Neuronal correlates of sensory discrimination in the somatosensory cortex

Disentangling Temporal and Rate Codes in the Primate Somatosensory Cortex

Millisecond-scale temporal spiking patterns encode sensory information in the periphery, but their role in the neocortex remains controversial. The sense of touch provides a window into temporal coding because tactile neurons often exhibit precise, repeatable, and informative temporal spiking patterns. In the somatosensory cortex (S1), responses to skin vibrations exhibit phase locking that faithfully carries information about vibratory frequency. However, the respective roles of spike timing and rate in frequency coding are confounded because vibratory frequency shapes both the timing and rates of responses. To disentangle the contributions of these two neural features, we measured S1 responses as rhesus macaques performed frequency discrimination tasks in which differences in frequency were accompanied by orthogonal variations in amplitude. We assessed the degree to which the strength and timing of responses could account for animal performance. First, we showed that animals can discriminate frequency, but their performance is biased by amplitude variations. Second, rate-based representations of frequency are susceptible to changes in amplitude but in ways that are inconsistent with the animals' behavioral biases, calling into question a rate-based neural code for frequency. In contrast, timing-based representations are highly informative about frequency but impervious to changes in amplitude, which is also inconsistent with the animals' behavior. We account for the animals' behavior with a model wherein frequency coding relies on a temporal code, but frequency judgments are biased by perceived magnitude. We conclude that information about vibratory frequency is not encoded in S1 firing rates but primarily in temporal patterning on millisecond timescales.

Neural Control of Naturalistic Behavior Choices

In the natural world, animals make decisions on an ongoing basis, continuously selecting which action to undertake next. In the lab, however, the neural bases of decision processes have mostly been studied using artificial trial structures. New experimental tools based on the genetic toolkit of model organisms now make it experimentally feasible to monitor and manipulate neural activity in small subsets of neurons during naturalistic behaviors. We thus propose a new approach to investigating decision processes, termed reverse neuroethology. In this approach, experimenters select animal models based on experimental accessibility and then utilize cutting-edge tools such as connectomes and genetically encoded reagents to analyze the flow of information through an animal's nervous system during naturalistic choice behaviors. We describe how the reverse neuroethology strategy has been applied to understand the neural underpinnings of innate, rapid decision making, with a focus on defensive behavioral choices in the vinegar fly Drosophila melanogaster.

Coexistence of state, choice, and sensory integration coding in barrel cortex LII/III

During perceptually guided decisions, correlates of choice are found as upstream as in the primary sensory areas. However, how well these choice signals align with early sensory representations, a prerequisite for their interpretation as feedforward substrates of perception, remains an open question. We designed a two alternative forced choice task (2AFC) in which male mice compared stimulation frequencies applied to two adjacent vibrissae. The optogenetic silencing of individual columns in the primary somatosensory cortex (wS1) resulted in predicted shifts of psychometric functions, demonstrating that perception depends on focal, early sensory representations. Functional imaging of layer II/III single neurons revealed mixed coding of stimuli, choices and engagement in the task. Neurons with multi-whisker suppression display improved sensory discrimination and had their activity increased during engagement in the task, enhancing selectively representation of the signals relevant to solving the task. From trial to trial, representation of stimuli and choice varied substantially, but mostly orthogonally to each other, suggesting that perceptual variability does not originate from wS1 fluctuations but rather from downstream areas. Together, our results highlight the role of primary sensory areas in forming a reliable sensory substrate that could be used for flexible downstream decision processes.

Learning induced neuronal identity switch in the superficial layers of the primary somatosensory cortex

During learning, multi-dimensional inputs are integrated within the sensory cortices. However, the strategies by which the sensory cortex employs to achieve learning remains poorly understood. We studied the sensory cortical neuronal coding of trace eyeblink conditioning (TEC) in head-fixed, freely running mice, where whisker deflection was used as a conditioned stimulus (CS) and an air puff to the cornea delivered after an interval was used as unconditioned stimulus (US). After training, mice learned the task with a set of stereotypical behavioral changes, most prominent ones include prolonged closure of eyelids, and increased reverse running between CS and US onset. The local blockade of the primary somatosensory cortex (S1) activities with muscimol abolished the behavior learning suggesting that S1 is required for the TEC. In naive animals, based on the response properties to the CS and US, identities of the small proportion (~20%) of responsive primary neurons (PNs) were divided into two subtypes: CR (i.e. CS-responsive) and UR neurons (i.e. US-responsive). After animals learned the task, identity of CR and UR neurons changed: while the CR neurons are less responsive to CS, UR neurons gain responsiveness to CS, a new phenomenon we defined as 'learning induced neuronal identity switch (LINIS)'. To explore the potential mechanisms underlying LINIS, we found that systemic and local (i.e. in S1) administration of the nicotinic receptor antagonist during TEC training blocked the LINIS, and concomitantly disrupted the behavior learning. Additionally, we monitored responses of two types of cortical interneurons (INs) and observed that the responses of the somatostatin-expressing (SST), but not parvalbumin-expressing (PV) INs are negatively correlated with the learning performance, suggesting that SST-INs contribute to the LINIS. Thus, we conclude that L2/3 PNs in S1 encode perceptual learning by LINIS like mechanisms, and cholinergic pathways and cortical SST interneurons are involved in the formation of LINIS.

Hierarchical differences in the encoding of sound and choice in the subcortical auditory system

Detection of sounds is a fundamental function of the auditory system. Although studies of auditory cortex have gained substantial insight into detection performance using behaving animals, previous subcortical studies have mostly taken place under anesthesia, in passively listening animals, or have not measured performance at threshold. These limitations preclude direct comparisons between neuronal responses and behavior. To address this, we simultaneously measured auditory detection performance and single-unit activity in the inferior colliculus (IC) and cochlear nucleus (CN) in macaques. The spontaneous activity and response variability of CN neurons were higher than those observed for IC neurons. Signal detection theoretic methods revealed that the magnitude of responses of IC neurons provided more reliable estimates of psychometric threshold and slope compared with the responses of single CN neurons. However, pooling small populations of CN neurons provided reliable estimates of psychometric threshold and slope, suggesting sufficient information in CN population activity. Trial-by-trial correlations between spike count and behavioral response emerged 50-75 ms after sound onset for most IC neurons, but for few neurons in the CN. These results highlight hierarchical differences between neurometric-psychometric correlations in CN and IC and have important implications for how subcortical information could be decoded.NEW & NOTEWORTHY The cerebral cortex is widely recognized to play a role in sensory processing and decision-making. Accounts of the neural basis of auditory perception and its dysfunction are based on this idea. However, significantly less attention has been paid to midbrain and brainstem structures in this regard. Here, we find that subcortical auditory neurons represent stimulus information sufficient for detection and predict behavioral choice on a trial-by-trial basis.

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.

Physiological noise facilitates multiplexed coding of vibrotactile-like signals in somatosensory cortex

Neurons can use different aspects of their spiking to simultaneously represent (multiplex) different features of a stimulus. For example, some pyramidal neurons in primary somatosensory cortex (S1) use the rate and timing of their spikes to, respectively, encode the intensity and frequency of vibrotactile stimuli. Doing so has several requirements. Because they fire at low rates, pyramidal neurons cannot entrain 1:1 with high-frequency (100 to 600 Hz) inputs and, instead, must skip (i.e., not respond to) some stimulus cycles. The proportion of skipped cycles must vary inversely with stimulus intensity for firing rate to encode stimulus intensity. Spikes must phase-lock to the stimulus for spike times (intervals) to encode stimulus frequency, but, in addition, skipping must occur irregularly to avoid aliasing. Using simulations and in vitro experiments in which mouse S1 pyramidal neurons were stimulated with inputs emulating those induced by vibrotactile stimuli, we show that fewer cycles are skipped as stimulus intensity increases, as required for rate coding, and that intrinsic or synaptic noise can induce irregular skipping without disrupting phase locking, as required for temporal coding. This occurs because noise can modulate the reliability without disrupting the precision of spikes evoked by small-amplitude, fast-onset signals. Specifically, in the fluctuation-driven regime associated with sparse spiking, rate and temporal coding are both paradoxically improved by the strong synaptic noise characteristic of the intact cortex. Our results demonstrate that multiplexed coding by S1 pyramidal neurons is not only feasible under in vivo conditions, but that background synaptic noise is actually beneficial.

Auditory clicks elicit equivalent temporal frequency perception to tactile pulses: A cross-modal psychophysical study

Both hearing and touch are sensitive to the frequency of mechanical oscillations—sound waves and tactile vibrations, respectively. The mounting evidence of parallels in temporal frequency processing between the two sensory systems led us to directly address the question of perceptual frequency equivalence between touch and hearing using stimuli of simple and more complex temporal features. In a cross-modal psychophysical paradigm, subjects compared the perceived frequency of pulsatile mechanical vibrations to that elicited by pulsatile acoustic (click) trains, and vice versa. Non-invasive pulsatile stimulation designed to excite a fixed population of afferents was used to induce desired temporal spike trains at frequencies spanning flutter up to vibratory hum (>50 Hz). The cross-modal perceived frequency for regular test pulse trains of either modality was a close match to the presented stimulus physical frequency up to 100 Hz. We then tested whether the recently discovered “burst gap” temporal code for frequency, that is shared by the two senses, renders an equivalent cross-modal frequency perception. When subjects compared trains comprising pairs of pulses (bursts) in one modality against regular trains in the other, the cross-sensory equivalent perceptual frequency best corresponded to the silent interval between the successive bursts in both auditory and tactile test stimuli. These findings suggest that identical acoustic and vibrotactile pulse trains, regardless of pattern, elicit equivalent frequencies, and imply analogous temporal frequency computation strategies in both modalities. This perceptual correspondence raises the possibility of employing a cross-modal comparison as a robust standard to overcome the prevailing methodological limitations in psychophysical investigations and strongly encourages cross-modal approaches for transmitting sensory information such as translating pitch into a similar pattern of vibration on the skin.

Behaviorally relevant decision coding in primary somatosensory cortex neurons

Primary sensory cortex is thought to process incoming sensory information, while decision variables important for driving behavior are assumed to arise downstream in the processing hierarchy. Here, we used population two-photon calcium imaging and targeted two-photon optogenetic stimulation of neurons in layer 2/3 of mouse primary somatosensory cortex (S1) during a texture discrimination task to test for the presence of decision signals and probe their behavioral relevance. Small but distinct populations of neurons carried information about the stimulus irrespective of the behavioral outcome (stimulus neurons), or about the choice irrespective of the presented stimulus (decision neurons). Decision neurons show categorical coding that develops during learning, and lack a conclusive decision signal in Miss trials. All-optical photostimulation of decision neurons during behavior improves behavioral performance, establishing a causal role in driving behavior. The fact that stimulus and decision neurons are intermingled challenges the idea of S1 as a purely sensory area, and causal perturbation suggests a direct involvement of S1 decision neurons in the decision-making process.

Intracortical microstimulation pulse waveform and frequency recruits distinct spatiotemporal patterns of cortical neuron and neuropil activation

OBJECTIVE

Neural prosthetics often use intracortical microstimulation (ICMS) for sensory restoration. To restore natural and functional feedback, we must first understand how stimulation parameters influence the recruitment of neural populations. ICMS waveform asymmetry modulates the spatial activation of neurons around an electrode at 10 Hz; however, it is unclear how asymmetry may differentially modulate population activity at frequencies typically employed in the clinic (e.g. 100 Hz). We hypothesized that stimulation waveform asymmetry would differentially modulate preferential activation of certain neural populations, and the differential population activity would be frequency-dependent.

APPROACH

We quantified how asymmetric stimulation waveforms delivered at 10 Hz or 100 Hz for 30s modulated spatiotemporal activity of cortical layer II/III pyramidal neurons using in vivo two-photon and mesoscale calcium imaging in anesthetized mice. Asymmetry is defined in terms of the ratio of the duration of the leading phase to the duration of the return phase of charge-balanced cathodal- and anodal-first waveforms (i.e. longer leading phase relative to return has larger asymmetry).

MAIN RESULTS

Neurons within 40-60µm of the electrode display stable stimulation-induced activity indicative of direct activation, which was independent of waveform asymmetry. The stability of 72% of activated neurons and the preferential activation of 20-90 % of neurons depended on waveform asymmetry. Additionally, this asymmetry-dependent activation of different neural populations was associated with differential progression of population activity. Specifically, neural activity tended to increase over time during 10 hz stimulation for some waveforms, whereas activity remained at the same level throughout stimulation for other waveforms. During 100 Hz stimulation, neural activity decreased over time for all waveforms, but decreased more for the waveforms that resulted in increasing neural activity during 10 Hz stimulation.

SIGNIFICANCE

These data demonstrate that at frequencies commonly used for sensory restoration, stimulation waveform alters the pattern of activation of different but overlapping populations of excitatory neurons. The impact of these waveform specific responses on the activation of different subtypes of neurons as well as sensory perception merits further investigation.

Effects of Peripheral Haptic Feedback on Intracortical Brain-Computer Interface Control and Associated Sensory Responses in Motor Cortex

Intracortical brain-computer interfaces (iBCIs) provide people with paralysis a means to control devices with signals decoded from brain activity. Despite recent impressive advances, these devices still cannot approach able-bodied levels of control. To achieve naturalistic control and improved performance of neural prostheses, iBCIs will likely need to include proprioceptive feedback. With the goal of providing proprioceptive feedback via mechanical haptic stimulation, we aim to understand how haptic stimulation affects motor cortical neurons and ultimately, iBCI control. We provided skin shear haptic stimulation as a substitute for proprioception to the back of the neck of a person with tetraplegia. The neck location was determined via assessment of touch sensitivity using a monofilament test kit. The participant was able to correctly report skin shear at the back of the neck in 8 unique directions with 65% accuracy. We found motor cortical units that exhibited sensory responses to shear stimuli, some of which were strongly tuned to the stimuli and well modeled by cosine-shaped functions. In this article, we also demonstrated online iBCI cursor control with continuous skin-shear feedback driven by decoded command signals. Cursor control performance increased slightly but significantly when the participant was given haptic feedback, compared to the purely visual feedback condition.

Neural Basis of Somatosensory Spatial and Temporal Discrimination in Humans: The Role of Sensory Detection

While detecting somatic stimuli from the external environment, an accurate determination of their spatial and temporal properties is essential for human behavior. Whether and how detection relates to human capacity for somatosensory spatial discrimination (SD) and temporal discrimination (TD) remains unclear. Here, participants underwent functional magnetic resonance imaging scanning when simply detecting vibrotactile stimuli of the leg, judging their location (SD), or deciding their number in time (TD). By conceptualizing tactile discrimination as consisting of detection and determination processes, we found that tactile detection elicited activation specifically involved in SD within the right inferior and superior parietal lobules, 2 regions previously implicated in the control of spatial attention. These 2 regions remained activated in the determination process, during which functional connectivity between these 2 regions predicted individual SD ability. In contrast, tactile detection produced little activation specifically related to TD. Participants' TD ability was implemented in brain regions implicated in coding temporal structures of somatic stimuli (primary somatosensory cortex) and time estimation (anterior cingulate, pre-supplementary motor area, and putamen). Together, our findings indicate a close link between somatosensory detection and SD (but not TD) at the neural level, which aids in explaining why we can promptly respond toward detected somatic stimuli.

Temporal Encoding is Required for Categorization, But Not Discrimination

Core auditory cortex (AC) neurons encode slow fluctuations of acoustic stimuli with temporally patterned activity. However, whether temporal encoding is necessary to explain auditory perceptual skills remains uncertain. Here, we recorded from gerbil AC neurons while they discriminated between a 4-Hz amplitude modulation (AM) broadband noise and AM rates >4 Hz. We found a proportion of neurons possessed neural thresholds based on spike pattern or spike count that were better than the recorded session's behavioral threshold, suggesting that spike count could provide sufficient information for this perceptual task. A population decoder that relied on temporal information outperformed a decoder that relied on spike count alone, but the spike count decoder still remained sufficient to explain average behavioral performance. This leaves open the possibility that more demanding perceptual judgments require temporal information. Thus, we asked whether accurate classification of different AM rates between 4 and 12 Hz required the information contained in AC temporal discharge patterns. Indeed, accurate classification of these AM stimuli depended on the inclusion of temporal information rather than spike count alone. Overall, our results compare two different representations of time-varying acoustic features that can be accessed by downstream circuits required for perceptual judgments.

Treatment Recommendations for Phantom Limb Pain in People with Amputations: An Expert Consensus Delphi Study

Background

Phantom limb pain (PLP) is common and often accompanied by serious suffering. Current systematic‐review evidence suggests that recommended treatments are no more effective than placebo for reducing PLP. Given the difficulty in conducting a meta‐analysis for nonpharmacological treatments and the weak evidence for pharmacological treatments for PLP, consensus on the first‐line management of PLP needs to be reached using alternative methods.

Objective

To reach expert consensus and make recommendations on the effective management of PLP.

Design

A three‐round Delphi design was used.

Setting

The study was conducted using e‐mail and Google survey tool as the main methods of communication and providing feedback.

Participants

The study included 27 clinicians and researchers from various health disciplines who are experts in PLP management.

Method

Data were collected using three sequential rounds of anonymous online questionnaires where experts proposed and ranked the treatments for PLP. A consensus was reached on the treatments that were endorsed by 50% or more of the experts.

Results

Thirty‐seven treatments were proposed for the management of PLP at the beginning of the study. Consensus was reached on seven treatments that were considered effective for managing PLP and on two treatments that were considered ineffective. Graded motor imagery, mirror therapy, amitriptyline, sensory discrimination training, and use of a functional prosthesis were endorsed by most experts because of the available backing scientific evidence and their reported efficacy in clinical practice. Cognitive behavioral therapy and virtual reality training were endorsed by most experts because of their reported efficacy in clinical practice despite indicating a dearth of scientific evidence to support their ranking. Citalopram and dorsal root ganglion pulsed radiofrequency were rejected owing to a lack of relevant scientific evidence.

Conclusion

The results of this study suggest that the nonpharmacological treatments endorsed in this study may have an important role in the management of PLP.

Invariant timescale hierarchy across the cortical somatosensory network

The ability of cortical networks to integrate information from different sources is essential for cognitive processes. On one hand, sensory areas exhibit fast dynamics often phase-locked to stimulation; on the other hand, frontal lobe areas with slow response latencies to stimuli must integrate and maintain information for longer periods. Thus, cortical areas may require different timescales depending on their functional role. Studying the cortical somatosensory network while monkeys discriminated between two vibrotactile stimulus patterns, we found that a hierarchical order could be established across cortical areas based on their intrinsic timescales. Further, even though subareas (areas 3b, 1, and 2) of the primary somatosensory (S1) cortex exhibit analogous firing rate responses, a clear differentiation was observed in their timescales. Importantly, we observed that this inherent timescale hierarchy was invariant between task contexts (demanding vs. nondemanding). Even if task context severely affected neural coding in cortical areas downstream to S1, their timescales remained unaffected. Moreover, we found that these time constants were invariant across neurons with different latencies or coding. Although neurons had completely different dynamics, they all exhibited comparable timescales within each cortical area. Our results suggest that this measure is demonstrative of an inherent characteristic of each cortical area, is not a dynamical feature of individual neurons, and does not depend on task demands.

The temporal pattern of Intracortical Microstimulation pulses elicits distinct temporal and spatial recruitment of cortical neuropil and neurons

OBJECTIVE

The spacing or distribution of stimulation pulses of therapeutic neurostimulation waveforms-referred to here as the Temporal Pattern (TP)-has emerged as an important parameter for tuning the response to deep-brain stimulation and intracortical microstimulation (ICMS). While it has long been assumed that modulating the TP of ICMS may be effective by altering the rate coding of the neural response, it is unclear how it alters the neural response at the neural network level. The present study is designed to elucidate the neural response to TP at the network level.

APPROACH

We use in vivo two-photon imaging of ICMS in mice expressing the calcium sensor Thy1-GCaMP or the glutamate sensor hSyn-iGluSnFr to examine the layer II/III neural response to stimulations with different TPs. We study the neuronal calcium and glutamate response to TPs with the same average frequency (10Hz) and same total charge injection, but varying degrees of bursting. We also investigate one control pattern with an average frequency of 100Hz and 10X the charge injection.

MAIN RESULTS

Stimulation trains with the same average frequency (10 Hz) and same total charge injection but distinct temporal patterns recruits distinct sets of neurons. More-than-half (60% of 309 cells) prefer one temporal pattern over the other. Despite their distinct spatial recruitment patterns, both cells exhibit similar ability to follow 30s trains of both TPs without failing, and they exhibit similar levels of glutamate release during stimulation. Both neuronal calcium and glutamate release train to the bursting TP pattern (~21-fold increase in relative power at the frequency of bursting. Bursting also results in a statistically significant elevation in the correlation between somatic calcium activity and neuropil activity, which we explore as a metric for inhibitory-excitatory tone. Interestingly, soma-neuropil correlation during the bursting pattern is a statistically significant predictor of cell preference for TP, which exposes a key link between inhibitory-excitatory tone. Finally, using mesoscale imaging, we show that both TPs result in distal inhibition during stimulation, which reveals complex spatial and temporal interactions between temporal pattern and inhibitory-excitatory tone in ICMS.

SIGNIFICANCE

Our results may ultimately suggest that TP is a valuable parameter space to modulate inhibitory-excitatory tone as well as distinct network activity in ICMS. This presents a broader mechanism of action than rate coding, as previously thought. By implicating these additional mechanisms, TP may have broader utility in the clinic and should be pursued to expand the efficacy of ICMS therapies.

Neuronal Correlates of Tactile Working Memory in Prefrontal and Vibrissal Somatosensory Cortex

Tactile working memory engages a broad network of cortical regions in primates. To assess whether the conclusions drawn from primates apply to rodents, we examined the vibrissal primary somatosensory cortex (vS1) and the prelimbic cortex (PL) in a delayed comparison task. Rats compared the speeds of two vibrissal vibrations, stimulus1 and stimulus2, separated by a delay of 2 s. Neuronal firing rates in vS1 and PL encode both stimuli in real time. Across the delay, the stimulus1 representation declines more precipitously in vS1 than in PL. Theta-band local field potential (LFP) coherence between vS1 and PL peaks at trial onset and remains elevated during the interstimulus interval; simultaneously, vS1 spikes become phase locked to PL LFP. Phase locking is stronger on correct (versus error) trials. Tactile working memory in rats appears to be mediated by a posterior (vS1) to anterior (PL) flow of information, with performance facilitated through coherent LFP oscillation.

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Rats compared the speeds of two sequential vibrissal vibrations, separated by 2 s

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Neurons in the primary somatosensory (vS1) and prelimbic (PL) cortex coded the stimuli

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Theta local field potential coherence between vS1 and PL peaked at trial onset

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Intracortical coherent oscillations may play a role in rat tactile working memory

A Single-Neuron: Current Trends and Future Prospects

The brain is an intricate network with complex organizational principles facilitating a concerted communication between single-neurons, distinct neuron populations, and remote brain areas. The communication, technically referred to as connectivity, between single-neurons, is the center of many investigations aimed at elucidating pathophysiology, anatomical differences, and structural and functional features. In comparison with bulk analysis, single-neuron analysis can provide precise information about neurons or even sub-neuron level electrophysiology, anatomical differences, pathophysiology, structural and functional features, in addition to their communications with other neurons, and can promote essential information to understand the brain and its activity. This review highlights various single-neuron models and their behaviors, followed by different analysis methods. Again, to elucidate cellular dynamics in terms of electrophysiology at the single-neuron level, we emphasize in detail the role of single-neuron mapping and electrophysiological recording. We also elaborate on the recent development of single-neuron isolation, manipulation, and therapeutic progress using advanced micro/nanofluidic devices, as well as microinjection, electroporation, microelectrode array, optical transfection, optogenetic techniques. Further, the development in the field of artificial intelligence in relation to single-neurons is highlighted. The review concludes with between limitations and future prospects of single-neuron analyses.

Reproducibility of flutter-range vibrotactile detection and discrimination thresholds

Somatosensory processing can be probed empirically through vibrotactile psychophysical experiments. Psychophysical approaches are valuable for investigating both normal and abnormal tactile function in healthy and clinical populations. To date, the test-retest reliability of vibrotactile detection and discrimination thresholds has yet to be established. This study sought to assess the reproducibility of vibrotactile detection and discrimination thresholds in human adults using an established vibrotactile psychophysical battery. Fifteen healthy adults underwent three repeat sessions of an eleven-task battery that measured a range of vibrotactile measures, including reaction time, detection threshold, amplitude and frequency discrimination, and temporal order judgement. Coefficients of variation and intraclass correlation coefficients (ICCs) were calculated for the measures in each task. Linear mixed-effects models were used to test for length and training effects and differences between tasks within the same domain. Reaction times were shown to be the most reproducible (ICC: ~0.9) followed by detection thresholds (ICC: ~0.7). Frequency discrimination thresholds were the least reproducible (ICC: ~0.3). As reported in prior studies, significant differences in measures between related tasks were also found, demonstrating the reproducibility of task-related effects. These findings show that vibrotactile detection and discrimination thresholds are reliable, further supporting the use of psychophysical experiments to probe tactile function.

Designing and Interpreting Psychophysical Investigations of Cognition

Scientific experimentation depends on the artificial control of natural phenomena. The inaccessibility of cognitive processes to direct manipulation can make such control difficult to realize. Here, we discuss approaches for overcoming this challenge. We advocate the incorporation of experimental techniques from sensory psychophysics into the study of cognitive processes such as decision making and executive control. These techniques include the use of simple parameterized stimuli to precisely manipulate available information and computational models to jointly quantify behavior and neural responses. We illustrate the potential for such techniques to drive theoretical development, and we examine important practical details of how to conduct controlled experiments when using them. Finally, we highlight principles guiding the use of computational models in studying the neural basis of cognition.

Effects of Stimulus Exploration Length and Time on the Integration of Information in Haptic Softness Discrimination

In haptic perception, information is often sampled serially (e.g., a stimulus is repeatedly indented to estimate its softness), requiring that sensory information is retained and integrated over time. Hence, integration of sequential information is likely affected by memory. Particularly, when two sequentially explored stimuli are compared, integration of information on the second stimulus might be determined by the fading representation of the first stimulus. We investigated how the exploration length of the first stimulus and a temporal delay affect contributions of sequentially gathered estimates of the second stimulus in haptic softness discrimination. Participants subsequently explored two silicon rubber stimuli by indenting the first stimulus one or five times and the second stimulus always three times. In an additional experiment, we introduced a 5-s delay after the first stimulus was indented five times. We show that the longer the first stimulus is explored, the more estimates of the second stimulus' softness contribute to the discrimination of the two stimuli, independent of the delay. This suggests that the exploration length of the first stimulus influences the strength of its representation, persisting at least for 5 s, and determines how much information about the second stimulus is exploited for the comparison.

Computational and Psychophysical Experiments on the Pacinian Corpuscle's Ability to Discriminate Complex Stimuli

Recognizing and discriminating vibrotactile stimuli is an essential function of the Pacinian corpuscle. This function has been studied at length in both a computational and an experimental setting, but the two approaches have rarely been compared, especially when the computational model has a high level of structural detail. In this paper, we explored whether the predictions of a multiscale, multiphysical computational model of the Pacinian corpuscle can predict the outcome of a corresponding psychophysical experiment. The discrimination test involved either two simple stimuli with frequency in the 160-500 Hz range, or two complex stimuli formed by combining the waveforms for a 100-Hz stimulus with a second stimulus in the 160-500 Hz range. The subjects' ability to distinguish between the simple stimuli increased as the frequency increased, a result consistent with the model predictions for the same stimuli. The model also predicted correctly that subjects would find the complex stimuli more difficult to distinguish than the simple ones and also that the discriminability of the complex stimuli would show no trend with frequency difference.

A Robust Encoding Scheme for Delivering Artificial Sensory Information via Direct Brain Stimulation

Innovations for creating somatosensation via direct electrical stimulation of the brain will be required for the next generation of bi-directional cortical neuroprostheses. The current lack of tactile perception and proprioceptive input likely imposes a fundamental limit on speed and accuracy of brain-controlled prostheses or re-animated limbs. This study addresses the unique challenge of identifying a robust, high bandwidth sensory encoding scheme in a high-dimensional parameter space. Previous studies demonstrated single dimensional encoding schemes delivering low bandwidth sensory information, but no comparison has been performed across parameters, nor with update rates suitable for real-time operation of a neuroprosthesis. Here, we report the first comprehensive measurement of the resolution of key stimulation parameters such as pulse amplitude, pulse width, frequency, train interval and number of pulses. Surprisingly, modulation of stimulation frequency was largely undetectable. While we initially expected high frequency content to be an ideal candidate for passing high throughput sensory signals to the brain, we found only modulation of very low frequencies were detectable. Instead, the charge-per-phase of each pulse yields the highest resolution sensory signal, and is the key parameter modulating perceived intensity. The stimulation encoding patterns were designed for high-bandwidth information transfer that will be required for bi-directional brain interfaces. Our discovery of the stimulation features which best encode perceived intensity have significant implications for design of any neural interface seeking to convey information directly to the brain via electrical stimulation.

Whisker-Mediated Touch System in Rodents: From Neuron to Behavior

A key question in systems neuroscience is to identify how sensory stimuli are represented in neuronal activity, and how the activity of sensory neurons in turn is “read out” by downstream neurons and give rise to behavior. The choice of a proper model system to address these questions, is therefore a crucial step. Over the past decade, the increasingly powerful array of experimental approaches that has become available in non-primate models (e.g., optogenetics and two-photon imaging) has spurred a renewed interest for the use of rodent models in systems neuroscience research. Here, I introduce the rodent whisker-mediated touch system as a structurally well-established and well-organized model system which, despite its simplicity, gives rise to complex behaviors. This system serves as a behaviorally efficient model system; known as nocturnal animals, along with their olfaction, rodents rely on their whisker-mediated touch system to collect information about their surrounding environment. Moreover, this system represents a well-studied circuitry with a somatotopic organization. At every stage of processing, one can identify anatomical and functional topographic maps of whiskers; “barrelettes” in the brainstem nuclei, “barreloids” in the sensory thalamus, and “barrels” in the cortex. This article provides a brief review on the basic anatomy and function of the whisker system in rodents.

Functional Frequency Discrimination From Cortical Somatosensory Stimulation in Humans

Recently, efforts to produce artificial sensation through cortical stimulation of primary somatosensory cortex (PSC) in humans have proven safe and reliable. Changes in stimulation parameters like frequency and amplitude have been shown to elicit different percepts, but without clearly defined psychometric profiles. This study investigates the functionally useful limits of frequency changes on the percepts felt by three epilepsy patients with subdural electrocorticography (ECoG) grids. Subjects performing a hidden target task were stimulated with parameters of constant amplitude, pulse-width, and pulse-duration, and a randomly selected set of two frequencies (20, 30, 40, 50, 60, and 100 Hz). They were asked to decide which target had the “higher” frequency. Objectively, an increase in frequency differences was associated with an increase in perceived intensity. Reliable detection of stimulation occurred at and above 40 Hz with a lower limit of detection around 20 Hz and a just-noticeable difference estimated at less than 10 Hz. These findings suggest that frequency can be used as a reliable, adjustable parameter and may be useful in establishing settings and thresholds of functionality in future BCI systems.

Hierarchical and Nonlinear Dynamics in Prefrontal Cortex Regulate the Precision of Perceptual Beliefs

Actions are shaped not only by the content of our percepts but also by our confidence in them. To study the cortical representation of perceptual precision in decision making, we acquired functional imaging data whilst participants performed two vibrotactile forced-choice discrimination tasks: a fast-slow judgment, and a same-different judgment. The first task requires a comparison of the perceived vibrotactile frequencies to decide which one is faster. However, the second task requires that the estimated difference between those frequencies is weighed against the precision of each percept-if both stimuli are very precisely perceived, then any slight difference is more likely to be identified than if the percepts are uncertain. We additionally presented either pure sinusoidal or temporally degraded "noisy" stimuli, whose frequency/period differed slightly from cycle to cycle. In this way, we were able to manipulate the perceptual precision. We report a constellation of cortical regions in the rostral prefrontal cortex (PFC), dorsolateral PFC (DLPFC) and superior frontal gyrus (SFG) associated with the perception of stimulus difference, the presence of stimulus noise and the interaction between these factors. Dynamic causal modeling (DCM) of these data suggested a nonlinear, hierarchical model, whereby activity in the rostral PFC (evoked by the presence of stimulus noise) mutually interacts with activity in the DLPFC (evoked by stimulus differences). This model of effective connectivity outperformed competing models with serial and parallel interactions, hence providing a unique insight into the hierarchical architecture underlying the representation and appraisal of perceptual belief and precision in the PFC.

Neural Basis of Touch and Proprioception in Primate Cortex

The sense of proprioception allows us to keep track of our limb posture and movements and the sense of touch provides us with information about objects with which we come into contact. In both senses, mechanoreceptors convert the deformation of tissues-skin, muscles, tendons, ligaments, or joints-into neural signals. Tactile and proprioceptive signals are then relayed by the peripheral nerves to the central nervous system, where they are processed to give rise to percepts of objects and of the state of our body. In this review, we first examine briefly the receptors that mediate touch and proprioception, their associated nerve fibers, and pathways they follow to the cerebral cortex. We then provide an overview of the different cortical areas that process tactile and proprioceptive information. Next, we discuss how various features of objects-their shape, motion, and texture, for example-are encoded in the various cortical fields, and the susceptibility of these neural codes to attention and other forms of higher-order modulation. Finally, we summarize recent efforts to restore the senses of touch and proprioception by electrically stimulating somatosensory cortex. © 2018 American Physiological Society. Compr Physiol 8:1575-1602, 2018.

Context-dependent tactile texture-sensitivity in monkey M1 and S1 cortex

Caudal primary motor cortex (M1, area 4) is sensitive to cutaneous inputs, but the extent to which the physical details of complex stimuli are encoded is not known. We investigated the sensitivity of M1 neurons (4 Macaca mulatta monkeys) to textured stimuli (smooth/rough or rough/rougher) during the performance of a texture discrimination task and, for some cells, during a no-task condition (same surfaces; no response). The recordings were made from the hemisphere contralateral to the stimulated digits; the motor response (sensory decision) was made with the nonstimulated arm. Most M1 cells were modulated during surface scanning in the task (88%), but few of these were texture-related (24%). In contrast, 44% of M1 neurons were texture related in the no-task condition. Recordings from the neighboring primary somatosensory cortex (S1), the potential source of texture-related signals to M1, showed that S1 neurons were significantly more likely to be texture related during the task (57 vs 24%) than M1. No difference was observed in the no-task condition (52 vs. 44%). In these recordings, the details about surface texture were relevant for S1 but not for M1. We suggest that tactile inputs to M1 were selectively suppressed when the animals were engaged in the task. S1 was spared these controls, as the same inputs were task-relevant. Taken together, we suggest that the suppressive effects are most likely exerted directly at the level of M1, possibly through the activation of a top-down gating mechanism specific to motor set/intention. NEW & NOTEWORTHY Sensory feedback is important for motor control, but we have little knowledge of the contribution of sensory inputs to M1 discharge during behavior. We showed that M1 neurons signal changes in tactile texture, but mainly outside the context of a texture discrimination task. Tactile inputs to M1 were selectively suppressed during the task because this input was not relevant for the recorded hemisphere, which played no role in generating the discrimination response.

How Visual Body Perception Influences Somatosensory Plasticity

The study of somatosensory plasticity offers unique insights into the neuronal mechanisms that underlie human adaptive and maladaptive plasticity. So far, little attention has been paid on the specific influence of visual body perception on somatosensory plasticity and learning in humans. Here, we review evidence on how visual body perception induces changes in the functional architecture of the somatosensory system and discuss the specific influence the social environment has on tactile plasticity and learning. We focus on studies that have been published in the areas of human cognitive and clinical neuroscience and refer to animal studies when appropriate. We discuss the therapeutic potential of socially mediated modulations of somatosensory plasticity and introduce specific paradigms to induce plastic changes under controlled conditions. This review offers a contribution to understanding the complex interactions between social perception and somatosensory learning by focusing on a novel research field: socially mediated sensory plasticity.

Slip-Based Coding of Local Shape and Texture in Mouse S1

Tactile objects have both local geometry (shape) and broader macroscopic texture, but how these different spatial scales are simultaneously encoded during active touch is unknown. In the whisker system, we tested for a shared code based on localized whisker micromotions (stick-slips) and slip-evoked spikes. We trained mice to discriminate smooth from rough surfaces, including ridged gratings and sandpaper. Whisker slips locked to ridges and evoked temporally precise spikes (<10 ms jitter) in somatosensory cortex (S1) that could resolve ridges with ∼1 mm accuracy. Slip-sensitive neurons also encoded touch and texture. On rough surfaces, both slip-evoked spikes and an additional non-slip signal elevated mean firing rate, allowing accurate rough-smooth texture decoding from population firing rate. Eighteen percent of neurons were selective among rough surfaces. Thus, slips elicit spatially and temporally precise spiking in S1 that simultaneously encodes local shape (ridges) and is integrated into a macroscopic firing rate code for roughness.

Cusps enable line attractors for neural computation

Line attractors in neuronal networks have been suggested to be the basis of many brain functions, such as working memory, oculomotor control, head movement, locomotion, and sensory processing. In this paper, we make the connection between line attractors and pulse gating in feed-forward neuronal networks. In this context, because of their neutral stability along a one-dimensional manifold, line attractors are associated with a time-translational invariance that allows graded information to be propagated from one neuronal population to the next. To understand how pulse-gating manifests itself in a high-dimensional, nonlinear, feedforward integrate-and-fire network, we use a Fokker-Planck approach to analyze system dynamics. We make a connection between pulse-gated propagation in the Fokker-Planck and population-averaged mean-field (firing rate) models, and then identify an approximate line attractor in state space as the essential structure underlying graded information propagation. An analysis of the line attractor shows that it consists of three fixed points: a central saddle with an unstable manifold along the line and stable manifolds orthogonal to the line, which is surrounded on either side by stable fixed points. Along the manifold defined by the fixed points, slow dynamics give rise to a ghost. We show that this line attractor arises at a cusp catastrophe, where a fold bifurcation develops as a function of synaptic noise; and that the ghost dynamics near the fold of the cusp underly the robustness of the line attractor. Understanding the dynamical aspects of this cusp catastrophe allows us to show how line attractors can persist in biologically realistic neuronal networks and how the interplay of pulse gating, synaptic coupling, and neuronal stochasticity can be used to enable attracting one-dimensional manifolds and, thus, dynamically control the processing of graded information.

Neocortical dynamics during whisker-based sensory discrimination in head-restrained mice

A fundamental task frequently encountered by brains is to rapidly and reliably discriminate between sensory stimuli of the same modality, be it distinct auditory sounds, odors, visual patterns, or tactile textures. A key mammalian brain structure involved in discrimination behavior is the neocortex. Sensory processing not only involves the respective primary sensory area, which is crucial for perceptual detection, but additionally relies on cortico-cortical communication among several regions including higher-order sensory areas as well as frontal cortical areas. It remains elusive how these regions exchange information to process neural representations of distinct stimuli to bring about a decision and initiate appropriate behavioral responses. Likewise, it is poorly understood how these neural computations are conjured during task learning. In this review, we discuss recent studies investigating cortical dynamics during discrimination behaviors that utilize head-fixed behavioral tasks in combination with in vivo electrophysiology, two-photon calcium imaging, and cell-type-specific targeting. We particularly focus on information flow in distinct cortico-cortical pathways when mice use their whiskers to discriminate between different objects or different locations. Within the primary and secondary somatosensory cortices (S1 and S2, respectively) as well as vibrissae motor cortex (M1), intermingled functional representations of touch, whisking, and licking were found, which partially re-organized during discrimination learning. These findings provide first glimpses of cortico-cortical communication but emphasize that for understanding the complete process of discrimination it will be crucial to elucidate the details of how neural processing is coordinated across brain-wide neuronal networks including the S1-S2-M1 triangle and cortical areas beyond.

Content-Specific Codes of Parametric Vibrotactile Working Memory in Humans

To understand how the brain handles mentally represented information flexibly in the absence of sensory stimulation, working memory (WM) studies have been essential. A seminal finding in monkey research is that neurons in the prefrontal cortex (PFC) retain stimulus-specific information when vibrotactile frequencies were memorized. A direct mapping between monkey studies and human research is still controversial. Although oscillatory signatures, in terms of frequency-dependent parametric beta-band modulation, have been observed recently in human EEG studies, the content specificity of these representations in terms of multivariate pattern analysis has not yet been shown. Here, we used fMRI in combination with multivariate classification techniques to determine which brain regions retain information during WM. In a retro-cue delayed-match-to-sample task, human subjects memorized the frequency of vibrotactile stimulation over a 12 s delay phase. Using an assumption-free whole-brain searchlight approach, we tested with support vector regression which brain regions exhibited multivariate parametric WM codes of the maintained frequencies during the WM delay. Interestingly, our analysis revealed an overlap with regions previously identified in monkeys composed of bilateral premotor cortices, supplementary motor area, and the right inferior frontal gyrus as part of the PFC. Therefore, our results establish a link between the WM codes found in monkeys and those in humans and emphasize the importance of the PFC for information maintenance during WM also in humans.SIGNIFICANCE STATEMENT Working memory (WM) research in monkeys has identified a network of regions, including prefrontal regions, to code stimulus-specific information when vibrotactile frequencies are memorized. Here, we performed an fMRI study during which human subjects had to memorize vibratory frequencies in parallel to previous monkey research. Using an assumption-free, whole-brain searchlight decoding approach, we identified for the first time regions in the human brain that exhibit multivariate patterns of activity to code the vibratory frequency parametrically during WM. Our results parallel previous monkey findings and show that the supplementary motor area, premotor, and the right prefrontal cortex are involved in vibrotactile WM coding in humans.

Response-Modality-Specific Encoding of Human Choices in Upper Beta Band Oscillations during Vibrotactile Comparisons

Perceptual decisions based on the comparison of two vibrotactile frequencies have been extensively studied in non-human primates. Recently, we obtained corresponding findings from human oscillatory electroencephalography (EEG) activity in the form of choice-selective modulations of upper beta band amplitude in medial premotor areas. However, the research in non-human primates as well as its human counterpart was so far limited to decisions reported by button presses. Thus, here we investigated whether the observed human beta band modulation is specific to the response modality. We recorded EEG activity from participants who compared two sequentially presented vibrotactile frequencies (f1 and f2), and decided whether f2 > f1 or f2 < f1, by performing a horizontal saccade to either side of a computer screen. Contrasting time-frequency transformed EEG data between both choices revealed that upper beta band amplitude (∼24–32 Hz) was modulated by participants’ choices before actual responses were given. In particular, “f2 > f1” choices were always associated with higher beta band amplitude than “f2 < f1” choices, irrespective of whether the choice was correct or not, and independent of the specific association between saccade direction and choice. The observed pattern of beta band modulation was virtually identical to our previous results when participants responded with button presses. In line with an intentional framework of decision making, the most likely sources of the beta band modulation were now, however, located in lateral as compared to medial premotor areas including the frontal eye fields. Hence, we could show that the choice-selective modulation of upper beta band amplitude is on the one hand consistent across different response modalities (i.e., same modulation pattern in similar frequency band), and on the other hand effector specific (i.e., modulation originating from areas involved in planning and executing saccades).

Emergence of an abstract categorical code enabling the discrimination of temporally structured tactile stimuli

The problem of neural coding in perceptual decision making revolves around two fundamental questions: (i) How are the neural representations of sensory stimuli related to perception, and (ii) what attributes of these neural responses are relevant for downstream networks, and how do they influence decision making? We studied these two questions by recording neurons in primary somatosensory (S1) and dorsal premotor (DPC) cortex while trained monkeys reported whether the temporal pattern structure of two sequential vibrotactile stimuli (of equal mean frequency) was the same or different. We found that S1 neurons coded the temporal patterns in a literal way and only during the stimulation periods and did not reflect the monkeys' decisions. In contrast, DPC neurons coded the stimulus patterns as broader categories and signaled them during the working memory, comparison, and decision periods. These results show that the initial sensory representation is transformed into an intermediate, more abstract categorical code that combines past and present information to ultimately generate a perceptually informed choice.

Short Time-Scale Sensory Coding in S1 during Discrimination of Whisker Vibrotactile Sequences

Rodent whisker input consists of dense microvibration sequences that are often temporally integrated for perceptual discrimination. Whether primary somatosensory cortex (S1) participates in temporal integration is unknown. We trained rats to discriminate whisker impulse sequences that varied in single-impulse kinematics (5–20-ms time scale) and mean speed (150-ms time scale). Rats appeared to use the integrated feature, mean speed, to guide discrimination in this task, consistent with similar prior studies. Despite this, 52% of S1 units, including 73% of units in L4 and L2/3, encoded sequences at fast time scales (≤20 ms, mostly 5–10 ms), accurately reflecting single impulse kinematics. 17% of units, mostly in L5, showed weaker impulse responses and a slow firing rate increase during sequences. However, these units did not effectively integrate whisker impulses, but instead combined weak impulse responses with a distinct, slow signal correlated to behavioral choice. A neural decoder could identify sequences from fast unit spike trains and behavioral choice from slow units. Thus, S1 encoded fast time scale whisker input without substantial temporal integration across whisker impulses.

Recordings in whisker somatosensory cortex of rats during discrimination of rapid whisker deflection sequences show that whisker input is encoded at very short time scales (less than 20 ms).

Sensory input is rich in temporal patterns, but how the brain processes this temporal information is not well understood. This process is important in the whisker tactile system of rodents, in which active whisking on objects generates dense streams of stick-slip and contact events. Rats can discriminate vibrotactile sequences applied to the whiskers, and prior studies show that this often involves behavioral integration over time to calculate mean whisker-speed. How the brain represents and integrates vibrotactile input is not known. We recorded neural activity in primary somatosensory cortex as rats discriminated rapid vibrotactile sequences. We found that neurons in the primary somatosensory cortex encoded whisker sensory information at very fast time scales (<20 ms), without evidence for substantial temporal integration. A subset of neurons encoded relatively little stimulus information but strongly encoded the rat’s behavioral choice on each trial. Thus, primary sensory cortex represents immediate sensory input, suggesting that temporal integration occurs in downstream brain areas.

Bilateral representations of touch in the primary somatosensory cortex

According to current textbook knowledge, the primary somatosensory cortex (SI) supports unilateral tactile representations, whereas structures beyond SI, in particular the secondary somatosensory cortex (SII), support bilateral tactile representations. However, dexterous and well-coordinated bimanual motor tasks require early integration of bilateral tactile information. Sequential processing, first of unilateral and subsequently of bilateral sensory information, might not be sufficient to accomplish these tasks. This view of sequential processing in the somatosensory system might therefore be questioned, at least for demanding bimanual tasks. Evidence from the last 15 years is forcing a revision of this textbook notion. Studies in animals and humans indicate that SI is more than a simple relay for unilateral sensory information and, together with SII, contributes to the integration of somatosensory inputs from both sides of the body. Here, we review a series of recent works from our own and other laboratories in favour of interactions between tactile stimuli on the two sides of the body at early stages of processing. We focus on tactile processing, although a similar logic may also apply to other aspects of somatosensation. We begin by describing the basic anatomy and physiology of interhemispheric transfer, drawing on neurophysiological studies in animals and behavioural studies in humans that showed tactile interactions between body sides, both in healthy and in brain-damaged individuals. Then we describe the neural substrates of bilateral interactions in somatosensation as revealed by neurophysiological work in animals and neuroimaging studies in humans (i.e., functional magnetic resonance imaging, magnetoencephalography, and transcranial magnetic stimulation). Finally, we conclude with considerations on the dilemma of how efficiently integrating bilateral sensory information at early processing stages can coexist with more lateralized representations of somatosensory input, in the context of motor control.

Upper Beta Band Oscillations in Human Premotor Cortex Encode Subjective Choices in a Vibrotactile Comparison Task

Comparisons of sequentially presented vibrotactile frequencies have been extensively studied using electrophysiological recordings in nonhuman primates. Although neural signatures for working memory aspects of such tasks were recently also identified in human oscillatory EEG activity, homologue correlates of the comparison process are yet unknown. Here, we recorded EEG activity while participants decided which of two sequentially presented vibrotactile stimuli had a higher frequency. Because choices in this type of task are known to be systematically biased by the time-order effect, we applied Bayesian modeling to account for individual choice behavior. Using model-based EEG analysis, we found that upper beta band amplitude (∼20–30 Hz) was modulated by participants' choices. The modulation emerged ∼750 msec before a behavioral response was given and was source-localized to premotor areas.Importantly, the choice-dependent modulation of beta band amplitude was invariant to different motor response mappings and reflected the categorical outcome of the subjective comparison between the two frequencies. Consistently, this pattern was evident for both correct and incorrect trials, indicating that the beta band amplitude mirrors the internal representation of the comparison outcome. Our data complement previous findings in nonhuman primates and corroborate that the beta band activity in premotor areas reflects the categorical outcome of a sensory comparison prior to translation into an effector-specific motor command.

Tactile texture signals in primate primary somatosensory cortex and their relation to subjective roughness intensity

This study investigated the hypothesis that a simple intensive code, based on mean firing rate, could explain the cortical representation of subjective roughness intensity and its invariance with scanning speed. We examined the sensitivity of neurons in the cutaneous, finger representation of primary somatosensory cortex (S1) to a wide range of textures [1 mm high, raised-dot surfaces; spatial periods (SPs), 1.5-8.5 mm], scanned under the digit tips at different speeds (40-115 mm/s). Since subjective roughness estimates show a monotonic increase over this range and are independent of speed, we predicted that the mean firing rate of a subgroup of S1 neurons would share these properties. Single-unit recordings were made in four alert macaques (areas 3b, 1 and 2). Cells whose discharge rate showed a monotonic increase with SP, independent of speed, were particularly concentrated in area 3b. Area 2 was characterized by a high proportion of cells sensitive to speed, with or without texture sensitivity. Area 1 had intermediate properties. We suggest that area 3b and most likely area 1 play a key role in signaling roughness intensity, and that a mean rate code, signaled by both slowly and rapidly adapting neurons, is present at the level of area 3b. Finally, the substantial proportion of neurons that showed a monotonic change in discharge limited to a small range of SPs (often independent of response saturation) could play a role in discriminating smaller changes in SP.

Neural Coding of Perceived Odor Intensity

Stimulus intensity is a fundamental perceptual feature in all sensory systems. In olfaction, perceived odor intensity depends on at least two variables: odor concentration; and duration of the odor exposure or adaptation. To examine how neural activity at early stages of the olfactory system represents features relevant to intensity perception, we studied the responses of mitral/tufted cells (MTCs) while manipulating odor concentration and exposure duration. Temporal profiles of MTC responses to odors changed both as a function of concentration and with adaptation. However, despite the complexity of these responses, adaptation and concentration dependencies behaved similarly. These similarities were visualized by principal component analysis of average population responses and were quantified by discriminant analysis in a trial-by-trial manner. The qualitative functional dependencies of neuronal responses paralleled psychophysics results in humans. We suggest that temporal patterns of MTC responses in the olfactory bulb contribute to an internal perceptual variable: odor intensity.

Perceptual decision-making difficulty modulates feedforward effective connectivity to the dorsolateral prefrontal cortex

Diverse cortical structures are known to coordinate activity as a network in relaying and processing of visual information to discriminate visual objects. However, how this discrimination is achieved is still largely unknown. To contribute to answering this question, we used face-house categorization tasks with three levels of noise in face and house images in functional magnetic resonance imaging (fMRI) experiments involving thirty-three participants. The behavioral performance error and response time (RT) were correlated with noise in face-house images. We then built dynamical causal models (DCM) of fMRI blood-oxygenation level dependent (BOLD) signals from the face and house category-specific regions in ventral temporal (VT) cortex, the fusiform face area (FFA) and parahippocampal place area (PPA), and the dorsolateral prefrontal cortex (dlPFC). We found a strong feed-forward intrinsic connectivity pattern from FFA and PPA to dlPFC. Importantly, the feed-forward connectivity to dlPFC was significantly modulated by the perception of both faces and houses. The dlPFC-BOLD activity, the connectivity from FFA and PPA to the dlPFC all increased with noise level. These results suggest that the FFA-PPA-dlPFC network plays an important role for relaying and integrating competing sensory information to arrive at perceptual decisions.

Wideband phase locking to modulated whisker vibration point to a temporal code for texture in the rat's barrel cortex

Rats probe objects with their whiskers and make decisions about sizes, shapes, textures and distances within a few tens of milliseconds. This perceptual analysis requires the processing of tactile high-frequency object components reflecting surface roughness. We have shown that neurons in the barrel cortex of rats encode high-frequency sinusoidal vibrations of whiskers for sustained periods when presented with constant amplitudes and frequencies. In a natural situation, however, stimulus parameters change rapidly when whiskers are brushing across objects. In this study, we therefore analysed cortical responses to vibratory movements of single whiskers with rapidly changing amplitudes and frequencies. The results show that different neural codes are employed for a processing of stimulus parameters. The frequency of whisker vibration is encoded by the temporal pattern of spike discharges, i.e., the phase-locked responses of barrel cortex neurons. In addition, oscillatory gamma band activity was induced during high-frequency stimulation. The pivotal descriptor of the amplitude of whisker displacement, the velocity, is reflected in the rate of spike discharges. While phase-locked discharges occurred over the entire range of frequencies tested (10-600 Hz), the discharge rate increased with stimulus velocity only up to about 60 µm/ms, saturating at a mean rate of ~117 spikes/s. In addition, the results show that whisker movements of more than 500 Hz bandwidth may be encoded by phase-locked responses of small groups of cortical neurons. Thus, even single whiskers may transmit information about wide ranges of textural components owing to their set of different types of hair follicle mechanoreceptors.

Behavioral dependence of auditory cortical responses

Neural responses in the auditory cortex have historically been measured from either anesthetized or awake but non-behaving animals. A growing body of work has begun to focus instead on recording from auditory cortex of animals actively engaged in behavior tasks. These studies have shown that auditory cortical responses are dependent upon the behavioral state of the animal. The longer ascending subcortical pathway of the auditory system and unique characteristics of auditory processing suggest that such dependencies may have a more profound influence on cortical processing in the auditory system compared to other sensory systems. It is important to understand the nature of these dependencies and their functional implications. In this article, we review the literature on this topic pertaining to cortical processing of sounds.

Sparse, reliable, and long-term stable representation of periodic whisker deflections in the mouse barrel cortex

The rodent whisker system is a preferred model for studying plasticity in the somatosensory cortex (barrel cortex). Contrarily, only a small amount of research has been conducted to characterize the stability of neuronal population activity in the barrel cortex. We used the mouse whisker system to address the neuronal basis of stable perception in the somatosensory cortex. Cortical representation of periodic whisker deflections was studied in populations of neurons in supragranular layers over extended time periods (up to 3 months) with long-term two-photon Ca(2+) imaging in anesthetized mice. We found that in most of the neurons (87%), Ca(2+) responses increased sublinearly with increasing number of contralateral whisker deflections. The imaged population of neurons was activated in a stereotypic way over days and for different deflection rates (pulse frequencies). Thus, pulse frequencies are coded by response strength rather than by distinct neuronal sub-populations. A small population of highly responsive neurons (~3%) was sufficient to decode the whisker stimulus. This conserved functional map, led by a small set of highly responsive neurons, might form the foundation of stable sensory percepts.

Decoding stimulus features in primate somatosensory cortex during perceptual categorization

Neurons of the primary somatosensory cortex (S1) respond as functions of frequency or amplitude of a vibrotactile stimulus. However, whether S1 neurons encode both frequency and amplitude of the vibrotactile stimulus or whether each sensory feature is encoded by separate populations of S1 neurons is not known, To further address these questions, we recorded S1 neurons while trained monkeys categorized only one sensory feature of the vibrotactile stimulus: frequency, amplitude, or duration. The results suggest a hierarchical encoding scheme in S1: from neurons that encode all sensory features of the vibrotactile stimulus to neurons that encode only one sensory feature. We hypothesize that the dynamic representation of each sensory feature in S1 might serve for further downstream processing that leads to the monkey's psychophysical behavior observed in these tasks.

On the number of neurons and time scale of integration underlying the formation of percepts in the brain

All of our perceptual experiences arise from the activity of neural populations. Here we study the formation of such percepts under the assumption that they emerge from a linear readout, i.e., a weighted sum of the neurons’ firing rates. We show that this assumption constrains the trial-to-trial covariance structure of neural activities and animal behavior. The predicted covariance structure depends on the readout parameters, and in particular on the temporal integration window w and typical number of neurons K used in the formation of the percept. Using these predictions, we show how to infer the readout parameters from joint measurements of a subject’s behavior and neural activities. We consider three such scenarios: (1) recordings from the complete neural population, (2) recordings of neuronal sub-ensembles whose size exceeds K, and (3) recordings of neuronal sub-ensembles that are smaller than K. Using theoretical arguments and artificially generated data, we show that the first two scenarios allow us to recover the typical spatial and temporal scales of the readout. In the third scenario, we show that the readout parameters can only be recovered by making additional assumptions about the structure of the full population activity. Our work provides the first thorough interpretation of (feed-forward) percept formation from a population of sensory neurons. We discuss applications to experimental recordings in classic sensory decision-making tasks, which will hopefully provide new insights into the nature of perceptual integration.

This article deals with the interpretation of neural activities during perceptual decision-making tasks, where animals must assess the value of a sensory stimulus and take a decision on the basis of their percept. A “standard model” for these tasks has progressively emerged, whence the animal’s percept and subsequent choice on each trial are obtained from a linear integration of the activity of sensory neurons. However, up to date, there has been no principled method to estimate the parameters of this model: mainly, the typical number of neurons K from the population involved in conveying the percept, and the typical time scale w during which these neurons’ activities are integrated. In this article, we propose a novel method to estimate these quantities from experimental data, and thus assess the validity of the standard model of percept formation. In the process, we clarify the predictions of the standard model regarding two classic experimental measures in these tasks: sensitivity, which is the animal’s ability to distinguish nearby stimulus values, and choice signals, which assess the amount of correlation between the activity of single neurons and the animal’s ultimate choice on each trial.

Complementary contributions of spike timing and spike rate to perceptual decisions in rat S1 and S2 cortex

When a neuron responds to a sensory stimulus, two fundamental codes [1-6] may transmit the information specifying stimulus identity--spike rate (the total number of spikes in the sequence, normalized by time) and spike timing (the detailed millisecond-scale temporal structure of the response). To assess the functional significance of these codes, we recorded neuronal responses in primary (S1) and secondary (S2) somatosensory cortex of five rats as they used their whiskers to identify textured surfaces. From the spike trains evoked during whisker contact with the texture, we computed the information that rate and timing codes carried about texture identity and about the rat's choice. S1 and S2 spike timing carried more information about stimulus and about choice than spike rates; the conjunction of rate and timing carried more information than either code alone. Moreover, on trials when our spike-timing-decoding algorithm extracted faithful texture information, the rat was more likely to choose correctly; when our spike-timing-decoding algorithm extracted misleading texture information, the rat was more likely to err. For spike rate information, the relationship between faithfulness of the message and correct choice was significant but weaker. These results indicate that spike timing makes crucial contributions to tactile perception, complementing and surpassing those made by rate. The language by which somatosensory cortical neurons transmit information, and the readout mechanism used to produce behavior, appears to rely on multiplexed signals from spike rate and timing.