Patterns in the brain. Neuronal population coding in the somatosensory system

Exploratory evaluation of spinal cord stimulation with dynamic pulse patterns: a promising approach to improve stimulation sensation, coverage of pain areas, and expected pain relief

Background

The societal burden of chronic pain and the contribution-in-part to the opioid crisis, is a strong motivation to improve and expand non-addictive treatments, including spinal cord stimulation (SCS). For several decades standard SCS has consisted in delivery of tonic pulses with static parameter settings in frequency, pulse width, and amplitude. These static parameters have limited ability to personalize the quality of paresthesia, the dermatomal coverage, and thus may affect SCS efficacy. Further, static settings may contribute to the build-up of tolerance or loss of efficacy of the therapy over time in some patients.

Methods

We conducted an acute exploratory study to evaluate the effects of SCS using time-dynamic pulses as compared to time-static (conventional tonic) stimulation pulses, with the hypotheses that dynamic pulse SCS may enable beneficial tailoring of the sensation and the patient's expectation for better pain relief with SCS. During a single clinic visit, consented subjects undergoing a standard SCS trial had their implanted leads temporarily connected to an investigational external stimulator capable of delivering time-static and six categories of time-dynamic pulse sequences, each characterized by continuously varying a stimulation parameter. Study subjects provided several assessments while blinded to the stimulation pattern, including: drawing of paresthesia maps, descriptions of sensation, and ratings for comfort and helpfulness to pain relief.

Results

Even without optimization of the field location, a majority of subjects rated sensations from dynamic stimulation as better or equal to that of static stimulation for comfortableness and for helpfulness to pain relief. The initial data showed a gender and/or pain dermatomal location related preference to a stimulation pattern. In particular, female subjects and subjects with pain at higher dermatomes tended to rank the sensation from dynamic stimulation better. Dynamic stimulation produced greater pain coverage without optimization; in 70% (9/13) of subjects, maximal pain coverage was achieved with a dynamic stimulation pattern. There was also greater variety in the words used by patients to describe stimulation sensation in the free text and free form verbal descriptions associated with dynamic stimulation.

Conclusions

With the same electrode configuration and comparable parameter settings, acute SCS using dynamic pulses produced more positive ratings, expanded paresthesia coverage, and greater variation in sensation as compared to SCS using static pulses, suggesting that dynamic stimulation has the potential to improve capabilities of SCS for the treatment of chronic pain. Further study is warranted.

Trial Registration

This study was registered at ClinicalTrials.gov under ID NCT02988713, November 2016 (URL: https://clinicaltrials.gov/ct2/show/NCT02988713).

Artificial Intelligence Meets Flexible Sensors: Emerging Smart Flexible Sensing Systems Driven by Machine Learning and Artificial Synapses

The recent wave of the artificial intelligence (AI) revolution has aroused unprecedented interest in the intelligentialize of human society. As an essential component that bridges the physical world and digital signals, flexible sensors are evolving from a single sensing element to a smarter system, which is capable of highly efficient acquisition, analysis, and even perception of vast, multifaceted data. While challenging from a manual perspective, the development of intelligent flexible sensing has been remarkably facilitated owing to the rapid advances of brain-inspired AI innovations from both the algorithm (machine learning) and the framework (artificial synapses) level. This review presents the recent progress of the emerging AI-driven, intelligent flexible sensing systems. The basic concept of machine learning and artificial synapses are introduced. The new enabling features induced by the fusion of AI and flexible sensing are comprehensively reviewed, which significantly advances the applications such as flexible sensory systems, soft/humanoid robotics, and human activity monitoring. As two of the most profound innovations in the twenty-first century, the deep incorporation of flexible sensing and AI technology holds tremendous potential for creating a smarter world for human beings.

Stretchable Transistor-Structured Artificial Synapses for Neuromorphic Electronics

Stretchable synaptic transistors, a core technology in neuromorphic electronics, have functions and structures similar to biological synapses and can concurrently transmit signals and learn. Stretchable synaptic transistors are usually soft and stretchy and can accommodate various mechanical deformations, which presents significant prospects in soft machines, electronic skin, human-brain interfaces, and wearable electronics. Considerable efforts have been devoted to developing stretchable synaptic transistors to implement electronic device neuromorphic functions, and remarkable advances have been achieved. Here, this review introduces the basic concept of artificial synaptic transistors and summarizes the recent progress in device structures, functional-layer materials, and fabrication processes. Classical stretchable synaptic transistors, including electric double-layer synaptic transistors, electrochemical synaptic transistors, and optoelectronic synaptic transistors, as well as the applications of stretchable synaptic transistors in light-sensory systems, tactile-sensory systems, and multisensory artificial-nerves systems, are discussed. Finally, the current challenges and potential directions of stretchable synaptic transistors are analyzed. This review presents a detailed introduction to the recent progress in stretchable synaptic transistors from basic concept to applications, providing a reference for the development of stretchable synaptic transistors in the future.

Stretchable Neuromorphic Transistor That Combines Multisensing and Information Processing for Epidermal Gesture Recognition

We fabricated a nanowire-channel intrinsically stretchable neuromorphic transistor (NISNT) that perceives both tactile and visual information and emulates neuromorphic processing capabilities. The device demonstrated excellent stretching endurance of 1000 stretch cycles while retaining stable electrical properties. The device was then applied as a multisensitive afferent nerve that processes information in parallel. Compatible with skin deformation, the devices are attached to fingers to serve as conformal strain sensors and neuromorphic information-processing units for gesture recognition. The excitatory postsynaptic current in each device represents shape changes and is then analyzed using softmax activation processing of the neural network to recognize gestures. A multistage neural network that uses NISNT was used to further confirm the gestures. This work demonstrated an idea toward multisensory artificial nerves and neuromorphic systems.

Distinct patterns of activity in individual cortical neurons and local networks in primary somatosensory cortex of mice evoked by square-wave mechanical limb stimulation

Artificial forms of mechanical limb stimulation are used within multiple fields of study to determine the level of cortical excitability and to map the trajectory of neuronal recovery from cortical damage or disease. Square-wave mechanical or electrical stimuli are often used in these studies, but a characterization of sensory-evoked response properties to square-waves with distinct fundamental frequencies but overlapping harmonics has not been performed. To distinguish between somatic stimuli, the primary somatosensory cortex must be able to represent distinct stimuli with unique patterns of activity, even if they have overlapping features. Thus, mechanical square-wave stimulation was used in conjunction with regional and cellular imaging to examine regional and cellular response properties evoked by different frequencies of stimulation. Flavoprotein autofluorescence imaging was used to map the somatosensory cortex of anaesthetized C57BL/6 mice, and in vivo two-photon Ca2+ imaging was used to define patterns of neuronal activation during mechanical square-wave stimulation of the contralateral forelimb or hindlimb at various frequencies (3, 10, 100, 200, and 300 Hz). The data revealed that neurons within the limb associated somatosensory cortex responding to various frequencies of square-wave stimuli exhibit stimulus-specific patterns of activity. Subsets of neurons were found to have sensory-evoked activity that is either primarily responsive to single stimulus frequencies or broadly responsive to multiple frequencies of limb stimulation. High frequency stimuli were shown to elicit more population activity, with a greater percentage of the population responding and greater percentage of cells with high amplitude responses. Stimulus-evoked cell-cell correlations within these neuronal networks varied as a function of frequency of stimulation, such that each stimulus elicited a distinct pattern that was more consistent across multiple trials of the same stimulus compared to trials at different frequencies of stimulation. The variation in cortical response to different square-wave stimuli can thus be represented by the population pattern of supra-threshold Ca2+ transients, the magnitude and temporal properties of the evoked activity, and the structure of the stimulus-evoked correlation between neurons.

A Functional Topographic Map for Spinal Sensorimotor Reflexes

Cutaneous somatosensory modalities play pivotal roles in generating a wide range of sensorimotor behaviors, including protective and corrective reflexes that dynamically adapt ongoing movement and posture. How interneurons (INs) in the dorsal horn encode these modalities and transform them into stimulus-appropriate motor behaviors is not known. Here, we use an intersectional genetic approach to functionally assess the contribution that eight classes of dorsal excitatory INs make to sensorimotor reflex responses. We demonstrate that the dorsal horn is organized into spatially restricted excitatory modules composed of molecularly heterogeneous cell types. Laminae I/II INs drive chemical itch-induced scratching, laminae II/III INs generate paw withdrawal movements, and laminae III/IV INs modulate dynamic corrective reflexes. These data reveal a key principle in spinal somatosensory processing, namely, sensorimotor reflexes are driven by the differential spatial recruitment of excitatory neurons.

Time-dynamic pulse modulation of spinal cord stimulation reduces mechanical hypersensitivity and spontaneous pain in rats

Enhancing the efficacy of spinal cord stimulation (SCS) is needed to alleviate the burden of chronic pain and dependence on opioids. Present SCS therapies are characterized by the delivery of constant stimulation in the form of trains of tonic pulses (TPs). We tested the hypothesis that modulated SCS using novel time-dynamic pulses (TDPs) leads to improved analgesia and compared the effects of SCS using conventional TPs and a collection of TDPs in a rat model of neuropathic pain according to a longitudinal, double-blind, and crossover design. We tested the effects of the following SCS patterns on paw withdrawal threshold and resting state EEG theta power as a biomarker of spontaneous pain: Tonic (conventional), amplitude modulation, pulse width modulation, sinusoidal rate modulation, and stochastic rate modulation. Results demonstrated that under the parameter settings tested in this study, all tested patterns except pulse width modulation, significantly reversed mechanical hypersensitivity, with stochastic rate modulation achieving the highest efficacy, followed by the sinusoidal rate modulation. The anti-nociceptive effects of sinusoidal rate modulation on EEG outlasted SCS duration on the behavioral and EEG levels. These results suggest that TDP modulation may improve clinical outcomes by reducing pain intensity and possibly improving the sensory experience.

Stretchable elastic synaptic transistors for neurologically integrated soft engineering systems

Artificial synaptic devices that can be stretched similar to those appearing in soft-bodied animals, such as earthworms, could be seamlessly integrated onto soft machines toward enabled neurological functions. Here, we report a stretchable synaptic transistor fully based on elastomeric electronic materials, which exhibits a full set of synaptic characteristics. These characteristics retained even the rubbery synapse that is stretched by 50%. By implementing stretchable synaptic transistor with mechanoreceptor in an array format, we developed a deformable sensory skin, where the mechanoreceptors interface the external stimulations and generate presynaptic pulses and then the synaptic transistors render postsynaptic potentials. Furthermore, we demonstrated a soft adaptive neurorobot that is able to perform adaptive locomotion based on robotic memory in a programmable manner upon physically tapping the skin. Our rubbery synaptic transistor and neurologically integrated devices pave the way toward enabled neurological functions in soft machines and other applications.

The search for pain biomarkers in the human brain

Non-invasive functional brain imaging is used more than ever to investigate pain in health and disease, with the prospect of finding new means to alleviate pain and improve patient wellbeing. The observation that several brain areas are activated by transient painful stimuli, and that the magnitude of this activity is often graded with pain intensity, has prompted researchers to extract features of brain activity that could serve as biomarkers to measure pain objectively. However, most of the brain responses observed when pain is present can also be observed when pain is absent. For example, similar brain responses can be elicited by salient but non-painful auditory, tactile and visual stimuli, and such responses can even be recorded in patients with congenital analgesia. Thus, as argued in this review, there is still disagreement on the degree to which current measures of brain activity exactly relate to pain. Furthermore, whether more recent analysis techniques can be used to identify distributed patterns of brain activity specific for pain can be only warranted using carefully designed control conditions. On a more general level, the clinical utility of current pain biomarkers derived from human functional neuroimaging appears to be overstated, and evidence for their efficacy in real-life clinical conditions is scarce. Rather than searching for biomarkers of pain perception, several researchers are developing biomarkers to achieve mechanism-based stratification of pain conditions, predict response to medication and offer personalized treatments. Initial results with promising clinical perspectives need to be further tested for replicability and generalizability.

Inverted Encoding Models Reconstruct an Arbitrary Model Response, Not the Stimulus

Probing how large populations of neurons represent stimuli is key to understanding sensory representations as many stimulus characteristics can only be discerned from population activity and not from individual single-units. Recently, inverted encoding models have been used to produce channel response functions from large spatial-scale measurements of human brain activity that are reminiscent of single-unit tuning functions and have been proposed to assay "population-level stimulus representations" (Sprague et al., 2018a). However, these channel response functions do not assay population tuning. We show by derivation that the channel response function is only determined up to an invertible linear transform. Thus, these channel response functions are arbitrary, one of an infinite family and therefore not a unique description of population representation. Indeed, simulations demonstrate that bimodal, even random, channel basis functions can account perfectly well for population responses without any underlying neural response units that are so tuned. However, the approach can be salvaged by extending it to reconstruct the stimulus, not the assumed model. We show that when this is done, even using bimodal and random channel basis functions, a unimodal function peaking at the appropriate value of the stimulus is recovered which can be interpreted as a measure of population selectivity. More precisely, the recovered function signifies how likely any value of the stimulus is, given the observed population response. Whether an analysis is recovering the hypothetical responses of an arbitrary model rather than assessing the selectivity of population representations is not an issue unique to the inverted encoding model and human neuroscience, but a general problem that must be confronted as more complex analyses intervene between measurement of population activity and presentation of data.

The neural circuits of thermal perception

Thermal information about skin surface temperature is a key sense for the perception of object identity and valence. The identification of ion channels involved in the transduction of thermal changes has provided a genetic access point to the thermal system. However, from sensory specific 'labeled-lines' to multimodal interactive pathways, the functional organization and identity of the neural circuits mediating innocuous thermal perception have been debated for over 100 years. Here we highlight points in the system that require further attention and review recent advances using in vivo electrophysiology, cellular resolution calcium imaging, optogenetics and thermal perceptual tasks in behaving mice that have begun to uncover the anatomical principles and neural processing mechanisms underlying innocuous thermal perception.

Spatial Tuning Shifts Increase the Discriminability and Fidelity of Population Codes in Visual Cortex

Selective visual attention enables organisms to enhance the representation of behaviorally relevant stimuli by altering the encoding properties of single receptive fields (RFs). Yet we know little about how the attentional modulations of single RFs contribute to the encoding of an entire visual scene. Addressing this issue requires (1) measuring a group of RFs that tile a continuous portion of visual space, (2) constructing a population-level measurement of spatial representations based on these RFs, and (3) linking how different types of RF attentional modulations change the population-level representation. To accomplish these aims, we used fMRI to characterize the responses of thousands of voxels in retinotopically organized human cortex. First, we found that the response modulations of voxel RFs (vRFs) depend on the spatial relationship between the RF center and the visual location of the attended target. Second, we used two analyses to assess the spatial encoding quality of a population of voxels. We found that attention increased fine spatial discriminability and representational fidelity near the attended target. Third, we linked these findings by manipulating the observed vRF attentional modulations and recomputing our measures of the fidelity of population codes. Surprisingly, we discovered that attentional enhancements of population-level representations largely depend on position shifts of vRFs, rather than changes in size or gain. Our data suggest that position shifts of single RFs are a principal mechanism by which attention enhances population-level representations in visual cortex.SIGNIFICANCE STATEMENT Although changes in the gain and size of RFs have dominated our view of how attention modulates visual information codes, such hypotheses have largely relied on the extrapolation of single-cell responses to population responses. Here we use fMRI to relate changes in single voxel receptive fields (vRFs) to changes in population-level representations. We find that vRF position shifts contribute more to population-level enhancements of visual information than changes in vRF size or gain. This finding suggests that position shifts are a principal mechanism by which spatial attention enhances population codes for relevant visual information. This poses challenges for labeled line theories of information processing, suggesting that downstream regions likely rely on distributed inputs rather than single neuron-to-neuron mappings.

Alterations in Hippocampal Network Activity after In Vitro Traumatic Brain Injury

Traumatic brain injury (TBI) alters function and behavior, which can be characterized by changes in electrophysiological function in vitro. A common cognitive deficit after mild-to-moderate TBI is disruption of persistent working memory, of which the in vitro correlate is long-lasting, neuronal network synchronization that can be induced pharmacologically by the gamma-aminobutyric acid A antagonist, bicuculline. We utilized a novel in vitro platform for TBI research, the stretchable microelectrode array (SMEA), to investigate the effects of TBI on bicuculline-induced, long-lasting network synchronization in the hippocampus. Mechanical stimulation significantly disrupted bicuculline-induced, long-lasting network synchronization 24 h after injury, despite the continued ability of the injured neurons to fire, as revealed by a significant increase in the normalized spontaneous event rate in the dentate gyrus (DG) and CA1. A second challenge with bicuculline 24 h after the first challenge significantly decreased the normalized spontaneous event rate in the DG. In addition, we illustrate the utility of the SMEA for TBI research by combining multiple experimental paradigms in one platform, which has the potential to enable novel investigations into the mechanisms responsible for functional consequences of TBI and speed the rate of drug discovery.

Using c-fos to study neuronal ensembles in corticostriatal circuitry of addiction

Learned associations between drugs and environment play an important role in addiction and are thought to be encoded within specific patterns of sparsely distributed neurons called neuronal ensembles. This hypothesis is supported by correlational data from in vivo electrophysiology and cellular imaging studies in relapse models in rodents. In particular, cellular imaging with the immediate early gene c-fos and its protein product Fos has been used to identify sparsely distributed neurons that were strongly activated during conditioned drug behaviors such as drug self-administration and context- and cue-induced reinstatement of drug seeking. Here we review how Fos and the c-fos promoter have been employed to demonstrate causal roles for Fos-expressing neuronal ensembles in prefrontal cortex and nucleus accumbens in conditioned drug behaviors. This work has allowed identification of unique molecular and electrophysiological alterations within Fos-expressing neuronal ensembles that may contribute to the development and expression of learned associations in addiction.

A wavelet-based neural model to optimize and read out a temporal population code

It has been proposed that the dense excitatory local connectivity of the neo-cortex plays a specific role in the transformation of spatial stimulus information into a temporal representation or a temporal population code (TPC). TPC provides for a rapid, robust, and high-capacity encoding of salient stimulus features with respect to position, rotation, and distortion. The TPC hypothesis gives a functional interpretation to a core feature of the cortical anatomy: its dense local and sparse long-range connectivity. Thus far, the question of how the TPC encoding can be decoded in downstream areas has not been addressed. Here, we present a neural circuit that decodes the spectral properties of the TPC using a biologically plausible implementation of a Haar transform. We perform a systematic investigation of our model in a recognition task using a standardized stimulus set. We consider alternative implementations using either regular spiking or bursting neurons and a range of spectral bands. Our results show that our wavelet readout circuit provides for the robust decoding of the TPC and further compresses the code without loosing speed or quality of decoding. We show that in the TPC signal the relevant stimulus information is present in the frequencies around 100 Hz. Our results show that the TPC is constructed around a small number of coding components that can be well decoded by wavelet coefficients in a neuronal implementation. The solution to the TPC decoding problem proposed here suggests that cortical processing streams might well consist of sequential operations where spatio-temporal transformations at lower levels forming a compact stimulus encoding using TPC that are subsequently decoded back to a spatial representation using wavelet transforms. In addition, the results presented here show that different properties of the stimulus might be transmitted to further processing stages using different frequency components that are captured by appropriately tuned wavelet-based decoders.

Monitoring hippocampus electrical activity in vitro on an elastically deformable microelectrode array

Interfacing electronics and recording electrophysiological activity in mechanically active biological tissues is challenging. This challenge extends to recording neural function of brain tissue in the setting of traumatic brain injury (TBI), which is caused by rapid (within hundreds of milliseconds) and large (greater than 5% strain) brain deformation. Interfacing electrodes must be biocompatible on multiple levels and should deform with the tissue to prevent additional mechanical damage. We describe an elastically stretchable microelectrode array (SMEA) that is capable of undergoing large, biaxial, 2-D stretch while remaining functional. The new SMEA consists of elastically stretchable thin metal films on a silicone membrane. It can stimulate and detect electrical activity from cultured brain tissue (hippocampal slices), before, during, and after large biaxial deformation. We have incorporated the SMEA into a well-characterized in vitro TBI research platform, which reproduces the biomechanics of TBI by stretching the SMEA and the adherent brain slice culture. Mechanical injury parameters, such as strain and strain rate, can be precisely controlled to generate specific levels of damage. The SMEA allowed for quantification of neuronal function both before and after injury, without breaking culture sterility or repositioning the electrodes for the injury event, thus enabling serial and long-term measurements. We report tests of the SMEA and an initial application to study the effect of mechanical stimuli on neuron function, which could be employed as a high-content, drug-screening platform for TBI.

Neural sensing of electrical activity with stretchable microelectrode arrays

Sensing neural activity within mechanically active tissues poses particular hurdles because most electrodes are much stiffer than biological tissues. As the tissue deforms, the rigid electrodes may damage the surrounding tissue. The problem is exacerbated when sensing neural activity in experimental models of traumatic brain injury (TBI) which is caused by the rapid and large deformation of brain tissue. We have developed a stretchable microelectrode array (SMEA) that can withstand large elastic deformations (>5% biaxial strain) while continuing to function. The SMEA were fabricated from thin metal conductors patterned on polydimethylsiloxane (PDMS) and encapsulated with a photo-patternable silicone. SMEA were used to record spontaneous activity from brain slice cultures, as well as evoked activity after stimulating through SMEA electrodes. Slices of brain tissue were grown on SMEA in long-term culture and then mechanically injured with our well-characterized in vitro injury model by stretching the SMEA and the adherent culture, which was confirmed by image analysis. Because brain tissue was grown on the substrate-integrated SMEA, post-injury changes in electrophysiological function were normalized to pre-injury function since the SMEA deformed with the tissue and remained in place during mechanical stimulation. The combination of our injury model and SMEA could help elucidate mechanisms responsible for post-traumatic neuronal dysfunction in the quest for TBI therapies. The SMEA may have additional sensing applications in other mechanically active tissues such as peripheral nerve and heart.

Neuronal nociceptive responses in thalamocortical pathways

The sensation of pain is critical for the survival of animals and humans. However, the brain mechanisms underlying pain perception remain largely unknown. How does the brain decode the pain-evoked activity into a particular sensory experience? Over the past decade, attempts have been made to answer these questions by employing electrophysiological, functional brain imaging, and behavioral approaches, and some basic properties of pain formation have been revealed. Researchers have gradually recognized that there exists a distributed neural network that participates in the transmission and processing of pain information. These studies will further guide the development of more effective treatment for many disorders such as chronic pain.

Principles of neural ensemble physiology underlying the operation of brain-machine interfaces

Research on brain-machine interfaces has been ongoing for at least a decade. During this period, simultaneous recordings of the extracellular electrical activity of hundreds of individual neurons have been used for direct, real-time control of various artificial devices. Brain-machine interfaces have also added greatly to our knowledge of the fundamental physiological principles governing the operation of large neural ensembles. Further understanding of these principles is likely to have a key role in the future development of neuroprosthetics for restoring mobility in severely paralysed patients.

Behavior-related neuron reactions and the dynamics of neuronal activity

The spike activity of neurons with associative functions, studied as a neural correlate of behavior, constitutes an efferent spike flow which operates continuously throughout each of an animal's actions. However, research practice is dominated by methods based on the "stimulus-response" principle. Analysis from other points of view, directed to investigating the dynamics of neuron activity in monkeys during performance of a multistep behavioral program showed that differences in neuron activity of neurons during performance of different behavioral actions are not so much in terms of the numbers of cells responding or the activation of neurons specialized for the action concerned as in terms of changes in the composition of active neurons, with the formation of different combinations. As each combination of active neurons determines the distribution of efferent signals characteristic of this combination, these data suggest the existence of an addressing mechanism encoding efferent signals.

Fos expression in the vestibular brainstem: what one marker can tell us about the network

Fos inducible transcription factor expression in rodent brains (rats and gerbils) during manipulations of vestibular input is reviewed. Stimuli included centripetal hypergravity, unilateral labyrinth lesion or semicircular canal plugging, rotational axis cross-coupling (Coriolis forces), high and low rotational vestibulo-ocular reflex gain adaptation, translabyrinth galvanic stimulation, pharmacological manipulation, and combinations thereof. Each type of stimulation elicited unique but partially redundant response patterns in the vestibulo-olivo-cerebellar (VOC) network that reflect the origin and interaction of the labyrinth inputs. On the basis of these patterns, a trained observer can predict what the animal experienced during testing; the patterns of VOC Fos expression reveal a trace of recent genomic activity. Based on principal component analysis, VOC network modules associated with lesion recovery, spatial representation and the calibration of gravity, and optokinetic influences are proposed. Probable and possible gene targets of the Fos protein are also reviewed.

Perceptual context-dependent remodeling of the forepaw map in the SI cortex of rats trained on tactile discrimination

We combined behavioral assessment of texture discrimination and electrophysiological mapping of concomitant reorganization in the forepaw representation within the SI cortex. Rats were housed in enriched (EE) or impoverished (IE) environments which have been shown to remodel the forepaw map and possibly alter discriminative abilities. In addition, animals were trained to discriminate homogeneous floorboards of invariant roughness from heterogeneous floorboards of gradually decreasing roughness contrasts during locomotion. As reported recently, differences in perceptual abilities were not related to housing conditions, but to a predilection for a floorboard type [Bourgeon S, Xerri C, Coq JO. Abilities in tactile discrimination of textures in adult rats exposed to enriched or impoverished environments. Behav Brain Res 2004;153:217-231]. Consistently, the present study shows that cortical map remodeling resulting from short-duration daily experience can prevail over changes induced by housing conditions. The relative area of glabrous skin representation was related to the discrimination performance and learning abilities in the rats (H) with a predilection for heterogeneous floorboards, i.e. in the animals performing discrimination in the most challenging perceptual context. By contrast, this cortical area was influenced by the duration of sensory experience in rats (h) with a predilection for homogeneous floorboards. Both EE condition and training to discrimination selectively decreased the sizes of the SI neurons' receptive fields (RFs) located on glabrous skin. Smaller RFs and larger cortical areas serving glabrous skin were correlated with better perceptual performances and learning abilities in the H rats only. The present study shows that representational reorganization related to tactile discrimination performances depends upon the perceptual context.

Sequential rearrangements of the ensemble activity of putamen neurons in the monkey brain as a correlate of continuous behavior

Simultaneous recordings were made of the spike activity of groups of 6-7 neurons in the putamen in two monkeys (Macaca nemestrina and Macaca mulatta) during performance of alternative spatial selection. Discriminant analysis was used to evaluate the magnitude of rearrangements in spike activity in groups of neurons during transitions from each step of the behavioral program to the next, along with the degree of differences in reactivity mosaics formed at each step in different versions of task execution. Rearrangements in spike activity were noted at all steps of the program. The dynamics of rearrangements on selection of the right and left feeders were different, leading to the appearance of significant differences in the reactivity mosaics at the decision-taking and reinforcement-receiving steps. The rearrangements preceding voluntary movement of one hand were more marked in the contralateral hemisphere. During performance of movements, the volume of rearrangements could increase, though differences in rearrangements accompanying movements of the right and left hands decreased. On receipt of reinforcement, rearrangements were greater when the animals selected a specified feeder (the left feeder) independently of which hemisphere was recorded.

Behavior-reactive neuron populations in the monkey neostriatum

Comparative analysis of neuron activity in the monkey putamen during multistep behavior showed that putamen neurons are active during all the animal's behavioral actions. The difference between the number of active neurons at a given step of the behavior as compared with the preceding step was found to be significantly smaller than the number of neurons reorganizing their activity at this step. Reorganization of neuron activity in the putamen is regarded as a reflection of the efferent code controlling the behavior, while the extent of reorganization is regarded as a measure of the change in this code in association with the organization of a sequential behavioral action. Changes in the numbers of active neurons at different stage of behavior and reorganization of their activity occurred independently of each other. This may be associated with the two afferent systems of the striatum: that ascending from the brainstem and the corticofugal, which carries differential information to the neural network of the striatum from various parts of the cortex.

Temperature perception and nociception

The specificity theory of somesthesis holds that perceptions of warmth, cold, and pain are served by separate senses. Although no longer accepted in all its details, the theory's basic assumptions of anatomical and functional specificity have remained guiding principles in research on temperature perception and its relationship to pain. This article reviews the response characteristics of thermoreceptors, temperature-sensitive nociceptors, and their associated pathways in the context of old and new perceptual phenomena, most of which cannot be satisfactorily explained by the specificity theory. The evidence indicates that throughout most of the perceptual range, temperature sensitivity depends upon coactivation of, and interactions among, thermal and nociceptive pathways that are composed of both specific "labeled lines" and nonspecific, multimodal fibers. Adding to this complexity is evidence that tactile stimulation can influence the way in which thermal stimulation is perceived. It is argued that thermoreception is best defined as a functional subsystem of somesthesis that serves the very different and sometimes conflicting demands of thermoregulation, protection from thermal injury, and haptic perception.

Cooperation between area 17 neuron pairs enhances fine discrimination of orientation

We examined 66 complex cells in area 17 of cats that were paralyzed and anesthetized with propofol and N2O. We studied changes in ensemble responses for small (<10 degrees ) and large (>10 degrees ) differences in orientation. Examination of temporal resolution and discharge history revealed advantages in discrimination from both dependent (e.g., synchronization) and independent (e.g., bursting) interspike interval properties. For 27 pairs of neurons, we found that the average cooperation (the advantage gained from the joint activity) was 57.6% for fine discrimination of orientation but <5% for gross discrimination. Dependency (probabilistic quantification of the interaction between the cells) was measured between 29 pairs of neurons while varying orientation. On average, the dependency tuning for orientation was 35.5% narrower than the average firing rate tuning. The changes in dependency around the peak orientation (at which the firing rate remains relatively constant) lead to substantial cooperation that can improve discrimination in this region. The narrow tuning of dependency and the cooperation provide evidence to support a population-encoding scheme that is based on biologically plausible mechanisms and that could account for hyperacuities.

Serotonin in the inferior colliculus

It has been recognized for some time that serotonin fibers originating in raphe nuclei are present in the inferior colliculi of all mammalian species studied. More recently, serotonin has been found to modulate the responses of single inferior colliculus neurons to many types of auditory stimuli, ranging from simple tone bursts to complex species-specific vocalizations. The effects of serotonin are often quite strong, and for some neurons are also highly specific. A dramatic illustration of this is that serotonin can change the selectivity of some neurons for sounds, including species-specific vocalizations. These results are discussed in light of several theories on the function of serotonin in the IC, and of outstanding issues that remain to be addressed.

Tactile discrimination of edge shape: limits on spatial resolution imposed by parameters of the peripheral neural population

When the flat faces of a coin are grasped between thumb and index finger, a "curved edge" is felt. Analogous curved edges were generated by our stimuli, which comprised the flat face of segments of annuli applied passively to immobilized fingers. Humans could scale the curvature of the annulus and could discriminate changes in curvature of approximately 20 m(-1). The responses of single slowly adapting type I afferents (SAIs) recorded in anesthetized monkeys could be quantified by the product of two factors: their sensitivity and a spatial profile dependent only on the radius of the annulus. This allowed us to reconstruct realistic SAI population responses that included noise, variation in fiber sensitivity, and varying innervation patterns. The critical question was how relatively small populations ( approximately 70 active fibers) can encode edge curvature with such precision. A template-matching approach was used to establish the accuracy of edge representation in the population. The known large interfiber variability in sensitivity had no effect on curvature resolution. Neural resolution was superior to human performance until large levels of central noise were present showing that, unlike simple detection, spatial processing is limited centrally. In contrast to the behavior of mean response codes, neural resolution improved with increasing covariance in noise. Surprisingly, resolution for any single population varied considerably with small changes in the position of the stimulus relative to the SAI matrix. Overall innervation density was not as critical as the spacing of receptive fields at right angles to the edge.

The evolution of neural coding ideas in the chemical senses

A brief review of the evolution of hypotheses about neural coding in the chemical senses provides some perspective on the current status of these fields, and implications for further development.