Misunderstanding and Misuse of Darwinism

2010 ◽  
Vol 18 (3) ◽  
pp. 329-345
Author(s):  
Hubert Markl
Keyword(s):  
Cultural Evolution ◽  
Ethnic Diversity ◽  
Mother Tongue ◽  
Human Species ◽  
Wilhelm Von Humboldt ◽  
Gregory Bateson ◽  
Neural Imaging ◽  
The World ◽  
True Meaning ◽  
The Many

The reason why I wavered a bit with this topic is that, after all, it has to do with Darwin, after a great Darwin year, as seen by a German scientist. Not that Darwin was very adept in German: Gregor Mendel’s ‘Versuche über Pflanzenhybriden’ (Experiments on Plant Hybrids) was said to have stayed uncut and probably unread on his shelf, which is why he never got it right with heredity in his life – only Gregory Bateson, Ronald A. Fisher, and JBS Haldane, together with Sewall Wright merged evolution with genetics. But Darwin taught us, nevertheless, in essence why the single human species shows such tremendous ethnic diversity, which impresses us above all through a diversity of languages – up to 7000 altogether – and among them, as a consequence, also German, my mother tongue, and English. It would thus have been a truly Darwinian message, if I had written this article in German. I would have called that the discommunication function of the many different languages in humans, which would have been a most significant message of cultural evolution, indeed. I finally decided to overcome the desire to demonstrate so bluntly what cultural evolution is all about, or rather to show that nowadays, with global cultural progress, ‘the world is flat’ indeed – even linguistically. The real sign of its ‘flatness’ is that English is used everywhere, even if Thomas L. Friedman may not have noticed this sign. But I will also come back to that later, when I hope to show how Darwinian principles connect both natural and cultural evolution, and how they first have been widely misunderstood as to their true meaning, and then have been terribly misused – although more so by culturalists, or some self-proclaimed ‘humanists’, rather than by biologists – or at least most of them. Let me, however, quickly add a remark on human languages. That languages even influence our brains and our thinking, that is: how we see the world, has first been remarked upon by Wilhelm von Humboldt and later, more extensively so, by Benjamin Whorf. It has recently been shown by neural imaging – for instance by Angela Friederici – that one’s native language, first as learned from one’s mother and from those around us when we are babies, later from one’s community of speakers, can deeply impinge on a baby’s brain development and stay imprinted in it throughout life, even if language is, of course, learned and not fully genetically preformed. This shows once more how deep the biological roots are that ground our cultures, according to truly Darwinian principles, even if these cultures are completely learned.

scholarly journals Multi-modality optical neural imaging using coherence control of VCSELs

2011 ◽  
Vol 19 (11) ◽  
pp. 10747 ◽  
Author(s):  
Elizabeth A. Munro ◽  
Hart Levy ◽  
Dene Ringuette ◽  
Thomas D. O’Sullivan ◽  
Ofer Levi
Keyword(s):  
Neural Imaging

Can Neural Imaging Explain Pain?

2011 ◽  
Vol 34 (3) ◽  
pp. 595-604 ◽  
Author(s):  
Stuart W.G. Derbyshire
Keyword(s):  
Neural Imaging

scholarly journals Potential Mechanisms of Failure in Sids As Revealed By Neural Imaging of Controls and Cchs Patients

1999 ◽  
Vol 45 ◽  
pp. 3A-3A ◽  
Author(s):  
R M Harper ◽  
M M Saeed ◽  
D Spriggs ◽  
M A Woo ◽  
M S Woo ◽  
...  
Keyword(s):  
Neural Imaging

scholarly journals Graphene-based carbon-layered electrode array technology for neural imaging and optogenetic applications

2014 ◽  
Vol 5 (1) ◽  
Author(s):  
Dong-Wook Park ◽  
Amelia A. Schendel ◽  
Solomon Mikael ◽  
Sarah K. Brodnick ◽  
Thomas J. Richner ◽  
...  
Keyword(s):  
Soft Tissues ◽  
Electrode Array ◽  
Electrode Arrays ◽  
Neural Imaging ◽  
Brain Surface ◽  
Array Technology ◽  
Micro Electrode Arrays ◽  
The Brain

Abstract Neural micro-electrode arrays that are transparent over a broad wavelength spectrum from ultraviolet to infrared could allow for simultaneous electrophysiology and optical imaging, as well as optogenetic modulation of the underlying brain tissue. The long-term biocompatibility and reliability of neural micro-electrodes also require their mechanical flexibility and compliance with soft tissues. Here we present a graphene-based, carbon-layered electrode array (CLEAR) device, which can be implanted on the brain surface in rodents for high-resolution neurophysiological recording. We characterize optical transparency of the device at >90% transmission over the ultraviolet to infrared spectrum and demonstrate its utility through optical interface experiments that use this broad spectrum transparency. These include optogenetic activation of focal cortical areas directly beneath electrodes, in vivo imaging of the cortical vasculature via fluorescence microscopy and 3D optical coherence tomography. This study demonstrates an array of interfacing abilities of the CLEAR device and its utility for neural applications.

scholarly journals Neural–metabolic coupling in the central visual pathway

2016 ◽  
Vol 371 (1705) ◽  
pp. 20150357 ◽  
Author(s):  
Ralph D. Freeman ◽  
Baowang Li
Keyword(s):  
Blood Flow ◽  
Neural Activity ◽  
Visual Pathway ◽  
Blood Oxygenation ◽  
Neural Function ◽  
Neural Activation ◽  
Visual Response ◽  
Tissue Oxygen ◽  
Neural Imaging ◽  
Initial Dip

Studies are described which are intended to improve our understanding of the primary measurements made in non-invasive neural imaging. The blood oxygenation level-dependent signal used in functional magnetic resonance imaging (fMRI) reflects changes in deoxygenated haemoglobin. Tissue oxygen concentration, along with blood flow, changes during neural activation. Therefore, measurements of tissue oxygen together with the use of a neural sensor can provide direct estimates of neural–metabolic interactions. We have used this relationship in a series of studies in which a neural microelectrode is combined with an oxygen micro-sensor to make simultaneous co-localized measurements in the central visual pathway. Oxygen responses are typically biphasic with small initial dips followed by large secondary peaks during neural activation. By the use of established visual response characteristics, we have determined that the oxygen initial dip provides a better estimate of local neural function than the positive peak. This contrasts sharply with fMRI for which the initial dip is unreliable. To extend these studies, we have examined the relationship between the primary metabolic agents, glucose and lactate, and associated neural activity. For this work, we also use a Doppler technique to measure cerebral blood flow (CBF) together with neural activity. Results show consistent synchronously timed changes such that increases in neural activity are accompanied by decreases in glucose and simultaneous increases in lactate. Measurements of CBF show clear delays with respect to neural response. This is consistent with a slight delay in blood flow with respect to oxygen delivery during neural activation. This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’.

scholarly journals Head motion in children with ADHD during resting-state brain imaging

2014 ◽  
Author(s):  
Xiang-zhen Kong
Keyword(s):  
Resting State ◽  
Head Motion ◽  
Control Group ◽  
Adhd Group ◽  
Typically Developing ◽  
Children With Adhd ◽  
Neural Imaging ◽  
Hyperactivity Disorder ◽  
Healthy Control ◽  
Motion Parameters

Resting-state functional MRI (rs-fMRI) has become an important method for analyzing the neural mechanisms underlying mental disorders. But studies targeting head motion during an rs-fMRI examination are rare. Since head motion may pollute the data in the neural imaging studies and further mislead the understanding of the causes of some disorders, systematic investigations on this topic were badly needed. To this end, in this study, children with attention-deficit/hyperactivity disorder (ADHD) and demographically-matched typically developing control (TDC) participants underwent an rs-fMRI examination. We obtained a summary motion index and six mean single head motion parameters (three translational and three rotational) for each participant. With the summary index, we found that motion was significantly increased in the ADHD group and the results showed that the increase was mainly contributed by the motion around and along the superior-to-inferior direction. Moreover, the classification analysis showed that these head motion parameters during scanning could accurately distinguish children with ADHD from the healthy control group. These results suggest that accounting for head motion during scanning may be helpful for ADHD diagnosis and treatment with neuroimaging.

scholarly journals Online learning for orientation estimation during translation in an insect ring attractor network

2021 ◽  
Author(s):  
Brian S Robinson ◽  
Raphael Norman-Tenazas ◽  
Martha Cervantes ◽  
Danilo Symonette ◽  
Erik C Johnson ◽  
...  
Keyword(s):  
Estimation Error ◽  
Central Complex ◽  
Robotic Systems ◽  
Orientation Estimation ◽  
Theoretical Understanding ◽  
Neural Imaging ◽  
Physical Environments ◽  
Underlying Mechanisms ◽  
Network Weight ◽  
Promising Source

Insect neural systems are a promising source of inspiration for new algorithms for navigation, especially on low size, weight, and power platforms. There have been unprecedented recent neuroscience breakthroughs with Drosophila in behavioral and neural imaging experiments as well as the mapping of detailed connectivity of neural structures. General mechanisms for learning orientation in the central complex (CX) of Drosophila have been investigated previously; however, it is unclear how these underlying mechanisms extend to cases where there is translation through an environment (beyond only rotation), which is critical for navigation in robotic systems. Here, we develop a CX neural connectivity-constrained model that performs sensor fusion, as well as unsupervised learning of visual features for path integration; we demonstrate the viability of this circuit for use in robotic systems in simulated and physical environments. Furthermore, we propose a theoretical understanding of how distributed online unsupervised network weight modification can be leveraged for learning in a trajectory through an environment by minimizing of orientation estimation error. Overall, our results here may enable a new class of CX-derived low power robotic navigation algorithms and lead to testable predictions to inform future neuroscience experiments.

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