Encoding of tactile stimulus location by somatosensory thalamocortical ensembles

Tactile Location Perception Encoded by Gamma-Band Power

BACKGROUND

The perception of tactile-stimulation locations is an important function of the human somatosensory system during body movements and its interactions with the surroundings. Previous psychophysical and neurophysiological studies have focused on spatial location perception of the upper body. In this study, we recorded single-trial electroencephalography (EEG) responses evoked by four vibrotactile stimulators placed on the buttocks and thighs while the human subject was sitting in a chair with a cushion.

METHODS

Briefly, 14 human subjects were instructed to sit in a chair for a duration of 1 h or 1 h and 45 min. Two types of cushions were tested with each subject: a foam cushion and an air-cell-based cushion dedicated for wheelchair users to alleviate tissue stress. Vibrotactile stimulations were applied to the sitting interface at the beginning and end of the sitting period. Somatosensory-evoked potentials were obtained using a 32-channel EEG. An artificial neural net was used to predict the tactile locations based on the evoked EEG power.

RESULTS

We found that single-trial beta (13-30 Hz) and gamma (30-50 Hz) waves can best predict the tactor locations with an accuracy of up to 65%. Female subjects showed the highest performances, while males' sensitivity tended to degrade after the sitting period. A three-way ANOVA analysis indicated that the air-cell cushion maintained location sensitivity better than the foam cushion.

CONCLUSION

Our finding shows that tactile location information is encoded in EEG responses and provides insights on the fundamental mechanisms of the tactile system, as well as applications in brain-computer interfaces that rely on tactile stimulation.

Enhancing Prediction of Forelimb Movement Trajectory through a Calibrating-Feedback Paradigm Incorporating RAT Primary Motor and Agranular Cortical Ensemble Activity in the Goal-Directed Reaching Task

Complete reaching movements involve target sensing, motor planning, and arm movement execution, and this process requires the integration and communication of various brain regions. Previously, reaching movements have been decoded successfully from the motor cortex (M1) and applied to prosthetic control. However, most studies attempted to decode neural activities from a single brain region, resulting in reduced decoding accuracy during visually guided reaching motions. To enhance the decoding accuracy of visually guided forelimb reaching movements, we propose a parallel computing neural network using both M1 and medial agranular cortex (AGm) neural activities of rats to predict forelimb-reaching movements. The proposed network decodes M1 neural activities into the primary components of the forelimb movement and decodes AGm neural activities into internal feedforward information to calibrate the forelimb movement in a goal-reaching movement. We demonstrate that using AGm neural activity to calibrate M1 predicted forelimb movement can improve decoding performance significantly compared to neural decoders without calibration. We also show that the M1 and AGm neural activities contribute to controlling forelimb movement during goal-reaching movements, and we report an increase in the power of the local field potential (LFP) in beta and gamma bands over AGm in response to a change in the target distance, which may involve sensorimotor transformation and communication between the visual cortex and AGm when preparing for an upcoming reaching movement. The proposed parallel computing neural network with the internal feedback model improves prediction accuracy for goal-reaching movements.

Bayesian prediction of psychophysical detection responses from spike activity in the rat sensorimotor cortex

Decoding of sensorimotor information is essential for brain-computer interfaces (BCIs) as well as in normal functioning organisms. In this study, Bayesian models were developed for the prediction of binary decisions of 10 awake freely-moving male/female rats based on neural activity in a vibrotactile yes/no detection task. The vibrotactile stimuli were 40-Hz sinusoidal displacements (amplitude: 200 µm, duration: 0.5 s) applied on the glabrous skin. The task was to depress the right lever for stimulus detection and left lever for stimulus-off condition. Spike activity was recorded from 16-channel microwire arrays implanted in the hindlimb representation of primary somatosensory cortex (S1), overlapping also with the associated representation in the primary motor cortex (M1). Single-/multi-unit average spike rate (R_d) within the stimulus analysis window was used as the predictor of the stimulus state and the behavioral response at each trial based on a Bayesian network model. Due to high neural and psychophysical response variability for each rat and also across subjects, mean R_d was not correlated with hit and false alarm rates. Despite the fluctuations in the neural data, the Bayesian model for each rat generated moderately good accuracy (0.60-0.90) and good class prediction scores (recall, precision, F1) and was also tested with subsets of data (e.g. regular vs. fast spike groups). It was generally observed that the models were better for rats with lower psychophysical performance (lower sensitivity index A'). This suggests that Bayesian inference and similar machine learning techniques may be especially helpful during the training phase of BCIs or for rehabilitation with neuroprostheses.

Alpha Oscillations Are Involved in Localizing Touch on Handheld Tools

The sense of touch is not restricted to the body but can also extend to external objects. When we use a handheld tool to contact an object, we feel the touch on the tool and not in the hand holding the tool. The ability to perceive touch on a tool actually extends along its entire surface, allowing the user to accurately localize where it is touched similarly as they would on their body. Although the neural mechanisms underlying the ability to localize touch on the body have been largely investigated, those allowing to localize touch on a tool are still unknown. We aimed to fill this gap by recording the electroencephalography signal of participants while they localized tactile stimuli on a handheld rod. We focused on oscillatory activity in the alpha (7–14 Hz) and beta (15–30 Hz) ranges, as they have been previously linked to distinct spatial codes used to localize touch on the body. Beta activity reflects the mapping of touch in skin-based coordinates, whereas alpha activity reflects the mapping of touch in external space. We found that alpha activity was solely modulated by the location of tactile stimuli applied on a handheld rod. Source reconstruction suggested that this alpha power modulation was localized in a network of fronto-parietal regions previously implicated in higher-order tactile and spatial processing. These findings are the first to implicate alpha oscillations in tool-extended sensing and suggest an important role for processing touch in external space when localizing touch on a tool.

Region-specific elevations of glutamate + glutamine correlate with the sensory symptoms of autism spectrum disorders

Individuals on the autism spectrum are often reported as being hyper- and/or hyporeactive to sensory input. These sensory symptoms were one of the key observations that led to the development of the altered excitation-inhibition (E-I) model of autism, which posits that an increase ratio of excitatory to inhibitory signaling may explain certain phenotypical expressions of autism spectrum disorders (ASD). While there has been strong support for the altered E-I model of autism, much of the evidence has come from animal models. With regard to in-vivo human studies, evidence for altered E-I balance in ASD come from studies adopting magnetic resonance spectroscopy (MRS). Spectral-edited MRS can be used to provide measures of the levels of GABA + (GABA + macromolecules) and Glx (glutamate + glutamine) in specific brain regions as proxy markers of inhibition and excitation respectively. In the current study, we found region-specific elevations of Glx in the primary sensorimotor cortex (SM1) in ASD. There were no group differences of GABA+ in either the SM1 or thalamus. Higher levels of Glx were associated with more parent reported difficulties of sensory hyper- and hyporeactivity, as well as reduced feed-forward inhibition during tactile perception in children with ASD. Critically, the finding of elevated Glx provides strong empirical support for increased excitation in ASD. Our results also provide a clear link between Glx and the sensory symptoms of ASD at both behavioral and perceptual levels.

Spatial Information of Somatosensory Stimuli in the Brain: Multivariate Pattern Analysis of Functional Magnetic Resonance Imaging Data

Background

Multivoxel pattern analysis has provided new evidence on somatotopic representation in the human brain. However, the effects of stimulus modality (e.g., penetrating needle versus non-penetrating touch) and level of classification (e.g., multiclass versus binary classification) on patterns of brain activity encoding spatial information of body parts have not yet been studied. We hypothesized that performance of brain-based prediction models may vary across the types of stimuli, and neural patterns of voxels in the SI and parietal cortex would significantly contribute to the prediction of stimulated locations.

Objective

We aimed to (1) test whether brain responses to tactile stimuli could distinguish among stimulated locations on the body surface, (2) investigate whether the stimulus modality and number of classes affect classification performance, and (3) localize brain regions encoding the spatial information of somatosensory stimuli.

Methods

Fifteen healthy participants completed two functional magnetic resonance imaging (MRI) scans and were stimulated via the insertion of acupuncture needles or by non-invasive touch stimuli (5.46-sized von Frey filament). Participants received the stimuli at four different locations on the upper and lower limbs (two sites each) for 5 min while blood-oxygen-level-dependent activity (BOLD) was measured using 3-Tesla MRI. We performed multivariate pattern analysis (MVPA) using parameter estimate images of each trial for each participant and the support vector classifier (SVC) function, and the prediction accuracy and other MVPA outcomes were evaluated using stratified five-fold cross validation. We estimated the significance of the classification accuracy using a permutation test with randomly labeled training data (n = 10,000). Searchlight analysis was conducted to identify brain regions associated with significantly higher accuracy compared to predictions based on chance as obtained from a random classifier.

Results

For the four-class classification (classifying four stimulated points on the body), SVC analysis of whole-brain beta values in response to acupuncture stimulation was able to discriminate among stimulated locations (mean accuracy, 0.31; q < 0.01). The searchlight analysis found that values related to the right primary somatosensory cortex (SI) and intraparietal sulcus were significantly more accurate than those due to chance (p < 0.01). On the other hand, the same classifier did not predict stimulated locations accurately for touch stimulation (mean accuracy, 0.25; q = 0.66). For binary classification (discriminating between two stimulated body parts, i.e., the arm or leg), the SVC algorithm successfully predicted the stimulated body parts for both acupuncture (mean accuracy, 0.63; q < 0.001) and touch stimulation (mean accuracy, 0.60; q < 0.01). Searchlight analysis revealed that predictions based on the right SI, primary motor cortex (MI), paracentral gyrus, and superior frontal gyrus were significantly more accurate compared to predictions based on chance (p < 0.05).

Conclusion

Our findings suggest that the SI, as well as the MI, intraparietal sulcus, paracentral gyrus, and superior frontal gyrus, is responsible for the somatotopic representation of body parts stimulated by tactile stimuli. The MVPA approach for identifying neural patterns encoding spatial information of somatosensory stimuli may be affected by the stimulus type (penetrating needle versus non-invasive touch) and the number of classes (classification of four small points on the body versus two large body parts). Future studies with larger samples will identify stimulus-specific neural patterns representing stimulated locations, independent of subjective tactile perception and emotional responses. Identification of distinct neural patterns of body surfaces will help in improving neural biomarkers for pain and other sensory percepts in the future.

Hidden Markov Models Predict the Future Choice Better Than a PSTH-Based Method

Beyond average firing rate, other measurable signals of neuronal activity are fundamental to an understanding of behavior. Recently, hidden Markov models (HMMs) have been applied to neural recordings and have described how neuronal ensembles process information by going through sequences of different states. Such collective dynamics are impossible to capture by just looking at the average firing rate. To estimate how well HMMs can decode information contained in single trials, we compared HMMs with a recently developed classification method based on the peristimulus time histogram (PSTH). The accuracy of the two methods was tested by using the activity of prefrontal neurons recorded while two monkeys were engaged in a strategy task. In this task, the monkeys had to select one of three spatial targets based on an instruction cue and on their previous choice. We show that by using the single trial's neural activity in a period preceding action execution, both models were able to classify the monkeys' choice with an accuracy higher than by chance. Moreover, the HMM was significantly more accurate than the PSTH-based method, even in cases in which the HMM performance was low, although always above chance. Furthermore, the accuracy of both methods was related to the number of neurons exhibiting spatial selectivity within an experimental session. Overall, our study shows that neural activity is better described when not only the mean activity of individual neurons is considered and that therefore, the study of other signals rather than only the average firing rate is fundamental to an understanding of the dynamics of neuronal ensembles.

Assessing the Impact of Single-Cell Stimulation on Local Networks in Rat Barrel Cortex-A Feasibility Study

In contrast to the long-standing notion that the role of individual neurons in population activity is vanishingly small, recent studies have shown that electrical activation of only a single cortical neuron can have measurable effects on global brain state, movement, and perception. Although highly important for understanding how neuronal activity in cortex is orchestrated, the cellular and network mechanisms underlying this phenomenon are unresolved. Here, we first briefly review the current state of knowledge regarding the phenomenon of single-cell induced network modulation and discuss possible underpinnings. Secondly, we show proof of principle for an experimental approach to elucidate the mechanisms of single-cell induced changes in cortical activity. The setup allows simultaneous recordings of the spiking activity of multiple neurons across all layers of the cortex using a multi-electrode array, while manipulating the activity of one individual neuron in close proximity to the array. We demonstrate that single cells can be recorded and stimulated reliably for hundreds of trials, conferring high statistical power even for expectedly small effects of single-neuron spiking on network activity. Preliminary results suggest that single-cell stimulation on average decreases the firing rate of local network units. We expect that characterization of the spatiotemporal spread of single-cell evoked activity across layers and columns will yield novel insights into intracortical processing.

Biases in tactile localization by pointing: compression for weak stimuli and centering for distributions of stimuli

Weak electrocutaneous stimuli applied to the forearm are erroneously localized toward its middle (Steenbergen P, Buitenweg JR, Trojan J, Veltink PH. Exp Brain Res 232: 597-607, 2014). We asked whether mechanical touch stimuli exhibit a similar bias and whether the bias is toward the middle of the forearm or toward the middle of the recent stimulus distribution. In experiments 1 and 2, participants ( n = 12 and n = 10) localized by pointing von Frey filaments applied to four locations on the dorsal forearm. Individually adjusted weak and strong stimuli ( experiment 1) or two levels of strong stimuli ( experiment 2) were presented in single sessions in random order. Weaker stimuli were localized with greater variability than the strong, with compression toward the middle of the forearm. Responses to the two levels of strong stimuli did not differ. In experiment 3, participants ( n = 16) were presented two spatially offset stimulus distributions (8 cm center-to-center), each offset from the forearm middle, on 2 different days. Out of four target locations comprising each distribution, two were shared. Responses to weak stimuli were compressed compared with responses to strong stimuli. Importantly, biases for the common targets had opposite directions, each being toward the middle of the distribution within which targets were presented. Responses to strong stimuli also exhibited a distribution-dependent bias, a 2-cm overall shift across the forearm midpoint. We conclude that touch localization is subject to intensity-dependent biases determined by the recent history of stimulation and possibly also by the available or perceived response space. NEW & NOTEWORTHY Recent findings show that weak electrical stimuli applied to the forearm are mislocalized toward the forearm middle, relative to strong stimuli. We found that weak mechanical stimuli are similarly mislocalized. The bias changed if, as a group, stimuli were not centered on the forearm middle: weak stimuli gravitated toward the center of prior stimulation. Localization of strong stimuli was also biased, consistent with the tendency to center responses within the available response space.

Effects of thalamic hemorrhagic lesions on explicit and implicit learning during the acquisition and retrieval phases in an animal model of central post-stroke pain

Hemorrhagic stroke has many symptoms, including central pain, learning and memory impairments, motor deficits, language problems, emotional disturbances, and social maladjustment. Lesions of the ventral basal complex (VBC) of the thalamus elicit thermal and mechanical hyperalgesia, forming an animal model of central post-stroke pain (CPSP). However, no research has yet examined the involvement of learning and memory in CPSP using an animal model. The present study examined whether VBC lesions affect motor function, conditioned place preference (CPP; implicit memory), and spatial learning (explicit memory) in the acquisition and retrieval phases. The results showed that rats with VBC lesions exhibited thermal hyperalgesia in the acquisition and retrieval phases, indicating that these lesions can induce CPSP. During these phases, the rats with VBC lesions exhibited enhanced (morphine-induced) CPP learning. These lesions did not affect the rats' total distance travelled, time spent, or velocity in the spatial learning tasks. The lesions also did not affect motor function in the rotarod task. Altogether, VBC lesions resulted in CPSP and facilitated CPP (implicit memory). However, the lesions did not affect spatial learning (explicit memory) or motor function. The relationship between CPSP and learning and memory is important for patients who suffer from such central pain. The implications of the present study may provide insights into helping reduce CPSP and its associated symptoms.

Chronic recordings reveal tactile stimuli can suppress spontaneous activity of neurons in somatosensory cortex of awake and anesthetized primates

In somatosensory cortex, tactile stimulation within the neuronal receptive field (RF) typically evokes a transient excitatory response with or without postexcitatory inhibition. Here, we describe neuronal responses in which stimulation on the hand is followed by suppression of the ongoing discharge. With the use of 16-channel microelectrode arrays implanted in the hand representation of primary somatosensory cortex of New World monkeys and prosimian galagos, we recorded neuronal responses from single units and neuron clusters. In 66% of our sample, neuron activity tended to display suppression of firing when regions of skin outside of the excitatory RF were stimulated. In a small proportion of neurons, single-site indentations suppressed firing without initial increases in response to any of the tested sites on the hand. Latencies of suppressive responses to skin indentation (usually 12-34 ms) were similar to excitatory response latencies. The duration of inhibition varied across neurons. Although most observations were from anesthetized animals, we also found similar neuron response properties in one awake galago. Notably, suppression of ongoing neuronal activity did not require conditioning stimuli or multi-site stimulation. The suppressive effects were generally seen following single-site skin indentations outside of the neuron's minimal RF and typically on different digits and palm pads, which have not often been studied in this context. Overall, the characteristics of widespread suppressive or inhibitory response properties with and without initial facilitative or excitatory responses add to the growing evidence that neurons in primary somatosensory cortex provide essential processing for integrating sensory stimulation from across the hand.

High Stimulus-Related Information in Barrel Cortex Inhibitory Interneurons

The manner in which populations of inhibitory (INH) and excitatory (EXC) neocortical neurons collectively encode stimulus-related information is a fundamental, yet still unresolved question. Here we address this question by simultaneously recording with large-scale multi-electrode arrays (of up to 128 channels) the activity of cell ensembles (of up to 74 neurons) distributed along all layers of 3–4 neighboring cortical columns in the anesthetized adult rat somatosensory barrel cortex in vivo. Using two different whisker stimulus modalities (location and frequency) we show that individual INH neurons – classified as such according to their distinct extracellular spike waveforms – discriminate better between restricted sets of stimuli (≤6 stimulus classes) than EXC neurons in granular and infra-granular layers. We also demonstrate that ensembles of INH cells jointly provide as much information about such stimuli as comparable ensembles containing the ~20% most informative EXC neurons, however presenting less information redundancy – a result which was consistent when applying both theoretical information measurements and linear discriminant analysis classifiers. These results suggest that a consortium of INH neurons dominates the information conveyed to the neocortical network, thereby efficiently processing incoming sensory activity. This conclusion extends our view on the role of the inhibitory system to orchestrate cortical activity.

Perception of the environment relies on neuronal computation in the cerebral cortex. However, the exact algorithms by which cortical neuronal networks process relevant information from the inputs of sensory organs are only poorly understood. To address this problem we stimulated distinct whiskers and recorded the neuronal responses from identified cortical whisker representations of the rat using multi-site electrodes. For rodents the whisker system is one main sensory input channel, offering the unique property that for each whisker an identified cortical area ("barrel-related column") represents its main cortical input station. In the present study we were able to demonstrate that the action potential firing of single inhibitory neurons provides more information about behaviorally relevant qualities of whisker stimulation (identity of the stimulated whisker and frequency of stimulation) than excitatory neurons. In addition, information about stimulation qualities was encoded with less redundancy in inhibitory neurons. In summary, the results of our study suggest that inhibitory neurons carry substantial information about the sensory environment and can thereby adequately orchestrate neuronal activity in sensory cortices.

Detection of optogenetic stimulation in somatosensory cortex by non-human primates--towards artificial tactile sensation

Neuroprosthesis research aims to enable communication between the brain and external assistive devices while restoring lost functionality such as occurs from stroke, spinal cord injury or neurodegenerative diseases. In future closed-loop sensorimotor prostheses, one approach is to use neuromodulation as direct stimulus to the brain to compensate for a lost sensory function and help the brain to integrate relevant information for commanding external devices via, e.g. movement intention. Current neuromodulation techniques rely mainly of electrical stimulation. Here we focus specifically on the question of eliciting a biomimetically relevant sense of touch by direct stimulus of the somatosensory cortex by introducing optogenetic techniques as an alternative to electrical stimulation. We demonstrate that light activated opsins can be introduced to target neurons in the somatosensory cortex of non-human primates and be optically activated to create a reliably detected sensation which the animal learns to interpret as a tactile sensation localized within the hand. The accomplishment highlighted here shows how optical stimulation of a relatively small group of mostly excitatory somatosensory neurons in the nonhuman primate brain is sufficient for eliciting a useful sensation from data acquired by simultaneous electrophysiology and from behavioral metrics. In this first report to date on optically neuromodulated behavior in the somatosensory cortex of nonhuman primates we do not yet dissect the details of the sensation the animals exerience or contrast it to those evoked by electrical stimulation, issues of considerable future interest.

Spike count, spike timing and temporal information in the cortex of awake, freely moving rats

OBJECTIVE

Sensory processing of peripheral information is not stationary but is, in general, a dynamic process related to the behavioral state of the animal. Yet the link between the state of the behavior and the encoding properties of neurons is unclear. This report investigates the impact of the behavioral state on the encoding mechanisms used by cortical neurons for both detection and discrimination of somatosensory stimuli in awake, freely moving, rats.

APPROACH

Neuronal activity was recorded from the primary somatosensory cortex of five rats under two different behavioral states (quiet versus whisking) while electrical stimulation of increasing stimulus strength was delivered to the mystacial pad. Information theoretical measures were then used to measure the contribution of different encoding mechanisms to the information carried by neurons in response to the whisker stimulation.

MAIN RESULTS

We found that the behavioral state of the animal modulated the total amount of information conveyed by neurons and that the timing of individual spikes increased the information compared to the total count of spikes alone. However, the temporal information, i.e. information exclusively related to when the spikes occur, was not modulated by behavioral state.

SIGNIFICANCE

We conclude that information about somatosensory stimuli is modulated by the behavior of the animal and this modulation is mainly expressed in the spike count while the temporal information is more robust to changes in behavioral state.

A brain-to-brain interface for real-time sharing of sensorimotor information

A brain-to-brain interface (BTBI) enabled a real-time transfer of behaviorally meaningful sensorimotor information between the brains of two rats. In this BTBI, an “encoder” rat performed sensorimotor tasks that required it to select from two choices of tactile or visual stimuli. While the encoder rat performed the task, samples of its cortical activity were transmitted to matching cortical areas of a “decoder” rat using intracortical microstimulation (ICMS). The decoder rat learned to make similar behavioral selections, guided solely by the information provided by the encoder rat's brain. These results demonstrated that a complex system was formed by coupling the animals' brains, suggesting that BTBIs can enable dyads or networks of animal's brains to exchange, process, and store information and, hence, serve as the basis for studies of novel types of social interaction and for biological computing devices.

Trial-to-trial variability in the responses of neurons carries information about stimulus location in the rat whisker thalamus

From the perspective of neural coding, the considerable trial-to-trial variability in the responses of neurons to sensory stimuli is puzzling. Trial-to-trial response variability is typically interpreted in terms of "noise" (i.e., it represents either intrinsic noise of the system or information unrelated to the stimuli). However, trial-to-trial response variability can be considerably different across stimuli, suggesting that it could also provide an important contribution to the information conveyed by the neural responses about the stimuli. To test this hypothesis, we addressed the problem of discriminating stimulus location from the spike-count responses of neurons recorded in the ventro-postero-medial (VPM) nucleus of the thalamus in anesthetized rats. Using a recently developed information theory approach, we verified that differences between stimuli in the trial-to-trial spike-count variability of the responses provided an important contribution to the overall information carried by the neurons. In addition, we found that the relatively reliable (sub-Poisson) firing regime of our VPM neurons was not only more informative, but also more redundant between neurons compared with a more variable (Poisson) firing regime with the same total number of spikes. The typical increase in trial-to-trial response variability from the periphery to the cortex could therefore serve as a strategy to reduce redundancy between neurons and promote efficient sparse coding distributed in large populations of neurons. Overall, our data suggest that the trial-to-trial response variability plays a critical role in establishing the trade-off between total information and redundancy between neurons in population codes.

An ensemble analysis of electromyographic activity during whole body pointing with the use of support vector machines

We explored the use of support vector machines (SVM) in order to analyze the ensemble activities of 24 postural and focal muscles recorded during a whole body pointing task. Because of the large number of variables involved in motor control studies, such multivariate methods have much to offer over the standard univariate techniques that are currently employed in the field to detect modifications. The SVM was used to uncover the principle differences underlying several variations of the task. Five variants of the task were used. An unconstrained reaching, two constrained at the focal level and two at the postural level. Using the electromyographic (EMG) data, the SVM proved capable of distinguishing all the unconstrained from the constrained conditions with a success of approximately 80% or above. In all cases, including those with focal constraints, the collective postural muscle EMGs were as good as or better than those from focal muscles for discriminating between conditions. This was unexpected especially in the case with focal constraints. In trying to rank the importance of particular features of the postural EMGs we found the maximum amplitude rather than the moment at which it occurred to be more discriminative. A classification using the muscles one at a time permitted us to identify some of the postural muscles that are significantly altered between conditions. In this case, the use of a multivariate method also permitted the use of the entire muscle EMG waveform rather than the difficult process of defining and extracting any particular variable. The best accuracy was obtained from muscles of the leg rather than from the trunk. By identifying the features that are important in discrimination, the use of the SVM permitted us to identify some of the features that are adapted when constraints are placed on a complex motor task.

The balance between excitation and inhibition and functional sensory processing in the somatosensory cortex

The balance between excitation and inhibition (E/I balance) is tightly regulated in adult cortices to maintain proper nervous system function. Disturbed E/I balance is associated with numerous neuropsychological disorders, such as autism, epilepsy and schizophrenia. The present review will discuss aspects of Hebbian and homeostatic mechanisms regulating excitatory and inhibitory balance related to sensory processing in somatosensory cortex of rodents. Additionally, changes in the E/I balance during sensory manipulation will be discussed.

The Matrix: a new tool for probing the whisker-to-barrel system with natural stimuli

The whisker to barrel system in rodents has become one of the major models for the study of sensory processing. Several tens of whiskers (or vibrissae) are distributed in a regular manner on both sides of the snout. Many tactile discrimination tasks using this system need multiple contacts with more than one whisker to be solved. With the aim of mimicking those multi-whisker stimuli during electrophysiological recordings, we developed a novel mechanical stimulator composed of 24 independent multi-directional piezoelectric benders adapted to the five rows and the five caudal arcs of the rat whisker pad. The most widely used technology for producing mechanical deflections of the whiskers is based on piezoelectric benders that display a non-linear behavior when driven with high frequency input commands and, if not compensated, show high unwanted ringing at particular resonance frequencies. If not corrected, this non-linear behavior precludes the application of high frequency deflections and the study of cortical responses to behaviorally relevant stimuli. To cope with the ringing problem, a mechanical and a software based solutions have been developed. With these corrections, the upper bound of the linear range of the bender is increased to 1 kHz. This new device allows the controlled delivery of large scale natural patterns of whisker deflections characterized by rapid high frequency vibrations of multiple whiskers.

Cutaneous afferents from the monkeys fingers: responses to tangential and normal forces

Control of tangential force plays a key role in everyday manipulations. In anesthetized monkeys, forces tangential to the skin were applied at a range of magnitudes comparable to those used in routine manipulations and in eight different directions. The paradigm used enabled separation of responses to tangential force from responses to the background normal force. For slowly adapting type I (SAI) afferents, tangential force responses ranged from excitatory through no response to suppression, with both a static and dynamic component. For fast adapting type I (FAI) afferents, responses were dynamic and excitatory only. Responses of both afferent types were scaled by tangential force magnitude, elucidating the neural basis for previous human psychophysical scaling data. Most afferents were direction selective with a range of preferred directions and a range in sharpness of tuning. Both the preferred direction and the degree of tuning were independent of the background normal force. Preferred directions were distributed uniformly over 360 degrees for SAI afferents, but for FAI afferents they were biased toward the proximo-ulnar direction. Afferents from all over the glabrous skin of the distal segment of the finger responded; there was no evident relationship between the position of an afferent's receptive field on the finger and its preferred direction or its degree of tuning. Nor were preferred directions biased either toward or away from the receptive field center. In response to the relatively large normal forces, some afferents saturated and others did not, regardless of the positions of their receptive fields. Total afferent response matched human psychophysical scaling functions for normal force.

Coadaptive brain-machine interface via reinforcement learning

This paper introduces and demonstrates a novel brain-machine interface (BMI) architecture based on the concepts of reinforcement learning (RL), coadaptation, and shaping. RL allows the BMI control algorithm to learn to complete tasks from interactions with the environment, rather than an explicit training signal. Coadaption enables continuous, synergistic adaptation between the BMI control algorithm and BMI user working in changing environments. Shaping is designed to reduce the learning curve for BMI users attempting to control a prosthetic. Here, we present the theory and in vivo experimental paradigm to illustrate how this BMI learns to complete a reaching task using a prosthetic arm in a 3-D workspace based on the user's neuronal activity. This semisupervised learning framework does not require user movements. We quantify BMI performance in closed-loop brain control over six to ten days for three rats as a function of increasing task difficulty. All three subjects coadapted with their BMI control algorithms to control the prosthetic significantly above chance at each level of difficulty.

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.

Mutual information expansion for studying the role of correlations in population codes: how important are autocorrelations?

The role of correlations in the activity of neural populations responding to a set of stimuli can be studied within an information theory framework. Regardless of whether one approaches the problem from an encoding or decoding perspective, the main measures used to study the role of correlations can be derived from a common source: the expansion of the mutual information. Two main formalisms of mutual information expansion have been proposed: the series expansion and the exact breakdown. Here we clarify that these two formalisms have a different representation of autocorrelations, so that even when the total information estimated differs by less than 1%, individual terms can diverge. More precisely, the series expansion explicitly evaluates the informational contribution of autocorrelations in the count of spikes, that is, count autocorrelations, whereas the exact breakdown does not. We propose a new formalism of mutual information expansion, the Poisson exact breakdown, which introduces Poisson equivalents in order to explicitly evaluate the informational contribution of count autocorrelations with no approximation involved. Because several widely employed manipulations of spike trains, most notably binning and pooling, alter the structure of count autocorrelations, the new formalism can provide a useful general framework for studying the role of correlations in population codes.

NeuroMEMS: Neural Probe Microtechnologies

Neural probe technologies have already had a significant positive effect on our understanding of the brain by revealing the functioning of networks of biological neurons. Probes are implanted in different areas of the brain to record and/or stimulate specific sites in the brain. Neural probes are currently used in many clinical settings for diagnosis of brain diseases such as seizers, epilepsy, migraine, Alzheimer's, and dementia. We find these devices assisting paralyzed patients by allowing them to operate computers or robots using their neural activity. In recent years, probe technologies were assisted by rapid advancements in microfabrication and microelectronic technologies and thus are enabling highly functional and robust neural probes which are opening new and exciting avenues in neural sciences and brain machine interfaces. With a wide variety of probes that have been designed, fabricated, and tested to date, this review aims to provide an overview of the advances and recent progress in the microfabrication techniques of neural probes. In addition, we aim to highlight the challenges faced in developing and implementing ultra-long multi-site recording probes that are needed to monitor neural activity from deeper regions in the brain. Finally, we review techniques that can improve the biocompatibility of the neural probes to minimize the immune response and encourage neural growth around the electrodes for long term implantation studies.

Computational role of large receptive fields in the primary somatosensory cortex

Computational studies are challenging the intuitive view that neurons with broad tuning curves are necessarily less discriminative than neurons with sharp tuning curves. In the context of somatosensory processing, broad tuning curves are equivalent to large receptive fields. To clarify the computational role of large receptive fields for cortical processing of somatosensory information, we recorded ensembles of single neurons from the infragranular forelimb/forepaw region of the rat primary somatosensory cortex while tactile stimuli were separately delivered to different locations on the forelimbs/forepaws under light anesthesia. We specifically adopted the perspective of individual columns/segregates receiving inputs from multiple body location. Using single-trial analyses of many single-neuron responses, we obtained two main results. 1) The responses of even small populations of neurons recorded from within the same estimated column/segregate can be used to discriminate between stimuli delivered to different surround locations in the excitatory receptive fields. 2) The temporal precision of surround responses is sufficiently high for spike timing to add information over spike count in the discrimination between surround locations. This surround spike-timing code (i) is particularly informative when spike count is ambiguous, e.g., in the discrimination between close locations or when receptive fields are large, (ii) becomes progressively more informative as the number of neurons increases, (iii) is a first-spike code, and (iv) is not limited by the assumption that the time of stimulus onset is known. These results suggest that even though large receptive fields result in a loss of spatial selectivity of single neurons, they can provide as a counterpart a sophisticated temporal code based on latency differences in large populations of neurons without necessarily sacrificing basic information about stimulus location.

Tactile responses of hindpaw, forepaw and whisker neurons in the thalamic ventrobasal complex of anesthetized rats

The majority of studies investigating responses of thalamocortical neurons to tactile stimuli have focused on the whisker representation of the rat thalamus: the ventral–posterior–medial nucleus (VPM). To test whether the basic properties of thalamocortical responses to tactile stimuli could be extended to the entire ventrobasal complex, we recorded single neurons from the whisker, forepaw and hindpaw thalamic representations. We performed a systematic analysis of responses to stereotyped tactile stimuli − 500 ms pulses (i.e. ON–OFF stimuli) or 1 ms pulses (i.e. impulsive stimuli) − under two different anesthetics (pentobarbital or urethane). We obtained the following main results: (i) the tuning of cells to ON vs. OFF stimuli displayed a gradient across neurons, so that two-thirds of cells responded more to ON stimuli and one-third responded more to OFF stimuli; (ii) on average, response magnitudes did not differ between ON and OFF stimuli, whereas latencies of response to OFF stimuli were a few milliseconds longer; (iii) latencies of response to ON and OFF stimuli were highly correlated; (iv) responses to impulsive stimuli and ON stimuli showed a strong correlation, whereas the relationship between the responses to impulsive stimuli and OFF stimuli was subtler; (v) unlike ON responses, OFF responses did not decrease when stimuli were moved from the receptive field center to a close location in the excitatory surround. We obtained the same results for hindpaw, forepaw and whisker neurons. Our results support the view of a neurophysiologically homogeneous ventrobasal complex, in which OFF responses participate in the structure of the spatiotemporal receptive field of thalamocortical neurons for tactile stimuli.

Using hardware models to quantify sensory data acquisition across the rat vibrissal array

Our laboratory investigates how animals acquire sensory data to understand the neural computations that permit complex sensorimotor behaviors. We use the rat whisker system as a model to study active tactile sensing; our aim is to quantitatively describe the spatiotemporal structure of incoming sensory information to place constraints on subsequent neural encoding and processing. In the first part of this paper we describe the steps in the development of a hardware model (a 'sensobot') of the rat whisker array that can perform object feature extraction. We show how this model provides insights into the neurophysiology and behavior of the real animal. In the second part of this paper, we suggest that sensory data acquisition across the whisker array can be quantified using the complete derivative. We use the example of wall-following behavior to illustrate that computing the appropriate spatial gradients across a sensor array would enable an animal or mobile robot to predict the sensory data that will be acquired at the next time step.

Processing of tactile information by the hippocampus

The ability to detect unusual events occurring in the environment is essential for survival. Several studies have pointed to the hippocampus as a key brain structure in novelty detection, a claim substantiated by its wide access to sensory information through the entorhinal cortex and also distinct aspects of its intrinsic circuitry. Novelty detection is implemented by an associative match-mismatch algorithm involving the CA1 and CA3 hippocampal subfields that compares the stream of sensory inputs received by CA1 to the stored representation of spatiotemporal sequences in CA3. In some rodents, including the rat, the highly sensitive facial whiskers are responsible for providing accurate tactile information about nearby objects. Surprisingly, however, not much is known about how inputs from the whiskers reach CA1 and how they are processed therein. Using concurrent multielectrode neuronal recordings and chemical inactivation in behaving rats, we show that trigeminal inputs from the whiskers reach the CA1 region through thalamic and cortical relays associated with discriminative touch. Ensembles of hippocampal neurons also carry precise information about stimulus identity when recorded during performance in an aperture-discrimination task using the whiskers. We also found broad similarities between tactile responses of trigeminal stations and the hippocampus during different vigilance states (wake and sleep). Taken together, our results show that tactile information associated with fine whisker discrimination is readily available to the hippocampus for dynamic updating of spatial maps.

Heterogeneity in the coding in rat barrel cortex of the velocity of protraction of the macrovibrissae

Rats whisk to explore their environment and obtain information on object features, and the responses of somatosensory cortical neurones must precisely encode aspects of whisker movements. Using trapezoidal stimuli to deflect whiskers, with a wide range of velocities and amplitudes of whisker protraction, we recorded responses from a relatively homogeneous population of isolated cells and neuronal multiunits within the postero-medial barrel sub-field of somatosensory cortex, and analysed responses in an early post-stimulus-onset window. For 92% of neurones the function relating response strength to velocity was a saturating sigmoid but there were differences between neurones in the slopes and ranges over which responses changed. Responses of other neurones were non-monotonic, with response strength decaying at very high whisker deflection velocities. Generally, barrel cortex neurones were responsive to a much wider range of whisker protraction velocities than hitherto reported, especially to much slower velocities than generally assumed to be the main range of sensitivity. This carries implications for coding of whisker deflection velocity, a parameter that appears to be a significant information-bearing element of natural whisking. The effect of amplitude of deflection upon neural responses was evident in only approximately 24% of units and only when the dominant velocity effect had saturated.

Corticofugal influences on thalamic neurons during nociceptive transmission in awake rats

Pain is a multidimensional phenomenon and processed in a neural network. The supraspinal, brain mechanisms are increasingly recognized in playing a major role in the representation and modulation of pain. The aim of the current study is to investigate the functional interactions between cortex and thalamus during nociceptive processing, by observing the pain-related information flow and neuronal correlations within thalamo-cortical pathways. Pain-evoked, single-neuron activity was recorded in awake Sprague-Dawley rats with a Magnet system. Eight-wire microarrays were implanted into four different brain regions, i.e., the primary somatosensory (SI) and anterior cingulate cortex (ACC), as well as ventral posterior (VP) and medial dorsal thalamus (MD). Noxious radiant heat was delivered to the rat hind paws on the side contralateral to the recording regions. A large number of responsive neurons were recorded in the four brain areas. Directed coherence analysis revealed that the amount of information flow was significantly increased from SI cortex to VP thalamus following noxious stimuli, suggesting that SI cortex has descending influence on thalamic neurons during pain processing. Moreover, more correlated neuronal activities indicated by crosscorrelation histograms were found between cortical and thalamic neurons, with cortical neurons firing ahead of thalamic units. On basis of the above findings, we propose that nociceptive responses are modulated by corticothalamic feedback during nociceptive transmission, which may be tight in the lateral pathway, while loose in the medial pathway.

Subspace projection approaches to classification and visualization of neural network-level encoding patterns

Recent advances in large-scale ensemble recordings allow monitoring of activity patterns of several hundreds of neurons in freely behaving animals. The emergence of such high-dimensional datasets poses challenges for the identification and analysis of dynamical network patterns. While several types of multivariate statistical methods have been used for integrating responses from multiple neurons, their effectiveness in pattern classification and predictive power has not been compared in a direct and systematic manner. Here we systematically employed a series of projection methods, such as Multiple Discriminant Analysis (MDA), Principal Components Analysis (PCA) and Artificial Neural Networks (ANN), and compared them with non-projection multivariate statistical methods such as Multivariate Gaussian Distributions (MGD). Our analyses of hippocampal data recorded during episodic memory events and cortical data simulated during face perception or arm movements illustrate how low-dimensional encoding subspaces can reveal the existence of network-level ensemble representations. We show how the use of regularization methods can prevent these statistical methods from over-fitting of training data sets when the trial numbers are much smaller than the number of recorded units. Moreover, we investigated the extent to which the computations implemented by the projection methods reflect the underlying hierarchical properties of the neural populations. Based on their ability to extract the essential features for pattern classification, we conclude that the typical performance ranking of these methods on under-sampled neural data of large dimension is MDA>PCA>ANN>MGD.

Developmental synaptic plasticity at the thalamocortical input to barrel cortex: mechanisms and roles

The thalamocortical (TC) input to layer IV provides the major pathway for ascending sensory information to the mammalian sensory cortex. During development there is a dramatic refinement of this input that underlies the maturation of the topographical map in layer IV. Over the last 10 years our understanding of the mechanisms of the developmental and experience-driven changes in synaptic function at TC synapses has been greatly advanced. Here we describe these studies that point to a key role for NMDA receptor-dependent synaptic plasticity, a role for kainate receptors and for a rapid maturation in GABAergic inhibition. The expression mechanisms of some of the forms of neonatal synaptic plasticity are novel and, in combination with other mechanisms, produce a layer IV circuit that exhibits functional properties necessary for mature sensory processing.

Responses of Trigeminal Ganglion Neurons during Natural Whisking Behaviors in the Awake Rat

Rats use their whiskers to locate and discriminate tactile features of their environment. Mechanoreceptors surrounding each whisker encode and transmit sensory information from the environment to the brain via afferents whose cell bodies lie in the trigeminal ganglion (Vg). These afferents are classified as rapidly (RA) or slowly (SA) adapting by their response to stimulation. The activity of these cells in the awake behaving rat is yet unknown. Therefore, we developed a method to chronically record Vg neurons during natural whisking behaviors and found that all cells exhibited (1) no neuronal activity when the whiskers were not in motion, (2) increased activity when the rat whisked, with activity correlated to whisk frequency, and (3) robust increases in activity when the whiskers contacted an object. Moreover, we observed distinct differences in the firing rates between RA and SA cells, suggesting that they encode distinct aspects of stimuli in the awake rat.

A novel stimulus system for applying tactile stimuli to the macrovibrissae in electrophysiological experiments

The rat's vibrissae are a wonderful system for the study of sensory neural encoding in relation to behaviour because the vibrissae are easily identifiable and accessible for manipulation, allowing easy application of a variety of different types of deflections that mimic natural whisking. Here we report the development of a powerful and flexible method for precisely deflecting these vibrissae. Recordings from CNS neurons showed, in response to variations in the parameters of a trapezoid whisker deflection stimulus that mimics the basic unit of whisking, a variety of complex responses as well as complex interactions between different response components. The recordings also included a response that is reported to be found during active whisking (movement under muscle control) and not passive whisker movements and thus to differentiate active from passive whisker deflections. Thus, this system could well be used in anaesthetized animals to apply whisker deflections that well mimic natural active whisking in awake animals, thereby allowing highly detailed study of the neuronal responses and neuronal interactions found with natural whisking behaviour.

Brain–machine interfaces: past, present and future

Since the original demonstration that electrical activity generated by ensembles of cortical neurons can be employed directly to control a robotic manipulator, research on brain-machine interfaces (BMIs) has experienced an impressive growth. Today BMIs designed for both experimental and clinical studies can translate raw neuronal signals into motor commands that reproduce arm reaching and hand grasping movements in artificial actuators. Clearly, these developments hold promise for the restoration of limb mobility in paralyzed subjects. However, as we review here, before this goal can be reached several bottlenecks have to be passed. These include designing a fully implantable biocompatible recording device, further developing real-time computational algorithms, introducing a method for providing the brain with sensory feedback from the actuators, and designing and building artificial prostheses that can be controlled directly by brain-derived signals. By reaching these milestones, future BMIs will be able to drive and control revolutionary prostheses that feel and act like the human arm.

Distributed BOLD-response in association cortex vector state space predicts reaction time during selective attention

Human cortical information processing is thought to be dominated by distributed activity in vector state space (Churchland, P.S., Sejnowski, T.J., 1992. The Computational Brain. MIT Press, Cambridge.). In principle, it should be possible to quantify distributed brain activation with independent component analysis (ICA) through vector-based decomposition, i.e., through a separation of a mixture of sources. Using event-related functional magnetic resonance imaging (fMRI) during a selective attention-requiring task (visual oddball), we explored how the number of independent components within activated cortical areas is related to reaction time. Prior to ICA, the activated cortical areas were determined on the basis of a General linear model (GLM) voxel-by-voxel analysis of the target stimuli (checkerboard reversal). Two activated cortical areas (temporoparietal cortex, medial prefrontal cortex) were further investigated as these cortical regions are known to be the sites of simultaneously active electromagnetic generators which give rise to the compound event-related potential P300 during oddball task conditions. We found that the number of independent components more strongly predicted reaction time than the overall level of "activation" (GLM BOLD-response) in the left temporoparietal area whereas in the medial prefrontal cortex both ICA and GLM predicted reaction time equally well. Comparable correlations were not seen when principle components were used instead of independent components. These results indicate that the number of independently activated components, i.e., a high level of cortical activation complexity in cortical vector state space, may index particularly efficient information processing during selective attention-requiring tasks. To our best knowledge, this is the first report describing a potential relationship between neuronal generators of cognitive processes, the associated electrophysiological evidence for the existence of distributed networks and BOLD fMRI signals using information from model order selection techniques.

Bayesian Population Decoding of Motor Cortical Activity Using a Kalman Filter

Effective neural motor prostheses require a method for decoding neural activity representing desired movement. In particular, the accurate reconstruction of a continuous motion signal is necessary for the control of devices such as computer cursors, robots, or a patient's own paralyzed limbs. For such applications, we developed a real-time system that uses Bayesian inference techniques to estimate hand motion from the firing rates of multiple neurons. In this study, we used recordings that were previously made in the arm area of primary motor cortex in awake behaving monkeys using a chronically implanted multielectrode microarray. Bayesian inference involves computing the posterior probability of the hand motion conditioned on a sequence of observed firing rates; this is formulated in terms of the product of a likelihood and a prior. The likelihood term models the probability of firing rates given a particular hand motion. We found that a linear gaussian model could be used to approximate this likelihood and could be readily learned from a small amount of training data. The prior term defines a probabilistic model of hand kinematics and was also taken to be a linear gaussian model. Decoding was performed using a Kalman filter, which gives an efficient recursive method for Bayesian inference when the likelihood and prior are linear and gaussian.In off-line experiments, the Kalman filter reconstructions of hand trajectory were more accurate than previously reported results.The resulting decoding algorithm provides a principled probabilistic model of motor-cortical coding, decodes hand motion in real time, provides an estimate of uncertainty, and is straightforward to implement. Additionally the formulation unifies and extends previous models of neural coding while providing insights into the motor-cortical code.

Trial-by-trial discrimination of three enantiomer pairs by neural ensembles in mammalian olfactory bulb

Populations of output neurons in the mammalian olfactory bulb (OB) exhibit distinct, widespread spatial and temporal activation patterns when stimulated with odorants. However, questions remain as to how ensembles of mitral/tufted (M/T) neurons in the mammalian OB represent odorant information. In this report, the single-trial encoding limits of random ensembles of putative single- and multiunit M/T cells in the anesthetized rat OB during presentations of enantiomers of limonene, carvone, and 2-butanol are investigated using simultaneous multielectrode recording techniques. The results of these experiments are: the individual constituents of our recorded ensembles broadly represent information about the presented odorants, the ensemble single-trial response of small spatially distributed populations of M/T neurons can readily discriminate between six different odorants, and the most consistent odorant discrimination is attained when the ensemble consists of all available units and their responses are integrated over an entire breathing cycle. These results suggest that small differences in spike counts among the ensemble members become significant when taken within the context of the entire ensemble. This may explain how ensembles of broadly tuned OB neurons contribute to olfactory perception and may explain how small numbers of individual units receiving input from distinct olfactory receptor neurons can be combined to form a robust representation of odorants.

Orbitofrontal ensemble activity monitors licking and distinguishes among natural rewards

The classification of rhythmic licking into clusters has proved to be useful for characterizing brain mechanisms that modulate the ingestion of natural rewards (sucrose and water). One cortical area that is responsive to rewarding stimuli is the orbitofrontal cortex (OFC). However, it is not presently known how OFC neurons respond while rodents freely lick for natural rewards and whether these responses are related to the structure of licking clusters. We addressed these issues by showing that temporary inactivation of the OFC decreases the duration and increases the number of clusters and that the activity of OFC neurons changed at precise times before, during, and after the cluster terminates. Furthermore, analysis of the activity of OFC neuronal ensembles showed that they could discriminate cluster onset from termination, predict when a behaving animal will begin a cluster, and distinguish and anticipate between natural rewards. These results provide a new role for the OFC in influencing licking clusters and anticipating specific rewards.

Neural signatures of cell assembly organization

Cortical neurons show irregular but structured spike trains. This has been interpreted as evidence for 'temporal coding', whereby stimuli are represented by precise spike-timing patterns. Here, we suggest an alternative interpretation based on the older concept of the cell assembly. The dynamic evolution of assembly sequences, which are steered but not deterministically controlled by sensory input, is the proposed substrate of psychological processes beyond simple stimulus-response associations. Accordingly, spike trains show a temporal structure that is stimulus-dependent and more variable than would be predicted by strict sensory control. We propose four signatures of assembly organization that can be experimentally tested. We argue that many observations that have been interpreted as evidence for temporal coding might instead reflect an underlying assembly structure.

Computing with thalamocortical ensembles during different behavioural states

A series of recent studies have indicated that ensembles of neurones, distributed within the neural structures that form the primary thalamocortical loop (TCL) of the trigeminal component of the rat somatosensory system, change the way they respond to similar tactile stimuli, according to both the behavioural strategy employed by animals to gather information and the animal's internal brain states. These findings suggest that top-down influences, which are more likely to play a role during active discrimination than during passive whisker stimulation, may alter the pattern of neuronal firing within both the distinct layers of the primary somatosensory cortex (S1) and the ventral posterior medial nucleus (VPM). We propose that through this physiological process, which involves concurrent dynamic modulations at both cellular and circuit levels in the TCL, rats can either optimize the detection of novel or hard to sense stimuli or they can analyse complex patterns of multi-whisker stimulation, during natural exploration of their surrounding environment.

Dynamics of sensory thalamocortical synaptic networks during information processing states

The thalamocortical network consists of the pathways that interconnect the thalamus and neocortex, including thalamic sensory afferents, corticothalamic and thalamocortical pathways. These pathways are essential to acquire, analyze, store and retrieve sensory information. However, sensory information processing mostly occurs during behavioral arousal, when activity in thalamus and neocortex consists of an electrographic sign of low amplitude fast activity, known as activation, which is caused by several neuromodulator systems that project to the thalamocortical network. Logically, in order to understand how the thalamocortical network processes sensory information it is essential to study its response properties during states of activation. This paper reviews the temporal and spatial response properties of synaptic pathways in the whisker thalamocortical network of rodents during activated states as compared to quiescent (non-activated) states. The evidence shows that these pathways are differentially regulated via the effects of neuromodulators as behavioral contingencies demand. Thus, during activated states, the temporal and spatial response properties of pathways in the thalamocortical network are transformed to allow the processing of sensory information.

Heterogeneous integration of bilateral whisker signals by neurons in primary somatosensory cortex of awake rats

Bilateral single-unit recordings in primary somatosensory cortex (S1) of anesthetized rats have revealed substantial cross talk between cortical hemispheres, suggesting the possibility that behaviorally relevant bilateral integration could occur in S1. To determine the extent of bilateral neural responses in awake animals, we recorded S1 multi- and single-unit activity in head-immobilized rats while stimulating groups of 4 whiskers from the same column on both sides of the head. Results from these experiments confirm the widespread presence of single units responding to tactile stimuli on either side of the face in S1 of awake animals. Quantification of bilateral integration by multiunits revealed both facilitative and suppressive integration of bilateral inputs. Varying the interval between left and right whisker stimuli between 0 and 120 ms showed the temporal integration of bilateral stimuli to be dominated on average by suppression at intervals around 30 ms, in agreement with comparable recordings in anesthetized animals. Contrary to the anesthetized data, in the awake animals we observed a high level of heterogeneity of bilateral responses and a strong interaction between synchronous bilateral stimuli. The results challenge the traditional conception of highly segregated hemispheric processing channels in the rat S1 cortex, and support the hypothesis that callosal cross-projections between the two hemispheres mediate rats' known ability to integrate bilateral whisker signals.