Responsive Nanostructured Polymer Particles

Responsive polymer particles with switchable properties are of great importance for designing smart materials in various applications. Recently, the self-assembly of block copolymers (BCPs) and polymer blends within evaporative emulsions has led to advances in the shape-controlled synthesis of polymer particles. Despite extensive recent progress on BCP particles, the responsive shape tuning of BCP particles and their applications have received little attention. This review provides a brief overview of recent approaches to developing non-spherical polymer particles from soft evaporative emulsions based on the physical principles affecting both particle shape and inner structure. Special attention is paid to the stimuli-responsive, shape-changing nanostructured polymer particles, i.e., design of polymers and surfactant pairs, detailed experimental results, and their applications, including the state-of-the-art progress in this field. Finally, the perspectives on current challenges and future directions in this research field are presented, including the development of surfactants with higher reversibility to multiple stimuli and polymers with unique structural functionality, and diversification of polymer architectures.

Curvature-processing domains in primate V4

Neurons in primate V4 exhibit various types of selectivity for contour shapes, including curves, angles, and simple shapes. How are these neurons organized in V4 remains unclear. Using intrinsic signal optical imaging and two-photon calcium imaging, we observed submillimeter functional domains in V4 that contained neurons preferring curved contours over rectilinear ones. These curvature domains had similar sizes and response amplitudes as orientation domains but tended to separate from these regions. Within the curvature domains, neurons that preferred circles or curve orientations clustered further into finer scale subdomains. Nevertheless, individual neurons also had a wide range of contour selectivity, and neighboring neurons exhibited a substantial diversity in shape tuning besides their common shape preferences. In strong contrast to V4, V1 and V2 did not have such contour-shape-related domains. These findings highlight the importance and complexity of curvature processing in visual object recognition and the key functional role of V4 in this process.

Unsupervised experience with temporal continuity of the visual environment is causally involved in the development of V1 complex cells

Unsupervised adaptation to the spatiotemporal statistics of visual experience is a key computational principle that has long been assumed to govern postnatal development of visual cortical tuning, including orientation selectivity of simple cells and position tolerance of complex cells in primary visual cortex (V1). Yet, causal empirical evidence supporting this hypothesis is scant. Here, we show that degrading the temporal continuity of visual experience during early postnatal life leads to a sizable reduction of the number of complex cells and to an impairment of their functional properties while fully sparing the development of simple cells. This causally implicates adaptation to the temporal structure of the visual input in the development of transformation tolerance but not of shape tuning, thus tightly constraining computational models of unsupervised cortical learning.

Shape- and size dependent piezoelectric properties of monolayer hexagonal boron nitride nanosheets

A symmetry analysis of 2D BN nanosheet geometries is carried out. We demonstrate effective shape tuning of piezoelectric properties.

Arousal regulates frequency tuning in primary auditory cortex

Changes in arousal influence cortical sensory representations, but the synaptic mechanisms underlying arousal-dependent modulation of cortical processing are unclear. Here, we use 2-photon Ca2+ imaging in the auditory cortex of awake mice to show that heightened arousal, as indexed by pupil diameter, broadens frequency-tuned activity of layer 2/3 (L2/3) pyramidal cells. Sensory representations are less sparse, and the tuning of nearby cells more similar when arousal increases. Despite the reduction in selectivity, frequency discrimination by cell ensembles improves due to a decrease in shared trial-to-trial variability. In vivo whole-cell recordings reveal that mechanisms contributing to the effects of arousal on sensory representations include state-dependent modulation of membrane potential dynamics, spontaneous firing, and tone-evoked synaptic potentials. Surprisingly, changes in short-latency tone-evoked excitatory input cannot explain the effects of arousal on the broadness of frequency-tuned output. However, we show that arousal strongly modulates a slow tone-evoked suppression of recurrent excitation underlying lateral inhibition [H. K. Kato, S. K. Asinof, J. S. Isaacson, Neuron, 95, 412–423, (2017)]. This arousal-dependent “network suppression” gates the duration of tone-evoked responses and regulates the broadness of frequency tuning. Thus, arousal can shape tuning via modulation of indirect changes in recurrent network activity.

Shape Tuning of Magnetite Nanoparticles Obtained by Hydrothermal Synthesis: Effect of Temperature

In this work, we present a simple and efficient method for pure phase magnetite (Fe3O4) nanoparticle synthesis. The phase structure, particle shape, and size of the samples were characterized by Raman spectroscopy (Rm), X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray (EDS), and transmission electron microscopy (TEM). The morphology tuning was controlled by the temperature of the reaction; the nanoparticles were synthesized via the hydrothermal method at 120°C, 140°C, and 160°C, respectively. The Rm and XRD spectra showed that all the nanoparticles were Fe3O4 in a pure magnetite phase. The obtained nanoparticles exhibited a high level of crystallinity with uniform morphology at each temperature, as can be observed through TEM and SEM. These magnetic nanoparticles exhibited good saturation magnetization and the resulting shapes were quasi-spheres, octahedrons, and cubes. The samples showed striking magnetic properties, which were examined by a vibrating sample magnetometer (VSM). It has been possible to obtain a good morphological control of nanostructured magnetite in a simple, economical, and scalable method by adjusting the temperature, without the modification of any other synthesis parameter.

'Artiphysiology' reveals V4-like shape tuning in a deep network trained for image classification

Deep networks provide a potentially rich interconnection between neuroscientific and artificial approaches to understanding visual intelligence, but the relationship between artificial and neural representations of complex visual form has not been elucidated at the level of single-unit selectivity. Taking the approach of an electrophysiologist to characterizing single CNN units, we found many units exhibit translation-invariant boundary curvature selectivity approaching that of exemplar neurons in the primate mid-level visual area V4. For some V4-like units, particularly in middle layers, the natural images that drove them best were qualitatively consistent with selectivity for object boundaries. Our results identify a novel image-computable model for V4 boundary curvature selectivity and suggest that such a representation may begin to emerge within an artificial network trained for image categorization, even though boundary information was not provided during training. This raises the possibility that single-unit selectivity in CNNs will become a guide for understanding sensory cortex.