimaging.