Place Cell-Like Activity in the Primary Sensorimotor and Premotor Cortex During Monkey Whole-Body Navigation.

Primary motor (M1), primary somatosensory (S1) and dorsal premotor (PMd) cortical areas of rhesus monkeys previously have been associated only with sensorimotor control of limb movements. Here we show that a significant number of neurons in these areas also represent body position and orientation in space. Two rhesus monkeys (K and M) used a wheelchair controlled by a brain-machine interface (BMI) to navigate in a room. During this whole-body navigation, the discharge rates of M1, S1, and PMd neurons correlated with the two-dimensional (2D) room position and the direction of the wheelchair and the monkey head. This place cell-like activity was observed in both monkeys, with 44.6% and 33.3% of neurons encoding room position in monkeys K and M, respectively, and the overlapping populations of 41.0% and 16.0% neurons encoding head direction. These observations suggest that primary sensorimotor and premotor cortical areas in primates are likely involved in allocentrically representing body position in space during whole-body navigation, which is an unexpected finding given the classical hierarchical model of cortical processing that attributes functional specialization for spatial processing to the hippocampal formation.

Gustatory and reward brain circuits in the control of food intake.

Gustation is a multisensory process allowing for the selection of nutrients and the rejection of irritating and/or toxic compounds. Since obesity is a highly prevalent condition that is critically dependent on food intake and energy expenditure, a deeper understanding of gustatory processing is an important objective in biomedical research. Recent findings have provided evidence that central gustatory processes are distributed across several cortical and subcortical brain areas. Furthermore, these gustatory sensory circuits are closely related to the circuits that process reward. Here, we present an overview of the activation and connectivity between central gustatory and reward areas. Moreover, and given the limitations in number and effectiveness of treatments currently available for overweight patients, we discuss the possibility of modulating neuronal activity in these circuits as an alternative in the treatment of obesity.

Multisensory Processing of Gustatory Stimuli.

Gustatory perception is inherently multimodal, since approximately the same time that intra-oral stimuli activate taste receptors, somatosensory information is concurrently sent to the CNS. We review evidence that gustatory perception is intrinsically linked to concurrent somatosensory processing. We will show that processing of multisensory information can occur at the level of the taste cells through to the gustatory cortex. We will also focus on the fact that the same chemical and physical stimuli that activate the taste system also activate the somatosensory system (SS), but they may provide different types of information to guide behavior.

Primate reaching cued by multichannel spatiotemporal cortical microstimulation.

Both humans and animals can discriminate signals delivered to sensory areas of their brains using electrical microstimulation. This opens the possibility of creating an artificial sensory channel that could be implemented in neuroprosthetic devices. Although microstimulation delivered through multiple implanted electrodes could be beneficial for this purpose, appropriate microstimulation protocols have not been developed. Here, we report a series of experiments in which owl monkeys performed reaching movements guided by spatiotemporal patterns of cortical microstimulation delivered to primary somatosensory cortex through chronically implanted multielectrode arrays. The monkeys learned to discriminate microstimulation patterns, and their ability to learn new patterns and new behavioral rules improved during several months of testing. Significantly, information was conveyed to the brain through the interplay of microstimulation patterns delivered to multiple electrodes and the temporal order in which these electrodes were stimulated. This suggests multichannel microstimulation as a viable means of sensorizing neural prostheses.

Dopamine levels modulate the updating of tastant values.

To survive, animals must constantly update the internal value of stimuli they encounter; a process referred to as incentive learning. Although there have been many studies investigating whether dopamine is necessary for reward, or for the association between stimuli and actions with rewards, less is known about the role of dopamine in the updating of the internal value of stimuli per se. We used a single-bottle forced-choice task to investigate the role of dopamine in learning the value of tastants. We show that dopamine transporter knock-out mice (DAT-KO), which have constitutively elevated dopamine levels, develop a more positive bias towards a hedonically positive tastant (sucrose 400 mM) than their wild-type littermates. Furthermore, when compared to wild-type littermates, DAT-KO mice develop a less negative bias towards a hedonically negative tastant (quinine HCl 10 mM). Importantly, these effects develop with training, because at the onset of training DAT-KO and wild-type mice display similar biases towards sucrose and quinine. These data suggest that dopamine levels can modulate the updating of tastant values, a finding with implications for understanding sensory-specific motivation and reward seeking.

A comparison of optimal MIMO linear and nonlinear models for brain-machine interfaces.

The field of brain-machine interfaces requires the estimation of a mapping from spike trains collected in motor cortex areas to the hand kinematics of the behaving animal. This paper presents a systematic investigation of several linear (Wiener filter, LMS adaptive filters, gamma filter, subspace Wiener filters) and nonlinear models (time-delay neural network and local linear switching models) applied to datasets from two experiments in monkeys performing motor tasks (reaching for food and target hitting). Ensembles of 100-200 cortical neurons were simultaneously recorded in these experiments, and even larger neuronal samples are anticipated in the future. Due to the large size of the models (thousands of parameters), the major issue studied was the generalization performance. Every parameter of the models (not only the weights) was selected optimally using signal processing and machine learning techniques. The models were also compared statistically with respect to the Wiener filter as the baseline. Each of the optimization procedures produced improvements over that baseline for either one of the two datasets or both.

Simultaneus prediction of four kinematic variables for a brain-machine interface using a single recurrent neural network.

Implementation of brain-machine interface neural-to-motor mapping algorithms in low-power, portable digital signal processors (DSPs) requires efficient use of model resources especially when predicting signals that show interdependencies. We show here that a single recurrent neural network can simultaneously predict hand position and velocity from the same ensemble of cells using a minimalist topology. Analysis of the trained topology showed that the model learns to concurrently represent multiple kinematic parameters in a single state variable. We further assess the expressive power of the state variables for both large and small topologies.

The brain decade in debate: VI. Sensory and motor maps: dynamics and plasticity

This article is an edited transcription of a virtual symposium promoted by the Brazilian Society of Neuroscience and Behavior (SBNeC). Although the dynamics of sensory and motor representations have been one of the most studied features of the central nervous system, the actual mechanisms of brain plasticity that underlie the dynamic nature of sensory and motor maps are not entirely unraveled. Our discussion began with the notion that the processing of sensory information depends on many different cortical areas. Some of them are arranged topographically and others have non-topographic (analytical) properties. Besides a sensory component, every cortical area has an efferent output that can be mapped and can influence motor behavior. Although new behaviors might be related to modifications of the sensory or motor representations in a given cortical area, they can also be the result of the acquired ability to make new associations between specific sensory cues and certain movements, a type of learning known as conditioning motor learning. Many types of learning are directly related to the emotional or cognitive context in which a new behavior is acquired. This has been demonstrated by paradigms in which the receptive field properties of cortical neurons are modified when an animal is engaged in a given discrimination task or when a triggering feature is paired with an aversive stimulus. The role of the cholinergic input from the nucleus basalis to the neocortex was also highlighted as one important component of the circuits responsible for the context-dependent changes that can be induced in cortical maps

Beyond maps: a dynamic view of the somatosensory system

Current theories on how tactile information is processed by the mammalian somatosensory system are based primarily on data obtained in studies in which the physiological properties of single neurons were characterized, one at a time, in behaving or anesthetized animals. Yet, the central nervous system relies on the concurrent activation of large populations of neurons to process the variety of sensory stimuli that contribute to normal tactile perception. The recent introduction of electrophysiological methods for chronic and simultaneous recordings of the extracellular activity of large numbers of single neurons per animal has allowed us to investigate, for the first time, how populations of neurons, located at multiple processing stages of the somatosensory system, interact following passive and active tactile stimulation. The rat trigeminal somatosensory system was used as a model for this investigation. Our results revealed the existence of highly dynamic and distributed representations of tactile information, not only in the somatosensory cortex, but also in the thalamus and even in the brainstem. In these structures, we identified broadly tuned neurons with multiwhisker receptive fields (RFs). In the thalamus, a large percentage of neurons exhibited shifts in the spatial domain of their RFs as a function of post-stimulus time. During these shifts, the center of the neuron's RF moved across the whisker pad from caudal to rostral whiskers, but not in the opposite direction, suggesting that these spatiotemporal RFs may encode directional information. Further studies revealed that somatosensory representations were maintained by dynamic interactions between multiple convergent afferents, since they could be altered in a matter of seconds by reversible sensory deprivations. Overall, these results suggest that the rat somatosensory system relies on both spatial and temporal interactions between populations of cortical and subcortical neurons to process multiple attributes of tactile stimuli.