Shaping the dynamics of a bidirectional neural interface

Progress in decoding neural signals has enabled the development of interfaces that translate cortical brain activities into commands for operating robotic arms and other devices. The electrical stimulation of sensory areas provides a means to create artificial sensory information about the state of a device. Taken together, neural activity recording and microstimulation techniques allow us to embed a portion of the central nervous system within a closed-loop system, whose behavior emerges from the combined dynamical properties of its neural and artificial components. In this study we asked if it is possible to concurrently regulate this bidirectional brain-machine interaction so as to shape a desired dynamical behavior of the combined system. To this end, we followed a well-known biological pathway. In vertebrates, the communications between brain and limb mechanics are mediated by the spinal cord, which combines brain instructions with sensory information and organizes coordinated patterns of muscle forces driving the limbs along dynamically stable trajectories. We report the creation and testing of the first neural interface that emulates this sensory-motor interaction. The interface organizes a bidirectional communication between sensory and motor areas of the brain of anaesthetized rats and an external dynamical object with programmable properties. The system includes (a) a motor interface decoding signals from a motor cortical area, and (b) a sensory interface encoding the state of the external object into electrical stimuli to a somatosensory area. The interactions between brain activities and the state of the external object generate a family of trajectories converging upon a selected equilibrium point from arbitrary starting locations. Thus, the bidirectional interface establishes the possibility to specify not only a particular movement trajectory but an entire family of motions, which includes the prescribed reactions to unexpected perturbations.     

Sensory-motor coordination during grasping and manipulative actions.

Goal-directed grasping and manipulation of objects are human skills that depend on automatic sensory control in which predictive feed-forward mechanisms integrate somatosensory and visual signals with sensory-motor memory systems. Memory representations of physical and task-relevant properties of the object play a pivotal role. Anticipatory strategies are crucial when purposeful actions arise from learned relationships between afferent patterns and efferent commands. The development of even elementary precision grip skills is a protracted process not concluded until early adolescence. Not surprisingly, the neural control of manual actions engages most central nervous system areas known to be involved in motor control.     

Spatial frames of reference and somatosensory processing: a neuropsychological perspective.

In patients with lesions in the right hemisphere, frequently involving the posterior parietal regions, left-sided somatosensory (and visual and motor) deficits not only reflect a disorder of primary sensory processes, but also have a higher-order component related to a defective spatial representation of the body. This additional factor, related to right brain damage, is clinically relevant: contralesional hemianaesthesia (and hemianopia and hemiplegia) is more frequent in right brain-damaged patients than in patients with damage to the left side of the brain. Three main lines of investigation suggest the existence of this higher-order pathological factor. (i) Right brain-damaged patients with left hemineglect may show physiological evidence of preserved processing of somatosensory stimuli, of which they are not aware. Similar results have been obtained in the visual domain. (ii) Direction-specific vestibular, visual optokinetic and somatosensory or proprioceptive stimulations may displace spatial frames of reference in right brain-damaged patients with left hemineglect, reducing or increasing the extent of the patients'' ipsilesional rightward directional error, and bring about similar directional effects in normal subjects. These stimulations, which may improve or worsen a number of manifestations of the neglect syndrome (such as extrapersonal and personal hemineglect), have similar effects on the severity of left somatosensory deficits (defective detection of tactile stimuli, position sense disorders). However, visuospatial hemineglect and the somatosensory deficits improved by these stimulations are independent, albeit related, disorders. (iii) The severity of left somatosensory deficits is affected by the spatial position of body segments, with reference to the midsagittal plane of the trunk. A general implication of these observations is that spatial (non-somatotopic) levels of representation contribute to corporeal awareness. The neural basis of these spatial frames includes the posterior parietal and the premotor frontal regions. These spatial representations could provide perceptual-premotor interfaces for the organization of movements (e.g. pointing, locomotion) directed towards targets in personal and extrapersonal space. In line with this view, there is evidence that the sensory stimulations that modulate left somatosensory deficits affect left motor disorders in a similar, direction-specific, fashion.     

TRP channels in thermosensation

The ability to sense external temperature is assumed by somatosensory neurons, in which temperature information is converted to neural activity by afferent input to the central nervous system. Somatosensory neurons consist of various populations with specialized gene expression, including thermosensitive transient receptor potential ion channels (thermo-TRPs). Thermo-TRPs are responsible for thermal transduction at the peripheral ends of somatosensory neurons and over a wide range of temperatures. In this review, we focus on several thermo-TRPs expressed in sensory neurons: TRPV1, TRPV4, TRPM2, TRPM3, TRPM8, TRPC5, and TRPA1. TRPV3, TRPV4, and TRPC5 expressed in non-neuronal cells that are also involved in somatosensation are also discussed, whereas TRPM2 and TRPM8 are involved in thermosensation in the brain.     

Integrating information from different senses in the auditory cortex

Multisensory integration was once thought to be the domain of brain areas high in the cortical hierarchy, with early sensory cortical fields devoted to unisensory processing of inputs from their given set of sensory receptors. More recently, a wealth of evidence documenting visual and somatosensory responses in auditory cortex, even as early as the primary fields, has changed this view of cortical processing. These multisensory inputs may serve to enhance responses to sounds that are accompanied by other sensory cues, effectively making them easier to hear, but may also act more selectively to shape the receptive field properties of auditory cortical neurons to the location or identity of these events. We discuss the new, converging evidence that multiplexing of neural signals may play a key role in informatively encoding and integrating signals in auditory cortex across multiple sensory modalities. We highlight some of the many open research questions that exist about the neural mechanisms that give rise to multisensory integration in auditory cortex, which should be addressed in future experimental and theoretical studies.     

A shift in sensory processing that enables the developing human brain to discriminate touch from pain

When and how infants begin to discriminate noxious from innocuous stimuli is a fundamental question in neuroscience [1]. However, little is known about the development of the necessary cortical somatosensory functional prerequisites in the intact human brain. Recent studies of developing brain networks have emphasized the importance of transient spontaneous and evoked neuronal bursting activity in the formation of functional circuits [2, 3]. These neuronal bursts are present during development and precede the onset of sensory functions [4, 5]. Their disappearance and the emergence of more adult-like activity are therefore thought to signal the maturation of functional brain circuitry [2, 4]. Here we show the changing patterns of neuronal activity that underlie the onset of nociception and touch discrimination in the preterm infant. We have conducted noninvasive electroencephalogram (EEG) recording of the brain neuronal activity in response to time-locked touches and clinically essential noxious lances of the heel in infants aged 28-45?weeks gestation. We show a transition in brain response following tactile and noxious stimulation from nonspecific, evenly dispersed neuronal bursts to modality-specific, localized, evoked potentials. The results suggest that specific neural circuits necessary for discrimination between touch and nociception emerge from 35-37?weeks gestation in the human brain.     

Coherent interaction of dynamical attractors for object-based selective attention

I investigate essential neuronal mechanisms of visual attention based on object-based theory and a biased-competition scheme. A neural network model is proposed that consists of two feature networks, FI and FII, and one object network, OJ. The FI and FII networks send feedforward projections to the OJ network and receive feedback projections from the OJ network in a convergent/divergent manner. The OJ network integrates information about sensory features originated from the FI and FII networks into information about objects. I let the feature networks and the object network memorize individual features and objects according to the Hebbian learning rule and create the point attractors corresponding to these features and objects as long-term memories in the network dynamics. When the model tries to attend to objects that are superimposed, the point attractors relevant to the two objects emerge in each network. After a short interval (hundreds of milliseconds), the point attractors relevant to one of the two objects are selected and the other point attractors are completely suppressed. I suggest that coherent interactions of dynamical attractors relevant to the selected object may be the neuronal substrate for object-based selective attention. Bottom-up (FI-to-OJ and FI-to-OJ) neuronal mechanisms separate candidate objects from the background, and top-down (OJ-to-FI and OJ-to-FII) mechanisms resolve object-competition by which one relevant object is selected from candidate objects.     

Causality in the association between P300 and alpha event-related desynchronization

Recent findings indicated that both P300 and alpha event-related desynchronization (α-ERD) were associated, and similarly involved in cognitive brain functioning, e.g., attention allocation and memory updating. However, an explicit causal influence between the neural generators of P300 and α-ERD has not yet been investigated. In the present study, using an oddball task paradigm, we assessed the task effect (target vs. non-target) on P300 and α-ERD elicited by stimuli of four sensory modalities, i.e., audition, vision, somatosensory, and pain, estimated their respective neural generators, and investigated the information flow among their neural generators using time-varying effective connectivity in the target condition. Across sensory modalities, the scalp topographies of P300 and α-ERD were similar and respectively maximal at parietal and occipital regions in the target condition. Source analysis revealed that P300 and α-ERD were mainly generated from posterior cingulate cortex and occipital lobe respectively. As revealed by time-varying effective connectivity, the cortical information was consistently flowed from α-ERD sources to P300 sources in the target condition for all four sensory modalities. All these findings showed that P300 in the target condition is modulated by the changes of α-ERD, which would be useful to explore neural mechanism of cognitive information processing in the human brain.     

Computation and physiology of sensory-motor processing in eye movements

Performance in sensory-motor behaviors guides our understanding of many of the key computational functions of the brain: the representation of sensory information, the translation of sensory signals to commands for movement, and the production of behavior. Eye movement behaviors have become a valuable testing ground for theories of neural computation because the neural circuitry has been well characterized and the mechanical control of the eye is comparatively simple. Here I review recent studies of eye movement behaviors that provide insight into sensory-motor computation at the single neuron and systems levels. They show that errors in sensory estimation dominate eye movement variability and that the motor system functions to reduce the behavioral impact of its own intrinsic noise sources.     

Physiology and physiopathology of somatic sensations studied in man by the method of evoked potentials

The physiology of somatic sensation can be investigated noninvasively in man by recording the electric activity of peripheral nerves, spinal cord and brain. Since these responses have a small voltage, it is necessary to use electronic averaging methods for improving the signal-to-noise ratio. These methods are described and discussed, as well as principles of interpretation of somatosensory evoked potentials. It is agreed that the traces thus obtained involve a series of components (extracellular potentials) which reflect distinct neural generators. These generators have been identified and localized at different levels of the subcortical somatosensory pathway and in different cortical areas. Several components reflect generators located under the recording electrodes (nearfield potentials), while other reflect extracellular potentials diffusing at a distance in the volume conductor of the neck and head (farfield potentials). The analysis of these components provides a wealth of new data for the physiology and pathophysiology of the somatic sensory system in man. Besides so-called "obligatory" components that are present irrespective of the attention of the subject, the studies have uncovered "cognitive" components which reflect neural mechanisms involved in the intellectual processus of perception and decision.     

Spatiotemporal dynamics of cortical sensorimotor integration in behaving mice

Tactile information is actively acquired and processed in the brain through concerted interactions between movement and sensation. Somatosensory input is often the result of self-generated movement during the active touch of objects, and conversely, sensory information is used to refine motor control. There must therefore be important interactions between sensory and motor pathways, which we chose to investigate in the mouse whisker sensorimotor system. Voltage-sensitive dye was applied to the neocortex of mice to directly image the membrane potential dynamics of sensorimotor cortex with subcolumnar spatial resolution and millisecond temporal precision. Single brief whisker deflections evoked highly distributed depolarizing cortical sensory responses, which began in the primary somatosensory barrel cortex and subsequently excited the whisker motor cortex. The spread of sensory information to motor cortex was dynamically regulated by behavior and correlated with the generation of sensory-evoked whisker movement. Sensory processing in motor cortex may therefore contribute significantly to active tactile sensory perception.     

Effects of Sensory Behavioral Tasks on Pain Threshold and Cortical Excitability

Background/Objective

Transcutaneous electrical stimulation has been proven to modulate nervous system activity, leading to changes in pain perception, via the peripheral sensory system, in a bottom up approach. We tested whether different sensory behavioral tasks induce significant effects in pain processing and whether these changes correlate with cortical plasticity.

Methodology/Principal Findings

This randomized parallel designed experiment included forty healthy right-handed males. Three different somatosensory tasks, including learning tasks with and without visual feedback and simple somatosensory input, were tested on pressure pain threshold and motor cortex excitability using transcranial magnetic stimulation (TMS). Sensory tasks induced hand-specific pain modulation effects. They increased pain thresholds of the left hand (which was the target to the sensory tasks) and decreased them in the right hand. TMS showed that somatosensory input decreased cortical excitability, as indexed by reduced MEP amplitudes and increased SICI. Although somatosensory tasks similarly altered pain thresholds and cortical excitability, there was no significant correlation between these variables and only the visual feedback task showed significant somatosensory learning.

Conclusions/Significance

Lack of correlation between cortical excitability and pain thresholds and lack of differential effects across tasks, but significant changes in pain thresholds suggest that analgesic effects of somatosensory tasks are not primarily associated with motor cortical neural mechanisms, thus, suggesting that subcortical neural circuits and/or spinal cord are involved with the observed effects. Identifying the neural mechanisms of somatosensory stimulation on pain may open novel possibilities for combining different targeted therapies for pain control.     

Escape behavior elicited by single, channelrhodopsin-2-evoked spikes in zebrafish somatosensory neurons

Somatosensory neurons in teleosts and amphibians are sensitive to thermal, mechanical, or nociceptive stimuli [1, 2]. The two main types of such cells in zebrafish--Rohon-Beard and trigeminal neurons--have served as models for neural development [3-6], but little is known about how they encode tactile stimuli. The hindbrain networks that transduce somatosensory stimuli into a motor output encode information by using very few spikes in a small number of cells [7], but it is unclear whether activity in the primary receptor neurons is similarly efficient. To address this question, we manipulated the activity of zebrafish neurons with the light-activated cation channel, Channelrhodopsin-2 (ChR2) [8, 9]. We found that photoactivation of ChR2 in genetically defined populations of somatosensory neurons triggered escape behaviors in 24-hr-old zebrafish. Electrophysiological recordings from ChR2-positive trigeminal neurons in intact fish revealed that these cells have extremely low rates of spontaneous activity and can be induced to fire by brief pulses of blue light. Using this technique, we find that even a single action potential in a single sensory neuron was at times sufficient to evoke an escape behavior. These results establish ChR2 as a powerful tool for the manipulation of neural activity in zebrafish and reveal a degree of efficiency in coding that has not been found in primary sensory neurons.     

Implicit multisensory associations influence voice recognition

Natural objects provide partially redundant information to the brain through different sensory modalities. For example, voices and faces both give information about the speech content, age, and gender of a person. Thanks to this redundancy, multimodal recognition is fast, robust, and automatic. In unimodal perception, however, only part of the information about an object is available. Here, we addressed whether, even under conditions of unimodal sensory input, crossmodal neural circuits that have been shaped by previous associative learning become activated and underpin a performance benefit. We measured brain activity with functional magnetic resonance imaging before, while, and after participants learned to associate either sensory redundant stimuli, i.e. voices and faces, or arbitrary multimodal combinations, i.e. voices and written names, ring tones, and cell phones or brand names of these cell phones. After learning, participants were better at recognizing unimodal auditory voices that had been paired with faces than those paired with written names, and association of voices with faces resulted in an increased functional coupling between voice and face areas. No such effects were observed for ring tones that had been paired with cell phones or names. These findings demonstrate that brief exposure to ecologically valid and sensory redundant stimulus pairs, such as voices and faces, induces specific multisensory associations. Consistent with predictive coding theories, associative representations become thereafter available for unimodal perception and facilitate object recognition. These data suggest that for natural objects effective predictive signals can be generated across sensory systems and proceed by optimization of functional connectivity between specialized cortical sensory modules.     

Constrained brain volume in an efficient coding model explains the fraction of excitatory and inhibitory neurons in sensory cortices

The number of neurons in mammalian cortex varies by multiple orders of magnitude across different species. In contrast, the ratio of excitatory to inhibitory neurons (E:I ratio) varies in a much smaller range, from 3:1 to 9:1 and remains roughly constant for different sensory areas within a species. Despite this structure being important for understanding the function of neural circuits, the reason for this consistency is not yet understood. While recent models of vision based on the efficient coding hypothesis show that increasing the number of both excitatory and inhibitory cells improves stimulus representation, the two cannot increase simultaneously due to constraints on brain volume. In this work, we implement an efficient coding model of vision under a constraint on the volume (using number of neurons as a surrogate) while varying the E:I ratio. We show that the performance of the model is optimal at biologically observed E:I ratios under several metrics. We argue that this happens due to trade-offs between the computational accuracy and the representation capacity for natural stimuli. Further, we make experimentally testable predictions that 1) the optimal E:I ratio should be higher for species with a higher sparsity in the neural activity and 2) the character of inhibitory synaptic distributions and firing rates should change depending on E:I ratio. Our findings, which are supported by our new preliminary analyses of publicly available data, provide the first quantitative and testable hypothesis based on optimal coding models for the distribution of excitatory and inhibitory neural types in the mammalian sensory cortices.     

Regional variation in neurovascular coupling and why we still lack a Rosetta Stone

Functional magnetic resonance imaging (fMRI) is the dominant tool in cognitive neuroscience although its relation to underlying neural activity, particularly in the human brain, remains largely unknown. A major research goal, therefore, has been to uncover a ‘Rosetta Stone’ providing direct translation between the blood oxygen level-dependent (BOLD) signal, the local field potential and single-neuron activity. Here, I evaluate the proposal that BOLD signal changes equate to changes in gamma-band activity, which in turn may partially relate to the spiking activity of neurons. While there is some support for this idea in sensory cortices, findings in deeper brain structures like the hippocampus instead suggest both regional and frequency-wise differences. Relatedly, I consider four important factors in linking fMRI to neural activity: interpretation of correlations between these signals, regional variability in local vasculature, distributed neural coding schemes and varying fMRI signal quality. Novel analytic fMRI techniques, such as multivariate pattern analysis (MVPA), employ the distributed patterns of voxels across a brain region to make inferences about information content rather than whether a small number of voxels go up or down relative to baseline in response to a stimulus. Although unlikely to provide a Rosetta Stone, MVPA, therefore, may represent one possible means forward for better linking BOLD signal changes to the information coded by underlying neural activity.This article is part of the theme issue ‘Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity’.     

Electrical neuroimaging of single trials to identify laterality and brain regions involved in finger movements

Thought-controlled neuroprostheses could allow paralyzed patients to interact with the external world using brain waves. Thus far, the fastest and more accurate control of neuroprostheses is achieved through direct recordings of neural activity [Nicolelis, M.A., 2001. Actions from thoughts. Nature 409, 403–407; Donoghue, J.P., 2002. Connecting cortex to machines: recent advances in brain interfaces. Nat. Neurosci. 5 (Suppl.), 1085–1088]. However, invasive recordings have inherent medical risks. Here we discuss some approaches that could enhance the speed and accuracy of non-invasive devices, namely, (1) enlarging the spectral analysis to include higher frequency oscillations, able to transmit substantial information over short analysis windows; (2) using spectral analysis procedures that minimize the variance of the estimates; and (3) transforming EEG recorded activity into local field potential estimates (eLFP). Theoretical and experimental arguments are used to explain why it is erroneous to think that scalp EEG cannot sense high frequency oscillations and how this might hinders further developments. We further illustrate how non-invasive eLFPs derived from the scalp-recorded electroencephalogram (EEG) can be combined with robust, broad band spectral analysis to accurately detect (off-line) the laterality of upcoming hand movements. Interestingly, the use of pattern recognition to select the brain voxels differentially engaged by the explored tasks leads to sound neural activation images. Consequently, our results indicate that both research lines, i.e., neuroprosthetics and electrical neuroimaging, might effectively benefit from their mutual interaction.     

Detection of cold pain, cold allodynia and cold hyperalgesia in freely behaving rats

In mammals, somatosensory input activates feedback and feed-forward inhibitory circuits within the spinal cord dorsal horn to modulate sensory processing and thereby affecting sensory perception by the brain. Conventionally, feedback and feed-forward inhibitory activity evoked by somatosensory input to the dorsal horn is believed to be driven by glutamate, the principle excitatory neurotransmitter in primary afferent fibers. Substance P (SP), the prototypic neuropeptide released from primary afferent fibers to the dorsal horn, is regarded as a pain substance in the mammalian somatosensory system due to its action on nociceptive projection neurons. Here we report that endogenous SP drives a novel form of feed-forward inhibitory activity in the dorsal horn. The SP-driven feed-forward inhibitory activity is long-lasting and has a temporal phase distinct from glutamate-driven feed-forward inhibitory activity. Compromising SP-driven feed-forward inhibitory activity results in behavioral sensitization. Our findings reveal a fundamental role of SP in recruiting inhibitory activity for sensory processing, which may have important therapeutic implications in treating pathological pain conditions using SP receptors as targets.     

Task-induced neural covariability as a signature of approximate Bayesian learning and inference

Perception is often characterized computationally as an inference process in which uncertain or ambiguous sensory inputs are combined with prior expectations. Although behavioral studies have shown that observers can change their prior expectations in the context of a task, robust neural signatures of task-specific priors have been elusive. Here, we analytically derive such signatures under the general assumption that the responses of sensory neurons encode posterior beliefs that combine sensory inputs with task-specific expectations. Specifically, we derive predictions for the task-dependence of correlated neural variability and decision-related signals in sensory neurons. The qualitative aspects of our results are parameter-free and specific to the statistics of each task. The predictions for correlated variability also differ from predictions of classic feedforward models of sensory processing and are therefore a strong test of theories of hierarchical Bayesian inference in the brain. Importantly, we find that Bayesian learning predicts an increase in so-called “differential correlations” as the observer’s internal model learns the stimulus distribution, and the observer’s behavioral performance improves. This stands in contrast to classic feedforward encoding/decoding models of sensory processing, since such correlations are fundamentally information-limiting. We find support for our predictions in data from existing neurophysiological studies across a variety of tasks and brain areas. Finally, we show in simulation how measurements of sensory neural responses can reveal information about a subject’s internal beliefs about the task. Taken together, our results reinterpret task-dependent sources of neural covariability as signatures of Bayesian inference and provide new insights into their cause and their function.