Critical Essay: Organizational cognitive neuroscience drives theoretical progress, or: The curious case of the straw man murder:organizational cognitive neuroscience drives theoretical progress, or: The curious case of the straw man murder

In this critical essay, we respond to Lindebaum’s (2016) argument that neuroscientific methodologies and data have been accepted prematurely in proposing novel management theory. We acknowledge that building new management theories requires firm foundations. We also find his distinction between demand and supply side forces helpful as an analytical framework identifying the momentum for the contemporary production of management theory. Nevertheless, some of the arguments Lindebaum (2016) puts forward, on closer inspection, can be contested, especially those related to the supply side of organizational cognitive neuroscience (OCN) research: fMRI data, motherhood statements and ethical concerns. We put forward a more positive case for OCN methodologies and data, as well as clarifying exactly what OCN really means, and its consequences for the development of strong management theory

In Vivo Assessment of Cold Adaptation in Insect Larvae by Magnetic Resonance Imaging and Magnetic Resonance Spectroscopy

Background Temperatures below the freezing point of water and the ensuing ice crystal formation pose serious challenges to cell structure and function. Consequently, species living in seasonally cold environments have evolved a multitude of strategies to reorganize their cellular architecture and metabolism, and the underlying mechanisms are crucial to our understanding of life. In multicellular organisms, and poikilotherm animals in particular, our knowledge about these processes is almost exclusively due to invasive studies, thereby limiting the range of conclusions that can be drawn about intact living systems. Methodology Given that non-destructive techniques like 1H Magnetic Resonance (MR) imaging and spectroscopy have proven useful for in vivo investigations of a wide range of biological systems, we aimed at evaluating their potential to observe cold adaptations in living insect larvae. Specifically, we chose two cold-hardy insect species that frequently serve as cryobiological model systems–the freeze-avoiding gall moth Epiblema scudderiana and the freeze-tolerant gall fly Eurosta solidaginis. Results In vivo MR images were acquired from autumn-collected larvae at temperatures between 0°C and about -70°C and at spatial resolutions down to 27 µm. These images revealed three-dimensional (3D) larval anatomy at a level of detail currently not in reach of other in vivo techniques. Furthermore, they allowed visualization of the 3D distribution of the remaining liquid water and of the endogenous cryoprotectants at subzero temperatures, and temperature-weighted images of these distributions could be derived. Finally, individual fat body cells and their nuclei could be identified in intact frozen Eurosta larvae. Conclusions These findings suggest that high resolution MR techniques provide for interesting methodological options in comparative cryobiological investigations, especially in vivo

What scans we will read: imaging instrumentation trends in clinical oncology

Oncological diseases account for a significant portion of the burden on public healthcare systems with associated costs driven primarily by complex and long-lasting therapies. Through the visualization of patient-specific morphology and functional-molecular pathways, cancerous tissue can be detected and characterized non- invasively, so as to provide referring oncologists with essential information to support therapy management decisions. Following the onset of stand-alone anatomical and functional imaging, we witness a push towards integrating molecular image information through various methods, including anato-metabolic imaging (e.g., PET/ CT), advanced MRI, optical or ultrasound imaging. This perspective paper highlights a number of key technological and methodological advances in imaging instrumentation related to anatomical, functional, molecular medicine and hybrid imaging, that is understood as the hardware-based combination of complementary anatomical and molecular imaging. These include novel detector technologies for ionizing radiation used in CT and nuclear medicine imaging, and novel system developments in MRI and optical as well as opto-acoustic imaging. We will also highlight new data processing methods for improved non-invasive tissue characterization. Following a general introduction to the role of imaging in oncology patient management we introduce imaging methods with well-defined clinical applications and potential for clinical translation. For each modality, we report first on the status quo and point to perceived technological and methodological advances in a subsequent status go section. Considering the breadth and dynamics of these developments, this perspective ends with a critical reflection on where the authors, with the majority of them being imaging experts with a background in physics and engineering, believe imaging methods will be in a few years from now. Overall, methodological and technological medical imaging advances are geared towards increased image contrast, the derivation of reproducible quantitative parameters, an increase in volume sensitivity and a reduction in overall examination time. To ensure full translation to the clinic, this progress in technologies and instrumentation is complemented by progress in relevant acquisition and image-processing protocols and improved data analysis. To this end, we should accept diagnostic images as “data”, and – through the wider adoption of advanced analysis, including machine learning approaches and a “big data” concept – move to the next stage of non-invasive tumor phenotyping. The scans we will be reading in 10 years from now will likely be composed of highly diverse multi- dimensional data from multiple sources, which mandate the use of advanced and interactive visualization and analysis platforms powered by Artificial Intelligence (AI) for real-time data handling by cross-specialty clinical experts with a domain knowledge that will need to go beyond that of plain imaging

Blood oxygenation level-dependent (BOLD) total and extravascular signal changes and ΔR2* in human visual cortex at 1.5, 3.0 and 7.0 T.

The characterisation of the extravascular (EV) contribution to the blood oxygenation level-dependent (BOLD) effect is important for understanding the spatial specificity of BOLD contrast and for modelling approaches that aim to extract quantitative metabolic parameters from the BOLD signal. Using bipolar crusher gradients, total (b = 0 s/mm(2) ) and predominantly EV (b = 100 s/mm(2) ) gradient echo BOLD ΔR(2)* and signal changes (ΔS/S) in response to visual stimulation (flashing checkerboard; f = 8 Hz) were investigated sequentially (within < 3 h) at 1.5, 3.0 and 7.0 T in the same subgroup of healthy volunteers (n = 7) and at identical spatial resolutions (3.5 × 3.5 × 3.5 mm(3)). Total ΔR(2)* (z-score analysis) values were -0.61 ± 0.10 s(-1) (1.5 T), -0.74 ± 0.05 s(-1) (3.0 T) and -1.37 ± 0.12 s(-1) (7.0 T), whereas EV ΔR(2)* values were -0.28 ± 0.07 s(-1) (1.5 T), -0.52 ± 0.07 s(-1) (3.0 T) and -1.25 ± 0.11 s(-1) (7.0 T). Although EV ΔR(2)* increased linearly with field, as expected, it was found that EV ΔS/S increased less than linearly with field in a manner that varied with TE choice. Furthermore, unlike ΔR(2)*, total and EV ΔS/S did not converge at 7.0 T. These trends were similar whether a z-score analysis or occipital lobe-based region-of-interest approach was used for voxel selection. These findings suggest that calibrated BOLD approaches may benefit from an EV ΔR(2)* measurement as opposed to a ΔS/S measurement at a single TE

Blood oxygenation level-dependent (BOLD) total and extravascular signal changes and ΔR2* in human visual cortex at 1.5, 3.0 and 7.0 T.

The characterisation of the extravascular (EV) contribution to the blood oxygenation level-dependent (BOLD) effect is important for understanding the spatial specificity of BOLD contrast and for modelling approaches that aim to extract quantitative metabolic parameters from the BOLD signal. Using bipolar crusher gradients, total (b = 0 s/mm(2) ) and predominantly EV (b = 100 s/mm(2) ) gradient echo BOLD ΔR(2)* and signal changes (ΔS/S) in response to visual stimulation (flashing checkerboard; f = 8 Hz) were investigated sequentially (within &lt; 3 h) at 1.5, 3.0 and 7.0 T in the same subgroup of healthy volunteers (n = 7) and at identical spatial resolutions (3.5 × 3.5 × 3.5 mm(3)). Total ΔR(2)* (z-score analysis) values were -0.61 ± 0.10 s(-1) (1.5 T), -0.74 ± 0.05 s(-1) (3.0 T) and -1.37 ± 0.12 s(-1) (7.0 T), whereas EV ΔR(2)* values were -0.28 ± 0.07 s(-1) (1.5 T), -0.52 ± 0.07 s(-1) (3.0 T) and -1.25 ± 0.11 s(-1) (7.0 T). Although EV ΔR(2)* increased linearly with field, as expected, it was found that EV ΔS/S increased less than linearly with field in a manner that varied with TE choice. Furthermore, unlike ΔR(2)*, total and EV ΔS/S did not converge at 7.0 T. These trends were similar whether a z-score analysis or occipital lobe-based region-of-interest approach was used for voxel selection. These findings suggest that calibrated BOLD approaches may benefit from an EV ΔR(2)* measurement as opposed to a ΔS/S measurement at a single TE