Neuron orientation selectivity, otherwise known as the ability to respond optimally to a preferred orientation, has been extensively described in both primary and secondary visual cortices. This orientation selectivity, conserved through all cortical layers of a given column, is the primary basis for cortical organization and functional network emergence. While this selectivity is programmed and acquired since critical period, it has always been believed that in a mature brain, neurons' inherent functional features could not be changed. However, a plurality of studies has investigated the mature brain plasticity in V1, by changing the cells' orientation selectivity with visual adaptation. Using electrophysiological data in both V1 and V2 areas, this study aims to investigate the effects of adaptation on simultaneously recorded cells in both areas. Visual adaptation had an enhanced effect on V2 units, as they exhibited greater tuning curve shifts and a more pronounced decrease of their OSI. Not only did adaptation have a different effect on V2 neurons, it also elicited a different response depending on the neuron's cortical depth. Indeed, in V2, cells in layers II-III were more affected by visual adaptation, while infragranular layer V units exhibited little to no effect at all.

Effects of visual adaptation on orientation selectivity in cat secondary visual cortex.

The Common and Distinct Orientation Adaptation Effect at Pinwheel Centers in Areas 21a and 17 of Cats.

Effect of amorphous calcium phosphate coatings on tribological properties of titanium grade 4 in protein-free artificial saliva

The visual system is organized in a parallel and hierarchical architecture. However, the plasticity in hierarchical neural networks is controversial across different response features and at different levels. In this study, we recorded areas 17 and 21a, earlier and intermediate stages of the visual cortex in the cat, respectively, by single-unit recording and intrinsic-signal optical imaging. We found that ocular dominance (OD) plasticity evoked by monocular deprivation (MD) was stronger in area 21a than in area 17 in the critical period (CP), and this plasticity became weaker but still persisted in area 21a while it disappeared in area 17 beyond the CP. These results suggest a diversified functional plasticity along the visual information processing pathways in a hierarchical neural network.

Ocular Dominance Plasticity of Areas 17 and 21a in the Cat.

Neurons can change their properties in relation to the sensory experience, and different protocols have been employed to study this plastic ability of the brain (Turrigiano & Nelson, 2000; Vetencourt et al., 2008) including sensory deprivation, neuronal adaptation, environmental enrichment and many others (Dragoi et al., 2000; Draganski et al., 2004; Vetencourt et al., 2008; Ghisovan et al., 2009; Ptito et al., 2012; Salvanes et al., 2013). However, in this commentary we will only be discussing neuronal adaptation, which refers to the imposition of a non-preferred stimulus (adapter), from several seconds to minutes, to a neuronal population under observation (Dragoi et al., 2000; Ghisovan et al., 2009). This article is protected by copyright. All rights reserved.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/ejn.14393

The speed of neuronal adaptation: A perspective through the visual cortex

Adaptation plays a key role in visual information processing, and investigations on the adaptation across different visual regions will be helpful to understand how information is processed dynamically along the visual streams. Recent studies have found the enhanced adaptation effects in the early visual system (from LGN to V1) and the dorsal stream (from V1 to MT). However, it remains unclear how adaptation effect propagates along the form/orientation stream in the visual system. In this study, we compared the orientation and direction adaptation evoked by drifting gratings and stationary flashing gratings, as well as moving random dots, in areas 17 and 21a simultaneously of cats. Recorded by single-unit and intrinsic signal optical imaging, induced by both top-up and biased adaptation protocols, the orientation adaptation effect was greater in response decline and preferred orientation shifts in area 21a compared to area 17. However, for the direction adaptation, no difference was observed between these two areas. These results suggest the feature-specific propagation of the adaptation effect along the visual stream.

/pdf/the-feature-specific-propagation-of-orientation-and-2vrq00jzew.pdf

The feature-specific propagation of orientation and direction adaptation from areas 17 to 21a in cats

The role of gingival mechanoreceptors in the tactile function of dental implants

The preoperative differentiation of breast phyllodes tumors (PTs) from fibroadenomas (FAs) plays a critical role in identifying an appropriate surgical treatment. Although several imaging modalities are available, reliable differentiation between PT and FA remains a great challenge for radiologists in clinical work. Artificial intelligence (AI)-assisted diagnosis has shown promise in distinguishing PT from FA. However, a very small sample size was adopted in previous studies. In this work, we retrospectively enrolled 656 breast tumors (372 FAs and 284 PTs) with 1945 ultrasound images in total. Two experienced ultrasound physicians independently evaluated the ultrasound images. Meanwhile, three deep-learning models (i.e., ResNet, VGG, and GoogLeNet) were applied to classify FAs and PTs. The robustness of the models was evaluated by fivefold cross validation. The performance of each model was assessed by using the receiver operating characteristic (ROC) curve. The area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were also calculated. Among the three models, the ResNet model yielded the highest AUC value, of 0.91, with an accuracy value of 95.3%, a sensitivity value of 96.2%, and a specificity value of 94.7% in the testing data set. In contrast, the two physicians yielded an average AUC value of 0.69, an accuracy value of 70.7%, a sensitivity value of 54.4%, and a specificity value of 53.2%. Our findings indicate that the diagnostic performance of deep learning is better than that of physicians in the distinction of PTs from FAs. This further suggests that AI is a valuable tool for aiding clinical diagnosis, thereby advancing precision therapy.

/pdf/differentiation-between-phyllodes-tumors-and-fibroadenomas-2es3r8xu.pdf

Differentiation between Phyllodes Tumors and Fibroadenomas through Breast Ultrasound: Deep-Learning Model Outperforms Ultrasound Physicians

Response of the somatosensory cortex following thermal stimuli to dental implants

The invention belongs to the technical field of composite nanometer materials, and in particular discloses a composite nanometer material with a fluorescence enhancement effect, and a preparation method and application thereof. The composite nanometer material of the invention is a silica-coated nanometer gold composite material with silica as the shell and nanometer gold as the core. The preparation method comprises the following steps: preparing a single nanometer gold ball by using a solution of chloroauric acid and sodium citrate; coating the nanometer gold ball with polyvinylpyrrolidone;and finally, coating a silica layer by using tetraethyl orthosilicate through a hydrolysis method, so as to prepare the composite nanometer material. The composite nanometer material has a fluorescence enhancement effect, and can obviously enhance the fluorescence effect of a fluorescent dye 2,7-difluorofluorescein. The method of the invention has the advantages of mild reaction conditions, simplepreparation process and good reproducibility, and the obtained product has relatively uniform particles and high sensitivity, and can be applied to the field of biological tracing.

Composite nanometer material with fluorescence enhancement effect, and preparation method and application thereof

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