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Emergence of a contrast-invariant representation of naturalistic texture in macaque visual cortex.
bioRxiv
January 2025
Center for Neural Science, New York University, New York, NY, USA.
Unlabelled: Sensory stimuli vary across a variety of dimensions, like contrast, orientation, or texture. The brain must rely on population representations to disentangle changes in one dimension from changes in another. To understand how the visual system might extract separable stimulus representations, we recorded multiunit neuronal responses to texture images varying along two dimensions: contrast, a property represented as early as the retina, and naturalistic statistical structure, a property that modulates neuronal responses in V2 and V4, but not in V1.
View Article and Find Full Text PDFProtein Recognition Based on Temperature-Stimulated Multiparameter Response Virtual Array Sensing Strategy.
Anal Chem
November 2023
Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, Innovative Drug Research Center, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China.
In the field of array sensing, researchers are committed to miniaturizing array sensing systems while ensuring the acquisition of multiple sensing information. Here, a new strategy called "stimulus responsive array sensing" was presented to obtain virtual multiple sensing without constructing multiple physical sensing units. Based on bioluminescence resonance energy transfer, where luciferase acts as the donor and temperature stimulus response polymers act as the receptors, by using only one sensing unit to output multiple stimulus responsive sensing signals in temperature dimension, an equivalent array sensing could be achieved.
View Article and Find Full Text PDFStimulus-Specific Prediction Error Neurons in Mouse Auditory Cortex.
J Neurosci
October 2023
Center for Neural Science, New York University, New York, New York 10003
Comparing expectation with experience is an important neural computation performed throughout the brain and is a hallmark of predictive processing. Experiments that alter the sensory outcome of an animal's behavior reveal enhanced neural responses to unexpected self-generated stimuli, indicating that populations of neurons in sensory cortex may reflect prediction errors (PEs), mismatches between expectation and experience. However, enhanced neural responses to self-generated stimuli could also arise through nonpredictive mechanisms, such as the movement-based facilitation of a neuron's inherent sound responses.
View Article and Find Full Text PDFDynamically Reconfigurable DNA Origami Crystals Driven by a Designated Path Diagram.
J Am Chem Soc
February 2023
College of Engineering and Applied Sciences, State Key Laboratory of Analytical Chemistry for Life Science, Jiangsu Key Laboratory of Artificial Functional Materials, Chemistry and Biomedicine Innovation Center, Nanjing University, Nanjing 210023, China.
Constructing adaptable and switchable crystal structures renders it possible to dynamically control the properties and functions of adaptive materials, thereby expanding the potential application of these structures in fields such as optics, biology, and catalysis. Recently, researchers have developed various dynamic crystals possessing phase transition abilities. However, manufacturing switchable crystals with multiple-phase-transition ability by integrating various responsive behaviors into different dimensions of a single lattice remains considerably challenging.
View Article and Find Full Text PDFCNN-XGBoost fusion-based affective state recognition using EEG spectrogram image analysis.
Sci Rep
August 2022
SINTEF Digital, Trondheim, Norway.
Recognizing emotional state of human using brain signal is an active research domain with several open challenges. In this research, we propose a signal spectrogram image based CNN-XGBoost fusion method for recognising three dimensions of emotion, namely arousal (calm or excitement), valence (positive or negative feeling) and dominance (without control or empowered). We used a benchmark dataset called DREAMER where the EEG signals were collected from multiple stimulus along with self-evaluation ratings.
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