We present a method to dissociate the sign-dependent (linear or odd-order) response from the sign-independent (quadratic or even-order) response of a neuron to sequences of random orthonormal stimulus elements. The method is based on a modification of the classical linear-nonlinear model of neural response. The analysis produces estimates of the stimulus features to which the neuron responds in a sign-dependent manner, the stimulus features to which the neuron responds in a sign-independent manner and the relative weight of the sign-independent response. We propose that this method could be used to characterize simple and complex cells in the primary visual cortex.
Speech comprehension involves detecting words and interpreting their meaning according to the preceding semantic context. This process is thought to be underpinned by a predictive neural system that uses that context to anticipate upcoming words. Recent work demonstrated that such a predictive process can be probed from neural signals recorded during ecologically-valid speech listening tasks by using linear lagged models, such as the temporal response function.
A central topic in neuroscience is the neural coding problem which aims to decipher how the brain signals sensory information through neural activity. Despite significant advancements in this area, the characterisation of information encoding through the precise timing of spikes in the somatosensory cortex is limited. Here, we utilised a comprehensive dataset from previous studies to identify and characterise temporal response patterns of Layer 4 neurons of the rat barrel cortex to five distinct stimuli with varying complexities: Basic, Contact, Whisking, Rough, and Smooth.
Currently, the research in memristor-based associative memory neural networks pays more attention to positive stimuli and lays less attention to negative stimuli. Negative stimuli are superior to positive stimuli in some ways, but lack the associated circuit implementation. In this paper, a memristor-based circuit design of avoidance learning with time delay is designed.
Center for Theoretical Neuroscience and Mortimer B Zuckerman Mind Brain Behavior Institute, Columbia University, New York City, NY 10027, USA; Department of Neuroscience, Swartz Program in Theoretical Neuroscience, Kavli Institute for Brain Science, College of Physicians and Surgeons and Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York City, NY 10027, USA.
Sensory systems use context to infer meaning. Accordingly, context profoundly influences neural responses to sensory stimuli. However, a cohesive understanding of the circuit mechanisms governing contextual effects across different stimulus conditions is still lacking.
Background: Nocebo responding involves the experience of adverse health outcomes in response to contextual cues. These deleterious responses impact numerous features of mental and physical health but are characterized by pronounced heterogeneity. Suggestion is widely recognized as a contributing factor to nocebo responding but the moderating role of trait responsiveness to verbal suggestions (suggestibility) in nocebo responding remains poorly understood.
