Modeling uncertainty-seeking behavior mediated by cholinergic influence on dopamine

Enhancement, integration, expansion: Activating representation of detailed features for occluded person re-identification

A proposed method, Enhancement, integration, and Expansion, aims to activate the representation of detailed features for occluded person re-identification. Region and context are two important and complementary features, and integrating them in an occluded environment can effectively improve the robustness of the model. Firstly, a self-enhancement module is designed. Based on the constructed multi-stream architecture, rich and meaningful feature interference is introduced in the feature extraction stage to enhance the model's ability to perceive noise. Next, a collaborative integration module similar to cascading cross-attention is proposed. By studying the intrinsic interaction patterns of regional and contextual features, it adaptively fuses features across streams and enhances the diverse and complete representation of internal information. The module is not only robust to complex occlusions, but also mitigates the feature interference problem due to similar appearances or scenes. Finally, a matching expansion module that enhances feature discriminability and completeness is proposed. Providing more stable and accurate features for recognition. Compared with state-of-the-art methods on two occluded and holistic datasets, the proposed method is proved to be advanced and the effectiveness of the module is proved by extensive ablation studies.

Aging, uncertainty, and decision making-A review

There is a great deal of uncertainty in the world. One common source of uncertainty results from incomplete or missing information about probabilistic outcomes (i.e., outcomes that may occur), which influences how people make decisions. The impact of this type of uncertainty may particularly pronounced for older adults, who, as the primary leaders around the world, make highly impactful decisions with lasting outcomes. This review examines the ways in which uncertainty about probabilistic outcomes is perceived, handled, and represented in the aging brain, with an emphasis on how uncertainty may specifically affect decision making in later life. We describe the role of uncertainty in decision making and aging from four perspectives, including 1) theoretical, 2) self-report, 3) behavioral, and 4) neuroscientific. We report evidence of any age-related differences in uncertainty among these contexts and describe how these changes may affect decision making. We then integrate the findings across the distinct perspectives, followed by a discussion of important future directions for research on aging and uncertainty, including prospection, domain-specificity in risk-taking behaviors, and choice overload.

Design Principles for Neurorobotics

In their book "How the Body Shapes the Way We Think: A New View of Intelligence," Pfeifer and Bongard put forth an embodied approach to cognition. Because of this position, many of their robot examples demonstrated "intelligent" behavior despite limited neural processing. It is our belief that neurorobots should attempt to follow many of these principles. In this article, we discuss a number of principles to consider when designing neurorobots and experiments using robots to test brain theories. These principles are strongly inspired by Pfeifer and Bongard, but build on their design principles by grounding them in neuroscience and by adding principles based on neuroscience research. Our design principles fall into three categories. First, organisms must react quickly and appropriately to events. Second, organisms must have the ability to learn and remember over their lifetimes. Third, organisms must weigh options that are crucial for survival. We believe that by following these design principles a robot's behavior will be more naturalistic and more successful.

Memristive LIF Spiking Neuron Model and Its Application in Morse Code

The leaky integrate-and-fire (LIF) spiking model can successively mimic the firing patterns and information propagation of a biological neuron. It has been applied in neural networks, cognitive computing, and brain-inspired computing. Due to the resistance variability and the natural storage capacity of the memristor, the LIF spiking model with a memristor (MLIF) is presented in this article to simulate the function and working mode of neurons in biological systems. First, the comparison between the MLIF spiking model and the LIF spiking model is conducted. Second, it is experimentally shown that a single memristor could mimic the function of the integration and filtering of the dendrite and emulate the function of the integration and firing of the soma. Finally, the feasibility of the proposed MLIF spiking model is verified by the generation and recognition of Morse code. The experimental results indicate that the presented MLIF model efficiently performs good biological frequency adaptation, high firing frequency, and rich spiking patterns. A memristor can be used as the dendrite and the soma, and the MLIF spiking model can emulate the axon. The constructed single neuron can efficiently complete the generation and propagation of firing patterns.

Reliability of behavioral test with fish: How neurotransmitters may exert neuromodulatory effects and alter the biological responses to neuroactive agents

Toxic agents such as pharmaceuticals and pesticides are continuously dispersed especially in the aquatic environment, as a result of human use. Their presence in the environment presents serious concerns, since these compounds interfere with the normal function of the central nervous system (CNS), causing behavior alterations, whose consequences are difficult to predict. However, behavioral responses, even those that occur after exposure to neurotoxic agents, might be modulated by the release of neurotransmitters in the brain of exposed organisms, making even more difficult to ascertain the real consequences of pollution by neurotoxic or neuroactive agents. This study aimed to understand the potential of dopamine as neuromodulator in cases of acute exposure to a pesticide (the carbamate carbofuran) and to a therapeutic agent (the benzodiazepinic drug diazepam) in the freshwater fish Gambusia holbrooki. After acute exposure to both carbofuran and to diazepam it was possible to observe deleterious alterations in the motor function, reflected by significant reductions of both average speed and distance in exposed animals. These changes were later diminished and reverted by dopamine exposure. Despite the indications obtained from our experiments, more research is needed to clarify the consequences of these behavior alterations in a more integrative perspective, namely by adding behavioral endpoints of increased ecological relevance to the adopted experimental design.