Neural networks consisting of globally coupled excitatory and inhibitory nonidentical neurons may exhibit a complex dynamic behavior including synchronization, multiclustered solutions in phase space, and oscillator death. We investigate the conditions under which these behaviors occur in a multidimensional parametric space defined by the connectivity strengths and dispersion of the neuronal membrane excitability. Using mode decomposition techniques, we further derive analytically a low dimensional description of the neural population dynamics and show that the various dynamic behaviors of the entire network can be well reproduced by this reduced system. Examples of networks of FitzHugh-Nagumo and Hindmarsh-Rose neurons are discussed in detail.
Tinnitus, the phantom perception of sound, is physiologically characterized by an increase in spontaneous neural activity in the central auditory system. However, as tinnitus is often associated with hearing impairment, it is unclear how a decrease of afferent drive can result in central hyperactivity. In this review, we first assess methods for tinnitus induction and objective measures of the tinnitus percept in animal models. From animal studies, we discuss evidence that tinnitus originates in the cochlear nucleus (CN), and hypothesize mechanisms whereby hyperactivity may develop in the CN after peripheral auditory nerve damage. We elaborate how this process is likely mediated by plasticity of auditory-somatosensory integration in the CN: the circuitry in normal circumstances maintains a balance of auditory and somatosensory activities, and loss of auditory inputs alters the balance of auditory somatosensory integration in a stimulus timing dependent manner, which propels the circuit towards hyperactivity. Understanding the mechanisms underlying tinnitus generation is essential for its prevention and treatment.
Neuronal oscillations and cross-frequency interactions in the rat hippocampus relate in important ways to memory processes and serve as a model for studying oscillatory activity in cognition more broadly. We report here that hippocampal synchrony (CA3-CA1 coherence) increased markedly in the low gamma range as rats were exploring novel objects, particularly those for which the rat subsequently showed good memory. The gamma synchrony varied across phases of the theta rhythm such that coherence was highest at the falling slope and trough of the theta wave. Further, the shape of the theta wave was more asymmetric and elongated at the falling slope during exploration of objects for which the rat subsequently showed good memory as compared to objects for which the rat subsequently showed poor memory. The results showed a strong association between event-related gamma synchrony in rat hippocampus and memory encoding for novel objects. In addition, a novel potential mechanism of cross-frequency interactions was observed whereby dynamic alterations in the shape of theta wave related to memory in correspondence with the strength of gamma synchrony. These findings add to our understanding of how theta and gamma oscillations interact in the hippocampus in the service of memory.
Conventionally, sensory systems are viewed as separate entities, each with its own physiological process serving a different purpose. However, many functions require integrative inputs from multiple sensory systems, and sensory intersection and convergence occur throughout the central nervous system. The neural processes for hearing perception undergo significant modulation by the two other major sensory systems, vision and somatosensation. This synthesis occurs at every level of the ascending auditory pathway: the cochlear nucleus, inferior colliculus, medial geniculate body, and the auditory cortex. In this review, we explore the process of multisensory integration from 1) anatomical (inputs and connections), 2) physiological (cellular responses), 3) functional, and 4) pathological aspects. We focus on the convergence between auditory and somatosensory inputs in each ascending auditory station. This review highlights the intricacy of sensory processing, and offers a multisensory perspective regarding the understanding of sensory disorders.
We conclude with a discussion on the utility of computational models for the development of new epilepsy treatment protocols.
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