How does a bicycle work? A new instrument to assess mechanical reasoning in school aged children

This study demonstrated that a brief interview can reveal the mechanical reasoning that could not be assessed via the Bicycle Drawing Test. This study, conducted on 190 children (6 to 11 years old), shows that mechanical reasoning improves with age. It shows correlations with spatial reasoning and motor control, and with visual reasonin

Electrophysiological measures of low-level vision reveal spatial processing deficits and hemispheric asymmetry in autism spectrum disorder

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Seamless tuning range based-on available gain bandwidth in multiwavelength Brillouin fiber laser.

We experimentally demonstrate a simple widely tunable multiwavelength Brillouin/Erbium fiber laser that can be tuned over the entire C-band, thereby greatly improving the tuning range limitation faced by the previous Brillouin-erbium fiber laser architectures. Tuning range of 39 nm from 1527 nm to 1566 nm, which is only limited by the amplification bandwidth of the erbium gain was successfully achieved. At Brillouin pump wavelength of 1550 nm and 1480 nm laser pump and Brillouin pump powers of 130 mW and 2 mW respectively, all the generated output channels have peak power above 0 dBm, with the first output channel having a peak power of 8.52 dBm. The experimental set up that consists of only 4 optical components, is simple, devoid of the complex structure employed previously to enhance the tunability and feedback mechanism normally associated with multiwavelength Brillouin-erbium fiber laser sources. The generated output channels are stable, rigidly separated by 10 GHz (0.08 nm)

Mid-circuit qubit measurement and rearrangement in a 171^{171}Yb atomic array

Measurement-based quantum error correction relies on the ability to determine the state of a subset of qubits (ancillae) within a processor without revealing or disturbing the state of the remaining qubits. Among neutral-atom based platforms, a scalable, high-fidelity approach to mid-circuit measurement that retains the ancilla qubits in a state suitable for future operations has not yet been demonstrated. In this work, we perform imaging using a narrow-linewidth transition in an array of tweezer-confined $^{171}$Yb atoms to demonstrate nondestructive state-selective and site-selective detection. By applying site-specific light shifts, selected atoms within the array can be hidden from imaging light, which allows a subset of qubits to be measured while causing only percent-level errors on the remaining qubits. As a proof-of-principle demonstration of conditional operations based on the results of the mid-circuit measurements, and of our ability to reuse ancilla qubits, we perform conditional refilling of ancilla sites to correct for occasional atom loss, while maintaining the coherence of data qubits. Looking towards true continuous operation, we demonstrate loading of a magneto-optical trap with a minimal degree of qubit decoherence.Comment: 9 pages, 6 figure

In pursuit of visual attention: SSVEP frequency-tagging moving targets.

Previous research has shown that visual attention does not always exactly follow gaze direction, leading to the concepts of overt and covert attention. However, it is not yet clear how such covert shifts of visual attention to peripheral regions impact the processing of the targets we directly foveate as they move in our visual field. The current study utilised the co-registration of eye-position and EEG recordings while participants tracked moving targets that were embedded with a 30 Hz frequency tag in a Steady State Visually Evoked Potentials (SSVEP) paradigm. When the task required attention to be divided between the moving target (overt attention) and a peripheral region where a second target might appear (covert attention), the SSVEPs elicited by the tracked target at the 30 Hz frequency band were significantly, but transiently, lower than when participants did not have to covertly monitor for a second target. Our findings suggest that neural responses of overt attention are only briefly reduced when attention is divided between covert and overt areas. This neural evidence is in line with theoretical accounts describing attention as a pool of finite resources, such as the perceptual load theory. Altogether, these results have practical implications for many real-world situations where covert shifts of attention may discretely reduce visual processing of objects even when they are directly being tracked with the eyes

Individual Human Brain Areas Can Be Identified from Their Characteristic Spectral Activation Fingerprints

The human brain can be parcellated into diverse anatomical areas. We investigated whether rhythmic brain activity in these areas is characteristic and can be used for automatic classification. To this end, resting-state MEG data of 22 healthy adults was analysed. Power spectra of 1-s long data segments for atlas-defined brain areas were clustered into spectral profiles (“fingerprints”), using k-means and Gaussian mixture (GM) modelling. We demonstrate that individual areas can be identified from these spectral profiles with high accuracy. Our results suggest that each brain area engages in different spectral modes that are characteristic for individual areas. Clustering of brain areas according to similarity of spectral profiles reveals well-known brain networks. Furthermore, we demonstrate task-specific modulations of auditory spectral profiles during auditory processing. These findings have important implications for the classification of regional spectral activity and allow for novel approaches in neuroimaging and neurostimulation in health and disease

Managing Carbon Aspirations: The Influence of Corporate Climate Change Targets on Environmental Performance

Addressing climate change is among the most challenging ethical issues facing contemporary business and society. Unsustainable business activities are causing significant distributional and procedural injustices in areas such as public health and vulnerability to extreme weather events, primarily because of a distinction between primary emitters and those already experiencing the impacts of climate change. Business, as a significant contributor to climate change and beneficiary of externalizing environmental costs, has an obligation to address its environmental impacts. In this paper, we explore the role of firms’ climate change targets in shaping their emissions trends in the context of a large multi-country sample of companies. We contrast two intentions for setting emissions reductions targets: symbolic attempts to manage external stakeholder perceptions via “greenwashing” and substantive commitments to reducing environmental impacts. We argue that the attributes of firms’ climate change targets (their extent, form, and time horizon) are diagnostic of firms’ underlying intentions. Consistent with our hypotheses, while we find no overall effect of setting climate change targets on emissions, we show that targets characterized by a commitment to more ambitious emissions reductions, a longer target time frame, and absolute reductions in emissions are associated with significant reductions in firms’ emissions. Our evidence suggests the need for vigilance among policy-makers and environmental campaigners regarding the underlying intentions that accompany environmental management practices and shows that these can to some extent be diagnosed analytically

Vertical Binocular Disparity is Encoded Implicitly within a Model Neuronal Population Tuned to Horizontal Disparity and Orientation

Primary visual cortex is often viewed as a “cyclopean retina”, performing the initial encoding of binocular disparities between left and right images. Because the eyes are set apart horizontally in the head, binocular disparities are predominantly horizontal. Yet, especially in the visual periphery, a range of non-zero vertical disparities do occur and can influence perception. It has therefore been assumed that primary visual cortex must contain neurons tuned to a range of vertical disparities. Here, I show that this is not necessarily the case. Many disparity-selective neurons are most sensitive to changes in disparity orthogonal to their preferred orientation. That is, the disparity tuning surfaces, mapping their response to different two-dimensional (2D) disparities, are elongated along the cell's preferred orientation. Because of this, even if a neuron's optimal 2D disparity has zero vertical component, the neuron will still respond best to a non-zero vertical disparity when probed with a sub-optimal horizontal disparity. This property can be used to decode 2D disparity, even allowing for realistic levels of neuronal noise. Even if all V1 neurons at a particular retinotopic location are tuned to the expected vertical disparity there (for example, zero at the fovea), the brain could still decode the magnitude and sign of departures from that expected value. This provides an intriguing counter-example to the common wisdom that, in order for a neuronal population to encode a quantity, its members must be tuned to a range of values of that quantity. It demonstrates that populations of disparity-selective neurons encode much richer information than previously appreciated. It suggests a possible strategy for the brain to extract rarely-occurring stimulus values, while concentrating neuronal resources on the most commonly-occurring situations