Multimodal sensory information is represented by a combinatorial code in a sensorimotor system.

A ubiquitous feature of the nervous system is the processing of simultaneously arriving sensory inputs from different modalities. Yet, because of the difficulties of monitoring large populations of neurons with the single resolution required to determine their sensory responses, the cellular mechanisms of how populations of neurons encode different sensory modalities often remain enigmatic. We studied multimodal information encoding in a small sensorimotor system of the crustacean stomatogastric nervous system that drives rhythmic motor activity for the processing of food. This system is experimentally advantageous, as it produces a fictive behavioral output in vitro, and distinct sensory modalities can be selectively activated. It has the additional advantage that all sensory information is routed through a hub ganglion, the commissural ganglion, a structure with fewer than 220 neurons. Using optical imaging of a population of commissural neurons to track each individual neuron's response across sensory modalities, we provide evidence that multimodal information is encoded via a combinatorial code of recruited neurons. By selectively stimulating chemosensory and mechanosensory inputs that are functionally important for processing of food, we find that these two modalities were processed in a distributed network comprising the majority of commissural neurons imaged. In a total of 12 commissural ganglia, we show that 98% of all imaged neurons were involved in sensory processing, with the two modalities being processed by a highly overlapping set of neurons. Of these, 80% were multimodal, 18% were unimodal, and only 2% of the neurons did not respond to either modality. Differences between modalities were represented by the identities of the neurons participating in each sensory condition and by differences in response sign (excitation versus inhibition), with 46% changing their responses in the other modality. Consistent with the hypothesis that the commissural network encodes different sensory conditions in the combination of activated neurons, a new combination of excitation and inhibition was found when both pathways were activated simultaneously. The responses to this bimodal condition were distinct from either unimodal condition, and for 30% of the neurons, they were not predictive from the individual unimodal responses. Thus, in a sensorimotor network, different sensory modalities are encoded using a combinatorial code of neurons that are activated or inhibited. This provides motor networks with the ability to differentially respond to categorically different sensory conditions and may serve as a model to understand higher-level processing of multimodal information

Determinando Padrões Bursting-spiking num Modelo neural

Rulkov introduziu um modelo para o comportamento de bursting e spiking de tipos conhecidos de neurônios corticais. No presente trabalho desenvolveu-se um mapa topológico para estabelecer um padrão entre os tipos de atividades neurais relacionados a dois parâmetros de controle. No desenvolvimento deste trabalho foram utilizadas simulações numéricas com redes neurais.

A critical firing rate associated with tonic-to-bursting transitions in synchronized gap-junction coupled neurons

A transition between tonic and bursting neuronal behaviors is studied using a linear chain of three electrically coupled model neurons. Numerical simulations show that, depending on their individual dynamical states, the neurons first synchronize either in a tonic or in a bursting regime. Additionally, a characteristic firing rate, mediating tonic-to-bursting transitions in networked neurons, is found to be associated with a firing rate encountered in the single neuron's equivalent transition. A few cases describing this peculiar phenomenon are presented