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In an optical parametric generation of a femtosecond pulse for a biaxial crystal, the interaction of three waves can be used as a model of noncollinear phase matching in which the group velocities of the interacting pulses are suitably linked to each other. For satisfaction of group-velocity matching, the tunable parametric generation of femtosecond pulses must use noncollinear phase matching. We consider three conditions of group-velocity matching for femtosecond pulses. Signal and idler pulses can be obtained when the coupled-wave equations, including the group-velocity mismatch and group-velocity dispersion effects, are solved. A Fourier method is an effective method for solving the equations, and from the solution of the equations the relation between duration of output pulses and wavelengths can be obtained. In a comparison of collinear and noncollinear matches, when the latter is group-velocity matched, the duration of its outpulses are smaller, and the outpulses can be continually tuned from the visible to the mid-infrared.
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http://dx.doi.org/10.1364/ao.42.005596 | DOI Listing |
MAGMA
September 2025
Computational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, University Medical Center Utrecht, Heidelberglaan 100, 3585CX, Utrecht, The Netherlands.
Objective: Within gradient-spoiled transient-state MR sequences like Magnetic Resonance Fingerprinting or Magnetic Resonance Spin TomogrAphy in Time-domain (MR-STAT), it is examined whether an optimized RF phase modulation can help to improve the precision of the resulting relaxometry maps.
Methods: Using a Cramer-Rao based method called BLAKJac, optimized sequences of RF pulses have been generated for two scenarios (amplitude-only modulation and amplitude + phase modulation) and for several conditions. These sequences have been tested on a phantom, a healthy human brain and a healthy human leg, to reconstruct parametric maps ( and ) as well as their standard deviations.
Cereb Cortex
August 2025
Aix-Marseille Université, Institut National de la Santé et de la Recherche Médicale, Institut de Neurosciences des Systèmes (INS) UMR1106, Marseille 13005, France.
Over three decades, statistical parametric mapping has transformed neuroimaging from descriptive mapping to causal inference, placing generative models at the core of causal explanations for brain function. It inspired to a large degree The Virtual Brain, which builds subject-specific digital twins from multimodal data, enabling brain simulations and exploration. Both frameworks converge at parameter estimation, where model and data meet, providing the mathematical manifestation of cause-effect in pathophysiology.
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August 2025
The Clinical Hospital of Chengdu Brain Sciences Institute, University of Electronic Sciences and Technology of China (UESTC), 2006 Xiyuan Avenue, West Hi Tech Zone, 611731, Chengdu, China.
This commentary reflects three decades of interaction between the Cuban neuroinformatics tradition and the statistical parametric mapping (SPM) framework. From the early development of neurometrics in Cuba to global initiatives like the Global Brain Consortium, our trajectory has paralleled and intersected with that of SPM. We highlight shared commitments to generative modeling, Bayesian inference, and population-level brain mapping, as shaped through collaborations, workshops, and joint theoretical work with Karl Friston and his group.
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August 2025
Functional Imaging Laboratory (FIL), Department of Imaging Neuroscience, University College London, 12 Queen Square, London WC1N 3AR, United Kingdom.
This paper marks the 30th anniversary of the Statistical Parametric Mapping (SPM) software and the journal Cerebral Cortex: two modest milestones that mark the inception of cognitive neuroscience. We take this opportunity to reflect on SPM, a generation after its introduction. Each of the authors of this paper-who represent a small selection of the many contributors to SPM-were asked to consider lessons learned, what has gone well, and where there is room for improvement in future development.
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August 2025
Statistical Parametric Mapping is a widely used package of software for brain image analysis. It has also been the vehicle for sustained theoretical innovation and global impact in cognitive neuroscience. What can we learn from its success as it reaches middle age?
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